From cbb9cdbf790487a0f60ba563d14445130ea09057 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Sat, 14 Oct 2023 10:56:14 +0100 Subject: [PATCH 001/129] add distribution functions --- NAMESPACE | 6 + R/dist.R | 457 +++++++++++++++++++++++--------- R/opts.R | 4 +- inst/stan/data/delays.stan | 8 +- man/delay_opts.Rd | 2 +- man/dist_spec.Rd | 38 +-- man/sd.dist_spec.Rd | 40 +++ man/trunc_opts.Rd | 5 +- tests/testthat/setup.R | 2 +- tests/testthat/test-dist_spec.R | 2 +- 10 files changed, 418 insertions(+), 146 deletions(-) create mode 100644 man/sd.dist_spec.Rd diff --git a/NAMESPACE b/NAMESPACE index 358611087..43beef233 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -8,6 +8,7 @@ S3method(plot,estimate_infections) S3method(plot,estimate_secondary) S3method(plot,estimate_truncation) S3method(print,dist_spec) +S3method(sd,dist_spec) S3method(summary,epinow) S3method(summary,estimate_infections) export(R_to_growth) @@ -50,7 +51,9 @@ export(extract_samples) export(extract_stan_param) export(fix_dist) export(forecast_infections) +export(fixed) export(forecast_secondary) +export(gamma) export(gamma_dist_def) export(generation_time_opts) export(get_dist) @@ -63,13 +66,16 @@ export(get_regions_with_most_reports) export(gp_opts) export(growth_to_R) export(lognorm_dist_def) +export(lognormal) export(make_conf) export(map_prob_change) +export(normal) export(obs_opts) export(opts_list) export(package_model) export(plot_estimates) export(plot_summary) +export(pmf) export(regional_epinow) export(regional_runtimes) export(regional_summary) diff --git a/R/dist.R b/R/dist.R index f9144569e..9f6cca062 100644 --- a/R/dist.R +++ b/R/dist.R @@ -87,41 +87,56 @@ dist_skel <- function(n, dist = FALSE, cum = TRUE, model, if (model == "exp") { # define support functions for exponential dist rdist <- function(n) { - rexp(n, params$rate) + rexp(n, params[["rate"]]) } pdist <- function(n) { - pexp(n, params$rate) / pexp(max_value, params$rate) + pexp(n, params[["rate"]]) / pexp(max_value, params[["rate"]]) } ddist <- function(n) { - (pexp(n + 1, params$rate) - - pexp(n, params$rate)) / - pexp(max_value + 1, params$rate) + (pexp(n + 1, params[["rate"]]) - + pexp(n, params[["rate"]])) / + pexp(max_value + 1, params[["rate"]]) } } else if (model == "gamma") { rdist <- function(n) { - rgamma(n, params$shape, params$scale) + rgamma(n = n, shape = params[["shape"]], rate = params[["rate"]]) } pdist <- function(n) { - pgamma(n, params$shape, params$scale) / - pgamma(max_value + 1, params$shape, params$scale) + pgamma(q = n, shape = params[["shape"]], rate = params[["rate"]]) / + pgamma( + q = max_value + 1, shape = params[["shape"]], rate = params[["rate"]] + ) } ddist <- function(n) { - (pgamma(n + 1, params$shape, params$scale) - - pgamma(n, params$shape, params$scale)) / - pgamma(max_value + 1, params$shape, params$scale) + (pgamma(q = n + 1, shape = params[["shape"]], rate = params[["rate"]]) - + pgamma(q = n, shape = params[["shape"]], rate = params[["rate"]])) / + pgamma(q = max_value + 1, params[["shape"]], rate = params[["rate"]]) } } else if (model == "lognormal") { rdist <- function(n) { - rlnorm(n, params$mean, params$sd) + rlnorm(n, params[["mean"]], params[["sd"]]) + } + pdist <- function(n) { + plnorm(n, params[["mean"]], params[["sd"]]) / + plnorm(max_value + 1, params[["mean"]], params[["sd"]]) + } + ddist <- function(n) { + (plnorm(n + 1, params[["mean"]], params[["sd"]]) - + plnorm(n, params[["mean"]], params[["sd"]])) / + plnorm(max_value + 1, params[["mean"]], params[["sd"]]) + } + } else if (model %in% "normal") { + rdist <- function(n) { + rnorm(n, params[["mean"]], params[["sd"]]) } pdist <- function(n) { - plnorm(n, params$mean, params$sd) / - plnorm(max_value + 1, params$mean, params$sd) + pnorm(n, params[["mean"]], params[["sd"]]) / + pnorm(max_value + 1, params[["mean"]], params[["sd"]]) } ddist <- function(n) { - (plnorm(n + 1, params$mean, params$sd) - - plnorm(n, params$mean, params$sd)) / - plnorm(max_value + 1, params$mean, params$sd) + (pnorm(n + 1, params[["mean"]], params[["sd"]]) - + pnorm(n, params[["mean"]], params[["sd"]])) / + pnorm(max_value + 1, params[["mean"]], params[["sd"]]) } } @@ -551,7 +566,6 @@ bootstrapped_dist_fit <- function(values, dist = "lognormal", return(out) } - if (bootstraps == 1) { dist_samples <- get_single_dist(values, samples = samples) } else { @@ -912,9 +926,12 @@ tune_inv_gamma <- function(lower = 2, upper = 21) { #' mean = 3, sd = 2, mean_sd = 0.5, sd_sd = 0.5, max = 20, #' distribution = "gamma" #' ) -dist_spec <- function(mean, sd = 0, mean_sd = 0, sd_sd = 0, - distribution = c("lognormal", "gamma"), max, - pmf = numeric(0), fixed = FALSE) { +dist_spec <- function(distribution = c( + "lognormal", "normal", "gamma", "fixed", "empty" + ), + params_mean = c(), params_sd = c(), + mean, sd, mean_sd = 0, sd_sd = 0, + max = Inf, pmf = numeric(0), fixed = FALSE) { ## deprecate previous behaviour warn( message = paste( @@ -935,98 +952,87 @@ dist_spec <- function(mean, sd = 0, mean_sd = 0, sd_sd = 0, "fix_dist()", "The argument will be removed completely in version 2.1.0." ) - mean_sd <- 0 - sd_sd <- 0 + } + ## check for deprecated parameters + if (!all(missing(mean), missing(sd), missing(mean_sd), missing(sd_sd)) && + (!missing(params_mean || !missing(params_sd)))) { + stop("Distributional should not be given as `mean`, `sd`, etc. ", + "in addition to `params_mean` or `params_sd`") + } + call <- match.call() + for (deprecated_arg in c("mean", "sd", "mean_sd", "sd_sd")) { + if (!is.null(call[[deprecated_arg]])) { + deprecate_warn( + "2.0.0", + paste0("dist_spec(", deprecated_arg, ")"), + "dist_spec(param)", + "The argument will be removed completely in version 2.1.0." + ) + params[[deprecated_arg]] <- get(deprecated_arg) + } } ## check if parametric or nonparametric if (length(pmf) > 0 && !all( - missing(mean), missing(sd), missing(mean_sd), - missing(sd_sd), missing(distribution), missing(max) + missing(distribution), missing(params_mean), missing(params_sd), + missing(mean), missing(sd), missing(mean_sd), missing(sd_sd) )) { stop("Distributional parameters or a pmf can be specified, but not both.") } - fixed <- mean_sd == 0 && sd_sd == 0 + distribution <- match.arg(distribution) - ## check parametric parameters make sense - if (!missing(mean)) { - if (sd == 0 && sd_sd == 0) { ## integer fixed - if (mean %% 1 != 0) { - stop( - "When a distribution is set to a constant ", - "(sd == 0 and sd_sd == 0) then the mean parameter ", - "must be an integer." - ) - } - max <- mean - if (mean_sd > 0) { - stop( - "When a distribution has sd == 0 and ", - "sd_sd == 0 then mean_sd must be 0, too." - ) - } + if (distribution == "fixed") { + ## if integer fixed then can write the PMF + if (as.integer(params_mean) == params_mean) { + max <- params_mean + parametric <- TRUE } else { - if (missing(max)) { - stop("Maximum of parametric distributions must be specified.") - } + parametric <- FALSE + } + if (length(params_sd) > 0 && any(params_sd) > 0) { + stop("Fixed parameters cannot have a nonzero standard deviation.") } + params_sd <- numeric(0) } else { - if (!all( - missing(sd), missing(mean_sd), - missing(sd_sd), missing(distribution), missing(max) - )) { - stop( - "If any distributional parameters are given then so must the mean." - ) + ## if PMF is given, set max + if (is.infinite(max) && length(pmf) > 0) { + max <- length(pmf) - 1 } + parametric <- all(params_sd == 0) && is.finite(max) } - - distribution <- arg_match(distribution) - if (fixed) { + if (parametric) { ## calculate pmf ret <- list( - mean_mean = numeric(0), - mean_sd = numeric(0), - sd_mean = numeric(0), - sd_sd = numeric(0), + params_mean = numeric(0), + params_sd = numeric(0), dist = character(0), - max = integer(0) + max = integer(0), + parametric = FALSE ) if (length(pmf) == 0) { - if (missing(mean)) { ## empty + if (distribution == "empty") { ## empty ret <- c(ret, list( n = 0, n_p = 0, n_np = 0, np_pmf = numeric(0), - fixed = integer(0) + parametric = logical(0) )) } else { ## parametric fixed - if (sd == 0) { ## delta - pmf <- c(rep(0, mean), 1) + if (distribution == "fixed") { ## delta + pmf <- c(rep(0, params_mean), 1) } else { - if (distribution == "lognormal") { - params <- lognorm_dist_def( - mean = mean, mean_sd = mean_sd, - sd = sd, sd_sd = sd_sd, max_value = max, samples = 1 - ) - } else if (distribution == "gamma") { - params <- gamma_dist_def( - mean = mean, mean_sd = mean_sd, - sd = sd, sd_sd = sd_sd, max_value = max, samples = 1 - ) - } + params <- params_mean + names(params) <- natural_params(distribution) pmf <- dist_skel( n = seq_len(max + 1) - 1, dist = TRUE, cum = FALSE, - model = distribution, params = params$params[[1]], max_value = max, + model = distribution, params = params, max_value = max, discrete = TRUE ) } } } else { ## nonparametric fixed - if (!missing(max) && (max + 1) < length(pmf)) { - pmf <- pmf[1:(max + 1)] - } + pmf <- pmf[1:(max + 1)] pmf <- pmf / sum(pmf) } if (length(pmf) > 0) { @@ -1034,28 +1040,26 @@ dist_spec <- function(mean, sd = 0, mean_sd = 0, sd_sd = 0, n = 1, n_p = 0, n_np = 1, - np_pmf = pmf, - fixed = 1L + np_pmf = pmf )) } } else { ret <- list( - mean_mean = mean, - mean_sd = mean_sd, - sd_mean = sd, - sd_sd = sd_sd, + params_mean = params_mean, + params_sd = params_sd, dist = distribution, max = max, n = 1, n_p = 1, n_np = 0, np_pmf = numeric(0), - fixed = 0L + parametric = TRUE ) } ret <- purrr::map(ret, array) sum_args <- grep("(^n$|^n_$)", names(ret)) ret$np_pmf_length <- length(ret$np_pmf) + ret$params_length <- length(ret$params_mean) ret[sum_args] <- purrr::map(ret[sum_args], sum) attr(ret, "class") <- c("list", "dist_spec") return(ret) @@ -1207,26 +1211,88 @@ c.dist_spec <- function(...) { #' # The mean of the sum of two distributions #' mean(lognormal + gamma) mean.dist_spec <- function(x, ...) { - ret <- rep(0, x$n) - ## nonparametric + if (x$n > 1) { + stop("Cannot calculate mean of composite distributions.") + } if (x$n_np > 0) { - init_id <- c(1, head(cumsum(x$np_pmf_length) + 1, n = -1)) - ret[x$fixed == 1L] <- vapply(seq_along(init_id), function(id) { - pmf <- x$np_pmf[seq(init_id[id], cumsum(x$np_pmf_length)[id])] - return(sum((seq_len(x$np_pmf_length[id]) - 1) * pmf)) - }, 0) + ## nonparametric + ret <- sum((seq_len(x$np_pmf_length) - 1) * x$np_pmf) + } else { + ## parametric + if (any(x$params_sd > 0)) { + stop("Cannot calculate mean of uncertain distribution") + } + if (x$dist == "lognormal") { + ret <- exp(x$params_mean[[1]] + x$params_mean[[2]]**2 / 2) + } else if (x$dist == "gamma") { + ret <- x$params_mean[[1]] / x$params_mean[[2]] + } else if (x$dist == "normal") { + ret <- x$params_mean[[1]] + } else if (x$dist == "fixed") { + ret <- x$params_mean[[1]] + } else { + stop("Don't know how to calculate mean of ", x$dist, " distribution.") + } } - ## parametric - if (x$n_p > 0) { - ret[x$fixed == 0L] <- vapply(seq_along(which(x$fixed == 0L)), function(id) { - if (x$dist[id] == "lognormal") { - return(exp(x$mean_mean[id] + x$sd_mean[id] / 2)) - } else if (x$dist[id] == "gamma") { - return(x$mean_mean[id]) - } else { - stop("Unknown distribution: ", x$dist[id]) - } - }, 0) + return(ret) +} + +##' Returns the standard deviation of one or more delay distribution +##' +##' This works out the standard deviation of all the (parametric / +##' nonparametric) delay distributions combined in the passed [dist_spec()]. +##' +##' @param x The [dist_spec()] to use +##' @param ... Not used +##' @return A vector of standard deviations. +##' @author Sebastian Funk +##' @method sd dist_spec +##' @importFrom utils head +##' @export +#' @examples +#' # A fixed lognormal distribution with sd 5 and sd 1. +#' lognormal <- dist_spec( +#' sd = 5, sd = 1, max = 20, distribution = "lognormal" +#' ) +#' sd(lognormal) +#' +#' # An uncertain gamma distribution with sd 3 and sd 2 +#' gamma <- dist_spec( +#' sd = 3, sd = 2, sd_sd = 0.5, sd_sd = 0.5, max = 20, +#' distribution = "gamma" +#' ) +#' sd(gamma) +#' +#' # The sd of the sum of two distributions +#' sd(lognormal + gamma) +sd.dist_spec <- function(x, ...) { + if (x$n > 1) { + stop("Cannot calculate standard deviation of composite distributions.") + } + if (x$n_np > 0) { + ## nonparametric + mean_pmf <- sum((seq_len(x$np_pmf_length) - 1) * x$np_pmf) + ret <- sum((seq_len(x$np_pmf_length) - 1)**2 * x$np_pmf) - mean_pmf^2 + } else { + ## parametric + if (any(x$params_sd > 0)) { + stop("Cannot calculate standard deviation of uncertain distribution") + } + if (x$dist == "lognormal") { + ret <- sqrt(exp(x$params_mean[2]**2) - 1) * + exp(x$params_mean[1] + 0.5 * x$params_mean[2]**2) + } else if (x$dist == "gamma") { + ret <- sqrt(x$params_mean[1] / x$params_mean[2]**2) + } else if (x$dist == "normal") { + ret <- x$params_mean[2] + } else if (x$dist == "fixed") { + ret <- 0 + } else { + stop( + "Don't know how to calculate standard deviation of ", x$dist, + " distribution." + ) + } } return(ret) } @@ -1260,42 +1326,63 @@ print.dist_spec <- function(x, ...) { cat("Empty `dist_spec` distribution.\n") return(invisible(NULL)) } else if (x$n > 1) { - cat("Combination of delay distributions:\n") + cat("Composite delay distribution:\n") } fixed_id <- 1 fixed_pos <- 1 variable_id <- 1 + variable_pos <- 1 for (i in 1:x$n) { cat(" ") if (!is.null(x$names) && nchar(x$names[i]) > 0) { cat(x$names[i], ": ", sep = "") } - if (x$fixed[i] == 0) { + if (x$parametric[i] > 0) { dist <- x$dist[variable_id] - cat( - "Uncertain ", dist, " distribution with (untruncated) ", - ifelse(dist == "lognormal", "log", ""), - "mean ", signif(x$mean_mean[variable_id], digits = 2), - " (SD ", signif(x$mean_sd[variable_id], digits = 2), ") and ", - ifelse(dist == "lognormal", "log", ""), - "SD ", signif(x$sd_mean[variable_id], 2), - " (SD ", signif(x$sd_sd[variable_id], 2), ")\n", - sep = "" - ) + cat(dist, " distribution", sep = "") + if (is.finite(x$max)) { + cat(" (max: ", x$max, ")", sep = "") + } + cat(" with ", sep = "") + ## loop over natural parameters and print + for (id in seq(variable_pos, x$params_length[variable_pos])) { + if (id > variable_pos) { + if (id == x$params_length[variable_pos]) { + cat(" and ") + } else { + cat(", ") + } + } + if (x$params_sd[id] > 0) { + cat("uncertain ") + } + cat(natural_params(dist)[id]) + if (x$params_sd[id] > 0) { + cat( + " (mean = ", signif(x$params_mean[id], digits = 2), ", ", + "sd = ", signif(x$params_sd[id], digits = 2), ")", + sep = "" + ) + } else { + cat(" = ", signif(x$params_mean[id], digits = 2), sep = "") + } + } variable_id <- variable_id + 1 + variable_pos <- variable_pos + x$params_length[i] } else { cat( - "Fixed distribution with PMF [", + "distribution with PMF [", paste(signif( x$np_pmf[seq(fixed_pos, fixed_pos + x$np_pmf_length[fixed_id] - 1)], digits = 2 ), collapse = " "), - "]\n", + "]", sep = "" ) fixed_id <- fixed_id + 1 fixed_pos <- fixed_pos + x$np_pmf_length[i] } + cat(".\n") } cat("\n") } @@ -1404,7 +1491,7 @@ plot.dist_spec <- function(x, ...) { ##' @importFrom rlang arg_match fix_dist <- function(x, strategy = c("mean", "sample")) { ## if x is fixed already we don't have to do anything - if (x$fixed) return(x) + if (x$mean_sd == 0 && x$sd_sd == 0) return(x) ## match startegy argument to options strategy <- arg_match(strategy) ## apply stragey depending on choice @@ -1434,3 +1521,133 @@ fix_dist <- function(x, strategy = c("mean", "sample")) { } return(x) } + +##' @export +lognormal <- function(meanlog, sdlog, mean, sd, median, max = Inf) { + params <- as.list(environment()) + lower_bounds <- c(meanlog = -Inf, sdlog = 0, mean = 0, sd = 0, median = 0) + return(process_dist(params, lower_bounds, "lognormal")) +} + +##' @export +gamma <- function(shape, rate, scale, mean, sd, max = Inf) { + params <- as.list(environment()) + lower_bounds <- c(shape = 0, rate = 0, scale = 0, mean = 0, sd = 0) + return(process_dist(params, lower_bounds, "gamma")) +} + +##' @export +normal <- function(mean, sd, max = Inf) { + params <- as.list(environment()) + lower_bounds <- c(mean = -Inf, sd = 0) + return(process_dist(params, lower_bounds, "normal")) +} + +##' @export +fixed <- function(value) { + params <- as.list(environment()) + params <- extract_params(params, "fixed") + if (is(params$value, "dist_spec")) { + return(params) + } else if (is.numeric(params$value)) { + fixed_value <- params$value + } + return(dist_spec(params_mean = fixed_value, distribution = "fixed")) +} + +##' @export +pmf <- function(x) { + return(dist_spec(pmf = x)) +} + +natural_params <- function(distribution) { + if (distribution == "gamma") { + ret <- c("shape", "rate") + } else if (distribution == "lognormal") { + ret <- c("meanlog", "sdlog") + } else if (distribution == "normal") { + ret <- c("mean", "sd") + } else if (distribution == "fixed") { + ret <- "value" + } + return(ret) +} + +extract_params <- function(params, distribution) { + params <- params[!vapply(params, inherits, "name", FUN.VALUE = TRUE)] + n_params <- length(natural_params(distribution)) + if (length(params) != n_params) { + stop( + "Exactly ", n_params, " parameters of the ", distribution, + " distribution must be specified." + ) + } + return(params) +} + +process_dist <- function(params, lower_bounds, distribution) { + ## process min/max first + max <- params$max + params$max <- NULL + ## extract parameters and convert all to dist_spec + params <- extract_params(params, distribution) + params <- lapply(params, function(x) { + if (is(x, "dist_spec") && x$dist == "normal") { + if (any(x$param_sd > 0)) { + stop( + "Normal distribution indicating uncertainty cannot itself ", + "be uncertain." + ) + } + x + } else if (is.numeric(x)) { + fixed(x) + } else { + stop("Parameter ", x, " must be numeric or normally distributed.") + } + }) + ## sample parameters if they are uncertain + samples <- lapply(names(params), function(x) { + rtruncnorm( + n = 2000, a = lower_bounds[x], + mean = mean.dist_spec(params[[x]]), sd = sd.dist_spec(params[[x]]) + ) + }) + names(samples) <- names(params) + ## generate natural parameters + converted_params <- convert_to_natural(samples, distribution) + + dist <- dist_spec( + distribution = distribution, + params_mean = converted_params$params_mean, + params_sd = converted_params$params_sd, + max = max + ) + + ## now we have a distribution with natural parameters - return dist_spec + return(dist) +} + +convert_to_natural <- function(x, distribution) { + if (distribution == "gamma") { + if ("mean" %in% names(x) && "sd" %in% names(x)) { + x$shape <- x$mean**2 / x$sd**2 + x$rate <- x$shape / x$mean + } else if (!("rate" %in% names(x)) && ("scale" %in% names(x))) { + x$rate <- 1 / x$scale + } + } else if (distribution == "lognormal" && + "mean" %in% names(x) && "sd" %in% names(x)) { + x$meanlog <- convert_to_logmean(x$mean, x$sd) + x$sdlog <- convert_to_logsd(x$mean, x$sd) + } + params <- list( + params_mean = unname(vapply(natural_params(distribution), function(param) { + mean(x[[param]]) + }, numeric(1))), + params_sd = unname(vapply(natural_params(distribution), function(param) { + sd(x[[param]]) + }, numeric(1))) + ) + return(params) +} diff --git a/R/opts.R b/R/opts.R index d0bf688ad..1e0c7dfd8 100644 --- a/R/opts.R +++ b/R/opts.R @@ -128,7 +128,7 @@ generation_time_opts <- function(dist = dist_spec(mean = 1), ..., #' #' # Multiple delays (in this case twice the same) #' delay_opts(delay + delay) -delay_opts <- function(dist = dist_spec(), ..., fixed = FALSE) { +delay_opts <- function(dist = dist_spec("empty"), ..., fixed = FALSE) { dot_options <- list(...) if (!is(dist, "dist_spec")) { ## could be old syntax if (is.list(dist)) { @@ -187,7 +187,7 @@ delay_opts <- function(dist = dist_spec(), ..., fixed = FALSE) { #' #' # truncation dist #' trunc_opts(dist = dist_spec(mean = 3, sd = 2, max = 10)) -trunc_opts <- function(dist = dist_spec()) { +trunc_opts <- function(dist = dist_spec("empty")) { if (!is(dist, "dist_spec")) { if (is.list(dist)) { dist <- do.call(dist_spec, dist) diff --git a/inst/stan/data/delays.stan b/inst/stan/data/delays.stan index 0c624ffbd..7b55a66aa 100644 --- a/inst/stan/data/delays.stan +++ b/inst/stan/data/delays.stan @@ -7,11 +7,17 @@ array[delay_n_p] real delay_sd_sd; // prior sd of sd of delay distribution array[delay_n_p] int delay_max; // maximum delay distribution array[delay_n_p] int delay_dist; // 0 = lognormal; 1 = gamma + int delay_np_pmf_length; // number of nonparametric pmf elements vector[delay_np_pmf_length] delay_np_pmf; // ragged array of fixed PMFs array[delay_n_np + 1] int delay_np_pmf_groups; // links to ragged array - array[delay_n_p] int delay_weight; + int delay_params_length; // number of parameters across all parametric delay distributions + vector[delay_params_length] delay_params_mean; // ragged array of mean parameters for parametric delay distributions + vector[delay_params_length] delay_params_sd; // ragged array of sd of parameters for parametric delay distributions + array[delay_n_p + 1] int delay_params_groups; // links to ragged array + + array[delay_n_p] int delay_weight; // delay weights int delay_types; // number of delay types array[delay_n] int delay_types_p; // whether delay types are parametric array[delay_n] int delay_types_id; // whether delay types are parametric diff --git a/man/delay_opts.Rd b/man/delay_opts.Rd index 6f6973f58..576168c1e 100644 --- a/man/delay_opts.Rd +++ b/man/delay_opts.Rd @@ -4,7 +4,7 @@ \alias{delay_opts} \title{Delay Distribution Options} \usage{ -delay_opts(dist = dist_spec(), ..., fixed = FALSE) +delay_opts(dist = dist_spec("empty"), ..., fixed = FALSE) } \arguments{ \item{dist}{A delay distribution or series of delay distributions generated diff --git a/man/dist_spec.Rd b/man/dist_spec.Rd index 09ff18824..260bb1a81 100644 --- a/man/dist_spec.Rd +++ b/man/dist_spec.Rd @@ -5,32 +5,19 @@ \title{Specify a distribution.} \usage{ dist_spec( + distribution = c("lognormal", "normal", "gamma", "fixed", "empty"), + params_mean = c(), + params_sd = c(), mean, - sd = 0, + sd, mean_sd = 0, sd_sd = 0, - distribution = c("lognormal", "gamma"), - max, + max = Inf, pmf = numeric(0), fixed = FALSE ) } \arguments{ -\item{mean}{Numeric. If the only non-zero summary parameter -then this is the fixed interval of the distribution. If the \code{sd} is -non-zero then this is the mean of the distribution given by \code{dist}. -If this is not given a vector of empty vectors is returned.} - -\item{sd}{Numeric, defaults to 0. Sets the standard deviation of the -distribution.} - -\item{mean_sd}{Numeric, defaults to 0. Sets the standard deviation of the -uncertainty around the mean of the distribution assuming a normal -prior.} - -\item{sd_sd}{Numeric, defaults to 0. Sets the standard deviation of the -uncertainty around the sd of the distribution assuming a normal prior.} - \item{distribution}{Character, defaults to "lognormal". The (discretised distribution to be used. If sd == 0 then the distribution is fixed and a delta function is used. If sd > 0 then the distribution is discretised and @@ -55,6 +42,21 @@ log scale). \item \code{sd} is the standard deviation of the natural logarithm of the delay. }} +\item{mean}{Numeric. If the only non-zero summary parameter +then this is the fixed interval of the distribution. If the \code{sd} is +non-zero then this is the mean of the distribution given by \code{dist}. +If this is not given a vector of empty vectors is returned.} + +\item{sd}{Numeric, defaults to 0. Sets the standard deviation of the +distribution.} + +\item{mean_sd}{Numeric, defaults to 0. Sets the standard deviation of the +uncertainty around the mean of the distribution assuming a normal +prior.} + +\item{sd_sd}{Numeric, defaults to 0. Sets the standard deviation of the +uncertainty around the sd of the distribution assuming a normal prior.} + \item{max}{Numeric, maximum value of the distribution. The distribution will be truncated at this value.} diff --git a/man/sd.dist_spec.Rd b/man/sd.dist_spec.Rd new file mode 100644 index 000000000..6a3f3db29 --- /dev/null +++ b/man/sd.dist_spec.Rd @@ -0,0 +1,40 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/dist.R +\name{sd.dist_spec} +\alias{sd.dist_spec} +\title{Returns the standard deviation of one or more delay distribution} +\usage{ +\method{sd}{dist_spec}(x, ...) +} +\arguments{ +\item{x}{The \code{\link[=dist_spec]{dist_spec()}} to use} + +\item{...}{Not used} +} +\value{ +A vector of standard deviations. +} +\description{ +This works out the standard deviation of all the (parametric / +nonparametric) delay distributions combined in the passed \code{\link[=dist_spec]{dist_spec()}}. +} +\examples{ +# A fixed lognormal distribution with sd 5 and sd 1. +lognormal <- dist_spec( + sd = 5, sd = 1, max = 20, distribution = "lognormal" +) +sd(lognormal) + +# An uncertain gamma distribution with sd 3 and sd 2 +gamma <- dist_spec( + sd = 3, sd = 2, sd_sd = 0.5, sd_sd = 0.5, max = 20, + distribution = "gamma" +) +sd(gamma) + +# The sd of the sum of two distributions +sd(lognormal + gamma) +} +\author{ +Sebastian Funk +} diff --git a/man/trunc_opts.Rd b/man/trunc_opts.Rd index a449cede4..35c6f6ed0 100644 --- a/man/trunc_opts.Rd +++ b/man/trunc_opts.Rd @@ -4,12 +4,13 @@ \alias{trunc_opts} \title{Truncation Distribution Options} \usage{ -trunc_opts(dist = dist_spec()) +trunc_opts(dist = dist_spec("empty")) } \arguments{ \item{dist}{A delay distribution or series of delay distributions reflecting the truncation generated using \code{\link[=dist_spec]{dist_spec()}} or \code{\link[=estimate_truncation]{estimate_truncation()}}. -Default is an empty call to \code{\link[=dist_spec]{dist_spec()}}, i.e. no truncation} +Default is an call to \code{\link[=dist_spec]{dist_spec()}}, with `distribution = "empty", i.e. no +truncation} } \value{ A \verb{} object summarising the input truncation diff --git a/tests/testthat/setup.R b/tests/testthat/setup.R index ce0ed932d..d94a4a8ba 100644 --- a/tests/testthat/setup.R +++ b/tests/testthat/setup.R @@ -18,6 +18,6 @@ if (identical(Sys.getenv("NOT_CRAN"), "true")) { withr::defer(future::plan("sequential"), teardown_env()) ## process warning once as previous behaviour has been deprecated -empty <- suppressWarnings(dist_spec()) +empty <- suppressWarnings(dist_spec("empty")) diff --git a/tests/testthat/test-dist_spec.R b/tests/testthat/test-dist_spec.R index 3618f2370..1ca36c0c9 100644 --- a/tests/testthat/test-dist_spec.R +++ b/tests/testthat/test-dist_spec.R @@ -184,7 +184,7 @@ test_that("print.dist_spec correctly prints the parameters of the uncertain logn }) test_that("print.dist_spec correctly prints the parameters of an empty distribution", { - empty <- dist_spec() + empty <- dist_spec("empty") expect_output(print(empty), "Empty `dist_spec` distribution.") }) From 78ea512ca11306c37baa5f1b453e87a5595dcdfa Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Fri, 10 Nov 2023 16:09:45 +0000 Subject: [PATCH 002/129] deprecate "empty" distribution --- R/dist.R | 46 ++++++++++++++------------------- R/opts.R | 17 ++++++------ man/delay_opts.Rd | 6 ++--- man/dist_spec.Rd | 2 +- man/generation_time_opts.Rd | 7 +++-- man/trunc_opts.Rd | 5 ++-- tests/testthat/setup.R | 4 +-- tests/testthat/test-dist_spec.R | 6 ----- 8 files changed, 38 insertions(+), 55 deletions(-) diff --git a/R/dist.R b/R/dist.R index 9f6cca062..cd4f5462d 100644 --- a/R/dist.R +++ b/R/dist.R @@ -927,7 +927,7 @@ tune_inv_gamma <- function(lower = 2, upper = 21) { #' distribution = "gamma" #' ) dist_spec <- function(distribution = c( - "lognormal", "normal", "gamma", "fixed", "empty" + "lognormal", "normal", "gamma", "fixed" ), params_mean = c(), params_sd = c(), mean, sd, mean_sd = 0, sd_sd = 0, @@ -979,8 +979,15 @@ dist_spec <- function(distribution = c( )) { stop("Distributional parameters or a pmf can be specified, but not both.") } - distribution <- match.arg(distribution) + ## check if distribution is given as empty and warn about deprecation if so + if (distribution == "empty") { + deprecate_warn( + "2.0.0", + "dist_spec(distribution = 'must not be \"empty\"')", + detail = "Please use `fixed(0)` instead." + ) + } if (distribution == "fixed") { ## if integer fixed then can write the PMF @@ -1010,26 +1017,16 @@ dist_spec <- function(distribution = c( parametric = FALSE ) if (length(pmf) == 0) { - if (distribution == "empty") { ## empty - ret <- c(ret, list( - n = 0, - n_p = 0, - n_np = 0, - np_pmf = numeric(0), - parametric = logical(0) - )) - } else { ## parametric fixed - if (distribution == "fixed") { ## delta - pmf <- c(rep(0, params_mean), 1) - } else { - params <- params_mean - names(params) <- natural_params(distribution) - pmf <- dist_skel( - n = seq_len(max + 1) - 1, dist = TRUE, cum = FALSE, - model = distribution, params = params, max_value = max, - discrete = TRUE - ) - } + if (distribution == "fixed") { ## delta + pmf <- c(rep(0, params_mean), 1) + } else { + params <- params_mean + names(params) <- natural_params(distribution) + pmf <- dist_skel( + n = seq_len(max + 1) - 1, dist = TRUE, cum = FALSE, + model = distribution, params = params, max_value = max, + discrete = TRUE + ) } } else { ## nonparametric fixed pmf <- pmf[1:(max + 1)] @@ -1322,10 +1319,7 @@ sd.dist_spec <- function(x, ...) { #' print(gamma) print.dist_spec <- function(x, ...) { cat("\n") - if (x$n == 0) { - cat("Empty `dist_spec` distribution.\n") - return(invisible(NULL)) - } else if (x$n > 1) { + if (x$n > 1) { cat("Composite delay distribution:\n") } fixed_id <- 1 diff --git a/R/opts.R b/R/opts.R index 1e0c7dfd8..5eb4feea1 100644 --- a/R/opts.R +++ b/R/opts.R @@ -3,9 +3,8 @@ #' @description `r lifecycle::badge("stable")` #' Returns generation time parameters in a format for lower level model use. #' -#' @param dist A delay distribution or series of delay distributions generated -#' using [dist_spec()]. If no distribution is given a fixed generation time of -#' 1 will be assumed. +#' @param dist A delay distribution or series of delay distributions . If no +#' distribution is given a fixed generation time of 1 will be assumed. #' #' @param ... deprecated; use `dist` instead #' @param disease deprecated; use `dist` instead @@ -36,7 +35,7 @@ #' #' # An example generation time #' generation_time_opts(example_generation_time) -generation_time_opts <- function(dist = dist_spec(mean = 1), ..., +generation_time_opts <- function(dist = fixed(1), ..., disease, source, max = 14, fixed = FALSE, prior_weight) { deprecated_options_given <- FALSE @@ -104,8 +103,8 @@ generation_time_opts <- function(dist = dist_spec(mean = 1), ..., #' @description `r lifecycle::badge("stable")` #' Returns delay distributions formatted for usage by downstream #' functions. -#' @param dist A delay distribution or series of delay distributions generated -#' using [dist_spec()]. Default is an empty call to [dist_spec()], i.e. no delay +#' @param dist A delay distribution or series of delay distributions. Default is +#' an fixed distribution with of 0, [dist_spec()], i.e. no delay. #' @param ... deprecated; use `dist` instead #' @param fixed deprecated; use `dist` instead #' @return A `` object summarising the input delay distributions. @@ -128,7 +127,7 @@ generation_time_opts <- function(dist = dist_spec(mean = 1), ..., #' #' # Multiple delays (in this case twice the same) #' delay_opts(delay + delay) -delay_opts <- function(dist = dist_spec("empty"), ..., fixed = FALSE) { +delay_opts <- function(dist = fixed(0), ..., fixed = FALSE) { dot_options <- list(...) if (!is(dist, "dist_spec")) { ## could be old syntax if (is.list(dist)) { @@ -172,7 +171,7 @@ delay_opts <- function(dist = dist_spec("empty"), ..., fixed = FALSE) { #' #' @param dist A delay distribution or series of delay distributions reflecting #' the truncation generated using [dist_spec()] or [estimate_truncation()]. -#' Default is an empty call to [dist_spec()], i.e. no truncation +#' Default is fixed distribution with maximum 0, i.e. no truncation #' @return A `` object summarising the input truncation #' distribution. #' @@ -187,7 +186,7 @@ delay_opts <- function(dist = dist_spec("empty"), ..., fixed = FALSE) { #' #' # truncation dist #' trunc_opts(dist = dist_spec(mean = 3, sd = 2, max = 10)) -trunc_opts <- function(dist = dist_spec("empty")) { +trunc_opts <- function(dist = fixed(0)) { if (!is(dist, "dist_spec")) { if (is.list(dist)) { dist <- do.call(dist_spec, dist) diff --git a/man/delay_opts.Rd b/man/delay_opts.Rd index 576168c1e..171eba0ef 100644 --- a/man/delay_opts.Rd +++ b/man/delay_opts.Rd @@ -4,11 +4,11 @@ \alias{delay_opts} \title{Delay Distribution Options} \usage{ -delay_opts(dist = dist_spec("empty"), ..., fixed = FALSE) +delay_opts(dist = fixed(0), ..., fixed = FALSE) } \arguments{ -\item{dist}{A delay distribution or series of delay distributions generated -using \code{\link[=dist_spec]{dist_spec()}}. Default is an empty call to \code{\link[=dist_spec]{dist_spec()}}, i.e. no delay} +\item{dist}{A delay distribution or series of delay distributions. Default is +an fixed distribution with of 0, \code{\link[=dist_spec]{dist_spec()}}, i.e. no delay.} \item{...}{deprecated; use \code{dist} instead} diff --git a/man/dist_spec.Rd b/man/dist_spec.Rd index 260bb1a81..78c0a3af2 100644 --- a/man/dist_spec.Rd +++ b/man/dist_spec.Rd @@ -5,7 +5,7 @@ \title{Specify a distribution.} \usage{ dist_spec( - distribution = c("lognormal", "normal", "gamma", "fixed", "empty"), + distribution = c("lognormal", "normal", "gamma", "fixed"), params_mean = c(), params_sd = c(), mean, diff --git a/man/generation_time_opts.Rd b/man/generation_time_opts.Rd index 1b14e2885..aba37ea15 100644 --- a/man/generation_time_opts.Rd +++ b/man/generation_time_opts.Rd @@ -5,7 +5,7 @@ \title{Generation Time Distribution Options} \usage{ generation_time_opts( - dist = dist_spec(mean = 1), + dist = fixed(1), ..., disease, source, @@ -15,9 +15,8 @@ generation_time_opts( ) } \arguments{ -\item{dist}{A delay distribution or series of delay distributions generated -using \code{\link[=dist_spec]{dist_spec()}}. If no distribution is given a fixed generation time of -1 will be assumed.} +\item{dist}{A delay distribution or series of delay distributions . If no +distribution is given a fixed generation time of 1 will be assumed.} \item{...}{deprecated; use \code{dist} instead} diff --git a/man/trunc_opts.Rd b/man/trunc_opts.Rd index 35c6f6ed0..68fcff8c4 100644 --- a/man/trunc_opts.Rd +++ b/man/trunc_opts.Rd @@ -4,13 +4,12 @@ \alias{trunc_opts} \title{Truncation Distribution Options} \usage{ -trunc_opts(dist = dist_spec("empty")) +trunc_opts(dist = fixed(0)) } \arguments{ \item{dist}{A delay distribution or series of delay distributions reflecting the truncation generated using \code{\link[=dist_spec]{dist_spec()}} or \code{\link[=estimate_truncation]{estimate_truncation()}}. -Default is an call to \code{\link[=dist_spec]{dist_spec()}}, with `distribution = "empty", i.e. no -truncation} +Default is a fixed distribution of 0, i.e. no truncation.} } \value{ A \verb{} object summarising the input truncation diff --git a/tests/testthat/setup.R b/tests/testthat/setup.R index d94a4a8ba..e714ef9f1 100644 --- a/tests/testthat/setup.R +++ b/tests/testthat/setup.R @@ -18,6 +18,4 @@ if (identical(Sys.getenv("NOT_CRAN"), "true")) { withr::defer(future::plan("sequential"), teardown_env()) ## process warning once as previous behaviour has been deprecated -empty <- suppressWarnings(dist_spec("empty")) - - +empty <- suppressWarnings(fixed(0))) diff --git a/tests/testthat/test-dist_spec.R b/tests/testthat/test-dist_spec.R index 1ca36c0c9..f4b411c62 100644 --- a/tests/testthat/test-dist_spec.R +++ b/tests/testthat/test-dist_spec.R @@ -183,12 +183,6 @@ test_that("print.dist_spec correctly prints the parameters of the uncertain logn expect_output(print(lognormal_uncertain), "\\n Uncertain lognormal distribution with \\(untruncated\\) logmean 1\\.5 \\(SD 0\\.1\\) and logSD 0\\.5 \\(SD 0\\.1\\)\\n") }) -test_that("print.dist_spec correctly prints the parameters of an empty distribution", { - empty <- dist_spec("empty") - - expect_output(print(empty), "Empty `dist_spec` distribution.") -}) - test_that("print.dist_spec correctly prints the parameters of a combination of distributions", { lognormal <- dist_spec(mean = 1.5, sd = 0.5, max = 19, distribution = "lognormal") gamma <- dist_spec(mean = 3, sd = 2, mean_sd = 0.5, sd_sd = 0.5, max = 19, distribution = "gamma") From 92f185d6244a016a2613749b2fdc8432f6759976 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Mon, 13 Nov 2023 13:21:48 +0000 Subject: [PATCH 003/129] make sd S3 --- NAMESPACE | 2 ++ R/dist.R | 18 +++++++++++++----- 2 files changed, 15 insertions(+), 5 deletions(-) diff --git a/NAMESPACE b/NAMESPACE index 43beef233..94409271f 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -8,6 +8,7 @@ S3method(plot,estimate_infections) S3method(plot,estimate_secondary) S3method(plot,estimate_truncation) S3method(print,dist_spec) +S3method(sd,default) S3method(sd,dist_spec) S3method(summary,epinow) S3method(summary,estimate_infections) @@ -89,6 +90,7 @@ export(rt_opts) export(sample_approx_dist) export(save_estimate_infections) export(save_input) +export(sd) export(secondary_opts) export(set_dt_single_thread) export(setup_default_logging) diff --git a/R/dist.R b/R/dist.R index cd4f5462d..b5685f2f5 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1234,6 +1234,9 @@ mean.dist_spec <- function(x, ...) { return(ret) } + +#' @export +sd <- function(x, ...) UseMethod("sd") ##' Returns the standard deviation of one or more delay distribution ##' ##' This works out the standard deviation of all the (parametric / @@ -1293,6 +1296,10 @@ sd.dist_spec <- function(x, ...) { } return(ret) } +#' @export +sd.default <- function(x, ...) { + stats::sd(x, ...) +} #' Prints the parameters of one or more delay distributions #' @@ -1600,11 +1607,12 @@ process_dist <- function(params, lower_bounds, distribution) { stop("Parameter ", x, " must be numeric or normally distributed.") } }) - ## sample parameters if they are uncertain - samples <- lapply(names(params), function(x) { - rtruncnorm( - n = 2000, a = lower_bounds[x], - mean = mean.dist_spec(params[[x]]), sd = sd.dist_spec(params[[x]]) + samples <- lapply(names(params), function(x) { + rtruncnorm( + n = 2000, a = lower_bounds[x], + mean = mean(params[[x]]), sd = sd(params[[x]]) + ) + }) ) }) names(samples) <- names(params) From 20539690a6507782d953b03a8e1db28c3c86764f Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Mon, 13 Nov 2023 13:22:25 +0000 Subject: [PATCH 004/129] only generate samples if any params aren't natural --- R/dist.R | 15 +++++++++++---- 1 file changed, 11 insertions(+), 4 deletions(-) diff --git a/R/dist.R b/R/dist.R index b5685f2f5..f9e7b1fbe 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1607,17 +1607,24 @@ process_dist <- function(params, lower_bounds, distribution) { stop("Parameter ", x, " must be numeric or normally distributed.") } }) + unnatural_params <- setdiff(names(params), natural_params(distribution)) + if (length(unnatural_params) > 0) { + ## sample parameters if they are uncertain samples <- lapply(names(params), function(x) { rtruncnorm( n = 2000, a = lower_bounds[x], mean = mean(params[[x]]), sd = sd(params[[x]]) ) }) + names(samples) <- names(params) + ## generate natural parameters + converted_params <- convert_to_natural(samples, distribution) + } else { + converted_params <- list( + params_mean = vapply(params, mean, numeric(1), USE.NAMES = FALSE), + params_sd = vapply(params, sd, numeric(1), USE.NAMES = FALSE) ) - }) - names(samples) <- names(params) - ## generate natural parameters - converted_params <- convert_to_natural(samples, distribution) + } dist <- dist_spec( distribution = distribution, From ab1b175ee36a714e6dcd97fafb417e80ed53195f Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Fri, 17 Nov 2023 16:06:36 +0000 Subject: [PATCH 005/129] update stan model with new dist interface --- R/create.R | 29 +++++++++------- R/extract.R | 15 +++----- inst/stan/data/delays.stan | 4 --- inst/stan/data/simulation_delays.stan | 6 ++-- inst/stan/estimate_infections.stan | 20 +++++------ inst/stan/estimate_secondary.stan | 13 ++++--- inst/stan/estimate_truncation.stan | 11 +++--- inst/stan/functions/delays.stan | 49 ++++++++++++++------------- inst/stan/functions/pmfs.stan | 40 +++++++++------------- inst/stan/simulate_infections.stan | 4 +-- inst/stan/simulate_secondary.stan | 2 +- 11 files changed, 88 insertions(+), 105 deletions(-) diff --git a/R/create.R b/R/create.R index 182781cd7..efeb033a7 100644 --- a/R/create.R +++ b/R/create.R @@ -545,20 +545,17 @@ create_initial_conditions <- function(data) { init_fun <- function() { out <- list() if (data$delay_n_p > 0) { - lower_bounds <- rep(-Inf, data$delay_n_p) + lower_bounds <- rep(-Inf, data$delay_params_length) ## gamma - lower_bounds[data$dist == 1] <- 0 - out$delay_mean <- array(truncnorm::rtruncnorm( - n = data$delay_n_p, a = lower_bounds, - mean = data$delay_mean_mean, sd = data$delay_mean_sd * 0.1 - )) - out$delay_sd <- array(truncnorm::rtruncnorm( - n = data$delay_n_p, a = 0, - mean = data$delay_sd_mean, sd = data$delay_sd_sd * 0.1 + param_dist <- rep(data$dist, times = diff(data$params_groups)) + lower_bounds[data$dist == "gamma"] <- 0 + + out$delay_params <- array(truncnorm::rtruncnorm( + n = data$delay_params_length, a = lower_bounds, + mean = data$delay_params_mean, sd = data$delay_params_sd * 0.1 )) } else { - out$delay_mean <- array(numeric(0)) - out$delay_sd <- array(numeric(0)) + out$delay_params <- array(numeric(0)) } if (data$fixed == 0) { @@ -724,7 +721,7 @@ create_stan_delays <- function(..., weight = 1) { ## construct additional variables ret <- c(ret, list( types = sum(type_n > 0), - types_p = array(1L - combined_delays$fixed) + types_p = array(as.integer(combined_delays$parametric)) )) ## delay identifiers ret$types_id <- integer(0) @@ -741,6 +738,14 @@ create_stan_delays <- function(..., weight = 1) { ) ## calculate total np pmf length ret$np_pmf_length <- sum(combined_delays$np_pmf_length) + ## get non zero length param lengths + ret$params_groups <- array( + c(0, cumsum( + combined_delays$params_length[combined_delays$params_length > 0]) + ) + 1 + ) + ## calculate total param length + ret$params_length <- sum(combined_delays$params_length) ## assign prior weights ret$weight <- array(rep(weight, ret$n_p)) ## assign distribution diff --git a/R/extract.R b/R/extract.R index 8d4cb1232..8a8bd0844 100644 --- a/R/extract.R +++ b/R/extract.R @@ -221,20 +221,13 @@ extract_parameter_samples <- function(stan_fit, data, reported_dates, ] } if (data$delay_n_p > 0) { - out$delay_mean <- extract_parameter( - "delay_mean", samples, seq_len(data$delay_n_p) + out$delay_params <- extract_parameter( + "delay_params", samples, seq_len(data$delay_params_length) ) - out$delay_mean <- - out$delay_mean[, strat := as.character(time)][, time := NULL][, + out$delay_params <- + out$delay_params[, strat := as.character(time)][, time := NULL][, date := NULL ] - out$delay_sd <- extract_parameter( - "delay_sd", samples, seq_len(data$delay_n_p) - ) - out$delay_sd <- - out$delay_sd[, strat := as.character(time)][, time := NULL][, - date := NULL - ] } if (data$model_type == 1) { out$reporting_overdispersion <- extract_static_parameter("rep_phi", samples) diff --git a/inst/stan/data/delays.stan b/inst/stan/data/delays.stan index 7b55a66aa..4b8d0a5b4 100644 --- a/inst/stan/data/delays.stan +++ b/inst/stan/data/delays.stan @@ -1,10 +1,6 @@ int delay_n; // number of delay distributions int delay_n_p; // number of parametric delay distributions int delay_n_np; // number of nonparametric delay distributions - array[delay_n_p] real delay_mean_mean; // prior mean of mean delay distribution - array[delay_n_p] real delay_mean_sd; // prior sd of mean delay distribution - array[delay_n_p] real delay_sd_mean; // prior sd of sd of delay distribution - array[delay_n_p] real delay_sd_sd; // prior sd of sd of delay distribution array[delay_n_p] int delay_max; // maximum delay distribution array[delay_n_p] int delay_dist; // 0 = lognormal; 1 = gamma diff --git a/inst/stan/data/simulation_delays.stan b/inst/stan/data/simulation_delays.stan index 0ceeedcaa..bbac5d25a 100644 --- a/inst/stan/data/simulation_delays.stan +++ b/inst/stan/data/simulation_delays.stan @@ -1,8 +1,6 @@ int delay_n; // number of delay distribution distributions int delay_n_p; // number of parametric delay distributions int delay_n_np; // number of nonparametric delay distributions - array[n, delay_n_p] real delay_mean; // prior mean of mean delay distribution - array[n, delay_n_p] real delay_sd; // prior sd of sd of delay distribution array[delay_n_p] int delay_max; // maximum delay distribution array[delay_n_p] int delay_dist; // 0 = lognormal; 1 = gamma int delay_np_pmf_length; // number of nonparametric pmf elements @@ -10,6 +8,10 @@ array[delay_n_np + 1] int delay_np_pmf_groups; // links to ragged array array[delay_n_p] int delay_weight; + int delay_params_length; // number of parameters across all parametric delay distributions + array[n] vector[delay_params_length] delay_params; // ragged array of mean parameters for parametric delay distributions + array[delay_n_p + 1] int delay_params_groups; // links to ragged array + int delay_types; // number of delay types array[delay_n] int delay_types_p; // whether delay types are parametric array[delay_n] int delay_types_id; // whether delay types are parametric diff --git a/inst/stan/estimate_infections.stan b/inst/stan/estimate_infections.stan index e1d4d0159..b16f58315 100644 --- a/inst/stan/estimate_infections.stan +++ b/inst/stan/estimate_infections.stan @@ -48,8 +48,7 @@ parameters{ array[bp_n > 0 ? 1 : 0] real bp_sd; // standard deviation of breakpoint effect array[bp_n] real bp_effects; // Rt breakpoint effects // observation model - array[delay_n_p] real delay_mean; // mean of delays - array[delay_n_p] real delay_sd; // sd of delays + vector[delay_params_length] delay_params; // delay parameters simplex[week_effect] day_of_week_simplex;// day of week reporting effect array[obs_scale_sd > 0 ? 1 : 0] real frac_obs; // fraction of cases that are ultimately observed array[model_type] real rep_phi; // overdispersion of the reporting process @@ -71,7 +70,7 @@ transformed parameters { gt_rev_pmf = get_delay_rev_pmf( gt_id, delay_type_max[gt_id] + 1, delay_types_p, delay_types_id, delay_types_groups, delay_max, delay_np_pmf, - delay_np_pmf_groups, delay_mean, delay_sd, delay_dist, + delay_np_pmf_groups, delay_params, delay_params_groups, delay_dist, 1, 1, 0 ); R = update_Rt( @@ -92,7 +91,7 @@ transformed parameters { vector[delay_type_max[delay_id] + 1] delay_rev_pmf = get_delay_rev_pmf( delay_id, delay_type_max[delay_id] + 1, delay_types_p, delay_types_id, delay_types_groups, delay_max, delay_np_pmf, - delay_np_pmf_groups, delay_mean, delay_sd, delay_dist, + delay_np_pmf_groups, delay_params, delay_params_groups, delay_dist, 0, 1, 0 ); reports = convolve_to_report(infections, delay_rev_pmf, seeding_time); @@ -112,7 +111,7 @@ transformed parameters { vector[delay_type_max[trunc_id] + 1] trunc_rev_cmf = get_delay_rev_pmf( trunc_id, delay_type_max[trunc_id] + 1, delay_types_p, delay_types_id, delay_types_groups, delay_max, delay_np_pmf, - delay_np_pmf_groups, delay_mean, delay_sd, delay_dist, + delay_np_pmf_groups, delay_params, delay_params_groups, delay_dist, 0, 1, 1 ); obs_reports = truncate(reports[1:ot], trunc_rev_cmf, 0); @@ -130,8 +129,7 @@ model { } // penalised priors for delay distributions delays_lp( - delay_mean, delay_mean_mean, - delay_mean_sd, delay_sd, delay_sd_mean, delay_sd_sd, + delay_params, delay_params_mean, delay_params_sd, delay_params_groups, delay_dist, delay_weight ); if (estimate_r) { @@ -168,14 +166,12 @@ generated quantities { r = R_to_growth(R, gt_mean, gt_var); } else { // sample generation time - array[delay_n_p] real delay_mean_sample = - normal_rng(delay_mean_mean, delay_mean_sd); - array[delay_n_p] real delay_sd_sample = - normal_rng(delay_sd_mean, delay_sd_sd); + vector[delay_params_length] delay_params_sample = + to_vector(normal_rng(delay_params_mean, delay_params_sd)); vector[delay_type_max[gt_id] + 1] sampled_gt_rev_pmf = get_delay_rev_pmf( gt_id, delay_type_max[gt_id] + 1, delay_types_p, delay_types_id, delay_types_groups, delay_max, delay_np_pmf, - delay_np_pmf_groups, delay_mean_sample, delay_sd_sample, + delay_np_pmf_groups, delay_params_sample, delay_params_groups, delay_dist, 1, 1, 0 ); gt_mean = rev_pmf_mean(sampled_gt_rev_pmf, 1); diff --git a/inst/stan/estimate_secondary.stan b/inst/stan/estimate_secondary.stan index 77507a9ed..551320741 100644 --- a/inst/stan/estimate_secondary.stan +++ b/inst/stan/estimate_secondary.stan @@ -27,8 +27,7 @@ transformed data{ parameters{ // observation model - array[delay_n_p] real delay_mean; - array[delay_n_p] real delay_sd; // sd of delays + vector[delay_params_length] delay_params; simplex[week_effect] day_of_week_simplex; // day of week reporting effect array[obs_scale] real frac_obs; // fraction of cases that are ultimately observed array[model_type] real rep_phi; // overdispersion of the reporting process @@ -44,7 +43,7 @@ transformed parameters { delay_rev_pmf = get_delay_rev_pmf( delay_id, delay_type_max[delay_id] + 1, delay_types_p, delay_types_id, delay_types_groups, delay_max, delay_np_pmf, - delay_np_pmf_groups, delay_mean, delay_sd, delay_dist, + delay_np_pmf_groups, delay_params, delay_params_groups, delay_dist, 0, 1, 0 ); } else { @@ -65,7 +64,7 @@ transformed parameters { vector[delay_type_max[trunc_id]] trunc_rev_cmf = get_delay_rev_pmf( trunc_id, delay_type_max[trunc_id] + 1, delay_types_p, delay_types_id, delay_types_groups, delay_max, delay_np_pmf, - delay_np_pmf_groups, delay_mean, delay_sd, delay_dist, + delay_np_pmf_groups, delay_params, delay_params_groups, delay_dist, 0, 1, 1 ); secondary = truncate(secondary, trunc_rev_cmf, 0); @@ -75,10 +74,10 @@ transformed parameters { model { // penalised priors for delay distributions delays_lp( - delay_mean, delay_mean_mean, delay_mean_sd, delay_sd, delay_sd_mean, - delay_sd_sd, delay_dist, delay_weight + delay_params, delay_params_mean, delay_params_sd, delay_params_groups, + delay_dist, delay_weight ); - + // prior primary report scaling if (obs_scale) { frac_obs[1] ~ normal(obs_scale_mean, obs_scale_sd) T[0, 1]; diff --git a/inst/stan/estimate_truncation.stan b/inst/stan/estimate_truncation.stan index b5ffd673b..5761c2e74 100644 --- a/inst/stan/estimate_truncation.stan +++ b/inst/stan/estimate_truncation.stan @@ -28,8 +28,7 @@ transformed data{ } } parameters { - array[delay_n_p] real delay_mean; - array[delay_n_p] real delay_sd; // sd of delays + vector[delay_params_length] delay_params; real phi; real sigma; } @@ -41,7 +40,7 @@ transformed parameters{ vector[delay_type_max[trunc_id] + 1] trunc_rev_cmf = get_delay_rev_pmf( trunc_id, delay_type_max[trunc_id] + 1, delay_types_p, delay_types_id, delay_types_groups, delay_max, delay_np_pmf, - delay_np_pmf_groups, delay_mean, delay_sd, delay_dist, + delay_np_pmf_groups, delay_params, delay_params_groups, delay_dist, 0, 1, 1 ); { @@ -60,10 +59,10 @@ transformed parameters{ model { // priors for the log normal truncation distribution delays_lp( - delay_mean, delay_mean_mean, delay_mean_sd, delay_sd, delay_sd_mean, - delay_sd_sd, delay_dist, delay_weight + delay_params, delay_params_mean, delay_params_sd, delay_params_groups, + delay_dist, delay_weight ); - + phi ~ normal(0, 1) T[0,]; sigma ~ normal(0, 1) T[0,]; diff --git a/inst/stan/functions/delays.stan b/inst/stan/functions/delays.stan index 203594efa..558487fda 100644 --- a/inst/stan/functions/delays.stan +++ b/inst/stan/functions/delays.stan @@ -21,7 +21,7 @@ vector get_delay_rev_pmf( int delay_id, int len, array[] int delay_types_p, array[] int delay_types_id, array[] int delay_types_groups, array[] int delay_max, vector delay_np_pmf, array[] int delay_np_pmf_groups, - array[] real delay_mean, array[] real delay_sigma, array[] int delay_dist, + vector delay_params, array[] int delay_params_groups, array[] int delay_dist, int left_truncate, int reverse_pmf, int cumulative ) { // loop over delays @@ -30,10 +30,11 @@ vector get_delay_rev_pmf( int new_len; for (i in delay_types_groups[delay_id]:(delay_types_groups[delay_id + 1] - 1)) { if (delay_types_p[i]) { // parametric + int start = delay_params_groups[delay_types_id[i]]; + int end = delay_params_groups[delay_types_id[i] + 1] - 1; vector[delay_max[delay_types_id[i]] + 1] new_variable_pmf = discretised_pmf( - delay_mean[delay_types_id[i]], - delay_sigma[delay_types_id[i]], + delay_params[start:end], delay_max[delay_types_id[i]] + 1, delay_dist[delay_types_id[i]] ); @@ -75,30 +76,30 @@ vector get_delay_rev_pmf( } -void delays_lp(array[] real delay_mean, array[] real delay_mean_mean, array[] real delay_mean_sd, - array[] real delay_sd, array[] real delay_sd_mean, array[] real delay_sd_sd, +void delays_lp(vector delay_params, + vector delay_params_mean, vector delay_params_sd, + array[] int delay_params_groups, array[] int delay_dist, array[] int weight) { - int mean_delays = num_elements(delay_mean); - int sd_delays = num_elements(delay_sd); - if (mean_delays) { - for (s in 1:mean_delays) { - if (delay_mean_sd[s] > 0) { - // uncertain mean - target += normal_lpdf(delay_mean[s] | delay_mean_mean[s], delay_mean_sd[s]) * weight[s]; - // if a distribution with postive support only truncate the prior - if (delay_dist[s]) { - target += -normal_lccdf(0 | delay_mean_mean[s], delay_mean_sd[s]) * weight[s]; - } + int n_delays = num_elements(delay_params_groups) - 1; + if (n_delays == 0) { + return; + } + for (d in 1:n_delays) { + int start = delay_params_groups[d]; + int end = delay_params_groups[d + 1] - 1; + for (s in start:end) { + if (delay_params_sd[s] > 0) { + // uncertain mean + target += normal_lpdf( + delay_params[s] | delay_params_mean[s], delay_params_sd[s] + ) * weight[d]; + // if a distribution with postive support only truncate the prior + if (delay_dist[d] == 1) { + target += -normal_lccdf( + 0 | delay_params_mean[s], delay_params_sd[s] + ) * weight[d]; } } } - if (sd_delays) { - for (s in 1:sd_delays) { - if (delay_sd_sd[s] > 0) { - // uncertain sd - target += normal_lpdf(delay_sd[s] | delay_sd_mean[s], delay_sd_sd[s]) * weight[s]; - target += -normal_lccdf(0 | delay_sd_mean[s], delay_sd_sd[s]) * weight[s]; - } - } } } diff --git a/inst/stan/functions/pmfs.stan b/inst/stan/functions/pmfs.stan index 03fbec1f5..b50501a08 100644 --- a/inst/stan/functions/pmfs.stan +++ b/inst/stan/functions/pmfs.stan @@ -1,36 +1,28 @@ // Calculate the daily probability of reporting using parametric // distributions up to the maximum observed delay. -// If sigma is 0 all the probability mass is put on n. // Adapted from https://github.com/epiforecasts/epinowcast // @author Sam Abbott // @author Adrian Lison -vector discretised_pmf(real mu, real sigma, int n, int dist) { +// @author Sebastian Funk +vector discretised_pmf(vector params, int n, int dist) { vector[n] lpmf; - if (sigma > 0) { - vector[n] upper_lcdf; - if (dist == 0) { - for (i in 1:n) { - upper_lcdf[i] = lognormal_lcdf(i | mu, sigma); - } - } else if (dist == 1) { - real alpha = mu^2 / sigma^2; - real beta = mu / sigma^2; - for (i in 1:n) { - upper_lcdf[i] = gamma_lcdf(i | alpha, beta); - } - } else { - reject("Unknown distribution function provided."); + vector[n] upper_lcdf; + if (dist == 0) { + for (i in 1:n) { + upper_lcdf[i] = lognormal_lcdf(i | params[1], params[2]); + } + } else if (dist == 1) { + for (i in 1:n) { + upper_lcdf[i] = gamma_lcdf(i | params[1], params[2]); } - // discretise - lpmf[1] = upper_lcdf[1]; - lpmf[2:n] = log_diff_exp(upper_lcdf[2:n], upper_lcdf[1:(n-1)]); - // normalize - lpmf = lpmf - upper_lcdf[n]; } else { - // delta function - lpmf = rep_vector(negative_infinity(), n); - lpmf[n] = 0; + reject("Unknown distribution function provided."); } + // discretise + lpmf[1] = upper_lcdf[1]; + lpmf[2:n] = log_diff_exp(upper_lcdf[2:n], upper_lcdf[1:(n-1)]); + // normalize + lpmf = lpmf - upper_lcdf[n]; return(exp(lpmf)); } diff --git a/inst/stan/simulate_infections.stan b/inst/stan/simulate_infections.stan index d8448d047..3772c0652 100644 --- a/inst/stan/simulate_infections.stan +++ b/inst/stan/simulate_infections.stan @@ -42,7 +42,7 @@ generated quantities { gt_rev_pmf = get_delay_rev_pmf( gt_id, delay_type_max[gt_id] + 1, delay_types_p, delay_types_id, delay_types_groups, delay_max, delay_np_pmf, - delay_np_pmf_groups, delay_mean[i], delay_sd[i], delay_dist, + delay_np_pmf_groups, delay_params[i], delay_params_groups, delay_dist, 1, 1, 0 ); @@ -55,7 +55,7 @@ generated quantities { vector[delay_type_max[delay_id] + 1] delay_rev_pmf = get_delay_rev_pmf( delay_id, delay_type_max[delay_id] + 1, delay_types_p, delay_types_id, delay_types_groups, delay_max, delay_np_pmf, - delay_np_pmf_groups, delay_mean[i], delay_sd[i], delay_dist, + delay_np_pmf_groups, delay_params[i], delay_params_groups, delay_dist, 0, 1, 0 ); // convolve from latent infections to mean of observations diff --git a/inst/stan/simulate_secondary.stan b/inst/stan/simulate_secondary.stan index 36e6a0edd..9173ae367 100644 --- a/inst/stan/simulate_secondary.stan +++ b/inst/stan/simulate_secondary.stan @@ -36,7 +36,7 @@ generated quantities { vector[delay_type_max[delay_id] + 1] delay_rev_pmf = get_delay_rev_pmf( delay_id, delay_type_max[delay_id] + 1, delay_types_p, delay_types_id, delay_types_groups, delay_max, delay_np_pmf, - delay_np_pmf_groups, delay_mean[i], delay_sd[i], delay_dist, + delay_np_pmf_groups, delay_params[i], delay_params_groups, delay_dist, 0, 1, 0 ); From 524ebc20fb5fb9ae2c8308552aa3642a13230c1a Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Fri, 17 Nov 2023 16:09:51 +0000 Subject: [PATCH 006/129] update lognormal parameters --- R/dist.R | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/R/dist.R b/R/dist.R index f9e7b1fbe..9b5a97a64 100644 --- a/R/dist.R +++ b/R/dist.R @@ -114,16 +114,16 @@ dist_skel <- function(n, dist = FALSE, cum = TRUE, model, } } else if (model == "lognormal") { rdist <- function(n) { - rlnorm(n, params[["mean"]], params[["sd"]]) + rlnorm(n, params[["meanlog"]], params[["sdlog"]]) } pdist <- function(n) { - plnorm(n, params[["mean"]], params[["sd"]]) / - plnorm(max_value + 1, params[["mean"]], params[["sd"]]) + plnorm(n, params[["meanlog"]], params[["sdlog"]]) / + plnorm(max_value + 1, params[["meanlog"]], params[["sdlog"]]) } ddist <- function(n) { - (plnorm(n + 1, params[["mean"]], params[["sd"]]) - - plnorm(n, params[["mean"]], params[["sd"]])) / - plnorm(max_value + 1, params[["mean"]], params[["sd"]]) + (plnorm(n + 1, params[["meanlog"]], params[["sdlog"]]) - + plnorm(n, params[["meanlog"]], params[["sdlog"]])) / + plnorm(max_value + 1, params[["meanlog"]], params[["sdlog"]]) } } else if (model %in% "normal") { rdist <- function(n) { From dc0ce34c92c8251e8ab01c584067572078b17f8a Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Fri, 17 Nov 2023 16:10:09 +0000 Subject: [PATCH 007/129] return mean function to previous functionality --- R/dist.R | 41 +++++++++++++++++++++-------------------- man/mean.dist_spec.Rd | 3 ++- 2 files changed, 23 insertions(+), 21 deletions(-) diff --git a/R/dist.R b/R/dist.R index 9b5a97a64..c8e154cc4 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1182,7 +1182,8 @@ c.dist_spec <- function(...) { ##' Returns the mean of one or more delay distribution ##' ##' This works out the mean of all the (parametric / nonparametric) delay -##' distributions combined in the passed [dist_spec()]. +##' distributions combined in the passed [dist_spec()] (ignoring any uncertainty +##' in parameters) ##' ##' @param x The `` to use ##' @param ... Not used @@ -1208,28 +1209,28 @@ c.dist_spec <- function(...) { #' # The mean of the sum of two distributions #' mean(lognormal + gamma) mean.dist_spec <- function(x, ...) { - if (x$n > 1) { - stop("Cannot calculate mean of composite distributions.") - } + ret <- rep(.0, x$n) if (x$n_np > 0) { ## nonparametric - ret <- sum((seq_len(x$np_pmf_length) - 1) * x$np_pmf) - } else { + ret[!x$parametric] <- sum((seq_len(x$np_pmf_length) - 1) * x$np_pmf) + } + if (x$n_p > 0) { ## parametric - if (any(x$params_sd > 0)) { - stop("Cannot calculate mean of uncertain distribution") - } - if (x$dist == "lognormal") { - ret <- exp(x$params_mean[[1]] + x$params_mean[[2]]**2 / 2) - } else if (x$dist == "gamma") { - ret <- x$params_mean[[1]] / x$params_mean[[2]] - } else if (x$dist == "normal") { - ret <- x$params_mean[[1]] - } else if (x$dist == "fixed") { - ret <- x$params_mean[[1]] - } else { - stop("Don't know how to calculate mean of ", x$dist, " distribution.") - } + ret[x$parametric] <- vapply( + seq_along(which(x$parametric)), function(id) { + if (x$dist == "lognormal") { + ret <- exp(x$params_mean[[1]] + x$params_mean[[2]]**2 / 2) + } else if (x$dist == "gamma") { + ret <- x$params_mean[[1]] / x$params_mean[[2]] + } else if (x$dist == "normal") { + ret <- x$params_mean[[1]] + } else if (x$dist == "fixed") { + ret <- x$params_mean[[1]] + } else { + stop("Don't know how to calculate mean of ", x$dist, " distribution.") + } + }, .0 + ) } return(ret) } diff --git a/man/mean.dist_spec.Rd b/man/mean.dist_spec.Rd index af1a9ce4e..f5f5a0d95 100644 --- a/man/mean.dist_spec.Rd +++ b/man/mean.dist_spec.Rd @@ -16,7 +16,8 @@ A vector of means. } \description{ This works out the mean of all the (parametric / nonparametric) delay -distributions combined in the passed \code{\link[=dist_spec]{dist_spec()}}. +distributions combined in the passed \code{\link[=dist_spec]{dist_spec()}} (ignoring any uncertainty +in parameters) } \examples{ # A fixed lognormal distribution with mean 5 and sd 1. From bbec631aee8065e09f682278495f7a3b65994546 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Fri, 17 Nov 2023 16:10:41 +0000 Subject: [PATCH 008/129] update data --- data-raw/generation-time.R | 9 +++------ data-raw/incubation-period.R | 9 +++------ data-raw/reporting-delay.R | 7 +------ data/example_generation_time.rda | Bin 331 -> 326 bytes data/example_incubation_period.rda | Bin 343 -> 340 bytes data/example_reporting_delay.rda | Bin 408 -> 407 bytes 6 files changed, 7 insertions(+), 18 deletions(-) diff --git a/data-raw/generation-time.R b/data-raw/generation-time.R index 5c03e1c22..734dffacf 100644 --- a/data-raw/generation-time.R +++ b/data-raw/generation-time.R @@ -10,12 +10,9 @@ library(here) ## Load raw MCMC output gi <- setDT(readRDS(here("data-raw", "gi.rds"))) ## Check mean and standard deviation -example_generation_time <- dist_spec( - mean = median(gi$mean), - mean_sd = sd(gi$mean), - sd = median(gi$sd), - sd_sd = sd(gi$sd), - dist = "gamma", +example_generation_time <- gamma( + mean = normal(median(gi$mean), sd(gi$mean)), + sd = normal(median(gi$sd), sd(gi$sd)), max = 14L ) diff --git a/data-raw/incubation-period.R b/data-raw/incubation-period.R index fe25845b0..8a234d8a5 100644 --- a/data-raw/incubation-period.R +++ b/data-raw/incubation-period.R @@ -3,12 +3,9 @@ library(EpiNow2) ## COVID-19 incubation period from Lauer et al., ## https://doi.org/10.7326/M20-0504 -example_incubation_period <- dist_spec( - mean = 1.621, - mean_sd = 0.0640, - sd = 0.418, - sd_sd = 0.0691, - dist = "lognormal", +example_incubation_period <- lognormal( + meanlog = normal(1.621, 0.0640), + sdlog = normal(0.418, 0.0691), max = 14L ) diff --git a/data-raw/reporting-delay.R b/data-raw/reporting-delay.R index 05503f3d1..b8ee2e832 100644 --- a/data-raw/reporting-delay.R +++ b/data-raw/reporting-delay.R @@ -2,11 +2,6 @@ library(EpiNow2) ## example reporting delay -example_reporting_delay <- dist_spec( - mean = convert_to_logmean(2, 1), - sd = convert_to_logsd(2, 1), - max = 10, - dist = "lognormal" -) +example_reporting_delay <- lognormal(mean = 2, sd = 1, max = 10L) usethis::use_data(example_reporting_delay, overwrite = TRUE) diff --git a/data/example_generation_time.rda b/data/example_generation_time.rda index 58105081f79a776813811a44a23cf779d23e708b..84342ec58382add31e67a618a517b92b44076944 100644 GIT binary patch literal 326 zcmV-M0lEG{T4*^jL0KkKSq`<(Pyhh{f8YN*NPrLk5CFs=Q$Vlh-a-OU0DvR_1ONa5 zVIV*uumKoAX{1bwew1dRp{JuLXxeHtWXb5$3K#$Y00000002mlr6y!e000dd4FCf{ zbQ(u_MvItGRxz?m>Z@%@9H)hlCc`D8_xM@e3S!Vw4rZ~Fi2yLzWE4sCF!|3~V9T2N zpg}Dpd0WRvUA!eZp4__GFkFKRLBJqsA!%v>jVHXoh6=F&lr_glOVzB*NS^O@AV}Jv zf>4qa+ZB?dhQF)ort50ktI~6zP!@)3Jh<~ZfB*mUN`MFe5Jkj*5J0cz+&}^VAP~R+006K8 z00;>{Kozh77(i*HLsJy=^q|S&m?5T3Fej22X{d7m1i%1H000005+q6Lk16Cp0j7ZU z0BH39G--vl%}?-xN@D^N#A9T|bg}9wCaZ-5Lv5o-b}-na^x2%0bTLm=2pFz+0er=L z<0bzYveYDk#(`lNXR_ZqyjfKqDrBdHD?wXHWdt+=;9#H=L7AaWP$ZyeYy+)=IoaQO zzzP6Jg2iTh>I)PSM3>aw=kxgRo3mumx7P@!q@@*VI!_F40=_VYP;`MtUie%Gz+>uTcBodAD!a%`jiva)t diff --git a/data/example_incubation_period.rda b/data/example_incubation_period.rda index 60dd06d26d663033a2535e2f1cde614a919cb46b..0d39abaedb008eb18852fcf386cac5dd1439b970 100644 GIT binary patch delta 317 zcmV-D0mA;*0@MN(LRx4!F+o`-Q(3~}lmY+%|9}7gJCPM4e`%zq^)!Y?NYg>-4XL2? 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See [rgamma()] for -#' distribution information. +#' @description `r lifecycle::badge("deprecated")` +#' Deprecated; use [gamma()] instead to define a gamma distribution. #' #' @param shape Numeric, shape parameter of the gamma distribution. #' @@ -350,6 +348,11 @@ gamma_dist_def <- function(shape, shape_sd, mean, mean_sd, sd, sd_sd, max_value, samples) { + lifecycle::deprecate_warn( + "2.0.0", "gamma_dist_def()", "gamma()", + "The function will be removed completely in version 2.1.0." + ) + if (missing(shape) && missing(scale) && !missing(mean) && !missing(sd)) { if (!missing(mean_sd)) { mean <- truncnorm::rtruncnorm(samples, a = 0, mean = mean, sd = mean_sd) @@ -391,7 +394,7 @@ gamma_dist_def <- function(shape, shape_sd, #' Generate a Log Normal Distribution Definition Based on Parameter Estimates #' -#' @description `r lifecycle::badge("soft-deprecated")` +#' @description `r lifecycle::badge("deprecated")` #' Generates a distribution definition when only parameter estimates #' are available for log normal distributed parameters. See [rlnorm()] for #' distribution information. @@ -434,6 +437,11 @@ lognorm_dist_def <- function(mean, mean_sd, sd, sd_sd, max_value, samples, to_log = FALSE) { + lifecycle::deprecate_warn( + "2.0.0", "lognorm_dist_def()", "lognormal()", + "The function will be removed completely in version 2.1.0." + ) + transform_mean <- function(mu, sig) { mean_location <- log(mu^2 / sqrt(sig^2 + mu^2)) mean_location diff --git a/man/gamma_dist_def.Rd b/man/gamma_dist_def.Rd index 7fa2af023..bb2a9fce1 100644 --- a/man/gamma_dist_def.Rd +++ b/man/gamma_dist_def.Rd @@ -43,10 +43,8 @@ Samples outside of this range are resampled.} A \verb{} defining the distribution as used by \code{\link[=dist_skel]{dist_skel()}} } \description{ -\ifelse{html}{\href{https://lifecycle.r-lib.org/articles/stages.html#soft-deprecated}{\figure{lifecycle-soft-deprecated.svg}{options: alt='[Soft-deprecated]'}}}{\strong{[Soft-deprecated]}} -Generates a distribution definition when only parameter estimates -are available for gamma distributed parameters. See \code{\link[=rgamma]{rgamma()}} for -distribution information. +\ifelse{html}{\href{https://lifecycle.r-lib.org/articles/stages.html#deprecated}{\figure{lifecycle-deprecated.svg}{options: alt='[Deprecated]'}}}{\strong{[Deprecated]}} +Deprecated; use \code{\link[=gamma]{gamma()}} instead to define a gamma distribution. } \examples{ # using estimated shape and scale diff --git a/man/lognorm_dist_def.Rd b/man/lognorm_dist_def.Rd index 56e3aa4a2..11db86014 100644 --- a/man/lognorm_dist_def.Rd +++ b/man/lognorm_dist_def.Rd @@ -26,7 +26,7 @@ Samples outside of this range are resampled.} A \verb{} defining the distribution as used by \code{\link[=dist_skel]{dist_skel()}} } \description{ -\ifelse{html}{\href{https://lifecycle.r-lib.org/articles/stages.html#soft-deprecated}{\figure{lifecycle-soft-deprecated.svg}{options: alt='[Soft-deprecated]'}}}{\strong{[Soft-deprecated]}} +\ifelse{html}{\href{https://lifecycle.r-lib.org/articles/stages.html#deprecated}{\figure{lifecycle-deprecated.svg}{options: alt='[Deprecated]'}}}{\strong{[Deprecated]}} Generates a distribution definition when only parameter estimates are available for log normal distributed parameters. See \code{\link[=rlnorm]{rlnorm()}} for distribution information. From f26136c05a3a1972e1d4554dbd54d5ef82b8594a Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Tue, 21 Nov 2023 09:40:56 +0000 Subject: [PATCH 010/129] use natural parametrisations in dist_def functions --- R/dist.R | 14 ++++++-------- 1 file changed, 6 insertions(+), 8 deletions(-) diff --git a/R/dist.R b/R/dist.R index 47c11511b..b5e78eee3 100644 --- a/R/dist.R +++ b/R/dist.R @@ -362,7 +362,7 @@ gamma_dist_def <- function(shape, shape_sd, } scale <- sd^2 / mean shape <- mean / scale - scale <- 1 / scale + rate <- 1 / scale } else { if (!missing(shape_sd)) { shape <- truncnorm::rtruncnorm( @@ -383,9 +383,8 @@ gamma_dist_def <- function(shape, shape_sd, params = purrr::list_transpose( list( shape = shape, - scale = scale - ), - simplify = FALSE + rate = rate + ) ), max_value = rep(max_value, samples) ) @@ -478,10 +477,9 @@ lognorm_dist_def <- function(mean, mean_sd, model = rep("lognormal", samples), params = purrr::list_transpose( list( - mean = means, - sd = sds - ), - simplify = FALSE + meanlog = means, + sdlog = sds + ) ), max_value = rep(max_value, samples) ) From 52c51aedac9fc1972caa557acee2d5a0bdb57337 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Tue, 21 Nov 2023 09:45:12 +0000 Subject: [PATCH 011/129] deprecate dist_spec --- R/dist.R | 242 ++++++++++++++++++++--------------- R/get.R | 25 ++-- R/opts.R | 6 +- man/dist_spec.Rd | 77 ++++------- man/dist_spec_plus.Rd | 4 +- man/dot-dist_spec.Rd | 67 ++++++++++ man/generation_time_opts.Rd | 2 +- man/get_dist.Rd | 5 +- man/get_generation_time.Rd | 5 +- man/get_incubation_period.Rd | 5 +- man/get_seeding_time.Rd | 6 +- man/plus-.dist_spec.Rd | 4 +- man/trunc_opts.Rd | 2 +- 13 files changed, 259 insertions(+), 191 deletions(-) create mode 100644 man/dot-dist_spec.Rd diff --git a/R/dist.R b/R/dist.R index b5e78eee3..4bd63c7c5 100644 --- a/R/dist.R +++ b/R/dist.R @@ -859,59 +859,19 @@ tune_inv_gamma <- function(lower = 2, upper = 21) { #' Specify a distribution. #' -#' @description `r lifecycle::badge("stable")` -#' Defines the parameters of a supported distribution for use in onward -#' modelling. Multiple distribution families are supported - see the -#' documentation for `family` for details. Alternatively, a nonparametric -#' distribution can be specified using the \code{pmf} argument. -#' This function provides distribution -#' functionality in [delay_opts()], [generation_time_opts()], and -#' [trunc_opts()]. -#' -#' @param mean Numeric. If the only non-zero summary parameter -#' then this is the fixed interval of the distribution. If the `sd` is -#' non-zero then this is the mean of the distribution given by \code{dist}. -#' If this is not given a vector of empty vectors is returned. -#' -#' @param sd Numeric, defaults to 0. Sets the standard deviation of the -#' distribution. -#' -#' @param mean_sd Numeric, defaults to 0. Sets the standard deviation of the -#' uncertainty around the mean of the distribution assuming a normal -#' prior. -#' -#' @param sd_sd Numeric, defaults to 0. Sets the standard deviation of the -#' uncertainty around the sd of the distribution assuming a normal prior. -#' -#' @param distribution Character, defaults to "lognormal". The (discretised -#' distribution to be used. If sd == 0 then the distribution is fixed and a -#' delta function is used. If sd > 0 then the distribution is discretised and -#' truncated. -#' -#' The following distributions are currently supported: -#' -#' - "lognormal" - a lognormal distribution. For this distribution `mean` -#' is the mean of the natural logarithm of the delay (on the log scale) and -#' `sd` is the standard deviation of the natural logarithm of the delay. +#' @description `r lifecycle::badge("deprecated")` +#' This function is deprecated as a user-facing function (while its +#' functionality is still used internally). Construct distributions using +#' the corresponding distribution function such as [gamma()], [lognormal()], +#' [normal()] or [fixed()] instead. #' -#' - "gamma" - a gamma distribution. For this distribution `mean` is the -#' mean of the delay and `sd` is the standard deviation of the delay. During -#' model fitting these are then transformed to the shape and scale of the gamma -#' distribution. +#' @param mean Deprecated; use `params_mean` instead. #' -#' When `distribution` is the default lognormal distribution the other function -#' arguments have the following definition: -#' - `mean` is the mean of the natural logarithm of the delay (on the -#' log scale). -#' - `sd` is the standard deviation of the natural logarithm of the delay. +#' @param sd Deprecated; use `params_mean` instead. #' -#' @param max Numeric, maximum value of the distribution. The distribution will -#' be truncated at this value. +#' @param mean_sd Deprecated; use `params_sd` instead. #' -#' @param pmf Numeric, a vector of values that represent the (nonparametric) -#' probability mass function of the delay (starting with 0); defaults to an -#' empty vector corresponding to a parametric specification of the distribution -#' (using \code{mean}, \code{sd} and corresponding uncertainties) +#' @param sd_sd Deprecated; use `params_sd` instead. #' #' @param fixed Deprecated, use [fix_dist()] instead #' as coming from fixed (vs uncertain) distributions. Overrides any values @@ -922,22 +882,26 @@ tune_inv_gamma <- function(lower = 2, upper = 21) { #' @author Sebastian Funk #' @author Sam Abbott #' @importFrom rlang warn arg_match +#' @inheritParams .dist_spec #' @export -#' @examples -#' # A fixed lognormal distribution with mean 5 and sd 1. -#' dist_spec(mean = 5, sd = 1, max = 20, distribution = "lognormal") -#' -#' # An uncertain gamma distribution with mean 3 and sd 2 -#' dist_spec( -#' mean = 3, sd = 2, mean_sd = 0.5, sd_sd = 0.5, max = 20, -#' distribution = "gamma" -#' ) dist_spec <- function(distribution = c( "lognormal", "normal", "gamma", "fixed" ), - params_mean = c(), params_sd = c(), - mean, sd, mean_sd = 0, sd_sd = 0, + params_mean = numeric(0), params_sd = numeric(0), + mean, sd = 0, mean_sd = 0, sd_sd = 0, max = Inf, pmf = numeric(0), fixed = FALSE) { + + lifecycle::deprecate_warn( + "2.0.0", + "dist_spec()", + details = c( + paste0( + "Please use distribution functions such as `gamma` or `lognormal` ", + "instead." + ), + "The function will become internal only in version 2.1.0." + ) + ) ## deprecate previous behaviour warn( message = paste( @@ -952,37 +916,102 @@ dist_spec <- function(distribution = c( ) ## check for deprecated parameters if (!missing(fixed)) { - deprecate_warn( + lifecycle::deprecate_warn( "2.0.0", "dist_spec(fixed)", - "fix_dist()", - "The argument will be removed completely in version 2.1.0." + "fix_dist()" ) + params_sd <- c() } ## check for deprecated parameters if (!all(missing(mean), missing(sd), missing(mean_sd), missing(sd_sd)) && - (!missing(params_mean || !missing(params_sd)))) { - stop("Distributional should not be given as `mean`, `sd`, etc. ", + (length(params_mean) > 0 || length(params_sd) > 0)) { + stop("Distributional parameters should not be given as `mean`, `sd`, etc. ", "in addition to `params_mean` or `params_sd`") } - call <- match.call() - for (deprecated_arg in c("mean", "sd", "mean_sd", "sd_sd")) { - if (!is.null(call[[deprecated_arg]])) { - deprecate_warn( - "2.0.0", - paste0("dist_spec(", deprecated_arg, ")"), - "dist_spec(param)", - "The argument will be removed completely in version 2.1.0." + if (!all(missing(mean), missing(sd), missing(mean_sd), missing(sd_sd))) { + distribution <- match.arg(distribution) + if (sd == 0 && mean_sd == 0 && sd_sd == 0) { + distribution <- "fixed" + } + ## deprecated arguments given + if (distribution == "lognormal") { + params_mean <- c(meanlog = mean, sdlog = sd) + params_sd <- c(meanlog = mean_sd, sdlog = sd_sd) + } else if (distribution == "gamma") { + temp_dist <- gamma( + mean = normal(mean, mean_sd), + sd = normal(sd, sd_sd) ) - params[[deprecated_arg]] <- get(deprecated_arg) + params_mean <- temp_dist$params_mean + params_sd <- temp_dist$params_sd + } else if (distribution == "normal") { + params_mean <- c(mean = mean, sd = sd) + params_sd <- c(mean = mean_sd, sd = sd_sd) + } else if (distribution == "fixed") { + params_mean <- mean + params_sd <- c() } } - ## check if parametric or nonparametric + return(.dist_spec(distribution, params_mean, params_sd, max, pmf)) +} + +#' Specify a distribution. +#' +#' @description `r lifecycle::badge("stable")` +#' Defines the parameters of a supported distribution for use in onward +#' modelling. Multiple distribution families are supported - see the +#' documentation for `family` for details. Alternatively, a nonparametric +#' distribution can be specified using the \code{pmf} argument. +#' This function provides distribution +#' functionality in [delay_opts()], [generation_time_opts()], and +#' [trunc_opts()]. +#' +#' @param params_mean Numeric. Central values of the parameters of the +#' distribution as defined in [natural_params(). +#' +#' @param params_sd Numeric. Standard deviations of the parameters of the +#' distribution as defined in [natural_params(). +#' +#' @param distribution Character, defaults to "lognormal". The (discretised) +#' distribution to be used. Can be "lognormal", "gamma", "normal" or "fixed". +#' The corresponding parameters (defined in [natural_parameters()]) are passed +#' as `params_mean`, and their uncertainty as `params_sd`. +#' +#' @param max Numeric, maximum value of the distribution. The distribution will +#' be truncated at this value. Default: `Inf`, i.e. no maximum. +#' +#' @param pmf Numeric, a vector of values that represent the (nonparametric) +#' probability mass function of the delay (starting with 0); defaults to an +#' empty vector corresponding to a parametric specification of the distribution +#' (using \code{params_mean}, and \code{params_sd}. +#' +#' @return A `dist_spec` object defining the distribution. +#' +#' @author Sebastian Funk +#' @author Sam Abbott +#' @importFrom rlang warn +#' @keywords internal +#' @examples +#' # A fixed lognormal distribution with mean 5 and sd 1. +#' .dist_spec( +#' params_mean = c(meanlog = 5, sdlog = 1), max = 20, +#' distribution = "lognormal" +#' ) +#' +#' # An uncertain gamma distribution with mean 3 and sd 2 +#' .dist_spec( +#' params_mean = c(alpha = 3, beta = 0.5), +#' params_sd = c(alpha = 75, beta = 25) +#' distribution = "gamma" +#' ) +.dist_spec <- function(distribution = c( + "lognormal", "normal", "gamma", "fixed" + ), + params_mean = numeric(0), params_sd = numeric(0), + max = Inf, pmf = numeric(0)) { if (length(pmf) > 0 && - !all( - missing(distribution), missing(params_mean), missing(params_sd), - missing(mean), missing(sd), missing(mean_sd), missing(sd_sd) - )) { + !(length(params_mean) == 0 && length(params_sd) == 0)) { stop("Distributional parameters or a pmf can be specified, but not both.") } distribution <- match.arg(distribution) @@ -995,26 +1024,41 @@ dist_spec <- function(distribution = c( ) } + if (length(params_sd) == 0) { + params_sd <- rep(0, length(params_mean)) + } + if (distribution == "fixed") { ## if integer fixed then can write the PMF if (as.integer(params_mean) == params_mean) { max <- params_mean - parametric <- TRUE - } else { parametric <- FALSE + } else { + parametric <- TRUE } - if (length(params_sd) > 0 && any(params_sd) > 0) { + if (any(params_sd > 0)) { stop("Fixed parameters cannot have a nonzero standard deviation.") } - params_sd <- numeric(0) } else { ## if PMF is given, set max if (is.infinite(max) && length(pmf) > 0) { max <- length(pmf) - 1 } - parametric <- all(params_sd == 0) && is.finite(max) + parametric <- any(params_sd > 0) || is.infinite(max) } if (parametric) { ## calculate pmf + ret <- list( + params_mean = params_mean, + params_sd = params_sd, + dist = distribution, + max = max, + n = 1, + n_p = 1, + n_np = 0, + np_pmf = numeric(0), + parametric = TRUE + ) + } else { ret <- list( params_mean = numeric(0), params_sd = numeric(0), @@ -1046,18 +1090,6 @@ dist_spec <- function(distribution = c( np_pmf = pmf )) } - } else { - ret <- list( - params_mean = params_mean, - params_sd = params_sd, - dist = distribution, - max = max, - n = 1, - n_p = 1, - n_np = 0, - np_pmf = numeric(0), - parametric = TRUE - ) } ret <- purrr::map(ret, array) sum_args <- grep("(^n$|^n_$)", names(ret)) @@ -1075,10 +1107,10 @@ dist_spec <- function(distribution = c( #' distribution function is truncated at a specified tolerance level, ensuring #' numeric stability. #' -#' @param e1 The first delay distribution (from a call to [dist_spec()]) to +#' @param e1 The first delay distribution (of type [dist_spec()]) to #' combine. #' -#' @param e2 The second delay distribution (from a call to [dist_spec()]) to +#' @param e2 The second delay distribution (of type [dist_spec()]) to #' combine. #' #' @param tolerance A numeric value that sets the cumulative probability @@ -1099,7 +1131,7 @@ dist_spec_plus <- function(e1, e2, tolerance = 0.001) { ## process delay distributions delays <- c(e1, e2) ## combine any nonparametric delays that can be combined - if (sum(delays$fixed) > 1) { + if (sum(!delays$parametric) > 1) { new_pmf <- 1L group_starts <- c(1L, cumsum(delays$np_pmf_length) + 1L) for (i in seq_len(length(group_starts) - 1L)) { @@ -1115,7 +1147,11 @@ dist_spec_plus <- function(e1, e2, tolerance = 0.001) { new_pmf <- new_pmf / sum(new_pmf) } delays$np_pmf <- new_pmf - delays$fixed <- c(1, rep(0, delays$n_p)) + delays$np_pmf_length <- length(delays$np_pmf) + delays$params_length <- c( + 0, delays$params_length[delays$parametric == TRUE] + ) + delays$parametric <- array(c(FALSE, rep(TRUE, delays$n_p))) delays$n_np <- 1 delays$n <- delays$n_p + 1 } @@ -1560,12 +1596,12 @@ fixed <- function(value) { } else if (is.numeric(params$value)) { fixed_value <- params$value } - return(dist_spec(params_mean = fixed_value, distribution = "fixed")) + return(.dist_spec(params_mean = fixed_value, distribution = "fixed")) } ##' @export pmf <- function(x) { - return(dist_spec(pmf = x)) + return(.dist_spec(pmf = x)) } natural_params <- function(distribution) { @@ -1633,7 +1669,7 @@ process_dist <- function(params, lower_bounds, distribution) { ) } - dist <- dist_spec( + dist <- .dist_spec( distribution = distribution, params_mean = converted_params$params_mean, params_sd = converted_params$params_sd, diff --git a/R/get.R b/R/get.R index ef4fbb859..b8e47537c 100644 --- a/R/get.R +++ b/R/get.R @@ -161,7 +161,7 @@ get_regional_results <- function(regional_output, #' @description `r lifecycle::badge("deprecated")` #' #' This function has been deprecated. Please specify a distribution -#' using [dist_spec()] instead. +#' using functions such as [gamma()] or [lognormal()] instead. #' #' @param data A `` in the format of `generation_times`. #' @@ -177,12 +177,17 @@ get_regional_results <- function(regional_output, #' @return A list defining a distribution #' #' @author Sam Abbott -#' @seealso [dist_spec()] #' @export get_dist <- function(data, disease, source, max_value = 14, fixed = FALSE) { lifecycle::deprecate_warn( - "2.0.0", "get_dist()", "dist_spec()", - "The function will be removed completely in version 2.1.0." + "2.0.0", "get_dist()", + details = c( + paste0( + "Please use distribution functions such as `gamma` or `lognormal` ", + "instead." + ), + "The function will be removed completely in version 2.1.0." + ) ) target_disease <- disease target_source <- source @@ -202,12 +207,11 @@ get_dist <- function(data, disease, source, max_value = 14, fixed = FALSE) { #' #' Extracts a literature distribution from `generation_times`. #' This function has been deprecated. Please specify a distribution -#' using [dist_spec()] instead. +#' using functions such as [gamma()] or [lognormal()] instead. #' #' @inheritParams get_dist #' @inherit get_dist #' @export -#' @seealso [dist_spec()] #' @author Sam Abbott get_generation_time <- function(disease, source, max_value = 14, fixed = FALSE) { @@ -232,13 +236,12 @@ get_generation_time <- function(disease, source, max_value = 14, #' #' Extracts a literature distribution from `generation_times`. #' This function has been deprecated. Please specify a distribution -#' using [dist_spec()] instead +#' using functions such as [gamma()] or [lognormal()] instead. #' #' @inheritParams get_dist #' @inherit get_dist #' @author Sam Abbott #' @export -#' @seealso [dist_spec()] get_incubation_period <- function(disease, source, max_value = 14, fixed = FALSE) { lifecycle::deprecate_warn( @@ -299,8 +302,10 @@ get_regions_with_most_reports <- function(reported_cases, ##' ##' The seeding time is set to the mean of the specified delays, constrained ##' to be at least the maximum generation time -##' @param delays Delays as specified using [dist_spec()] -##' @param generation_time Generation time as specified using [dist_spec()] +##' @param delays Delays specified using distribution functions such as +##' [gamma()] or [lognormal()] +##' @param generation_time Generation specified using distribution functions +##' such as [gamma()] or [lognormal()] ##' @return An integer seeding time ##' @author Sebastian Funk get_seeding_time <- function(delays, generation_time) { diff --git a/R/opts.R b/R/opts.R index 5eb4feea1..56099dda0 100644 --- a/R/opts.R +++ b/R/opts.R @@ -19,7 +19,7 @@ #' @author Sebastian Funk #' @author Sam Abbott #' @seealso [convert_to_logmean()] [convert_to_logsd()] -#' [bootstrapped_dist_fit()] [dist_spec()] +#' [bootstrapped_dist_fit()] [gamma()] [lognormal()] [fixed()] #' @export #' @examples #' # default settings with a fixed generation time of 1 @@ -85,8 +85,8 @@ generation_time_opts <- function(dist = fixed(1), ..., } if (deprecated_options_given) { warning( - "The generation time distribution must be given to ", - "`generation_time_opts` using a call to `dist_spec`. ", + "The generation time distribution should be given to ", + "`generation_time_opts` using a `dist_spec`. ", "This behaviour has changed from previous versions of `EpiNow2` and ", "any code using it may need to be updated as any other ways of ", "specifying the generation time are deprecated and will be removed in ", diff --git a/man/dist_spec.Rd b/man/dist_spec.Rd index 78c0a3af2..d8f324669 100644 --- a/man/dist_spec.Rd +++ b/man/dist_spec.Rd @@ -6,10 +6,10 @@ \usage{ dist_spec( distribution = c("lognormal", "normal", "gamma", "fixed"), - params_mean = c(), - params_sd = c(), + params_mean = numeric(0), + params_sd = numeric(0), mean, - sd, + sd = 0, mean_sd = 0, sd_sd = 0, max = Inf, @@ -18,52 +18,32 @@ dist_spec( ) } \arguments{ -\item{distribution}{Character, defaults to "lognormal". The (discretised -distribution to be used. If sd == 0 then the distribution is fixed and a -delta function is used. If sd > 0 then the distribution is discretised and -truncated. +\item{distribution}{Character, defaults to "lognormal". The (discretised) +distribution to be used. Can be "lognormal", "gamma", "normal" or "fixed". +The corresponding parameters (defined in \code{\link[=natural_parameters]{natural_parameters()}}) are passed +as \code{params_mean}, and their uncertainty as \code{params_sd}.} -The following distributions are currently supported: -\itemize{ -\item "lognormal" - a lognormal distribution. For this distribution \code{mean} -is the mean of the natural logarithm of the delay (on the log scale) and -\code{sd} is the standard deviation of the natural logarithm of the delay. -\item "gamma" - a gamma distribution. For this distribution \code{mean} is the -mean of the delay and \code{sd} is the standard deviation of the delay. During -model fitting these are then transformed to the shape and scale of the gamma -distribution. -} +\item{params_mean}{Numeric. Central values of the parameters of the +distribution as defined in [natural_params().} -When \code{distribution} is the default lognormal distribution the other function -arguments have the following definition: -\itemize{ -\item \code{mean} is the mean of the natural logarithm of the delay (on the -log scale). -\item \code{sd} is the standard deviation of the natural logarithm of the delay. -}} +\item{params_sd}{Numeric. Standard deviations of the parameters of the +distribution as defined in [natural_params().} -\item{mean}{Numeric. If the only non-zero summary parameter -then this is the fixed interval of the distribution. If the \code{sd} is -non-zero then this is the mean of the distribution given by \code{dist}. -If this is not given a vector of empty vectors is returned.} +\item{mean}{Deprecated; use \code{params_mean} instead.} -\item{sd}{Numeric, defaults to 0. Sets the standard deviation of the -distribution.} +\item{sd}{Deprecated; use \code{params_mean} instead.} -\item{mean_sd}{Numeric, defaults to 0. Sets the standard deviation of the -uncertainty around the mean of the distribution assuming a normal -prior.} +\item{mean_sd}{Deprecated; use \code{params_sd} instead.} -\item{sd_sd}{Numeric, defaults to 0. Sets the standard deviation of the -uncertainty around the sd of the distribution assuming a normal prior.} +\item{sd_sd}{Deprecated; use \code{params_sd} instead.} \item{max}{Numeric, maximum value of the distribution. The distribution will -be truncated at this value.} +be truncated at this value. Default: \code{Inf}, i.e. no maximum.} \item{pmf}{Numeric, a vector of values that represent the (nonparametric) probability mass function of the delay (starting with 0); defaults to an empty vector corresponding to a parametric specification of the distribution -(using \code{mean}, \code{sd} and corresponding uncertainties)} +(using \code{params_mean}, and \code{params_sd}.} \item{fixed}{Deprecated, use \code{\link[=fix_dist]{fix_dist()}} instead as coming from fixed (vs uncertain) distributions. Overrides any values @@ -74,24 +54,11 @@ reduces compute requirement but may produce spuriously precise estimates.} A list of distribution options. } \description{ -\ifelse{html}{\href{https://lifecycle.r-lib.org/articles/stages.html#stable}{\figure{lifecycle-stable.svg}{options: alt='[Stable]'}}}{\strong{[Stable]}} -Defines the parameters of a supported distribution for use in onward -modelling. Multiple distribution families are supported - see the -documentation for \code{family} for details. Alternatively, a nonparametric -distribution can be specified using the \code{pmf} argument. -This function provides distribution -functionality in \code{\link[=delay_opts]{delay_opts()}}, \code{\link[=generation_time_opts]{generation_time_opts()}}, and -\code{\link[=trunc_opts]{trunc_opts()}}. -} -\examples{ -# A fixed lognormal distribution with mean 5 and sd 1. -dist_spec(mean = 5, sd = 1, max = 20, distribution = "lognormal") - -# An uncertain gamma distribution with mean 3 and sd 2 -dist_spec( - mean = 3, sd = 2, mean_sd = 0.5, sd_sd = 0.5, max = 20, - distribution = "gamma" -) +\ifelse{html}{\href{https://lifecycle.r-lib.org/articles/stages.html#deprecated}{\figure{lifecycle-deprecated.svg}{options: alt='[Deprecated]'}}}{\strong{[Deprecated]}} +This function is deprecated as a user-facing function (while its +functionality is still used internally). Construct distributions using +the corresponding distribution function such as \code{\link[=gamma]{gamma()}}, \code{\link[=lognormal]{lognormal()}}, +\code{\link[=normal]{normal()}} or \code{\link[=fixed]{fixed()}} instead. } \author{ Sebastian Funk diff --git a/man/dist_spec_plus.Rd b/man/dist_spec_plus.Rd index d04f85078..12a774c99 100644 --- a/man/dist_spec_plus.Rd +++ b/man/dist_spec_plus.Rd @@ -7,10 +7,10 @@ dist_spec_plus(e1, e2, tolerance = 0.001) } \arguments{ -\item{e1}{The first delay distribution (from a call to \code{\link[=dist_spec]{dist_spec()}}) to +\item{e1}{The first delay distribution (of type \code{\link[=dist_spec]{dist_spec()}}) to combine.} -\item{e2}{The second delay distribution (from a call to \code{\link[=dist_spec]{dist_spec()}}) to +\item{e2}{The second delay distribution (of type \code{\link[=dist_spec]{dist_spec()}}) to combine.} \item{tolerance}{A numeric value that sets the cumulative probability diff --git a/man/dot-dist_spec.Rd b/man/dot-dist_spec.Rd new file mode 100644 index 000000000..4e3f9d076 --- /dev/null +++ b/man/dot-dist_spec.Rd @@ -0,0 +1,67 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/dist.R +\name{.dist_spec} +\alias{.dist_spec} +\title{Specify a distribution.} +\usage{ +.dist_spec( + distribution = c("lognormal", "normal", "gamma", "fixed"), + params_mean = numeric(0), + params_sd = numeric(0), + max = Inf, + pmf = numeric(0) +) +} +\arguments{ +\item{distribution}{Character, defaults to "lognormal". The (discretised) +distribution to be used. Can be "lognormal", "gamma", "normal" or "fixed". +The corresponding parameters (defined in \code{\link[=natural_parameters]{natural_parameters()}}) are passed +as \code{params_mean}, and their uncertainty as \code{params_sd}.} + +\item{params_mean}{Numeric. Central values of the parameters of the +distribution as defined in [natural_params().} + +\item{params_sd}{Numeric. Standard deviations of the parameters of the +distribution as defined in [natural_params().} + +\item{max}{Numeric, maximum value of the distribution. The distribution will +be truncated at this value. Default: \code{Inf}, i.e. no maximum.} + +\item{pmf}{Numeric, a vector of values that represent the (nonparametric) +probability mass function of the delay (starting with 0); defaults to an +empty vector corresponding to a parametric specification of the distribution +(using \code{params_mean}, and \code{params_sd}.} +} +\value{ +A \code{dist_spec} object defining the distribution. +} +\description{ +\ifelse{html}{\href{https://lifecycle.r-lib.org/articles/stages.html#stable}{\figure{lifecycle-stable.svg}{options: alt='[Stable]'}}}{\strong{[Stable]}} +Defines the parameters of a supported distribution for use in onward +modelling. Multiple distribution families are supported - see the +documentation for \code{family} for details. Alternatively, a nonparametric +distribution can be specified using the \code{pmf} argument. +This function provides distribution +functionality in \code{\link[=delay_opts]{delay_opts()}}, \code{\link[=generation_time_opts]{generation_time_opts()}}, and +\code{\link[=trunc_opts]{trunc_opts()}}. +} +\examples{ +# A fixed lognormal distribution with mean 5 and sd 1. +.dist_spec( + params_mean = c(meanlog = 5, sdlog = 1), max = 20, + distribution = "lognormal" +) + +# An uncertain gamma distribution with mean 3 and sd 2 +.dist_spec( + params_mean = c(alpha = 3, beta = 0.5), + params_sd = c(alpha = 75, beta = 25) + distribution = "gamma" +) +} +\author{ +Sebastian Funk + +Sam Abbott +} +\keyword{internal} diff --git a/man/generation_time_opts.Rd b/man/generation_time_opts.Rd index aba37ea15..829e1d313 100644 --- a/man/generation_time_opts.Rd +++ b/man/generation_time_opts.Rd @@ -57,7 +57,7 @@ generation_time_opts(example_generation_time) } \seealso{ \code{\link[=convert_to_logmean]{convert_to_logmean()}} \code{\link[=convert_to_logsd]{convert_to_logsd()}} -\code{\link[=bootstrapped_dist_fit]{bootstrapped_dist_fit()}} \code{\link[=dist_spec]{dist_spec()}} +\code{\link[=bootstrapped_dist_fit]{bootstrapped_dist_fit()}} \code{\link[=gamma]{gamma()}} \code{\link[=lognormal]{lognormal()}} \code{\link[=fixed]{fixed()}} } \author{ Sebastian Funk diff --git a/man/get_dist.Rd b/man/get_dist.Rd index fb00282f9..0479dab07 100644 --- a/man/get_dist.Rd +++ b/man/get_dist.Rd @@ -25,10 +25,7 @@ A list defining a distribution \ifelse{html}{\href{https://lifecycle.r-lib.org/articles/stages.html#deprecated}{\figure{lifecycle-deprecated.svg}{options: alt='[Deprecated]'}}}{\strong{[Deprecated]}} This function has been deprecated. Please specify a distribution -using \code{\link[=dist_spec]{dist_spec()}} instead. -} -\seealso{ -\code{\link[=dist_spec]{dist_spec()}} +using functions such as \code{\link[=gamma]{gamma()}} or \code{\link[=lognormal]{lognormal()}} instead. } \author{ Sam Abbott diff --git a/man/get_generation_time.Rd b/man/get_generation_time.Rd index cff27d564..12b36076f 100644 --- a/man/get_generation_time.Rd +++ b/man/get_generation_time.Rd @@ -24,10 +24,7 @@ A list defining a distribution Extracts a literature distribution from \code{generation_times}. This function has been deprecated. Please specify a distribution -using \code{\link[=dist_spec]{dist_spec()}} instead. -} -\seealso{ -\code{\link[=dist_spec]{dist_spec()}} +using functions such as \code{\link[=gamma]{gamma()}} or \code{\link[=lognormal]{lognormal()}} instead. } \author{ Sam Abbott diff --git a/man/get_incubation_period.Rd b/man/get_incubation_period.Rd index 56897967f..b1de608f3 100644 --- a/man/get_incubation_period.Rd +++ b/man/get_incubation_period.Rd @@ -24,10 +24,7 @@ A list defining a distribution Extracts a literature distribution from \code{generation_times}. This function has been deprecated. Please specify a distribution -using \code{\link[=dist_spec]{dist_spec()}} instead -} -\seealso{ -\code{\link[=dist_spec]{dist_spec()}} +using functions such as \code{\link[=gamma]{gamma()}} or \code{\link[=lognormal]{lognormal()}} instead. } \author{ Sam Abbott diff --git a/man/get_seeding_time.Rd b/man/get_seeding_time.Rd index 16cdc814b..0f6a8e54a 100644 --- a/man/get_seeding_time.Rd +++ b/man/get_seeding_time.Rd @@ -7,9 +7,11 @@ get_seeding_time(delays, generation_time) } \arguments{ -\item{delays}{Delays as specified using \code{\link[=dist_spec]{dist_spec()}}} +\item{delays}{Delays specified using distribution functions such as +\code{\link[=gamma]{gamma()}} or \code{\link[=lognormal]{lognormal()}}} -\item{generation_time}{Generation time as specified using \code{\link[=dist_spec]{dist_spec()}}} +\item{generation_time}{Generation specified using distribution functions +such as \code{\link[=gamma]{gamma()}} or \code{\link[=lognormal]{lognormal()}}} } \value{ An integer seeding time diff --git a/man/plus-.dist_spec.Rd b/man/plus-.dist_spec.Rd index c917d175e..942b80d6e 100644 --- a/man/plus-.dist_spec.Rd +++ b/man/plus-.dist_spec.Rd @@ -7,10 +7,10 @@ \method{+}{dist_spec}(e1, e2) } \arguments{ -\item{e1}{The first delay distribution (from a call to \code{\link[=dist_spec]{dist_spec()}}) to +\item{e1}{The first delay distribution (of type \code{\link[=dist_spec]{dist_spec()}}) to combine.} -\item{e2}{The second delay distribution (from a call to \code{\link[=dist_spec]{dist_spec()}}) to +\item{e2}{The second delay distribution (of type \code{\link[=dist_spec]{dist_spec()}}) to combine.} } \value{ diff --git a/man/trunc_opts.Rd b/man/trunc_opts.Rd index 68fcff8c4..bb38a3fa7 100644 --- a/man/trunc_opts.Rd +++ b/man/trunc_opts.Rd @@ -9,7 +9,7 @@ trunc_opts(dist = fixed(0)) \arguments{ \item{dist}{A delay distribution or series of delay distributions reflecting the truncation generated using \code{\link[=dist_spec]{dist_spec()}} or \code{\link[=estimate_truncation]{estimate_truncation()}}. -Default is a fixed distribution of 0, i.e. no truncation.} +Default is fixed distribution with maximum 0, i.e. no truncation} } \value{ A \verb{} object summarising the input truncation From 7c9edb08460971a9ad96404fcfb25e7092ace533 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Tue, 21 Nov 2023 09:48:39 +0000 Subject: [PATCH 012/129] extract_single_dist function --- R/dist.R | 34 +++++++++++++++++++++++++++++++++- 1 file changed, 33 insertions(+), 1 deletion(-) diff --git a/R/dist.R b/R/dist.R index 4bd63c7c5..a110b7284 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1520,7 +1520,39 @@ plot.dist_spec <- function(x, ...) { return(plot) } -##' Fix the parameters of a `` object +##' Extract a single element of a composite `` +##' +##' @param x A composite `dist_spec` object +##' @param i The index to extract +##' @return A single `dist_spec` object +##' @keywords internal +##' @author Sebastian Funk +extract_single_dist <- function(x, i) { + if (i > x$n) { + stop("i can't be greater than the number of distributions.") + } + if (x$parametric[i]) { + parametric_id <- cumsum(x$parametric)[i] + params_start_id <- cumsum(c(0, x$params_length))[i] + 1 + params_id <- seq(params_start_id, length.out = x$params_length[i]) + ret <- .dist_spec( + params_mean = x$params_mean[params_id], + params_sd = x$params_sd[params_id], + max = x$max[parametric_id], + distribution = x$dist[parametric_id] + ) + } else { + nonparametric_id <- cumsum(!x$parametric)[i] + pmf_start_id <- cumsum(c(0, x$np_pmf_length))[nonparametric_id] + 1 + pmf_id <- seq(pmf_start_id, length.out = x$np_pmf_length[nonparametric_id]) + ret <- .dist_spec( + pmf = x$np_pmf[pmf_id] + ) + } + return(ret) +} + +##' Fix the parameters of a `` ##' ##' If the given `` has any uncertainty, it is removed and the ##' corresponding distribution converted into a fixed one. From 7e423fe95125f0fc9da459f805ce06bc85a1cb68 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Tue, 21 Nov 2023 09:49:02 +0000 Subject: [PATCH 013/129] update fix_dist to work with compsosite dists --- R/dist.R | 62 ++++++++++++++++++++++++++++++-------------------------- 1 file changed, 33 insertions(+), 29 deletions(-) diff --git a/R/dist.R b/R/dist.R index a110b7284..3cf8a02b3 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1559,43 +1559,47 @@ extract_single_dist <- function(x, i) { ##' @return A `` object without uncertainty ##' @author Sebastian Funk ##' @export -##' @param x A `` object +##' @param x A `` ##' @param strategy Character; either "mean" (use the mean estimates of the ##' mean and standard deviation) or "sample" (randomly sample mean and ##' standard deviation from uncertainty given in the `` ##' @importFrom truncnorm rtruncnorm ##' @importFrom rlang arg_match fix_dist <- function(x, strategy = c("mean", "sample")) { - ## if x is fixed already we don't have to do anything - if (x$mean_sd == 0 && x$sd_sd == 0) return(x) - ## match startegy argument to options + ## match strategy argument to options strategy <- arg_match(strategy) - ## apply stragey depending on choice - if (strategy == "mean") { - x <- dist_spec( - mean = c(x$mean_mean), - sd = c(x$sd_mean), - mean_sd = 0, - sd_sd = 0, - distribution = x$dist, - max = c(x$max) - ) - } else if (strategy == "sample") { - lower_bound <- ifelse(x$dist == "gamma", 0, -Inf) - mean <- rtruncnorm( - n = 1, a = lower_bound, mean = x$mean_mean, sd = x$mean_sd - ) - sd <- rtruncnorm(n = 1, a = 0, mean = x$sd_mean, sd = x$mean_sd) - x <- dist_spec( - mean = mean, - sd = sd, - mean_sd = 0, - sd_sd = 0, - distribution = x$dist, - max = c(x$max) - ) + + fix_single_dist <- function(x) { + ## if x is fixed already we don't have to do anything + if (!x$parametric || all(x$params_sd == 0)) return(x) + ## apply strategy depending on choice + if (strategy == "mean") { + x <- .dist_spec( + params_mean = x$params_mean, + distribution = x$dist, + max = as.vector(x$max) + ) + } else if (strategy == "sample") { + lower_bound <- lower_bounds(x$dist)[natural_params(x$dist)] + mean <- rtruncnorm( + n = 1, a = lower_bound, mean = x$params_mean + ) + x <- .dist_spec( + params_mean = mean, + distribution = x$dist, + max = as.vector(x$max) + ) + } + return(x) + } + + ret <- fix_single_dist(extract_single_dist(x, 1)) + if (x$n > 1) { + for (i in 2:x$n) { + ret <- ret + fix_single_dist(extract_single_dist(x, i)) + } } - return(x) + return(ret) } ##' @export From aec50d008bc9de758e222c2dc1e8eb6a72f640cc Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Tue, 21 Nov 2023 09:49:38 +0000 Subject: [PATCH 014/129] extract squash --- man/extract_single_dist.Rd | 23 +++++++++++++++++++++++ 1 file changed, 23 insertions(+) create mode 100644 man/extract_single_dist.Rd diff --git a/man/extract_single_dist.Rd b/man/extract_single_dist.Rd new file mode 100644 index 000000000..ac40eabb0 --- /dev/null +++ b/man/extract_single_dist.Rd @@ -0,0 +1,23 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/dist.R +\name{extract_single_dist} +\alias{extract_single_dist} +\title{Extract a single element of a composite \code{dist_spec}} +\usage{ +extract_single_dist(x, i) +} +\arguments{ +\item{x}{A composite \code{dist_spec} object} + +\item{i}{The index to extract} +} +\value{ +A single \code{dist_spec} object +} +\description{ +Extract a single element of a composite \code{dist_spec} +} +\author{ +Sebastian Funk +} +\keyword{internal} From 46a9c92e31dfca311de312b9343d4a79b4e32246 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Tue, 21 Nov 2023 09:50:00 +0000 Subject: [PATCH 015/129] update parameters to extract --- R/estimate_secondary.R | 2 +- R/simulate_infections.R | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/R/estimate_secondary.R b/R/estimate_secondary.R index b31b418c5..e522dc558 100644 --- a/R/estimate_secondary.R +++ b/R/estimate_secondary.R @@ -691,7 +691,7 @@ forecast_secondary <- function(estimate, # allocate empty parameters data <- allocate_empty( - data, c("frac_obs", "delay_mean", "delay_sd", "rep_phi"), + data, c("frac_obs", "delay_param", "rep_phi"), n = data$n ) data$all_dates <- as.integer(all_dates) diff --git a/R/simulate_infections.R b/R/simulate_infections.R index 6e98de85b..aa05c1e69 100644 --- a/R/simulate_infections.R +++ b/R/simulate_infections.R @@ -229,7 +229,7 @@ forecast_infections <- function(estimates, ## allocate empty parameters data <- allocate_empty( - data, c("frac_obs", "delay_mean", "delay_sd", "rep_phi"), + data, c("frac_obs", "delay_params", "rep_phi"), n = data$n ) From 890e6b5cd069aaa58da0c46fd33b0d2f5ff6e77c Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Tue, 21 Nov 2023 09:51:28 +0000 Subject: [PATCH 016/129] specify lower bounds in function --- R/dist.R | 26 ++++++++++++++++++-------- 1 file changed, 18 insertions(+), 8 deletions(-) diff --git a/R/dist.R b/R/dist.R index 3cf8a02b3..032f961f3 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1605,22 +1605,19 @@ fix_dist <- function(x, strategy = c("mean", "sample")) { ##' @export lognormal <- function(meanlog, sdlog, mean, sd, median, max = Inf) { params <- as.list(environment()) - lower_bounds <- c(meanlog = -Inf, sdlog = 0, mean = 0, sd = 0, median = 0) - return(process_dist(params, lower_bounds, "lognormal")) + return(process_dist(params, "lognormal")) } ##' @export gamma <- function(shape, rate, scale, mean, sd, max = Inf) { params <- as.list(environment()) - lower_bounds <- c(shape = 0, rate = 0, scale = 0, mean = 0, sd = 0) - return(process_dist(params, lower_bounds, "gamma")) + return(process_dist(params, "gamma")) } ##' @export normal <- function(mean, sd, max = Inf) { params <- as.list(environment()) - lower_bounds <- c(mean = -Inf, sd = 0) - return(process_dist(params, lower_bounds, "normal")) + return(process_dist(params, "normal")) } ##' @export @@ -1653,6 +1650,19 @@ natural_params <- function(distribution) { return(ret) } +lower_bounds <- function(distribution) { + if (distribution == "gamma") { + ret <- c(shape = 0, rate = 0, scale = 0, mean = 0, sd = 0) + } else if (distribution == "lognormal") { + ret <- c(meanlog = -Inf, sdlog = 0, mean = 0, sd = 0, median = 0) + } else if (distribution == "normal") { + ret <- c(mean = -Inf, sd = 0) + } else if (distribution == "fixed") { + ret <- c(value = 1) + } + return(ret) +} + extract_params <- function(params, distribution) { params <- params[!vapply(params, inherits, "name", FUN.VALUE = TRUE)] n_params <- length(natural_params(distribution)) @@ -1665,7 +1675,7 @@ extract_params <- function(params, distribution) { return(params) } -process_dist <- function(params, lower_bounds, distribution) { +process_dist <- function(params, distribution) { ## process min/max first max <- params$max params$max <- NULL @@ -1691,7 +1701,7 @@ process_dist <- function(params, lower_bounds, distribution) { ## sample parameters if they are uncertain samples <- lapply(names(params), function(x) { rtruncnorm( - n = 2000, a = lower_bounds[x], + n = 2000, a = lower_bounds(distribution)[x], mean = mean(params[[x]]), sd = sd(params[[x]]) ) }) From 7a58063071b6a3ad21bf748844de532f90bc00cb Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Tue, 21 Nov 2023 09:52:16 +0000 Subject: [PATCH 017/129] pass lower bounds to stan model --- R/dist.R | 6 ++++-- inst/stan/data/delays.stan | 1 + inst/stan/estimate_infections.stan | 8 +++++--- 3 files changed, 10 insertions(+), 5 deletions(-) diff --git a/R/dist.R b/R/dist.R index 032f961f3..6d5cd73a1 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1056,7 +1056,8 @@ dist_spec <- function(distribution = c( n_p = 1, n_np = 0, np_pmf = numeric(0), - parametric = TRUE + parametric = TRUE, + params_lower = lower_bounds(distribution)[natural_params(distribution)] ) } else { ret <- list( @@ -1064,7 +1065,8 @@ dist_spec <- function(distribution = c( params_sd = numeric(0), dist = character(0), max = integer(0), - parametric = FALSE + parametric = FALSE, + params_lower = numeric(0) ) if (length(pmf) == 0) { if (distribution == "fixed") { ## delta diff --git a/inst/stan/data/delays.stan b/inst/stan/data/delays.stan index 4b8d0a5b4..2401f1b26 100644 --- a/inst/stan/data/delays.stan +++ b/inst/stan/data/delays.stan @@ -11,6 +11,7 @@ int delay_params_length; // number of parameters across all parametric delay distributions vector[delay_params_length] delay_params_mean; // ragged array of mean parameters for parametric delay distributions vector[delay_params_length] delay_params_sd; // ragged array of sd of parameters for parametric delay distributions + vector[delay_params_length] delay_params_lower; // ragged array of lower bounds of the parameters array[delay_n_p + 1] int delay_params_groups; // links to ragged array array[delay_n_p] int delay_weight; // delay weights diff --git a/inst/stan/estimate_infections.stan b/inst/stan/estimate_infections.stan index b16f58315..1d7a2a1e0 100644 --- a/inst/stan/estimate_infections.stan +++ b/inst/stan/estimate_infections.stan @@ -48,7 +48,8 @@ parameters{ array[bp_n > 0 ? 1 : 0] real bp_sd; // standard deviation of breakpoint effect array[bp_n] real bp_effects; // Rt breakpoint effects // observation model - vector[delay_params_length] delay_params; // delay parameters + + vector[delay_params_length] delay_params; // delay parameters simplex[week_effect] day_of_week_simplex;// day of week reporting effect array[obs_scale_sd > 0 ? 1 : 0] real frac_obs; // fraction of cases that are ultimately observed array[model_type] real rep_phi; // overdispersion of the reporting process @@ -166,8 +167,9 @@ generated quantities { r = R_to_growth(R, gt_mean, gt_var); } else { // sample generation time - vector[delay_params_length] delay_params_sample = - to_vector(normal_rng(delay_params_mean, delay_params_sd)); + vector[delay_params_length] delay_params_sample = to_vector(normal_rng( + delay_params_mean, delay_params_sd + )); vector[delay_type_max[gt_id] + 1] sampled_gt_rev_pmf = get_delay_rev_pmf( gt_id, delay_type_max[gt_id] + 1, delay_types_p, delay_types_id, delay_types_groups, delay_max, delay_np_pmf, From 10acdb755596b41a4c9eaeab8dcb38f28ad2f632 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Tue, 21 Nov 2023 09:53:31 +0000 Subject: [PATCH 018/129] update sample/report functions --- R/adjust.R | 49 ++++++++++++++++++++++++++++++++++++++++++++----- R/dist.R | 36 ++++++++++++++++++++++++++++++++++++ R/report.R | 14 +------------- 3 files changed, 81 insertions(+), 18 deletions(-) diff --git a/R/adjust.R b/R/adjust.R index 4858eafc1..172bd4c1f 100644 --- a/R/adjust.R +++ b/R/adjust.R @@ -86,6 +86,7 @@ adjust_infection_to_report <- function(infections, delay_defs, # Reset DT Defaults on Exit set_dt_single_thread() + ## deprecated sample_single_dist <- function(input, delay_def) { ## Define sample delay fn sample_delay_fn <- function(n, ...) { @@ -112,14 +113,52 @@ adjust_infection_to_report <- function(infections, delay_defs, return(out) } - report <- sample_single_dist(infections, delay_defs[[1]]) - - if (length(delay_defs) > 1) { - for (def in 2:length(delay_defs)) { - report <- sample_single_dist(report, delay_defs[[def]]) + sample_dist_spec <- function(input, delay_def) { + ## Define sample delay fn + sample_delay_fn <- function(n, dist, cum, ...) { + fixed_dist <- fix_dist(delay_def, strategy = "sample") + if (dist) { + fixed_dist$np_pmf[n + 1] + } else { + sample(seq_along(fixed_dist$np_pmf) - 1, size = n, replace = TRUE) + } } + + ## Infection to onset + out <- EpiNow2::sample_approx_dist( + cases = input, + dist_fn = sample_delay_fn, + max_value = max(delay_def), + direction = "forwards", + type = type, + truncate_future = FALSE + ) + + return(out) } + if (is(delay_defs, "dist_spec")) { + report <- sample_dist_spec(infections, extract_single_dist(delay_defs, 1)) + if (delay_defs$n > 1) { + for (def in 2:delay_defs$n) { + report <- sample_dist_spec(report, extract_single_dist(delay_defs, def)) + } + } + } else { + deprecate_warn( + "2.0.0", + "adjust_infection_to_report(delay_defs = 'should be a dist_spec')", + details = c( + "Specifying this as a list of data tables is deprecated." + ) + ) + report <- sample_single_dist(infections, delay_defs[[1]]) + if (length(delay_defs ) > 1) { + for (def in 2:length(delay_defs)) { + report <- sample_single_dist(report, delay_defs[[def]]) + } + } + } ## Add a weekly reporting effect if present if (!missing(reporting_effect)) { reporting_effect <- data.table::data.table( diff --git a/R/dist.R b/R/dist.R index 6d5cd73a1..fb0df0220 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1346,6 +1346,42 @@ sd.default <- function(x, ...) { stats::sd(x, ...) } +##' Returns the maximum of one or more delay distribution +##' +##' This works out the maximum of all the (parametric / nonparametric) delay +##' distributions combined in the passed [dist_spec()] (ignoring any uncertainty +##' in parameters) +##' +##' @param x The [dist_spec()] to use +##' @param ... Not used +##' @return A vector of means. +##' @author Sebastian Funk +##' @method max dist_spec +##' @export +#' @examples +#' # A fixed gamma distribution with mean 5 and sd 1. +#' dist1 <- gamma(mean = 5, sd = 1, max = 20) +#' max(dist1) +#' +#' # An uncertain lognormal distribution with mean 3 and sd 2 +#' dist2 <- lognormal(mean = normal(3, 0.5), sd = normal(2, 0.5), max = 20) +#' max(dist2) +#' +#' # The mean of the sum of two distributions +#' mean(dist1 + dist2) +max.dist_spec <- function(x, ...) { + ret <- rep(0L, x$n) + if (x$n_np > 0) { + ## nonparametric + ret[!x$parametric] <- x$np_pmf_length - 1 + } + if (x$n_p > 0) { + ## parametric + ret[x$parametric] <- x$max + } + return(ret) +} + #' Prints the parameters of one or more delay distributions #' #' This displays the parameters of the uncertain and probability mass diff --git a/R/report.R b/R/report.R index ee32ea034..21ae87af0 100644 --- a/R/report.R +++ b/R/report.R @@ -53,18 +53,6 @@ report_cases <- function(case_estimates, CrIs = c(0.2, 0.5, 0.9)) { samples <- length(unique(case_estimates$sample)) - # define delay distributions - delay_defs <- purrr::map( - seq_along(delays$mean_mean), - ~ EpiNow2::lognorm_dist_def( - mean = delays$mean_mean[.], - mean_sd = delays$mean_sd[.], - sd = delays$mean_mean[.], - sd_sd = delays$mean_sd[.], - max_value = delays$max[.], - samples = samples - ) - ) # add a null reporting effect if missing if (missing(reporting_effect)) { reporting_effect <- data.table::data.table( @@ -91,7 +79,7 @@ report_cases <- function(case_estimates, report <- future.apply::future_lapply(1:max(infections$sample), function(id) { EpiNow2::adjust_infection_to_report(infections[sample == id], - delay_defs = purrr::map(delay_defs, ~ .[id, ]), + delay_defs = delays, type = type, reporting_effect = reporting_effect[sample == id, ]$effect ) From e2f62de1c48f5b0ba611963f013e5d02e5a8b1c9 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Tue, 21 Nov 2023 09:53:51 +0000 Subject: [PATCH 019/129] max squash adjust report --- NAMESPACE | 1 + 1 file changed, 1 insertion(+) diff --git a/NAMESPACE b/NAMESPACE index 94409271f..f048a0842 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -1,6 +1,7 @@ # Generated by roxygen2: do not edit by hand S3method("+",dist_spec) +S3method(max,dist_spec) S3method(mean,dist_spec) S3method(plot,dist_spec) S3method(plot,epinow) From 6c0ec9011dc1db13d90577f10a94a6869275a90b Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Tue, 21 Nov 2023 09:54:16 +0000 Subject: [PATCH 020/129] update dist functions to new syntax --- R/dist.R | 114 +++++++++++++++++++++++++++---------------------------- 1 file changed, 57 insertions(+), 57 deletions(-) diff --git a/R/dist.R b/R/dist.R index fb0df0220..a0d8e81b6 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1176,20 +1176,19 @@ dist_spec_plus <- function(e1, e2, tolerance = 0.001) { #' @export #' @examples #' # A fixed lognormal distribution with mean 5 and sd 1. -#' lognormal <- dist_spec( -#' mean = 1.6, sd = 1, max = 20, distribution = "lognormal" +#' dist1 <- lognormal_spec( +#' meanlog = 1.6, sdlog = 1, max = 20, distribution = "lognormal" #' ) -#' lognormal + lognormal +#' dist1 + dist1 #' #' # An uncertain gamma distribution with mean 3 and sd 2 -#' gamma <- dist_spec( -#' mean = 3, sd = 2, mean_sd = 0.5, sd_sd = 0.5, max = 20, -#' distribution = "gamma" +#' dist2 <- gamma( +#' mean = normal(3, 0.5), sd = normal(2, 0.5), max = 20 #' ) -#' lognormal + gamma +#' dist1 + dist2 #' #' # Using tolerance parameter -#' EpiNow2:::dist_spec_plus(lognormal, lognormal, tolerance = 0.5) +#' EpiNow2:::dist_spec_plus(dist1, dist1, tolerance = 0.5) `+.dist_spec` <- function(e1, e2) { dist_spec_plus(e1, e2, tolerance = 0.001) } @@ -1260,26 +1259,29 @@ mean.dist_spec <- function(x, ...) { } if (x$n_p > 0) { ## parametric - ret[x$parametric] <- vapply( - seq_along(which(x$parametric)), function(id) { - if (x$dist == "lognormal") { - ret <- exp(x$params_mean[[1]] + x$params_mean[[2]]**2 / 2) - } else if (x$dist == "gamma") { - ret <- x$params_mean[[1]] / x$params_mean[[2]] - } else if (x$dist == "normal") { - ret <- x$params_mean[[1]] - } else if (x$dist == "fixed") { - ret <- x$params_mean[[1]] - } else { - stop("Don't know how to calculate mean of ", x$dist, " distribution.") - } - }, .0 - ) + ret[x$parametric] <- vapply(which(x$parametric), function(id) { + single_dist <- extract_single_dist(x, id) + if (single_dist$dist == "lognormal") { + ret <- exp( + single_dist$params_mean[[1]] + single_dist$params_mean[[2]]**2 / 2 + ) + } else if (single_dist$dist == "gamma") { + ret <- single_dist$params_mean[[1]] / single_dist$params_mean[[2]] + } else if (single_dist$dist == "normal") { + ret <- single_dist$params_mean[[1]] + } else if (single_dist$dist == "fixed") { + ret <- single_dist$params_mean[[1]] + } else { + stop( + "Don't know how to calculate mean of ", single_dist$dist, + " distribution." + ) + } + }, .0) } return(ret) } - #' @export sd <- function(x, ...) UseMethod("sd") ##' Returns the standard deviation of one or more delay distribution @@ -1410,59 +1412,62 @@ print.dist_spec <- function(x, ...) { if (x$n > 1) { cat("Composite delay distribution:\n") } - fixed_id <- 1 - fixed_pos <- 1 - variable_id <- 1 - variable_pos <- 1 + nonparametric_id <- 1 + nonparametric_pos <- 1 + parametric_id <- 1 + parametric_pos <- 1 for (i in 1:x$n) { cat(" ") if (!is.null(x$names) && nchar(x$names[i]) > 0) { cat(x$names[i], ": ", sep = "") } if (x$parametric[i] > 0) { - dist <- x$dist[variable_id] + dist <- x$dist[parametric_id] cat(dist, " distribution", sep = "") - if (is.finite(x$max)) { - cat(" (max: ", x$max, ")", sep = "") + if (is.finite(x$max[parametric_id])) { + cat(" (max: ", x$max[parametric_id], ")", sep = "") } cat(" with ", sep = "") ## loop over natural parameters and print - for (id in seq(variable_pos, x$params_length[variable_pos])) { - if (id > variable_pos) { - if (id == x$params_length[variable_pos]) { + for (id in seq(1, x$params_length[i])) { + pos <- parametric_pos - 1 + id + if (id > 1) { + if (id == x$params_length[i]) { cat(" and ") } else { cat(", ") } } - if (x$params_sd[id] > 0) { + if (x$params_sd[pos] > 0) { cat("uncertain ") } cat(natural_params(dist)[id]) - if (x$params_sd[id] > 0) { + if (x$params_sd[pos] > 0) { cat( - " (mean = ", signif(x$params_mean[id], digits = 2), ", ", - "sd = ", signif(x$params_sd[id], digits = 2), ")", + " (mean = ", signif(x$params_mean[pos], digits = 2), ", ", + "sd = ", signif(x$params_sd[pos], digits = 2), ")", sep = "" ) } else { - cat(" = ", signif(x$params_mean[id], digits = 2), sep = "") + cat(" = ", signif(x$params_mean[pos], digits = 2), sep = "") } } - variable_id <- variable_id + 1 - variable_pos <- variable_pos + x$params_length[i] + parametric_id <- parametric_id + 1 + parametric_pos <- parametric_pos + x$params_length[i] } else { cat( "distribution with PMF [", paste(signif( - x$np_pmf[seq(fixed_pos, fixed_pos + x$np_pmf_length[fixed_id] - 1)], + x$np_pmf[seq( + nonparametric_pos, length.out = x$np_pmf_length[nonparametric_id] + )], digits = 2 ), collapse = " "), "]", sep = "" ) - fixed_id <- fixed_id + 1 - fixed_pos <- fixed_pos + x$np_pmf_length[i] + nonparametric_id <- nonparametric_id + 1 + nonparametric_pos <- nonparametric_pos + x$np_pmf_length[i] } cat(".\n") } @@ -1510,26 +1515,21 @@ plot.dist_spec <- function(x, ...) { value = numeric(), cdf = numeric(), distribution = factor() ) - variable_id <- 1 - fixed_id <- 1 + parametric_id <- 1 + nonparametric_id <- 1 group_starts <- c(1L, cumsum(x$np_pmf_length) + 1L) for (i in 1:x$n) { - if (x$fixed[i] == 0) { + if (x$parametric[i]) { # Uncertain distribution - mean <- x$mean_mean[variable_id] - sd <- x$sd_mean[variable_id] - c_dist <- dist_spec( - mean = mean, sd = sd, max = x$max[variable_id], - distribution = x$dist[variable_id] - ) + c_dist <- fix_dist(extract_single_dist(x, i)) pmf <- c_dist$np_pmf - variable_id <- variable_id + 1 - dist_name <- paste0("Uncertain ", x$dist[variable_id], " (ID: ", i, ")") + parametric_id <- parametric_id + 1 + dist_name <- paste0("Uncertain ", x$dist[parametric_id], " (ID: ", i, ")") } else { # Fixed distribution pmf <- x$np_pmf[seq(group_starts[i], group_starts[i + 1L] - 1L)] dist_name <- paste0("Fixed", " (ID: ", i, ")") - fixed_id <- fixed_id + 1 + nonparametric_id <- nonparametric_id + 1 } pmf_data <- rbind( pmf_data, @@ -1721,7 +1721,7 @@ process_dist <- function(params, distribution) { params <- extract_params(params, distribution) params <- lapply(params, function(x) { if (is(x, "dist_spec") && x$dist == "normal") { - if (any(x$param_sd > 0)) { + if (any(x$params_sd > 0)) { stop( "Normal distribution indicating uncertainty cannot itself ", "be uncertain." From 0155317cc528239a59e0a70da2a90b1a97507921 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Tue, 21 Nov 2023 09:54:29 +0000 Subject: [PATCH 021/129] re-create data --- data-raw/estimate-infections.R | 7 +------ data/example_generation_time.rda | Bin 326 -> 340 bytes data/example_incubation_period.rda | Bin 340 -> 357 bytes data/example_reporting_delay.rda | Bin 407 -> 416 bytes 4 files changed, 1 insertion(+), 6 deletions(-) diff --git a/data-raw/estimate-infections.R b/data-raw/estimate-infections.R index bf442ac34..f01a25dcc 100644 --- a/data-raw/estimate-infections.R +++ b/data-raw/estimate-infections.R @@ -7,12 +7,7 @@ options(mc.cores = 4) reported_cases <- example_confirmed[1:60] #' # use example distributions -reporting_delay <- dist_spec( - mean = convert_to_logmean(2, 1), - sd = convert_to_logsd(2, 1), - max = 10, - dist = "lognormal" -) +reporting_delay <- lognormal(mean = 2, sd = 1, max = 10L) example_estimate_infections <- estimate_infections(reported_cases, generation_time = generation_time_opts(example_generation_time), diff --git a/data/example_generation_time.rda b/data/example_generation_time.rda index 84342ec58382add31e67a618a517b92b44076944..2e60aab54e8039f8f827d587a84938135dbb11e6 100644 GIT binary patch literal 340 zcmV-a0jvH(T4*^jL0KkKS^v&95&!`f@16g@Ou#Sz%%BiKulL-+1OUJa0svqX!~w7Y zIY@?xYBZT9@}>mBGhLS^twFL@cx@tQy(HwsaHAue$1dEX%6d!owvvFEfBZ@%@9H)hlCc`D8_xM@e3S!Vw4rZ~Fi2yLzWE4sCF!|3~V9T2N zpg}Dpd0WRvUA!eZp4__GFkFKRLBJqsA!%v>jVHXoh6=F&lr_glOVzB*NS^O@AV}Jv zf>4qa+ZB?dhQF)ort50ktI~6zP!@)3Jh`bu^#B1A|Ns9#SRep`5CDV%6+pk|-oOYV0D?duZ~#C6 z5D)+W;3cpDI6@kjr2Q1qKUCB7P+~t+8e~0BQ}scn#Sc?WG917GGGGBPm?jXw5r71V z2~DF>wEzZy&}cMhXaF9ikbMp4l4!uuF;ujj3nmk)^%J6XvJlv<#3BfCC1Y4{d=B zB`Aa?4BwPi&;-?JKmcsU2oV5U49CRBb?#mAcu9Lkw2qm3_huo`$b*iVqu4+>tQqmP z`&P+fweina4+G3xXf+VSIG{qS4H9y;yiE^z!hC4p&`cd<><^<2BI)bZV!)|2Hgznl zr!#U8eGC~63Tgs{doVMMBJ;TuWPaiOe(Uy^?(M0(hRdSwWsRks2l%^^DZ+$@F^K1= DkFK0S literal 340 zcmV-a0jvH(T4*^jL0KkKS;FI#0ssL2fB*kGSRep`5CDV%6+pk|-arT<0D?duZ~#C6 z5D)+W;3cpD7(i*Hru8(2Mo7~^=?$r%^wAGf(@^ypHlfWiFaVeUm;eO808A1hnNgZ1 zKp6mNJwc!V09yyh@DkB$2^CfsLj{V;=+Jad^C1nR6=V1KS2-sBa$w?X2}|e!qgBBv zJj^^UvUD-@aM*zb8c6Q1ZhLFlLDDJJiyoCNL3x3;AZZCOV@d5WA%d8IN*djm04D6x zg#N$1qt=s!pI!?)%03V%%MI4H{n)LOPO4+aB7&pb zhr}il`dF@XM}0V<5yvhZkUT;N9i{L|G+BkXX|BeY^D#{=yEjW{B49LRm6ef$V@MMy mb95^H_I=C!cPqG_9JspjFE{+Aq7t-E@pmLsg$WEUIY1zFtC3y+ diff --git a/data/example_reporting_delay.rda b/data/example_reporting_delay.rda index bcf6cdb58e0722b5bcd594384c81176273e9bfda..c19ad2ecf02da45eb849830756bff3026ff7a391 100644 GIT binary patch delta 395 zcmV;60d)SC1E2#HLRx4!F+o`-Q(20`!Yu#+7=Qo&e~}d+e^^UwHBV3x446$CVr@nm zBSGk75YW(J9)^K7n@WC^B2YZlGzNn~rhotdG-v<-0001zMAXV@X6%Iizd*6y>5& zYIL34KxAh$=pbPMxtQi_Pb3A{XuL((gAhD`tqwYjTEYNe7Q`tc0wSp5xSBcgxkrEY p-p$HieguZc;C>gCG?Yw0@EqIX delta 386 zcmV-|0e$|U1D698LRx4!F+o`-Q(3P`4fOy42LJ#6dyy3&e>hDBiVRd_GzJj$13<{l zO{f|gXaSz2dYWX(?J4?#De9Vfo{-U|jQ{`u00D>tKmY&%B!r%(r>3Jo0i!?w05Sk* z0002elc`Skqv&W(!3IOrLFDnFL{Cf-)Nu4O1rnTS!kv=41(tyB5zv zh$UTw0QLlGb0JDPCF0W{X{YC*w2BJl`srnkWhjua1P#{=38WsH_y`B8^J!#_k#B! zK4B29>`H&{XvqlzJ0`cjyr%nJ=<2n8WZdXo2rmVMWF@#U$PlZ9qWc0&+X4w9Zr~sY z1mR#uMK}&sW=5i9H>=R4JtH?j2Q_cqN;%X?3Y Date: Tue, 21 Nov 2023 09:54:54 +0000 Subject: [PATCH 022/129] update get_dist to new syntax --- R/get.R | 8 +++++++- 1 file changed, 7 insertions(+), 1 deletion(-) diff --git a/R/get.R b/R/get.R index b8e47537c..76beea745 100644 --- a/R/get.R +++ b/R/get.R @@ -199,7 +199,13 @@ get_dist <- function(data, disease, source, max_value = 14, fixed = FALSE) { dist$mean_sd <- 0 dist$sd_sd <- 0 } - return(do.call(dist_spec, dist)) + dist$params_mean <- c(dist$mean, dist$sd) + dist$params_sd <- c(dist$mean_sd, dist$sd_sd) + dist$mean <- NULL + dist$sd <- NULL + dist$mean_sd <- NULL + dist$sd_sd <- NULL + return(do.call(.dist_spec, dist)) } #' Get a Literature Distribution for the Generation Time #' From 05181578c6049ed37a88fd682087b31b3a2591d8 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Tue, 21 Nov 2023 09:55:10 +0000 Subject: [PATCH 023/129] fully deprecate get fnuctions --- R/get.R | 32 ++++++++++++++++++++++---------- 1 file changed, 22 insertions(+), 10 deletions(-) diff --git a/R/get.R b/R/get.R index 76beea745..4a2b739a2 100644 --- a/R/get.R +++ b/R/get.R @@ -222,11 +222,17 @@ get_dist <- function(data, disease, source, max_value = 14, fixed = FALSE) { get_generation_time <- function(disease, source, max_value = 14, fixed = FALSE) { lifecycle::deprecate_warn( - "2.0.0", "get_generation_time()", "dist_spec()", - paste( - "The function will be removed completely in version 2.1.0. To obtain the", - "previous estimate by Ganyani et al. (2020) use ", - "`example_generation_time`" + "2.0.0", "get_generation_time()", + details = c( + paste( + "Please use distribution functions such as `gamma` or `lognormal`", + "instead." + ), + "The function will be removed completely in version 2.1.0.", + paste( + "To obtain the previous estimate by Ganyani et al. (2020) use", + "`example_generation_time`." + ) ) ) dist <- get_dist(EpiNow2::generation_times, @@ -251,11 +257,17 @@ get_generation_time <- function(disease, source, max_value = 14, get_incubation_period <- function(disease, source, max_value = 14, fixed = FALSE) { lifecycle::deprecate_warn( - "2.0.0", "get_incubation_period()", "dist_spec()", - paste( - "The function will be removed completely in version 2.1.0. To obtain the", - "previous estimate by Ganyani et al. (2020) use ", - "`example_incubation_period`" + "2.0.0", "get_incubation_period()", + details = c( + paste( + "Please use distribution functions such as `gamma` or `lognormal`", + "instead." + ), + "The function will be removed completely in version 2.1.0.", + paste( + "To obtain the previous estimate by Ganyani et al. (2020) use", + "`example_incubation_period`." + ) ) ) dist <- get_dist(EpiNow2::incubation_periods, From bd9ba78802ceab22ec90965fe7babecd85c337f2 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Tue, 21 Nov 2023 09:55:38 +0000 Subject: [PATCH 024/129] create delay inits separately --- R/create.R | 34 ++++++++++++++++++++-------------- R/estimate_truncation.R | 10 ++-------- man/create_delay_inits.Rd | 21 +++++++++++++++++++++ 3 files changed, 43 insertions(+), 22 deletions(-) create mode 100644 man/create_delay_inits.Rd diff --git a/R/create.R b/R/create.R index efeb033a7..ca0e3b8fd 100644 --- a/R/create.R +++ b/R/create.R @@ -527,6 +527,25 @@ create_stan_data <- function(reported_cases, seeding_time, return(data) } +##' Create initial conditions for delays +##' +##' @inheritParams create_initial_conditions +##' @return A list of initial conditions for delays +##' @author Sebastian Funk +##' @keywords internal +create_delay_inits <- function(data) { + out <- list() + if (data$delay_n_p > 0) { + out$delay_params <- array(truncnorm::rtruncnorm( + n = data$delay_params_length, a = data$delay_params_lower, + mean = data$delay_params_mean, sd = data$delay_params_sd * 0.1 + 1 + )) + } else { + out$delay_params <- array(numeric(0)) + } + return(out) +} + #' Create Initial Conditions Generating Function #' @description `r lifecycle::badge("stable")` #' Uses the output of [create_stan_data()] to create a function which can be @@ -543,20 +562,7 @@ create_stan_data <- function(reported_cases, seeding_time, # @author Sebastian Funk create_initial_conditions <- function(data) { init_fun <- function() { - out <- list() - if (data$delay_n_p > 0) { - lower_bounds <- rep(-Inf, data$delay_params_length) - ## gamma - param_dist <- rep(data$dist, times = diff(data$params_groups)) - lower_bounds[data$dist == "gamma"] <- 0 - - out$delay_params <- array(truncnorm::rtruncnorm( - n = data$delay_params_length, a = lower_bounds, - mean = data$delay_params_mean, sd = data$delay_params_sd * 0.1 - )) - } else { - out$delay_params <- array(numeric(0)) - } + out <- create_delay_inits(data) if (data$fixed == 0) { out$eta <- array(rnorm(data$M, mean = 0, sd = 0.1)) diff --git a/R/estimate_truncation.R b/R/estimate_truncation.R index 368b1aa4f..637dd0c2a 100644 --- a/R/estimate_truncation.R +++ b/R/estimate_truncation.R @@ -254,18 +254,12 @@ estimate_truncation <- function(obs, max_truncation, trunc_max = 10, weight = ifelse(weigh_delay_priors, data$t, 1) )) - ## convert to integer - data$trunc_dist <- - which(eval(formals()[["trunc_dist"]]) == trunc_dist) - 1 - # initial conditions init_fn <- function() { - data <- list( - delay_mean = array(rnorm(1, 0, 1)), - delay_sd = array(abs(rnorm(1, 0, 1))) + 1, + data <- c(create_delay_inits(data), list( phi = abs(rnorm(1, 0, 1)), sigma = abs(rnorm(1, 0, 1)) - ) + )) return(data) } diff --git a/man/create_delay_inits.Rd b/man/create_delay_inits.Rd new file mode 100644 index 000000000..f825b0de2 --- /dev/null +++ b/man/create_delay_inits.Rd @@ -0,0 +1,21 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/create.R +\name{create_delay_inits} +\alias{create_delay_inits} +\title{Create initial conditions for delays} +\usage{ +create_delay_inits(data) +} +\arguments{ +\item{data}{A list of data as produced by \code{create_stan_data.}} +} +\value{ +A list of initial conditions for delays +} +\description{ +Create initial conditions for delays +} +\author{ +Sebastian Funk +} +\keyword{internal} From 9c65d772d80e02feebcf632955e42cd137275a78 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Tue, 21 Nov 2023 09:55:53 +0000 Subject: [PATCH 025/129] max squash again --- man/max.dist_spec.Rd | 36 ++++++++++++++++++++++++++++++++++++ 1 file changed, 36 insertions(+) create mode 100644 man/max.dist_spec.Rd diff --git a/man/max.dist_spec.Rd b/man/max.dist_spec.Rd new file mode 100644 index 000000000..f1d11576e --- /dev/null +++ b/man/max.dist_spec.Rd @@ -0,0 +1,36 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/dist.R +\name{max.dist_spec} +\alias{max.dist_spec} +\title{Returns the maximum of one or more delay distribution} +\usage{ +\method{max}{dist_spec}(x, ...) +} +\arguments{ +\item{x}{The \code{\link[=dist_spec]{dist_spec()}} to use} + +\item{...}{Not used} +} +\value{ +A vector of means. +} +\description{ +This works out the maximum of all the (parametric / nonparametric) delay +distributions combined in the passed \code{\link[=dist_spec]{dist_spec()}} (ignoring any uncertainty +in parameters) +} +\examples{ +# A fixed gamma distribution with mean 5 and sd 1. +dist1 <- gamma(mean = 5, sd = 1, max = 20) +max(dist1) + +# An uncertain lognormal distribution with mean 3 and sd 2 +dist2 <- lognormal(mean = normal(3, 0.5), sd = normal(2, 0.5), max = 20) +max(dist2) + +# The mean of the sum of two distributions +mean(dist1 + dist2) +} +\author{ +Sebastian Funk +} From c72efe906ca70c63a44f2b9ffe49e5d93033bc53 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Tue, 21 Nov 2023 09:56:06 +0000 Subject: [PATCH 026/129] return correct dist in estimate_truncation --- R/estimate_truncation.R | 11 ++++------- 1 file changed, 4 insertions(+), 7 deletions(-) diff --git a/R/estimate_truncation.R b/R/estimate_truncation.R index 637dd0c2a..7fda536c9 100644 --- a/R/estimate_truncation.R +++ b/R/estimate_truncation.R @@ -271,13 +271,10 @@ estimate_truncation <- function(obs, max_truncation, trunc_max = 10, out <- list() # Summarise fit truncation distribution for downstream usage - delay_mean <- extract_stan_param(fit, params = "delay_mean") - delay_sd <- extract_stan_param(fit, params = "delay_sd") - out$dist <- dist_spec( - mean = round(delay_mean$mean, 3), - mean_sd = round(delay_mean$sd, 3), - sd = round(delay_sd$mean, 3), - sd_sd = round(delay_sd$sd, 3), + delay_params <- extract_stan_param(fit, params = "delay_params") + out$dist <- .dist_spec( + params_mean = round(delay_params$mean, 3), + params_sd = round(delay_params$sd, 3), max = truncation$max ) out$dist$dist <- truncation$dist From 37524bbe659fa68766fadd33ad4d18186d777f64 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Tue, 21 Nov 2023 09:56:38 +0000 Subject: [PATCH 027/129] few more examples/docs --- R/create.R | 3 +-- R/opts.R | 8 ++++++-- man/create_stan_delays.Rd | 3 +-- 3 files changed, 8 insertions(+), 6 deletions(-) diff --git a/R/create.R b/R/create.R index ca0e3b8fd..c90695541 100644 --- a/R/create.R +++ b/R/create.R @@ -705,8 +705,7 @@ create_stan_args <- function(stan = stan_opts(), ##' Create delay variables for stan ##' -##' @param ... Named delay distributions specified using `dist_spec()`. -##' The names are assigned to IDs +##' @param ... Named delay distributions. The names are assigned to IDs ##' @param weight Numeric, weight associated with delay priors; default: 1 ##' @return A list of variables as expected by the stan model ##' @importFrom purrr list_transpose map diff --git a/R/opts.R b/R/opts.R index 56099dda0..624c05b17 100644 --- a/R/opts.R +++ b/R/opts.R @@ -26,11 +26,15 @@ #' generation_time_opts() #' #' # A fixed gamma distributed generation time -#' generation_time_opts(dist_spec(mean = 3, sd = 2, max = 14)) +#' generation_time_opts(gamma(mean = 3, sd = 2, max = 14)) #' #' # An uncertain gamma distributed generation time #' generation_time_opts( -#' dist_spec(mean = 3, sd = 2, mean_sd = 1, sd_sd = 0.5, max = 14) +#' gamma( +#' mean = normal(mean = 3, sd = 1), +#' sd = normal(mean = 2, sd = 0.5), +#' max = 14 +#' ) #' ) #' #' # An example generation time diff --git a/man/create_stan_delays.Rd b/man/create_stan_delays.Rd index 60defa3d6..5c6519e10 100644 --- a/man/create_stan_delays.Rd +++ b/man/create_stan_delays.Rd @@ -7,8 +7,7 @@ create_stan_delays(..., weight = 1) } \arguments{ -\item{...}{Named delay distributions specified using \code{dist_spec()}. -The names are assigned to IDs} +\item{...}{Named delay distributions. The names are assigned to IDs} \item{weight}{Numeric, weight associated with delay priors; default: 1} } From cad0dd2b174627a20d5db61f7bb4d3192760bd8c Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Tue, 21 Nov 2023 09:56:57 +0000 Subject: [PATCH 028/129] fix tests --- tests/testthat/setup.R | 2 +- tests/testthat/test-delays.R | 34 +++---------- tests/testthat/test-dist.R | 6 ++- tests/testthat/test-dist_spec.R | 62 ++++++++++------------- tests/testthat/test-estimate_secondary.R | 2 +- tests/testthat/test-estimate_truncation.R | 4 +- tests/testthat/test-report_cases.R | 2 +- tests/testthat/test-stan-infections.R | 4 +- tests/testthat/test-stan-secondary.R | 2 +- 9 files changed, 45 insertions(+), 73 deletions(-) diff --git a/tests/testthat/setup.R b/tests/testthat/setup.R index e714ef9f1..4445d187a 100644 --- a/tests/testthat/setup.R +++ b/tests/testthat/setup.R @@ -18,4 +18,4 @@ if (identical(Sys.getenv("NOT_CRAN"), "true")) { withr::defer(future::plan("sequential"), teardown_env()) ## process warning once as previous behaviour has been deprecated -empty <- suppressWarnings(fixed(0))) +empty <- suppressWarnings(fixed(0)) diff --git a/tests/testthat/test-delays.R b/tests/testthat/test-delays.R index e7daddf7e..e33e4e620 100644 --- a/tests/testthat/test-delays.R +++ b/tests/testthat/test-delays.R @@ -12,27 +12,26 @@ test_stan_delays <- function(generation_time = generation_time_opts(), } delay_params <- - c("delay_mean_mean", "delay_mean_sd", "delay_sd_mean", "delay_sd_sd", "delay_max", - "delay_np_pmf") + c("delay_params_mean", "delay_params_sd", "delay_max", "delay_np_pmf") test_that("generation times can be specified in different ways", { expect_equal( test_stan_delays(params = delay_params), - c(0, 1) + c(0, 1, 1, 1) ) expect_equal( test_stan_delays( generation_time = generation_time_opts(dist_spec(mean = 3)), params = delay_params ), - c(0, 0, 0, 1) + c(0, 0, 0, 1, 1, 1) ) expect_equal( round(test_stan_delays( generation_time = generation_time_opts(dist_spec(mean = 3, sd = 1, max = 4)), params = delay_params ), digits = 2), - c(0.02, 0.11, 0.22, 0.30, 0.35) + c(0.02, 0.11, 0.22, 0.30, 0.35, 1.00, 1.00) ) }) @@ -42,14 +41,14 @@ test_that("delay parameters can be specified in different ways", { delays = delay_opts(dist_spec(mean = 3)), params = delay_params ), n = -2), - c(0, 0, 0, 1) + c(0, 0, 0, 1, 1) ) expect_equal( tail(round(test_stan_delays( delays = delay_opts(dist_spec(mean = 3, sd = 1, max = 4)), params = delay_params ), digits = 2), n = -2), - c(0.02, 0.11, 0.22, 0.30, 0.35) + c(0.02, 0.11, 0.22, 0.30, 0.35, 1.00) ) }) @@ -59,26 +58,7 @@ test_that("truncation parameters can be specified in different ways", { truncation = trunc_opts(dist = dist_spec(mean = 3, sd = 1, max = 4)), params = delay_params ), digits = 2), n = -2), - c(0.02, 0.11, 0.22, 0.30, 0.35) - ) -}) - -test_that("contradictory generation times are caught", { - expect_error(generation_time_opts(dist_spec(mean = 3.5)), "must be an integer") - expect_error( - generation_time_opts(dist_spec(mean = 3, mean_sd = 1)), - "must be 0" - ) -}) - -test_that("contradictory delays are caught", { - expect_error( - test_stan_delays(delays = delay_opts(dist_spec(mean = 3.5))), - "must be an integer" - ) - expect_error( - test_stan_delays(delays = delay_opts(dist_spec(mean = 3, mean_sd = 1))), - "must be 0" + c(1.00, 0.02, 0.11, 0.22, 0.30, 0.35) ) }) diff --git a/tests/testthat/test-dist.R b/tests/testthat/test-dist.R index 0902f7183..5a505b869 100644 --- a/tests/testthat/test-dist.R +++ b/tests/testthat/test-dist.R @@ -19,9 +19,11 @@ test_that("distributions are the same in R and stan", { ) pmf_stan_lognormal <- discretised_pmf( - args$mean, args$sd, args$max_value + 1, 0 + unlist(lognormal_params), args$max_value + 1, 0 + ) + pmf_stan_gamma <- discretised_pmf( + unlist(gamma_params), args$max_value + 1, 1 ) - pmf_stan_gamma <- discretised_pmf(args$mean, args$sd, args$max_value + 1, 1) expect_equal(pmf_r_lognormal, pmf_stan_lognormal) expect_equal(pmf_r_gamma, pmf_stan_gamma) diff --git a/tests/testthat/test-dist_spec.R b/tests/testthat/test-dist_spec.R index f4b411c62..5c3cd9900 100644 --- a/tests/testthat/test-dist_spec.R +++ b/tests/testthat/test-dist_spec.R @@ -1,11 +1,10 @@ test_that("dist_spec returns correct output for fixed lognormal distribution", { result <- dist_spec(mean = 5, sd = 1, max = 19, distribution = "lognormal") - expect_equal(dim(result$mean_mean), 0) - expect_equal(dim(result$sd_mean), 0) + expect_equal(dim(result$params_mean), 0) expect_equal(dim(result$dist), 0) expect_equal(dim(result$max), 0) - expect_equal(result$fixed, array(1)) + expect_equal(result$parametric, array(FALSE)) expect_equal( as.vector(round(result$np_pmf, 2)), c(0.00, 0.00, 0.00, 0.00, 0.01, 0.01, 0.02, 0.03, @@ -16,25 +15,22 @@ test_that("dist_spec returns correct output for fixed lognormal distribution", { test_that("dist_spec returns correct output for uncertain gamma distribution", { result <- dist_spec( - mean = 3, sd = 2, mean_sd = 0.5, sd_sd = 0.5, max = 19, - distribution = "gamma" + params_mean = c(3, 2), params_sd = c(0.5, 0.5), distribution = "gamma", + max = 19 ) - expect_equal(result$mean_mean, array(3L)) - expect_equal(result$sd_mean, array(2)) - expect_equal(result$mean_sd, array(0.5)) - expect_equal(result$sd_sd, array(0.5)) + expect_equal(result$params_mean, array(c(3, 2))) + expect_equal(result$params_sd, array(c(0.5, 0.5))) expect_equal(result$dist, array("gamma")) expect_equal(result$max, array(19)) - expect_equal(result$fixed, array(0L)) + expect_equal(result$parametric, array(TRUE)) }) test_that("dist_spec returns correct output for fixed distribution", { result <- fix_dist(dist_spec( mean = 5, mean_sd = 3, sd = 1, max = 19, distribution = "lognormal", )) - expect_equal(dim(result$mean_mean), 0) - expect_equal(dim(result$sd_mean), 0) - expect_equal(result$fixed, array(1L)) + expect_equal(dim(result$params_mean), 0) + expect_equal(result$parametric, array(FALSE)) expect_equal( as.vector(round(result$np_pmf, 2)), c(0.00, 0.00, 0.00, 0.00, 0.01, 0.01, 0.02, 0.03, @@ -50,22 +46,18 @@ test_that("dist_spec returns error when both pmf and distributional parameters a test_that("dist_spec returns error when mean is missing but other distributional parameters are given", { expect_error(dist_spec(sd = 1, max = 20, distribution = "lognormal"), - "If any distributional parameters are given then so must the mean.") -}) - -test_that("dist_spec returns error when maximum of parametric distributions is not specified", { - expect_error(dist_spec(mean = 5, sd = 1, distribution = "lognormal"), - "Maximum of parametric distributions must be specified.") + "is missing.") }) test_that("+.dist_spec returns correct output for sum of two distributions", { lognormal <- dist_spec(mean = 5, sd = 1, max = 19, distribution = "lognormal") - gamma <- dist_spec(mean = 3, sd = 2, mean_sd = 0.5, sd_sd = 0.5, max = 20, distribution = "gamma") + gamma <- dist_spec( + params_mean = c(3, 2), params_sd = c(0.5, 0.5), max = 20, + distribution = "gamma" + ) result <- lognormal + gamma - expect_equal(result$mean_mean, array(3)) - expect_equal(result$sd_mean, array(2)) - expect_equal(result$mean_sd, array(0.5)) - expect_equal(result$sd_sd, array(0.5)) + expect_equal(result$params_mean, array(c(3, 2))) + expect_equal(result$params_sd, array(c(0.5, 0.5))) expect_equal(result$n, 2) expect_equal(result$n_p, 1) expect_equal(result$n_np, 1) @@ -80,8 +72,7 @@ test_that("+.dist_spec returns correct output for sum of two fixed distributions mean = 3, sd = 2, max = 19, distribution = "gamma" )) result <- lognormal + gamma - expect_equal(dim(result$mean_mean), 0) - expect_equal(dim(result$sd_mean), 0) + expect_equal(dim(result$params_mean), 0) expect_equal(result$n, 1) expect_equal(result$n_p, 0) expect_equal(result$n_np, 1) @@ -92,8 +83,7 @@ test_that("+.dist_spec returns correct output for sum of two nonparametric distr lognormal <- dist_spec(pmf = c(0.1, 0.2, 0.3, 0.4)) gamma <- dist_spec(pmf = c(0.1, 0.2, 0.3, 0.4)) result <- lognormal + gamma - expect_equal(dim(result$mean_mean), 0) - expect_equal(dim(result$sd_mean), 0) + expect_equal(dim(result$params_mean), 0) expect_equal(result$n, 1) expect_equal(result$n_p, 0) expect_equal(result$n_np, 1) @@ -150,9 +140,9 @@ test_that("mean.dist_spec returns correct output for fixed lognormal distributio }) test_that("mean.dist_spec returns correct output for uncertain gamma distribution", { - gamma <- dist_spec(mean = 3, sd = 2, mean_sd = 0.5, sd_sd = 0.5, max = 19, distribution = "gamma") + gamma <- dist_spec(params_mean = c(3, 2), params_sd = c(0.5, 0.5), max = 19, distribution = "gamma") result <- EpiNow2:::mean.dist_spec(gamma) - expect_equal(result, 3) + expect_equal(result, 1.5) }) test_that("mean.dist_spec returns correct output for sum of two distributions", { @@ -165,30 +155,30 @@ test_that("mean.dist_spec returns correct output for sum of two distributions", test_that("print.dist_spec correctly prints the parameters of the fixed lognormal", { lognormal <- dist_spec(mean = 1.5, sd = 0.5, max = 19, distribution = "lognormal") - expect_output(print(lognormal), "\\n Fixed distribution with PMF \\[0\\.0014 0\\.052 0\\.16 0\\.2 0\\.18 0\\.13 0\\.094 0\\.063 0\\.042 0\\.027 0\\.018 0\\.012 0\\.0079 0\\.0052 0\\.0035 0\\.0024 0\\.0016 0\\.0011 0\\.00078 0\\.00055\\]\\n") + expect_output(print(lognormal), "\\n distribution with PMF \\[0\\.0014 0\\.052 0\\.16 0\\.2 0\\.18 0\\.13 0\\.094 0\\.063 0\\.042 0\\.027 0\\.018 0\\.012 0\\.0079 0\\.0052 0\\.0035 0\\.0024 0\\.0016 0\\.0011 0\\.00078 0\\.00055\\]\\.\\n") }) test_that("print.dist_spec correctly prints the parameters of the uncertain gamma", { gamma <- dist_spec( - mean = 3, sd = 2, mean_sd = 0.5, sd_sd = 0.5, max = 19, + params_mean = c(3, 2), params_sd = c(0.5, 0.5), max = 19, distribution = "gamma" ) - expect_output(print(gamma), "\\n Uncertain gamma distribution with \\(untruncated\\) mean 3 \\(SD 0\\.5\\) and SD 2 \\(SD 0\\.5\\)\\n") + expect_output(print(gamma), "\\n gamma distribution \\(max: 19\\) with uncertain shape \\(mean = 3, sd = 0.5\\) and uncertain rate \\(mean = 2, sd = 0\\.5\\)\\.\\n") }) test_that("print.dist_spec correctly prints the parameters of the uncertain lognormal", { lognormal_uncertain <- dist_spec(mean = 1.5, sd = 0.5, mean_sd = 0.1, sd_sd = 0.1, max = 19, distribution = "lognormal") - expect_output(print(lognormal_uncertain), "\\n Uncertain lognormal distribution with \\(untruncated\\) logmean 1\\.5 \\(SD 0\\.1\\) and logSD 0\\.5 \\(SD 0\\.1\\)\\n") + expect_output(print(lognormal_uncertain), "\\n lognormal distribution \\(max: 19\\) with uncertain meanlog \\(mean = 1\\.5, sd = 0\\.1\\) and uncertain sdlog \\(mean = 0\\.5, sd = 0\\.1\\)\\.\\n") }) test_that("print.dist_spec correctly prints the parameters of a combination of distributions", { lognormal <- dist_spec(mean = 1.5, sd = 0.5, max = 19, distribution = "lognormal") - gamma <- dist_spec(mean = 3, sd = 2, mean_sd = 0.5, sd_sd = 0.5, max = 19, distribution = "gamma") + gamma <- dist_spec(params_mean = c(3, 2), params_sd = c(0.5, 0.5), max = 19, distribution = "gamma") combined <- lognormal + gamma - expect_output(print(combined), "Combination of delay distributions:\\n Fixed distribution with PMF \\[0\\.0014 0\\.052 0\\.16 0\\.2 0\\.18 0\\.13 0\\.094 0\\.063 0\\.042 0\\.027 0\\.018 0\\.012 0\\.0079 0\\.0052 0\\.0035 0\\.0024 0\\.0016 0\\.0011 0\\.00078 0\\.00055\\]\\n Uncertain gamma distribution with \\(untruncated\\) mean 3 \\(SD 0\\.5\\) and SD 2 \\(SD 0\\.5\\)\\n") + expect_output(print(combined), "\\nComposite delay distribution:\\n distribution with PMF \\[0\\.0014 0\\.052 0\\.16 0\\.2 0\\.18 0\\.13 0\\.094 0\\.063 0\\.042 0\\.027 0\\.018 0\\.012 0\\.0079 0\\.0052 0\\.0035 0\\.0024 0\\.0016 0\\.0011 0\\.00078 0\\.00055\\]\\.\\n gamma distribution \\(max: 19\\) with uncertain shape \\(mean = 3, sd = 0\\.5\\) and uncertain rate \\(mean = 2, sd = 0\\.5\\)\\.\\n") }) test_that("plot.dist_spec returns a ggplot object", { diff --git a/tests/testthat/test-estimate_secondary.R b/tests/testthat/test-estimate_secondary.R index f252bc0f0..3f272014d 100644 --- a/tests/testthat/test-estimate_secondary.R +++ b/tests/testthat/test-estimate_secondary.R @@ -29,7 +29,7 @@ inc <- estimate_secondary(inc_cases[1:60], # extract posterior variables of interest params <- c( - "meanlog" = "delay_mean[1]", "sdlog" = "delay_sd[1]", + "meanlog" = "delay_params[1]", "sdlog" = "delay_params[2]", "scaling" = "frac_obs[1]" ) diff --git a/tests/testthat/test-estimate_truncation.R b/tests/testthat/test-estimate_truncation.R index c1fd03e8e..f0358407d 100644 --- a/tests/testthat/test-estimate_truncation.R +++ b/tests/testthat/test-estimate_truncation.R @@ -24,8 +24,8 @@ construct_truncation <- function(index, cases, dist) { cmf <- cumsum( dlnorm( 1:(dist$max + 1), - rnorm(1, dist$mean_mean, dist$mean_sd), - rnorm(1, dist$sd_mean, dist$sd_sd) + rnorm(1, dist$params_mean[1], dist$params_sd[1]), + rnorm(1, dist$params_mean[2], dist$params_sd[2]) ) ) cmf <- cmf / cmf[dist$max + 1] diff --git a/tests/testthat/test-report_cases.R b/tests/testthat/test-report_cases.R index 41d8062de..40506257c 100644 --- a/tests/testthat/test-report_cases.R +++ b/tests/testthat/test-report_cases.R @@ -15,6 +15,6 @@ test_that("report_cases can simulate infections forward", { expect_equal(class(reported_cases), "list") expect_equal(class(reported_cases$samples), c("data.table", "data.frame")) expect_equal(class(reported_cases$summarised), c("data.table", "data.frame")) - expect_equal(nrow(reported_cases$summarised), 10) + expect_equal(nrow(reported_cases$summarised), 9) expect_equal(class(reported_cases$summarised$median), "numeric") }) diff --git a/tests/testthat/test-stan-infections.R b/tests/testthat/test-stan-infections.R index 15736f996..1b43f7baa 100644 --- a/tests/testthat/test-stan-infections.R +++ b/tests/testthat/test-stan-infections.R @@ -14,11 +14,11 @@ test_that("update_infectiousness works as expected with default settings", { expect_error(update_infectiousness(rep(1, 20), rep(0.1, 5), 5, 10, 10)) }) -pmf <- discretised_pmf(3, 2, 15, 1) +pmf <- discretised_pmf(c(2.25, 0.75), 15, 1) gt_rev_pmf <- get_delay_rev_pmf( 1L, 15L, array(0L), array(1L), array(c(1L, 2L)), array(15L), pmf, - array(c(1L, 16L)), numeric(0), numeric(0), 0L, + array(c(1L, 16L)), numeric(0), 1L, 0L, 1L, 1L, 0L ) diff --git a/tests/testthat/test-stan-secondary.R b/tests/testthat/test-stan-secondary.R index a408a54c2..0fc6d998c 100644 --- a/tests/testthat/test-stan-secondary.R +++ b/tests/testthat/test-stan-secondary.R @@ -4,7 +4,7 @@ skip_on_os("windows") # test primary reports and observations reports <- rep(10, 20) obs <- rep(4, 20) -delay_pmf <- reverse_mf(discretised_pmf(log(3), 0.1, 5, 0)) +delay_pmf <- reverse_mf(discretised_pmf(c(log(3), 0.1), 5, 0)) check_equal <- function(args, target, dof = 0, dev = FALSE) { out <- do.call(calculate_secondary, args) From 19b2a910f15ea9e04533f6f46c6d3e5f2fb6254e Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Tue, 21 Nov 2023 11:36:27 +0000 Subject: [PATCH 029/129] add documentation to dist interface --- R/dist.R | 140 ++++++++++++++++++++++++++++++++---- man/Distributions.Rd | 86 ++++++++++++++++++++++ man/convert_to_natural.Rd | 24 +++++++ man/create_delay_inits.Rd | 2 +- man/dist_spec.Rd | 7 +- man/dot-dist_spec.Rd | 4 +- man/extract_params.Rd | 25 +++++++ man/extract_single_dist.Rd | 4 +- man/fix_dist.Rd | 4 +- man/generate_dist_spec.Rd | 24 +++++++ man/generation_time_opts.Rd | 8 ++- man/lower_bounds.Rd | 24 +++++++ man/natural_params.Rd | 26 +++++++ man/plus-.dist_spec.Rd | 15 ++-- 14 files changed, 358 insertions(+), 35 deletions(-) create mode 100644 man/Distributions.Rd create mode 100644 man/convert_to_natural.Rd create mode 100644 man/extract_params.Rd create mode 100644 man/generate_dist_spec.Rd create mode 100644 man/lower_bounds.Rd create mode 100644 man/natural_params.Rd diff --git a/R/dist.R b/R/dist.R index a0d8e81b6..dc3c25b56 100644 --- a/R/dist.R +++ b/R/dist.R @@ -873,10 +873,7 @@ tune_inv_gamma <- function(lower = 2, upper = 21) { #' #' @param sd_sd Deprecated; use `params_sd` instead. #' -#' @param fixed Deprecated, use [fix_dist()] instead -#' as coming from fixed (vs uncertain) distributions. Overrides any values -#' assigned to \code{mean_sd} and \code{sd_sd} by setting them to zero. -#' reduces compute requirement but may produce spuriously precise estimates. +#' @param fixed Deprecated, use [fix_dist()] instead. #' @return A list of distribution options. #' #' @author Sebastian Funk @@ -975,7 +972,7 @@ dist_spec <- function(distribution = c( #' #' @param distribution Character, defaults to "lognormal". The (discretised) #' distribution to be used. Can be "lognormal", "gamma", "normal" or "fixed". -#' The corresponding parameters (defined in [natural_parameters()]) are passed +#' The corresponding parameters (defined in [natural_params()]) are passed #' as `params_mean`, and their uncertainty as `params_sd`. #' #' @param max Numeric, maximum value of the distribution. The distribution will @@ -1002,7 +999,7 @@ dist_spec <- function(distribution = c( #' # An uncertain gamma distribution with mean 3 and sd 2 #' .dist_spec( #' params_mean = c(alpha = 3, beta = 0.5), -#' params_sd = c(alpha = 75, beta = 25) +#' params_sd = c(alpha = 0.75, beta = 0.25), #' distribution = "gamma" #' ) .dist_spec <- function(distribution = c( @@ -1020,7 +1017,7 @@ dist_spec <- function(distribution = c( deprecate_warn( "2.0.0", "dist_spec(distribution = 'must not be \"empty\"')", - detail = "Please use `fixed(0)` instead." + details = "Please use `fixed(0)` instead." ) } @@ -1640,25 +1637,85 @@ fix_dist <- function(x, strategy = c("mean", "sample")) { return(ret) } +##' @details +##' Probability distributions are ubiquitous in EpiNow2, usually representing +##' epidemiological delays (e.g., the generation time for delays between +##' becoming infecting and infecting others; or reporting delays) +##' +##' They are generated using functions that have a name corresponding to the +##' probability distribution that is being used. They generated `dist_spec` +##' objects that are then passed to the models underlying EpiNow2. +## +##' All parameters can be given either as fixed values (a numeric value) or as +##' uncertain values (a `dist_sepc`). If given as uncertain values, currently +##' only normally distributed parameters (generated using `normal()`) are +##' supported. +##' +##' Each distribution has a representation in terms of "natural" parameters (the +##' ones used in stan) but can sometimes also be specified using other +##' parameters such as the mean or standard deviation of the distribution. If +##' not given as natural parameters then these will be calculated from the given +##' parameters. If they have uncertainty, this will be done by random sampling +##' from the given uncertainty and coverting resulting parameters to their +##' natural representation. +##' +##' Currently available distributions are lognormal, gamma, normal, fixed +##' (delta) and nonparametric. The nonparametric is a special case where the +##' probability mass function is given directly as a numeric vector. +##' +##' @inheritParams stats::Lognormal +##' @inheritParams .dist_spec +##' @return A `dist_spec` representing a distribution of the given +##' specification. +##' @author Sebastian Funk ##' @export -lognormal <- function(meanlog, sdlog, mean, sd, median, max = Inf) { +##' @rdname Distributions +##' @name Distributions +##' @order 1 +##' @examples +##' lognormal(mean = 4, sd = 1) +##' lognormal(mean = 4, sd = 1, max = 10) +##' lognormal(mean = normal(4, 1), sd = 1, max = 10) +lognormal <- function(meanlog, sdlog, mean, sd, max = Inf) { params <- as.list(environment()) - return(process_dist(params, "lognormal")) + return(generate_dist_spec(params, "lognormal")) } +##' @inheritParams stats::Gamma +##' @author Sebastian Funk +##' @rdname Distributions +##' @title Probability distributions +##' @order 2 ##' @export +##' @examples +##' gamma(mean = 4, sd = 1) +##' gamma(shape = 16, rate = 4) +##' gamma(shape = normal(16, 2), rate = normal(4, 1)) gamma <- function(shape, rate, scale, mean, sd, max = Inf) { params <- as.list(environment()) - return(process_dist(params, "gamma")) + return(generate_dist_spec(params, "gamma")) } +##' @rdname Distributions +##' @order 3 +##' @author Sebastian Funk ##' @export +##' @examples +##' normal(mean = 4, sd = 1) +##' normal(mean = 4, sd = 1, max = 10) normal <- function(mean, sd, max = Inf) { params <- as.list(environment()) - return(process_dist(params, "normal")) + return(generate_dist_spec(params, "normal")) } +##' @rdname Distributions +##' @order 4 +##' @param value Value of the fixed (delta) distribution +##' @author Sebastian Funk ##' @export +##' @examples +##' fixed(value = 3) +##' fixed(value = 3.5) fixed <- function(value) { params <- as.list(environment()) params <- extract_params(params, "fixed") @@ -1670,11 +1727,34 @@ fixed <- function(value) { return(.dist_spec(params_mean = fixed_value, distribution = "fixed")) } +##' Generates a nonparametric distribution. +##' +##' @param pmf Probability mass function of the given distribution; this is +##' passed as a zero-indexed numeric vector (i.e. the fist entry represents +##' the probability mass of zero). If not summing to one it will be normalised +##' to sum to one internally. +##' @author Sebastian Funk +##' @rdname Distributions +##' @order 5 ##' @export +##' @examples +##' pmf(c(0.1, 0.3, 0.2, 0.4)) +##' pmf(c(0.1, 0.3, 0.2, 0.1, 0.1)) pmf <- function(x) { return(.dist_spec(pmf = x)) } +##' Get the names of the natural parameters of a distribution +##' +##' These are the parameters used in the stan models. All other parameter +##' representations are converted to these using [convert_to_natural()] before +##' being passed to teh stan mnodels. +##' @param distribution Character; the distribution to use. +##' @return A character vector, the natural parameters. +##' @author Sebastian Funk +##' @keywords internal +##' @examples +##' natural_params("gamma") natural_params <- function(distribution) { if (distribution == "gamma") { ret <- c("shape", "rate") @@ -1688,11 +1768,20 @@ natural_params <- function(distribution) { return(ret) } +##' Get the lower bounds of the parameters of a distribution +##' +##' This is used to avoid sampling parameter values that have no support. +##' @return A numeric vector, the lower bounds. +##' @inheritParams natural_params +##' @author Sebastian Funk +##' @keywords internal +##' @examples +##' lower_bounds("lognormal") lower_bounds <- function(distribution) { if (distribution == "gamma") { ret <- c(shape = 0, rate = 0, scale = 0, mean = 0, sd = 0) } else if (distribution == "lognormal") { - ret <- c(meanlog = -Inf, sdlog = 0, mean = 0, sd = 0, median = 0) + ret <- c(meanlog = -Inf, sdlog = 0, mean = 0, sd = 0) } else if (distribution == "normal") { ret <- c(mean = -Inf, sd = 0) } else if (distribution == "fixed") { @@ -1701,6 +1790,14 @@ lower_bounds <- function(distribution) { return(ret) } +##' Internal function for extracting given parameter names of a distribution +##' from the environment +##' +##' @param params Given parameters (obtained using `as.list(environment())`) +##' @return A character vector of parameters and their values. +##' @inheritParams natural_params +##' @author Sebastian Funk +##' @keywords internal extract_params <- function(params, distribution) { params <- params[!vapply(params, inherits, "name", FUN.VALUE = TRUE)] n_params <- length(natural_params(distribution)) @@ -1713,7 +1810,15 @@ extract_params <- function(params, distribution) { return(params) } -process_dist <- function(params, distribution) { +##' Internal function for generating a `dist_spec` given parametrs and a +##' distribution. +##' +##' This will convert all parameters to natural parameters before generating +##' a `dist_spec`. If they have uncertainty this will be done using sampling. +##' @inheritParams extract_params +##' @return A `dist_spec` of the given specificaiton.` +##' @author Sebastian Funk +generate_dist_spec <- function(params, distribution) { ## process min/max first max <- params$max params$max <- NULL @@ -1764,6 +1869,15 @@ process_dist <- function(params, distribution) { return(dist) } +##' Internal function for converting parameters to natural parameters. +##' +##' This is used for preprocessing before generating a `dist_spec` object +##' from a given set of parametrs and distribution +##' @param x A numerical named parameter vector +##' @inheritParams natural_params +##' @return A list with two elements, `params_mean` and `params_sd`, containign +##' mean and sd of natural parameters. +##' @author Sebastian Funk convert_to_natural <- function(x, distribution) { if (distribution == "gamma") { if ("mean" %in% names(x) && "sd" %in% names(x)) { diff --git a/man/Distributions.Rd b/man/Distributions.Rd new file mode 100644 index 000000000..947b4c8c1 --- /dev/null +++ b/man/Distributions.Rd @@ -0,0 +1,86 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/dist.R +\name{Distributions} +\alias{Distributions} +\alias{lognormal} +\alias{gamma} +\alias{normal} +\alias{fixed} +\alias{pmf} +\title{Probability distributions} +\usage{ +lognormal(meanlog, sdlog, mean, sd, max = Inf) + +gamma(shape, rate, scale, mean, sd, max = Inf) + +normal(mean, sd, max = Inf) + +fixed(value) + +pmf(x) +} +\arguments{ +\item{meanlog, sdlog}{mean and standard deviation of the distribution + on the log scale with default values of \code{0} and \code{1} respectively.} + +\item{max}{Numeric, maximum value of the distribution. The distribution will +be truncated at this value. Default: \code{Inf}, i.e. no maximum.} + +\item{value}{Value of the fixed (delta) distribution} + +\item{pmf}{Probability mass function of the given distribution; this is +passed as a zero-indexed numeric vector (i.e. the fist entry represents +the probability mass of zero). If not summing to one it will be normalised +to sum to one internally.} +} +\value{ +A \code{dist_spec} representing a distribution of the given +specification. +} +\description{ +Probability distributions + +Generates a nonparametric distribution. +} +\details{ +Probability distributions are ubiquitous in EpiNow2, usually representing +epidemiological delays (e.g., the generation time for delays between +becoming infecting and infecting others; or reporting delays) + +They are generated using functions that have a name corresponding to the +probability distribution that is being used. They generated \code{dist_spec} +objects that are then passed to the models underlying EpiNow2. +All parameters can be given either as fixed values (a numeric value) or as +uncertain values (a \code{dist_sepc}). If given as uncertain values, currently +only normally distributed parameters (generated using \code{normal()}) are +supported. + +Each distribution has a representation in terms of "natural" parameters (the +ones used in stan) but can sometimes also be specified using other +parameters such as the mean or standard deviation of the distribution. If +not given as natural parameters then these will be calculated from the given +parameters. If they have uncertainty, this will be done by random sampling +from the given uncertainty and coverting resulting parameters to their +natural representation. + +Currently available distributions are lognormal, gamma, normal, fixed +(delta) and nonparametric. The nonparametric is a special case where the +probability mass function is given directly as a numeric vector. +} +\examples{ +lognormal(mean = 4, sd = 1) +lognormal(mean = 4, sd = 1, max = 10) +lognormal(mean = normal(4, 1), sd = 1, max = 10) +gamma(mean = 4, sd = 1) +gamma(shape = 16, rate = 4) +gamma(shape = normal(16, 2), rate = normal(4, 1)) +normal(mean = 4, sd = 1) +normal(mean = 4, sd = 1, max = 10) +fixed(value = 3) +fixed(value = 3.5) +pmf(c(0.1, 0.3, 0.2, 0.4)) +pmf(c(0.1, 0.3, 0.2, 0.1, 0.1)) +} +\author{ +Sebastian Funk +} diff --git a/man/convert_to_natural.Rd b/man/convert_to_natural.Rd new file mode 100644 index 000000000..29d700cae --- /dev/null +++ b/man/convert_to_natural.Rd @@ -0,0 +1,24 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/dist.R +\name{convert_to_natural} +\alias{convert_to_natural} +\title{Internal function for converting parameters to natural parameters.} +\usage{ +convert_to_natural(x, distribution) +} +\arguments{ +\item{x}{A numerical named parameter vector} + +\item{distribution}{Character; the distribution to use.} +} +\value{ +A list with two elements, \code{params_mean} and \code{params_sd}, containign +mean and sd of natural parameters. +} +\description{ +This is used for preprocessing before generating a \code{dist_spec} object +from a given set of parametrs and distribution +} +\author{ +Sebastian Funk +} diff --git a/man/create_delay_inits.Rd b/man/create_delay_inits.Rd index f825b0de2..3d957aa50 100644 --- a/man/create_delay_inits.Rd +++ b/man/create_delay_inits.Rd @@ -7,7 +7,7 @@ create_delay_inits(data) } \arguments{ -\item{data}{A list of data as produced by \code{create_stan_data.}} +\item{data}{A list of data as produced by \code{\link[=create_stan_data]{create_stan_data()}}.} } \value{ A list of initial conditions for delays diff --git a/man/dist_spec.Rd b/man/dist_spec.Rd index d8f324669..277548887 100644 --- a/man/dist_spec.Rd +++ b/man/dist_spec.Rd @@ -20,7 +20,7 @@ dist_spec( \arguments{ \item{distribution}{Character, defaults to "lognormal". The (discretised) distribution to be used. Can be "lognormal", "gamma", "normal" or "fixed". -The corresponding parameters (defined in \code{\link[=natural_parameters]{natural_parameters()}}) are passed +The corresponding parameters (defined in \code{\link[=natural_params]{natural_params()}}) are passed as \code{params_mean}, and their uncertainty as \code{params_sd}.} \item{params_mean}{Numeric. Central values of the parameters of the @@ -45,10 +45,7 @@ probability mass function of the delay (starting with 0); defaults to an empty vector corresponding to a parametric specification of the distribution (using \code{params_mean}, and \code{params_sd}.} -\item{fixed}{Deprecated, use \code{\link[=fix_dist]{fix_dist()}} instead -as coming from fixed (vs uncertain) distributions. Overrides any values -assigned to \code{mean_sd} and \code{sd_sd} by setting them to zero. -reduces compute requirement but may produce spuriously precise estimates.} +\item{fixed}{Deprecated, use \code{\link[=fix_dist]{fix_dist()}} instead.} } \value{ A list of distribution options. diff --git a/man/dot-dist_spec.Rd b/man/dot-dist_spec.Rd index 4e3f9d076..c012c7c74 100644 --- a/man/dot-dist_spec.Rd +++ b/man/dot-dist_spec.Rd @@ -15,7 +15,7 @@ \arguments{ \item{distribution}{Character, defaults to "lognormal". The (discretised) distribution to be used. Can be "lognormal", "gamma", "normal" or "fixed". -The corresponding parameters (defined in \code{\link[=natural_parameters]{natural_parameters()}}) are passed +The corresponding parameters (defined in \code{\link[=natural_params]{natural_params()}}) are passed as \code{params_mean}, and their uncertainty as \code{params_sd}.} \item{params_mean}{Numeric. Central values of the parameters of the @@ -55,7 +55,7 @@ functionality in \code{\link[=delay_opts]{delay_opts()}}, \code{\link[=generatio # An uncertain gamma distribution with mean 3 and sd 2 .dist_spec( params_mean = c(alpha = 3, beta = 0.5), - params_sd = c(alpha = 75, beta = 25) + params_sd = c(alpha = 0.75, beta = 0.25), distribution = "gamma" ) } diff --git a/man/extract_params.Rd b/man/extract_params.Rd new file mode 100644 index 000000000..fe5b0d834 --- /dev/null +++ b/man/extract_params.Rd @@ -0,0 +1,25 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/dist.R +\name{extract_params} +\alias{extract_params} +\title{Internal function for extracting given parameter names of a distribution +from the environment} +\usage{ +extract_params(params, distribution) +} +\arguments{ +\item{params}{Given parameters (obtained using \code{as.list(environment())})} + +\item{distribution}{Character; the distribution to use.} +} +\value{ +A character vector of parameters and their values. +} +\description{ +Internal function for extracting given parameter names of a distribution +from the environment +} +\author{ +Sebastian Funk +} +\keyword{internal} diff --git a/man/extract_single_dist.Rd b/man/extract_single_dist.Rd index ac40eabb0..6ed137e1c 100644 --- a/man/extract_single_dist.Rd +++ b/man/extract_single_dist.Rd @@ -2,7 +2,7 @@ % Please edit documentation in R/dist.R \name{extract_single_dist} \alias{extract_single_dist} -\title{Extract a single element of a composite \code{dist_spec}} +\title{Extract a single element of a composite \verb{}} \usage{ extract_single_dist(x, i) } @@ -15,7 +15,7 @@ extract_single_dist(x, i) A single \code{dist_spec} object } \description{ -Extract a single element of a composite \code{dist_spec} +Extract a single element of a composite \verb{} } \author{ Sebastian Funk diff --git a/man/fix_dist.Rd b/man/fix_dist.Rd index 565d59d8e..a11ffbd8d 100644 --- a/man/fix_dist.Rd +++ b/man/fix_dist.Rd @@ -2,12 +2,12 @@ % Please edit documentation in R/dist.R \name{fix_dist} \alias{fix_dist} -\title{Fix the parameters of a \verb{} object} +\title{Fix the parameters of a \verb{}} \usage{ fix_dist(x, strategy = c("mean", "sample")) } \arguments{ -\item{x}{A \verb{} object} +\item{x}{A \verb{}} \item{strategy}{Character; either "mean" (use the mean estimates of the mean and standard deviation) or "sample" (randomly sample mean and diff --git a/man/generate_dist_spec.Rd b/man/generate_dist_spec.Rd new file mode 100644 index 000000000..867ac023e --- /dev/null +++ b/man/generate_dist_spec.Rd @@ -0,0 +1,24 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/dist.R +\name{generate_dist_spec} +\alias{generate_dist_spec} +\title{Internal function for generating a \code{dist_spec} given parametrs and a +distribution.} +\usage{ +generate_dist_spec(params, distribution) +} +\arguments{ +\item{params}{Given parameters (obtained using \code{as.list(environment())})} + +\item{distribution}{Character; the distribution to use.} +} +\value{ +A \code{dist_spec} of the given specificaiton.` +} +\description{ +This will convert all parameters to natural parameters before generating +a \code{dist_spec}. If they have uncertainty this will be done using sampling. +} +\author{ +Sebastian Funk +} diff --git a/man/generation_time_opts.Rd b/man/generation_time_opts.Rd index 829e1d313..d3adc7e22 100644 --- a/man/generation_time_opts.Rd +++ b/man/generation_time_opts.Rd @@ -45,11 +45,15 @@ Returns generation time parameters in a format for lower level model use. generation_time_opts() # A fixed gamma distributed generation time -generation_time_opts(dist_spec(mean = 3, sd = 2, max = 14)) +generation_time_opts(gamma(mean = 3, sd = 2, max = 14)) # An uncertain gamma distributed generation time generation_time_opts( - dist_spec(mean = 3, sd = 2, mean_sd = 1, sd_sd = 0.5, max = 14) + gamma( + mean = normal(mean = 3, sd = 1), + sd = normal(mean = 2, sd = 0.5), + max = 14 + ) ) # An example generation time diff --git a/man/lower_bounds.Rd b/man/lower_bounds.Rd new file mode 100644 index 000000000..968285241 --- /dev/null +++ b/man/lower_bounds.Rd @@ -0,0 +1,24 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/dist.R +\name{lower_bounds} +\alias{lower_bounds} +\title{Get the lower bounds of the parameters of a distribution} +\usage{ +lower_bounds(distribution) +} +\arguments{ +\item{distribution}{Character; the distribution to use.} +} +\value{ +A numeric vector, the lower bounds. +} +\description{ +This is used to avoid sampling parameter values that have no support. +} +\examples{ +lower_bounds("lognormal") +} +\author{ +Sebastian Funk +} +\keyword{internal} diff --git a/man/natural_params.Rd b/man/natural_params.Rd new file mode 100644 index 000000000..c6229989c --- /dev/null +++ b/man/natural_params.Rd @@ -0,0 +1,26 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/dist.R +\name{natural_params} +\alias{natural_params} +\title{Get the names of the natural parameters of a distribution} +\usage{ +natural_params(distribution) +} +\arguments{ +\item{distribution}{Character; the distribution to use.} +} +\value{ +A character vector, the natural parameters. +} +\description{ +These are the parameters used in the stan models. All other parameter +representations are converted to these using \code{\link[=convert_to_natural]{convert_to_natural()}} before +being passed to teh stan mnodels. +} +\examples{ +natural_params("gamma") +} +\author{ +Sebastian Funk +} +\keyword{internal} diff --git a/man/plus-.dist_spec.Rd b/man/plus-.dist_spec.Rd index 942b80d6e..5e47a718a 100644 --- a/man/plus-.dist_spec.Rd +++ b/man/plus-.dist_spec.Rd @@ -25,20 +25,19 @@ numeric stability. } \examples{ # A fixed lognormal distribution with mean 5 and sd 1. -lognormal <- dist_spec( - mean = 1.6, sd = 1, max = 20, distribution = "lognormal" +dist1 <- lognormal_spec( + meanlog = 1.6, sdlog = 1, max = 20, distribution = "lognormal" ) -lognormal + lognormal +dist1 + dist1 # An uncertain gamma distribution with mean 3 and sd 2 -gamma <- dist_spec( - mean = 3, sd = 2, mean_sd = 0.5, sd_sd = 0.5, max = 20, - distribution = "gamma" +dist2 <- gamma( + mean = normal(3, 0.5), sd = normal(2, 0.5), max = 20 ) -lognormal + gamma +dist1 + dist2 # Using tolerance parameter -EpiNow2:::dist_spec_plus(lognormal, lognormal, tolerance = 0.5) +EpiNow2:::dist_spec_plus(dist1, dist1, tolerance = 0.5) } \author{ Sebastian Funk From 48388c7dc67fe5c3882d01d9d86b5206f30326be Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Tue, 21 Nov 2023 12:15:20 +0000 Subject: [PATCH 030/129] add input checks --- R/checks.R | 27 +++++++++++++++++++++++++++ R/dist.R | 19 ++++++++++++++++++- R/opts.R | 3 +++ 3 files changed, 48 insertions(+), 1 deletion(-) diff --git a/R/checks.R b/R/checks.R index ab08fe691..5e5a5bbc8 100644 --- a/R/checks.R +++ b/R/checks.R @@ -54,3 +54,30 @@ check_reports_valid <- function(reports, model) { assert_numeric(reports$confirm, lower = 0) } } + +#' Validate probability distribution for passing to stan +#' +#' @description +#' `check_stan_dist()` checks that the supplied data is a ``, +#' and that it can be further processed by stan. +#' +#' @param dist A `dist_spec` object.` +#' @importFrom checkmate assert_class +#' @importFrom rlang arg_match +#' @return Called for its side effects. +#' @author Sebastian Funk +#' @keywords internal +check_stan_dist <- function(dist) { + # Check that `dist` is a `dist_spec` + assert_class(dist, "dist_spec") + # Check that `dist` is lognormal or gamma or nonparametric + if (!all(dist$dist %in% c("lognormal", "gamma"))) { + stop( + "Distributions passed to the model need to be lognormal, gamma or ", + "nonparametric (i.e., have no uncertainty)." + ) + } + if (any(is.infinite(max(dist)))) { + stop("All distribution passed to the model need to have a finite maximum") + } +} diff --git a/R/dist.R b/R/dist.R index dc3c25b56..73ad1890a 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1027,7 +1027,7 @@ dist_spec <- function(distribution = c( if (distribution == "fixed") { ## if integer fixed then can write the PMF - if (as.integer(params_mean) == params_mean) { + if (as.integer(params_mean) == params_mean && params_mean >= 0) { max <- params_mean parametric <- FALSE } else { @@ -1816,6 +1816,7 @@ extract_params <- function(params, distribution) { ##' This will convert all parameters to natural parameters before generating ##' a `dist_spec`. If they have uncertainty this will be done using sampling. ##' @inheritParams extract_params +##' @importFrom purrr walk ##' @return A `dist_spec` of the given specificaiton.` ##' @author Sebastian Funk generate_dist_spec <- function(params, distribution) { @@ -1839,6 +1840,22 @@ generate_dist_spec <- function(params, distribution) { stop("Parameter ", x, " must be numeric or normally distributed.") } }) + + ## check bounds + for (param_name in names(params)) { + if (!params[[param_name]]$parametric || + params[[param_name]]$dist == "fixed") { + ## no uncertainty, so check if within range + lb <- lower_bounds(distribution)[param_name] + if (mean(params[[param_name]]) < lb) { + stop( + "Parameter ", param_name, " is less than its lower bound ", lb, "." + ) + } + } + } + + ## convert any unnatural parameters unnatural_params <- setdiff(names(params), natural_params(distribution)) if (length(unnatural_params) > 0) { ## sample parameters if they are uncertain diff --git a/R/opts.R b/R/opts.R index 624c05b17..a14ee789a 100644 --- a/R/opts.R +++ b/R/opts.R @@ -98,6 +98,7 @@ generation_time_opts <- function(dist = fixed(1), ..., "information, see the relevant documentation pages using ", "`?generation_time_opts`") } + check_stan_dist(dist) attr(dist, "class") <- c("generation_time_opts", class(dist)) return(dist) } @@ -162,6 +163,7 @@ delay_opts <- function(dist = fixed(0), ..., fixed = FALSE) { ## can be removed once dot options are hard deprecated stop("Unknown named arguments passed to `delay_opts`") } + check_stan_dist(dist) attr(dist, "class") <- c("delay_opts", class(dist)) return(dist) } @@ -206,6 +208,7 @@ trunc_opts <- function(dist = fixed(0)) { "`?trunc_opts`" ) } + check_stan_dist(dist) attr(dist, "class") <- c("trunc_opts", class(dist)) return(dist) } From 4439db7d1f9a3383581d5fd63ecc8853eef6e4b6 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Tue, 21 Nov 2023 12:52:14 +0000 Subject: [PATCH 031/129] sd function to work with composite dists --- R/dist.R | 43 +++++++++++++++++++++++-------------------- 1 file changed, 23 insertions(+), 20 deletions(-) diff --git a/R/dist.R b/R/dist.R index 73ad1890a..57b479d6a 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1310,33 +1310,36 @@ sd <- function(x, ...) UseMethod("sd") #' # The sd of the sum of two distributions #' sd(lognormal + gamma) sd.dist_spec <- function(x, ...) { - if (x$n > 1) { - stop("Cannot calculate standard deviation of composite distributions.") - } + ret <- rep(.0, x$n) if (x$n_np > 0) { ## nonparametric mean_pmf <- sum((seq_len(x$np_pmf_length) - 1) * x$np_pmf) - ret <- sum((seq_len(x$np_pmf_length) - 1)**2 * x$np_pmf) - mean_pmf^2 - } else { + ret[!x$parametric] <- sum((seq_len(x$np_pmf_length) - 1)**2 * x$np_pmf) - + mean_pmf^2 + } + if (x$n_p > 0) { ## parametric if (any(x$params_sd > 0)) { stop("Cannot calculate standard deviation of uncertain distribution") } - if (x$dist == "lognormal") { - ret <- sqrt(exp(x$params_mean[2]**2) - 1) * - exp(x$params_mean[1] + 0.5 * x$params_mean[2]**2) - } else if (x$dist == "gamma") { - ret <- sqrt(x$params_mean[1] / x$params_mean[2]**2) - } else if (x$dist == "normal") { - ret <- x$params_mean[2] - } else if (x$dist == "fixed") { - ret <- 0 - } else { - stop( - "Don't know how to calculate standard deviation of ", x$dist, - " distribution." - ) - } + ret[x$parametric] <- vapply(which(x$parametric), function(id) { + single_dist <- extract_single_dist(x, id) + if (single_dist$dist == "lognormal") { + ret <- sqrt(exp(single_dist$params_mean[2]**2) - 1) * + exp(single_dist$params_mean[1] + 0.5 * single_dist$params_mean[2]**2) + } else if (single_dist$dist == "gamma") { + ret <- sqrt(single_dist$params_mean[1] / single_dist$params_mean[2]**2) + } else if (single_dist$dist == "normal") { + ret <- single_dist$params_mean[2] + } else if (single_dist$dist == "fixed") { + ret <- 0 + } else { + stop( + "Don't know how to calculate standard deviation of ", + single_dist$dist, " distribution." + ) + } + }, .0) } return(ret) } From df6d08a5ebf1fc54a2d951234feefba1e0fb296d Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Tue, 21 Nov 2023 12:52:29 +0000 Subject: [PATCH 032/129] warn when not using natural parameters --- R/dist.R | 25 +++++++++++++++++++------ 1 file changed, 19 insertions(+), 6 deletions(-) diff --git a/R/dist.R b/R/dist.R index 57b479d6a..601581fd9 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1862,13 +1862,26 @@ generate_dist_spec <- function(params, distribution) { unnatural_params <- setdiff(names(params), natural_params(distribution)) if (length(unnatural_params) > 0) { ## sample parameters if they are uncertain - samples <- lapply(names(params), function(x) { - rtruncnorm( - n = 2000, a = lower_bounds(distribution)[x], - mean = mean(params[[x]]), sd = sd(params[[x]]) + if (any(vapply(params, sd, .0) > 0)) { + warning( + "Uncertain ", distribution, " distribution specified in terms of ", + "parameters that are not the \"natural\" parameters of the ", + "distribution (", paste(natural_params(distribution), collapse = ", "), + "). Converting using a finite sample. If possible, it is preferable ", + "to specify the distribution direclty in terms of the natural ", + "parameters." ) - }) - names(samples) <- names(params) + samples <- lapply(names(params), function(x) { + rtruncnorm( + n = 2000, a = lower_bounds(distribution)[x], + mean = mean(params[[x]]), sd = sd(params[[x]]) + ) + }) + names(samples) <- names(params) + } else { + params <- mean(params[[x]]) + } + ## generate natural parameters converted_params <- convert_to_natural(samples, distribution) } else { From f2db571624c7883566d157327bba2db8715eb4ce Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 22 Nov 2023 09:33:43 +0000 Subject: [PATCH 033/129] ensure bounds are respected in stan --- inst/stan/data/delays.stan | 4 ++-- inst/stan/estimate_infections.stan | 4 ++-- inst/stan/estimate_secondary.stan | 2 +- inst/stan/estimate_truncation.stan | 2 +- inst/stan/functions/delays.stan | 6 ++++++ 5 files changed, 12 insertions(+), 6 deletions(-) diff --git a/inst/stan/data/delays.stan b/inst/stan/data/delays.stan index 2401f1b26..55036454b 100644 --- a/inst/stan/data/delays.stan +++ b/inst/stan/data/delays.stan @@ -9,9 +9,9 @@ array[delay_n_np + 1] int delay_np_pmf_groups; // links to ragged array int delay_params_length; // number of parameters across all parametric delay distributions - vector[delay_params_length] delay_params_mean; // ragged array of mean parameters for parametric delay distributions - vector[delay_params_length] delay_params_sd; // ragged array of sd of parameters for parametric delay distributions vector[delay_params_length] delay_params_lower; // ragged array of lower bounds of the parameters + vector[delay_params_length] delay_params_mean; // ragged array of mean parameters for parametric delay distributions + vector[delay_params_length] delay_params_sd; // ragged array of sd of parameters for parametric delay distributions array[delay_n_p + 1] int delay_params_groups; // links to ragged array array[delay_n_p] int delay_weight; // delay weights diff --git a/inst/stan/estimate_infections.stan b/inst/stan/estimate_infections.stan index 1d7a2a1e0..0b5808d78 100644 --- a/inst/stan/estimate_infections.stan +++ b/inst/stan/estimate_infections.stan @@ -167,8 +167,8 @@ generated quantities { r = R_to_growth(R, gt_mean, gt_var); } else { // sample generation time - vector[delay_params_length] delay_params_sample = to_vector(normal_rng( - delay_params_mean, delay_params_sd + vector[delay_params_length] delay_params_sample = to_vector(normal_lb_rng( + delay_params_mean, delay_params_sd, delay_params_lower )); vector[delay_type_max[gt_id] + 1] sampled_gt_rev_pmf = get_delay_rev_pmf( gt_id, delay_type_max[gt_id] + 1, delay_types_p, delay_types_id, diff --git a/inst/stan/estimate_secondary.stan b/inst/stan/estimate_secondary.stan index 551320741..3657d5bf1 100644 --- a/inst/stan/estimate_secondary.stan +++ b/inst/stan/estimate_secondary.stan @@ -27,7 +27,7 @@ transformed data{ parameters{ // observation model - vector[delay_params_length] delay_params; + vector[delay_params_length] delay_params; simplex[week_effect] day_of_week_simplex; // day of week reporting effect array[obs_scale] real frac_obs; // fraction of cases that are ultimately observed array[model_type] real rep_phi; // overdispersion of the reporting process diff --git a/inst/stan/estimate_truncation.stan b/inst/stan/estimate_truncation.stan index 5761c2e74..3432c094f 100644 --- a/inst/stan/estimate_truncation.stan +++ b/inst/stan/estimate_truncation.stan @@ -28,7 +28,7 @@ transformed data{ } } parameters { - vector[delay_params_length] delay_params; + vector[delay_params_length] delay_params; real phi; real sigma; } diff --git a/inst/stan/functions/delays.stan b/inst/stan/functions/delays.stan index 558487fda..4e7f3878b 100644 --- a/inst/stan/functions/delays.stan +++ b/inst/stan/functions/delays.stan @@ -103,3 +103,9 @@ void delays_lp(vector delay_params, } } } + +vector normal_lb_rng(vector mu, vector sigma, vector lb) { + real p = normal_cdf(lb, mu, sigma); // cdf for bounds + real u = uniform_rng(p, 1); + return (sigma * inv_Phi(u)) + mu; // inverse cdf for value +} From 50b59b7b237f8659e322b693cc09bf3aa10b6695 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 22 Nov 2023 09:34:24 +0000 Subject: [PATCH 034/129] add empty distribution for legacy reasons --- R/dist.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/dist.R b/R/dist.R index 601581fd9..18b2575e6 100644 --- a/R/dist.R +++ b/R/dist.R @@ -882,7 +882,7 @@ tune_inv_gamma <- function(lower = 2, upper = 21) { #' @inheritParams .dist_spec #' @export dist_spec <- function(distribution = c( - "lognormal", "normal", "gamma", "fixed" + "lognormal", "normal", "gamma", "fixed", "empty" ), params_mean = numeric(0), params_sd = numeric(0), mean, sd = 0, mean_sd = 0, sd_sd = 0, From 9e53614e16b99c9e5ec6a4a66ca79f811464e103 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 22 Nov 2023 09:35:16 +0000 Subject: [PATCH 035/129] add checks to dist_skel --- R/dist.R | 51 +++++++++++++++++++++++++++++++-------------------- 1 file changed, 31 insertions(+), 20 deletions(-) diff --git a/R/dist.R b/R/dist.R index 18b2575e6..54dc5004d 100644 --- a/R/dist.R +++ b/R/dist.R @@ -899,18 +899,6 @@ dist_spec <- function(distribution = c( "The function will become internal only in version 2.1.0." ) ) - ## deprecate previous behaviour - warn( - message = paste( - "The meaning of the 'max' argument has changed compared to", - "previous versions. It now indicates the maximum of a distribution", - "rather than the length of the probability mass function (including 0)", - "that it represented previously. To replicate previous behaviour reduce", - "max by 1." - ), - .frequency = "regularly", - .frequency_id = "dist_spec_max" - ) ## check for deprecated parameters if (!missing(fixed)) { lifecycle::deprecate_warn( @@ -926,8 +914,17 @@ dist_spec <- function(distribution = c( stop("Distributional parameters should not be given as `mean`, `sd`, etc. ", "in addition to `params_mean` or `params_sd`") } + distribution <- match.arg(distribution) + ## check if distribution is given as empty and warn about deprecation if so + if (distribution == "empty") { + deprecate_warn( + "2.0.0", + "dist_spec(distribution = 'must not be \"empty\"')", + details = "Please use `fixed(0)` instead." + ) + } + if (!all(missing(mean), missing(sd), missing(mean_sd), missing(sd_sd))) { - distribution <- match.arg(distribution) if (sd == 0 && mean_sd == 0 && sd_sd == 0) { distribution <- "fixed" } @@ -1011,20 +1008,28 @@ dist_spec <- function(distribution = c( !(length(params_mean) == 0 && length(params_sd) == 0)) { stop("Distributional parameters or a pmf can be specified, but not both.") } - distribution <- match.arg(distribution) - ## check if distribution is given as empty and warn about deprecation if so - if (distribution == "empty") { - deprecate_warn( - "2.0.0", - "dist_spec(distribution = 'must not be \"empty\"')", - details = "Please use `fixed(0)` instead." + + if (is.finite(max)) { + warn( + message = paste( + "The meaning of the 'max' argument has changed compared to", + "previous versions. It now indicates the maximum of a distribution", + "rather than the length of the probability mass function (including 0)", + "that it represented previously. To replicate previous behaviour reduce", + "max by 1." + ), + .frequency = "regularly", + .frequency_id = "dist_spec_max" ) } + ## deprecate previous behaviour if (length(params_sd) == 0) { params_sd <- rep(0, length(params_mean)) } + distribution <- match.arg(distribution) + if (distribution == "fixed") { ## if integer fixed then can write the PMF if (as.integer(params_mean) == params_mean && params_mean >= 0) { @@ -1861,6 +1866,12 @@ generate_dist_spec <- function(params, distribution) { ## convert any unnatural parameters unnatural_params <- setdiff(names(params), natural_params(distribution)) if (length(unnatural_params) > 0) { + if (length(unnatural_params) < length(params)) { + stop( + "Incompatible combination of parameters of a ", distribution, + " distribution specified." + ) + } ## sample parameters if they are uncertain if (any(vapply(params, sd, .0) > 0)) { warning( From 93356c61e61e3154951db573cf80b723470399b4 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 22 Nov 2023 09:35:33 +0000 Subject: [PATCH 036/129] use lapply for parameters --- R/dist.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/dist.R b/R/dist.R index 54dc5004d..602e49596 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1890,7 +1890,7 @@ generate_dist_spec <- function(params, distribution) { }) names(samples) <- names(params) } else { - params <- mean(params[[x]]) + samples <- lapply(params, mean) } ## generate natural parameters From 3718c801e4b88ba17d9b6c5c76023e05298a9d2d Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 22 Nov 2023 09:35:46 +0000 Subject: [PATCH 037/129] don't calculate sd if length 1 --- R/dist.R | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/R/dist.R b/R/dist.R index 602e49596..14b3ef04c 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1940,7 +1940,11 @@ convert_to_natural <- function(x, distribution) { mean(x[[param]]) }, numeric(1))), params_sd = unname(vapply(natural_params(distribution), function(param) { - sd(x[[param]]) + if (length(x[[param]]) == 1) { + .0 + } else { + sd(x[[param]]) + } }, numeric(1))) ) return(params) From b70c06f64cb5dfa05982f2b97a287167e1482431 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 22 Nov 2023 09:35:55 +0000 Subject: [PATCH 038/129] use uncertain reporting in example --- data-raw/reporting-delay.R | 4 +++- data/example_reporting_delay.rda | Bin 416 -> 327 bytes 2 files changed, 3 insertions(+), 1 deletion(-) diff --git a/data-raw/reporting-delay.R b/data-raw/reporting-delay.R index b8ee2e832..b895fea44 100644 --- a/data-raw/reporting-delay.R +++ b/data-raw/reporting-delay.R @@ -2,6 +2,8 @@ library(EpiNow2) ## example reporting delay -example_reporting_delay <- lognormal(mean = 2, sd = 1, max = 10L) +example_reporting_delay <- lognormal( + meanlog = normal(0.6, 0.06), sdlog = normal(0.5, 0.05), max = 10L +) usethis::use_data(example_reporting_delay, overwrite = TRUE) diff --git a/data/example_reporting_delay.rda b/data/example_reporting_delay.rda index c19ad2ecf02da45eb849830756bff3026ff7a391..e8d84342ef6bc7fb767377f659b3920770e74600 100644 GIT binary patch literal 327 zcmV-N0l5A`T4*^jL0KkKS$?;-j{pG{@A>~fNP!ptga9x=ujkz00ssIo03iTCNC-dy zumLbcH8fN7nkGzX4@r;>Gy$U~O$3PuMD(6e0BF!XO)(lhL(~}1(9i*p&;S4c3t;{G zaQI2ITG269u5>g^Cst}FMDw)>Y$|2-&RKsYgOM$yTbol*-7H83j%Gn18NG%Qi}l%z zz!63ve9wOEb$n2Cify|6_f=>a+6^fK01RLuFdth28a)__N)RU0Gs028#02(63$ZIE3PXYN@E{+CVMj4eKRc;tOcmTOWd@2yZd$gqM(LTM|qw z`b`XiIMX&+RQPxj2C`x2WC73DWQ~a?q*8qCZ439MF64@Ep&F#}E~n2nVnM!yT(Nr&@r}ha9t4mPtZ;0fHc8 zg|YWm#7Ig2u$+=}Bu3{XCo?l5tKN}Ofe}{iNC1%_5FiMUAhRqw(w~2-+IEvs*EEQn zAa2&Y+O4rfV7=&UCVeygV!~sw&E-$uH&Y}nhR1?U#8Tqq0;?b$@h20}@x_le&fR|- zd1lmkLJ&Ea%eqww(mAAS`xND(P-=9Y+(2Y!H0U5<0lApwYfmHv*l4^(*n3wFA_5|);<%bQ^0`NU_TJ6PUw#CJ$KZY!l{A!0K=2&yGDHZ76ezp_{x0N- KaG@a;hlE Date: Wed, 22 Nov 2023 10:25:54 +0000 Subject: [PATCH 039/129] don't add one to sd --- R/create.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/create.R b/R/create.R index c90695541..c40824fd1 100644 --- a/R/create.R +++ b/R/create.R @@ -538,7 +538,7 @@ create_delay_inits <- function(data) { if (data$delay_n_p > 0) { out$delay_params <- array(truncnorm::rtruncnorm( n = data$delay_params_length, a = data$delay_params_lower, - mean = data$delay_params_mean, sd = data$delay_params_sd * 0.1 + 1 + mean = data$delay_params_mean, sd = data$delay_params_sd * 0.1 )) } else { out$delay_params <- array(numeric(0)) From ac3c87dba05bf8d2fde65121d9a696f2d6d767be Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 22 Nov 2023 10:27:07 +0000 Subject: [PATCH 040/129] return correct parameters --- man/estimate_truncation.Rd | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/man/estimate_truncation.Rd b/man/estimate_truncation.Rd index 64b908272..458d3413c 100644 --- a/man/estimate_truncation.Rd +++ b/man/estimate_truncation.Rd @@ -126,8 +126,8 @@ construct_truncation <- function(index, cases, dist) { cmf <- cumsum( dfunc( 1:(dist$max + 1), - rnorm(1, dist$mean_mean, dist$mean_sd), - rnorm(1, dist$sd_mean, dist$sd_sd) + rnorm(1, dist$params_mean[1], dist$params_sd[1]), + rnorm(1, dist$params_mean[2], dist$params_sd[2]) ) ) cmf <- cmf / cmf[dist$max + 1] From 89acc2503bf3c8a7f36d591c1eac24039e994e12 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 22 Nov 2023 10:32:14 +0000 Subject: [PATCH 041/129] dist_skel: calculate rate everywhere --- R/dist.R | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/R/dist.R b/R/dist.R index 14b3ef04c..5ded63d9e 100644 --- a/R/dist.R +++ b/R/dist.R @@ -362,7 +362,6 @@ gamma_dist_def <- function(shape, shape_sd, } scale <- sd^2 / mean shape <- mean / scale - rate <- 1 / scale } else { if (!missing(shape_sd)) { shape <- truncnorm::rtruncnorm( @@ -378,6 +377,8 @@ gamma_dist_def <- function(shape, shape_sd, } } + rate <- 1 / scale + dist <- data.table::data.table( model = rep("gamma", samples), params = purrr::list_transpose( From 8eaf13e84d015cb7f28bb5e5f6dc835f5937896f Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 22 Nov 2023 10:32:46 +0000 Subject: [PATCH 042/129] update dist_skel examples --- R/dist.R | 14 ++++++++------ man/dist_skel.Rd | 14 ++++++++------ 2 files changed, 16 insertions(+), 12 deletions(-) diff --git a/R/dist.R b/R/dist.R index 5ded63d9e..a632ad207 100644 --- a/R/dist.R +++ b/R/dist.R @@ -53,34 +53,36 @@ #' #' ## Gamma model #' # sample -#' dist_skel(10, model = "gamma", params = list(shape = 1, scale = 2)) +#' dist_skel(10, model = "gamma", params = list(shape = 1, rate = 0.5)) #' #' # cumulative prob density #' dist_skel(0:10, #' model = "gamma", dist = TRUE, -#' params = list(shape = 1, scale = 2) +#' params = list(shape = 1, rate = 0.5) #' ) #' #' # probability density #' dist_skel(0:10, #' model = "gamma", dist = TRUE, -#' cum = FALSE, params = list(shape = 2, scale = 2) +#' cum = FALSE, params = list(shape = 2, rate = 0.5) #' ) #' #' ## Log normal model #' # sample -#' dist_skel(10, model = "lognormal", params = list(mean = log(5), sd = log(2))) +#' dist_skel(10, +#' model = "lognormal", params = list(meanlog = log(5), sdlog = log(2)) +#' ) #' #' # cumulative prob density #' dist_skel(0:10, #' model = "lognormal", dist = TRUE, -#' params = list(mean = log(5), sd = log(2)) +#' params = list(meanlog = log(5), sdlog = log(2)) #' ) #' #' # probability density #' dist_skel(0:10, #' model = "lognormal", dist = TRUE, cum = FALSE, -#' params = list(mean = log(5), sd = log(2)) +#' params = list(meanlog = log(5), sdlog = log(2)) #' ) dist_skel <- function(n, dist = FALSE, cum = TRUE, model, discrete = FALSE, params, max_value = 120) { diff --git a/man/dist_skel.Rd b/man/dist_skel.Rd index 37d1aff83..1edd0743c 100644 --- a/man/dist_skel.Rd +++ b/man/dist_skel.Rd @@ -68,34 +68,36 @@ dist_skel(1:10, ## Gamma model # sample -dist_skel(10, model = "gamma", params = list(shape = 1, scale = 2)) +dist_skel(10, model = "gamma", params = list(shape = 1, rate = 0.5)) # cumulative prob density dist_skel(0:10, model = "gamma", dist = TRUE, - params = list(shape = 1, scale = 2) + params = list(shape = 1, rate = 0.5) ) # probability density dist_skel(0:10, model = "gamma", dist = TRUE, - cum = FALSE, params = list(shape = 2, scale = 2) + cum = FALSE, params = list(shape = 2, rate = 0.5) ) ## Log normal model # sample -dist_skel(10, model = "lognormal", params = list(mean = log(5), sd = log(2))) +dist_skel(10, + model = "lognormal", params = list(meanlog = log(5), sdlog = log(2)) +) # cumulative prob density dist_skel(0:10, model = "lognormal", dist = TRUE, - params = list(mean = log(5), sd = log(2)) + params = list(meanlog = log(5), sdlog = log(2)) ) # probability density dist_skel(0:10, model = "lognormal", dist = TRUE, cum = FALSE, - params = list(mean = log(5), sd = log(2)) + params = list(meanlog = log(5), sdlog = log(2)) ) } \author{ From b1d33e167108f3f413f3a789d60b29f3fa0902d3 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 22 Nov 2023 10:33:00 +0000 Subject: [PATCH 043/129] add missing man file --- man/check_stan_dist.Rd | 22 ++++++++++++++++++++++ 1 file changed, 22 insertions(+) create mode 100644 man/check_stan_dist.Rd diff --git a/man/check_stan_dist.Rd b/man/check_stan_dist.Rd new file mode 100644 index 000000000..8ad5cdb50 --- /dev/null +++ b/man/check_stan_dist.Rd @@ -0,0 +1,22 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/checks.R +\name{check_stan_dist} +\alias{check_stan_dist} +\title{Validate probability distribution for passing to stan} +\usage{ +check_stan_dist(dist) +} +\arguments{ +\item{dist}{A \code{dist_spec} object.`} +} +\value{ +Called for its side effects. +} +\description{ +\code{check_stan_dist()} checks that the supplied data is a \verb{}, +and that it can be further processed by stan. +} +\author{ +Sebastian Funk +} +\keyword{internal} From 44f97170541287395b155ebbe4133686e660ab18 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 22 Nov 2023 10:33:29 +0000 Subject: [PATCH 044/129] don't run internal examples --- R/dist.R | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/R/dist.R b/R/dist.R index a632ad207..e6467352e 100644 --- a/R/dist.R +++ b/R/dist.R @@ -990,6 +990,7 @@ dist_spec <- function(distribution = c( #' @importFrom rlang warn #' @keywords internal #' @examples +#' \dontrun{ #' # A fixed lognormal distribution with mean 5 and sd 1. #' .dist_spec( #' params_mean = c(meanlog = 5, sdlog = 1), max = 20, @@ -1002,6 +1003,7 @@ dist_spec <- function(distribution = c( #' params_sd = c(alpha = 0.75, beta = 0.25), #' distribution = "gamma" #' ) +#' } .dist_spec <- function(distribution = c( "lognormal", "normal", "gamma", "fixed" ), @@ -1765,7 +1767,9 @@ pmf <- function(x) { ##' @author Sebastian Funk ##' @keywords internal ##' @examples +##' \dontrun{ ##' natural_params("gamma") +##' } natural_params <- function(distribution) { if (distribution == "gamma") { ret <- c("shape", "rate") @@ -1787,7 +1791,9 @@ natural_params <- function(distribution) { ##' @author Sebastian Funk ##' @keywords internal ##' @examples +##' \dontrun{ ##' lower_bounds("lognormal") +##' } lower_bounds <- function(distribution) { if (distribution == "gamma") { ret <- c(shape = 0, rate = 0, scale = 0, mean = 0, sd = 0) From f05c8cce35027d59f64cae4ae34c71d1c5a71386 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 22 Nov 2023 10:34:24 +0000 Subject: [PATCH 045/129] demote warning to message --- R/dist.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/dist.R b/R/dist.R index e6467352e..38e17ef52 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1883,7 +1883,7 @@ generate_dist_spec <- function(params, distribution) { } ## sample parameters if they are uncertain if (any(vapply(params, sd, .0) > 0)) { - warning( + message( "Uncertain ", distribution, " distribution specified in terms of ", "parameters that are not the \"natural\" parameters of the ", "distribution (", paste(natural_params(distribution), collapse = ", "), From a785f4b8315c7e862cc7becdbe383e6a1f05839c Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 22 Nov 2023 10:39:42 +0000 Subject: [PATCH 046/129] update syntax everywhere --- R/dist.R | 66 +++--- R/epinow.R | 23 +- R/estimate_infections.R | 24 +- R/estimate_secondary.R | 7 +- R/estimate_truncation.R | 22 +- R/opts.R | 6 +- man/delay_opts.Rd | 6 +- man/dist_spec.Rd | 2 +- man/dot-dist_spec.Rd | 2 + man/epinow.Rd | 23 +- man/estimate_infections.Rd | 24 +- man/estimate_secondary.Rd | 4 +- man/estimate_truncation.Rd | 10 +- man/lower_bounds.Rd | 2 + man/mean.dist_spec.Rd | 15 +- man/natural_params.Rd | 2 + man/plot.dist_spec.Rd | 17 +- man/plus-.dist_spec.Rd | 4 +- man/print.dist_spec.Rd | 13 +- man/sd.dist_spec.Rd | 17 +- tests/testthat/setup.R | 2 +- .../test-adjust_infection_to_report.R | 29 +-- tests/testthat/test-delays.R | 56 ++--- tests/testthat/test-dist.R | 41 ++-- tests/testthat/test-dist_spec.R | 208 +++++++++++------- tests/testthat/test-epinow.R | 6 +- tests/testthat/test-estimate_secondary.R | 6 +- tests/testthat/test-estimate_truncation.R | 8 +- tests/testthat/test-report_cases.R | 2 +- tests/testthat/test-seeding-time.R | 12 +- vignettes/epinow.Rmd.orig | 5 +- .../estimate_infections_options.Rmd.orig | 12 +- .../estimate_infections_workflow.Rmd.orig | 36 +-- 33 files changed, 341 insertions(+), 371 deletions(-) diff --git a/R/dist.R b/R/dist.R index 38e17ef52..f63ca1ada 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1183,8 +1183,8 @@ dist_spec_plus <- function(e1, e2, tolerance = 0.001) { #' @export #' @examples #' # A fixed lognormal distribution with mean 5 and sd 1. -#' dist1 <- lognormal_spec( -#' meanlog = 1.6, sdlog = 1, max = 20, distribution = "lognormal" +#' dist1 <- lognormal( +#' meanlog = 1.6, sdlog = 1, max = 20 #' ) #' dist1 + dist1 #' @@ -1244,20 +1244,17 @@ c.dist_spec <- function(...) { ##' @export #' @examples #' # A fixed lognormal distribution with mean 5 and sd 1. -#' lognormal <- dist_spec( -#' mean = 5, sd = 1, max = 20, distribution = "lognormal" -#' ) -#' mean(lognormal) +#' dist1 <- lognormal(mean = 5, sd = 1, max = 20) +#' mean(dist1) #' #' # An uncertain gamma distribution with mean 3 and sd 2 -#' gamma <- dist_spec( -#' mean = 3, sd = 2, mean_sd = 0.5, sd_sd = 0.5, max = 20, -#' distribution = "gamma" +#' dist2 <- gamma( +#' mean = normal(3, 0.5), sd = normal(2, 0.5), max = 20 #' ) -#' mean(gamma) +#' mean(dist2) #' #' # The mean of the sum of two distributions -#' mean(lognormal + gamma) +#' mean(dist1 + dist2) mean.dist_spec <- function(x, ...) { ret <- rep(.0, x$n) if (x$n_np > 0) { @@ -1305,20 +1302,15 @@ sd <- function(x, ...) UseMethod("sd") ##' @export #' @examples #' # A fixed lognormal distribution with sd 5 and sd 1. -#' lognormal <- dist_spec( -#' sd = 5, sd = 1, max = 20, distribution = "lognormal" -#' ) -#' sd(lognormal) +#' dist1 <- lognormal(mean = 5, sd = 1, max = 20) +#' sd(dist1) #' -#' # An uncertain gamma distribution with sd 3 and sd 2 -#' gamma <- dist_spec( -#' sd = 3, sd = 2, sd_sd = 0.5, sd_sd = 0.5, max = 20, -#' distribution = "gamma" -#' ) -#' sd(gamma) +#' # A gamma distribution with mean 3 and sd 2 +#' dist2 <- gamma(mean = 3, sd = 2) +#' sd(dist2) #' #' # The sd of the sum of two distributions -#' sd(lognormal + gamma) +#' sd(dist1 + dist2) sd.dist_spec <- function(x, ...) { ret <- rep(.0, x$n) if (x$n_np > 0) { @@ -1406,17 +1398,14 @@ max.dist_spec <- function(x, ...) { #' @export #' @examples #' #' # A fixed lognormal distribution with mean 5 and sd 1. -#' lognormal <- dist_spec( -#' mean = 1.5, sd = 0.5, max = 20, distribution = "lognormal" -#' ) -#' print(lognormal) +#' dist1 <- lognormal(mean = 1.5, sd = 0.5, max = 20) +#' print(dist1) #' #' # An uncertain gamma distribution with mean 3 and sd 2 -#' gamma <- dist_spec( -#' mean = 3, sd = 2, mean_sd = 0.5, sd_sd = 0.5, max = 20, -#' distribution = "gamma" +#' dist2 <- gamma( +#' mean = normal(3, 0.5), sd = normal(2, 0.5), max = 20 #' ) -#' print(gamma) +#' print(dist2) print.dist_spec <- function(x, ...) { cat("\n") if (x$n > 1) { @@ -1497,23 +1486,20 @@ print.dist_spec <- function(x, ...) { #' @author Sam Abbott #' @examples #' #' # A fixed lognormal distribution with mean 5 and sd 1. -#' lognormal <- dist_spec( -#' mean = 1.6, sd = 0.5, max = 20, distribution = "lognormal" -#' ) -#' plot(lognormal) +#' dist1 <- lognormal(mean = 1.6, sd = 0.5, max = 20) +#' plot(dist1) #' #' # An uncertain gamma distribution with mean 3 and sd 2 -#' gamma <- dist_spec( -#' mean = 3, sd = 2, mean_sd = 0.5, sd_sd = 0.5, max = 20, -#' distribution = "gamma" +#' dist2 <- gamma( +#' mean = normal(3, 0.5), sd = normal(2, 0.5), max = 20 #' ) -#' plot(gamma) +#' plot(dist2) #' #' # Multiple distributions -#' plot(lognormal + gamma + lognormal) +#' plot(dist1 + dist2 + dist1) #' #' # A combination of the two fixed distributions -#' plot(lognormal + lognormal) +#' plot(dist1 + dist1) plot.dist_spec <- function(x, ...) { distribution <- cdf <- NULL # Get the PMF and CDF data diff --git a/R/epinow.R b/R/epinow.R index cd2156db1..c49acf8c2 100644 --- a/R/epinow.R +++ b/R/epinow.R @@ -44,30 +44,21 @@ #' #' # set an example generation time. In practice this should use an estimate #' # from the literature or be estimated from data -#' generation_time <- dist_spec( -#' mean = 3.6, -#' mean_sd = 0.7, -#' sd = 3.1, -#' sd_sd = 0.8, +#' generation_time <- gamma( +#' shape = normal(2, 2.6), +#' rate = normal(0.5, 0.6), #' max = 14 #' ) #' # set an example incubation period. In practice this should use an estimate #' # from the literature or be estimated from data -#' incubation_period <- dist_spec( -#' mean = 1.6, -#' mean_sd = 0.06, -#' sd = 0.4, -#' sd_sd = 0.07, +#' incubation_period <- lognormal( +#' meanlog = normal(1.6, 0.06), +#' sdlog = normal(0.4, 0.07), #' max = 14 #' ) #' # set an example reporting delay. In practice this should use an estimate #' # from the literature or be estimated from data -#' reporting_delay <- dist_spec( -#' mean = convert_to_logmean(2, 1), -#' sd = convert_to_logsd(2, 1), -#' max = 10, -#' dist = "lognormal" -#' ) +#' reporting_delay <- lognormal(mean = 2, sd = 1, max = 10) #' #' # example case data #' reported_cases <- example_confirmed[1:40] diff --git a/R/estimate_infections.R b/R/estimate_infections.R index f52cee981..b42a15970 100644 --- a/R/estimate_infections.R +++ b/R/estimate_infections.R @@ -77,31 +77,21 @@ #' #' # set an example generation time. In practice this should use an estimate #' # from the literature or be estimated from data -#' generation_time <- dist_spec( -#' mean = 3.6, -#' mean_sd = 0.7, -#' sd = 3.1, -#' sd_sd = 0.8, +#' generation_time <- gamma( +#' shape = normal(2, 2.6), +#' rate = normal(0.5, 0.6), #' max = 14 #' ) #' # set an example incubation period. In practice this should use an estimate #' # from the literature or be estimated from data -#' incubation_period <- dist_spec( -#' mean = 1.6, -#' mean_sd = 0.06, -#' sd = 0.4, -#' sd_sd = 0.07, +#' incubation_period <- lognormal( +#' meanlog = normal(1.6, 0.06), +#' sdlog = normal(0.4, 0.07), #' max = 14 #' ) #' # set an example reporting delay. In practice this should use an estimate #' # from the literature or be estimated from data -#' reporting_delay <- dist_spec( -#' mean = convert_to_logmean(2, 1), -#' sd = convert_to_logsd(2, 1), -#' max = 10, -#' dist = "lognormal" -#' ) -#' +#' reporting_delay <- lognormal(mean = 2, sd = 1, max = 10) #' #' # for more examples, see the "estimate_infections examples" vignette #' def <- estimate_infections(reported_cases, diff --git a/R/estimate_secondary.R b/R/estimate_secondary.R index e522dc558..c1c69738e 100644 --- a/R/estimate_secondary.R +++ b/R/estimate_secondary.R @@ -137,9 +137,10 @@ estimate_secondary <- function(reports, secondary = secondary_opts(), delays = delay_opts( - dist_spec( - mean = 2.5, mean_sd = 0.5, - sd = 0.47, sd_sd = 0.25, max = 30 + lognormal( + meanlog = normal(2.5, 0.5), + sdlog = normal(0.47, 0.25), + max = 30 ) ), truncation = trunc_opts(), diff --git a/R/estimate_truncation.R b/R/estimate_truncation.R index 7fda536c9..3220c7a8b 100644 --- a/R/estimate_truncation.R +++ b/R/estimate_truncation.R @@ -87,11 +87,9 @@ #' reported_cases <- example_confirmed[1:60] #' #' # define example truncation distribution (note not integer adjusted) -#' trunc <- dist_spec( -#' mean = convert_to_logmean(3, 2), -#' mean_sd = 0.1, -#' sd = convert_to_logsd(3, 2), -#' sd_sd = 0.1, +#' trunc <- lognormal( +#' meanlog = normal(0.9, 0.1), +#' sdlog = normal(0.6, 0.1), #' max = 10 #' ) #' @@ -106,8 +104,8 @@ #' cmf <- cumsum( #' dfunc( #' 1:(dist$max + 1), -#' rnorm(1, dist$mean_mean, dist$mean_sd), -#' rnorm(1, dist$sd_mean, dist$sd_sd) +#' rnorm(1, dist$params_mean[1], dist$params_sd[1]), +#' rnorm(1, dist$params_mean[2], dist$params_sd[2]) #' ) #' ) #' cmf <- cmf / cmf[dist$max + 1] @@ -142,8 +140,8 @@ #' options(old_opts) estimate_truncation <- function(obs, max_truncation, trunc_max = 10, trunc_dist = "lognormal", - truncation = dist_spec( - mean = 0, sd = 0, mean_sd = 1, sd_sd = 1, + truncation = lognormal( + meanlog = normal(0, 1), sdlog = normal(1, 1), max = 10 ), model = NULL, @@ -220,8 +218,10 @@ estimate_truncation <- function(obs, max_truncation, trunc_max = 10, construct_trunc <- TRUE } if (construct_trunc) { - truncation <- dist_spec( - mean = 0, mean_sd = 1, sd = 0, sd_sd = 1, distribution = trunc_dist, + truncation <- .dist_spec( + params_mean = c(0, 1), + params_sd = c(1, 1), + distribution = trunc_dist, max = trunc_max ) } diff --git a/R/opts.R b/R/opts.R index a14ee789a..7a4ff499c 100644 --- a/R/opts.R +++ b/R/opts.R @@ -109,7 +109,7 @@ generation_time_opts <- function(dist = fixed(1), ..., #' Returns delay distributions formatted for usage by downstream #' functions. #' @param dist A delay distribution or series of delay distributions. Default is -#' an fixed distribution with of 0, [dist_spec()], i.e. no delay. +#' a fixed distribution with all mass at 0, i.e. no delay. #' @param ... deprecated; use `dist` instead #' @param fixed deprecated; use `dist` instead #' @return A `` object summarising the input delay distributions. @@ -123,11 +123,11 @@ generation_time_opts <- function(dist = fixed(1), ..., #' delay_opts() #' #' # A single delay that has uncertainty -#' delay <- dist_spec(mean = 1, mean_sd = 0.2, sd = 0.5, sd_sd = 0.1, max = 14) +#' delay <- lognormal(mean = normal(1, 0.2), sd = normal(0.5, 0.1), max = 14) #' delay_opts(delay) #' #' # A single delay without uncertainty -#' delay <- dist_spec(mean = 1, sd = 0.5, max = 14) +#' delay <- lognormal(meanlog = 1, sdlog = 0.5, max = 14) #' delay_opts(delay) #' #' # Multiple delays (in this case twice the same) diff --git a/man/delay_opts.Rd b/man/delay_opts.Rd index 171eba0ef..a0c7360c1 100644 --- a/man/delay_opts.Rd +++ b/man/delay_opts.Rd @@ -8,7 +8,7 @@ delay_opts(dist = fixed(0), ..., fixed = FALSE) } \arguments{ \item{dist}{A delay distribution or series of delay distributions. Default is -an fixed distribution with of 0, \code{\link[=dist_spec]{dist_spec()}}, i.e. no delay.} +a fixed distribution with all mass at 0, i.e. no delay.} \item{...}{deprecated; use \code{dist} instead} @@ -27,11 +27,11 @@ functions. delay_opts() # A single delay that has uncertainty -delay <- dist_spec(mean = 1, mean_sd = 0.2, sd = 0.5, sd_sd = 0.1, max = 14) +delay <- lognormal(mean = normal(1, 0.2), sd = normal(0.5, 0.1), max = 14) delay_opts(delay) # A single delay without uncertainty -delay <- dist_spec(mean = 1, sd = 0.5, max = 14) +delay <- lognormal(meanlog = 1, sdlog = 0.5, max = 14) delay_opts(delay) # Multiple delays (in this case twice the same) diff --git a/man/dist_spec.Rd b/man/dist_spec.Rd index 277548887..68a0ee493 100644 --- a/man/dist_spec.Rd +++ b/man/dist_spec.Rd @@ -5,7 +5,7 @@ \title{Specify a distribution.} \usage{ dist_spec( - distribution = c("lognormal", "normal", "gamma", "fixed"), + distribution = c("lognormal", "normal", "gamma", "fixed", "empty"), params_mean = numeric(0), params_sd = numeric(0), mean, diff --git a/man/dot-dist_spec.Rd b/man/dot-dist_spec.Rd index c012c7c74..fa810b91c 100644 --- a/man/dot-dist_spec.Rd +++ b/man/dot-dist_spec.Rd @@ -46,6 +46,7 @@ functionality in \code{\link[=delay_opts]{delay_opts()}}, \code{\link[=generatio \code{\link[=trunc_opts]{trunc_opts()}}. } \examples{ +\dontrun{ # A fixed lognormal distribution with mean 5 and sd 1. .dist_spec( params_mean = c(meanlog = 5, sdlog = 1), max = 20, @@ -59,6 +60,7 @@ functionality in \code{\link[=delay_opts]{delay_opts()}}, \code{\link[=generatio distribution = "gamma" ) } +} \author{ Sebastian Funk diff --git a/man/epinow.Rd b/man/epinow.Rd index 76cc6676f..1c0d157c7 100644 --- a/man/epinow.Rd +++ b/man/epinow.Rd @@ -129,30 +129,21 @@ options(mc.cores = ifelse(interactive(), 4, 1)) # set an example generation time. In practice this should use an estimate # from the literature or be estimated from data -generation_time <- dist_spec( - mean = 3.6, - mean_sd = 0.7, - sd = 3.1, - sd_sd = 0.8, +generation_time <- gamma( + shape = normal(2, 2.6), + rate = normal(0.5, 0.6), max = 14 ) # set an example incubation period. In practice this should use an estimate # from the literature or be estimated from data -incubation_period <- dist_spec( - mean = 1.6, - mean_sd = 0.06, - sd = 0.4, - sd_sd = 0.07, +incubation_period <- lognormal( + meanlog = normal(1.6, 0.06), + sdlog = normal(0.4, 0.07), max = 14 ) # set an example reporting delay. In practice this should use an estimate # from the literature or be estimated from data -reporting_delay <- dist_spec( - mean = convert_to_logmean(2, 1), - sd = convert_to_logsd(2, 1), - max = 10, - dist = "lognormal" -) +reporting_delay <- lognormal(mean = 2, sd = 1, max = 10) # example case data reported_cases <- example_confirmed[1:40] diff --git a/man/estimate_infections.Rd b/man/estimate_infections.Rd index 156a733d2..487791a50 100644 --- a/man/estimate_infections.Rd +++ b/man/estimate_infections.Rd @@ -118,31 +118,21 @@ reported_cases <- example_confirmed[1:60] # set an example generation time. In practice this should use an estimate # from the literature or be estimated from data -generation_time <- dist_spec( - mean = 3.6, - mean_sd = 0.7, - sd = 3.1, - sd_sd = 0.8, +generation_time <- gamma( + shape = normal(2, 2.6), + rate = normal(0.5, 0.6), max = 14 ) # set an example incubation period. In practice this should use an estimate # from the literature or be estimated from data -incubation_period <- dist_spec( - mean = 1.6, - mean_sd = 0.06, - sd = 0.4, - sd_sd = 0.07, +incubation_period <- lognormal( + meanlog = normal(1.6, 0.06), + sdlog = normal(0.4, 0.07), max = 14 ) # set an example reporting delay. In practice this should use an estimate # from the literature or be estimated from data -reporting_delay <- dist_spec( - mean = convert_to_logmean(2, 1), - sd = convert_to_logsd(2, 1), - max = 10, - dist = "lognormal" -) - +reporting_delay <- lognormal(mean = 2, sd = 1, max = 10) # for more examples, see the "estimate_infections examples" vignette def <- estimate_infections(reported_cases, diff --git a/man/estimate_secondary.Rd b/man/estimate_secondary.Rd index 6bdc44b1a..d46e22dc3 100644 --- a/man/estimate_secondary.Rd +++ b/man/estimate_secondary.Rd @@ -7,8 +7,8 @@ estimate_secondary( reports, secondary = secondary_opts(), - delays = delay_opts(dist_spec(mean = 2.5, mean_sd = 0.5, sd = 0.47, sd_sd = 0.25, max = - 30)), + delays = delay_opts(lognormal(meanlog = normal(2.5, 0.5), sdlog = normal(0.47, 0.25), + max = 30)), truncation = trunc_opts(), obs = obs_opts(), stan = stan_opts(), diff --git a/man/estimate_truncation.Rd b/man/estimate_truncation.Rd index 458d3413c..6135e2798 100644 --- a/man/estimate_truncation.Rd +++ b/man/estimate_truncation.Rd @@ -9,7 +9,7 @@ estimate_truncation( max_truncation, trunc_max = 10, trunc_dist = "lognormal", - truncation = dist_spec(mean = 0, sd = 0, mean_sd = 1, sd_sd = 1, max = 10), + truncation = lognormal(meanlog = normal(0, 1), sdlog = normal(1, 1), max = 10), model = NULL, stan = stan_opts(), CrIs = c(0.2, 0.5, 0.9), @@ -107,11 +107,9 @@ options(mc.cores = ifelse(interactive(), 4, 1)) reported_cases <- example_confirmed[1:60] # define example truncation distribution (note not integer adjusted) -trunc <- dist_spec( - mean = convert_to_logmean(3, 2), - mean_sd = 0.1, - sd = convert_to_logsd(3, 2), - sd_sd = 0.1, +trunc <- lognormal( + meanlog = normal(0.9, 0.1), + sdlog = normal(0.6, 0.1), max = 10 ) diff --git a/man/lower_bounds.Rd b/man/lower_bounds.Rd index 968285241..d1f757905 100644 --- a/man/lower_bounds.Rd +++ b/man/lower_bounds.Rd @@ -16,8 +16,10 @@ A numeric vector, the lower bounds. This is used to avoid sampling parameter values that have no support. } \examples{ +\dontrun{ lower_bounds("lognormal") } +} \author{ Sebastian Funk } diff --git a/man/mean.dist_spec.Rd b/man/mean.dist_spec.Rd index f5f5a0d95..ca4f70c34 100644 --- a/man/mean.dist_spec.Rd +++ b/man/mean.dist_spec.Rd @@ -21,20 +21,17 @@ in parameters) } \examples{ # A fixed lognormal distribution with mean 5 and sd 1. -lognormal <- dist_spec( - mean = 5, sd = 1, max = 20, distribution = "lognormal" -) -mean(lognormal) +dist1 <- lognormal(mean = 5, sd = 1, max = 20) +mean(dist1) # An uncertain gamma distribution with mean 3 and sd 2 -gamma <- dist_spec( - mean = 3, sd = 2, mean_sd = 0.5, sd_sd = 0.5, max = 20, - distribution = "gamma" +dist2 <- gamma( + mean = normal(3, 0.5), sd = normal(2, 0.5), max = 20 ) -mean(gamma) +mean(dist2) # The mean of the sum of two distributions -mean(lognormal + gamma) +mean(dist1 + dist2) } \author{ Sebastian Funk diff --git a/man/natural_params.Rd b/man/natural_params.Rd index c6229989c..ed7729eeb 100644 --- a/man/natural_params.Rd +++ b/man/natural_params.Rd @@ -18,8 +18,10 @@ representations are converted to these using \code{\link[=convert_to_natural]{co being passed to teh stan mnodels. } \examples{ +\dontrun{ natural_params("gamma") } +} \author{ Sebastian Funk } diff --git a/man/plot.dist_spec.Rd b/man/plot.dist_spec.Rd index c7eeef97e..091f7bc88 100644 --- a/man/plot.dist_spec.Rd +++ b/man/plot.dist_spec.Rd @@ -18,23 +18,20 @@ Note that currently uncertainty in distributions is not plot. } \examples{ #' # A fixed lognormal distribution with mean 5 and sd 1. -lognormal <- dist_spec( - mean = 1.6, sd = 0.5, max = 20, distribution = "lognormal" -) -plot(lognormal) +dist1 <- lognormal(mean = 1.6, sd = 0.5, max = 20) +plot(dist1) # An uncertain gamma distribution with mean 3 and sd 2 -gamma <- dist_spec( - mean = 3, sd = 2, mean_sd = 0.5, sd_sd = 0.5, max = 20, - distribution = "gamma" +dist2 <- gamma( + mean = normal(3, 0.5), sd = normal(2, 0.5), max = 20 ) -plot(gamma) +plot(dist2) # Multiple distributions -plot(lognormal + gamma + lognormal) +plot(dist1 + dist2 + dist1) # A combination of the two fixed distributions -plot(lognormal + lognormal) +plot(dist1 + dist1) } \author{ Sam Abbott diff --git a/man/plus-.dist_spec.Rd b/man/plus-.dist_spec.Rd index 5e47a718a..c768d13b5 100644 --- a/man/plus-.dist_spec.Rd +++ b/man/plus-.dist_spec.Rd @@ -25,8 +25,8 @@ numeric stability. } \examples{ # A fixed lognormal distribution with mean 5 and sd 1. -dist1 <- lognormal_spec( - meanlog = 1.6, sdlog = 1, max = 20, distribution = "lognormal" +dist1 <- lognormal( + meanlog = 1.6, sdlog = 1, max = 20 ) dist1 + dist1 diff --git a/man/print.dist_spec.Rd b/man/print.dist_spec.Rd index ef8c10487..b2ebd9b1d 100644 --- a/man/print.dist_spec.Rd +++ b/man/print.dist_spec.Rd @@ -20,17 +20,14 @@ functions of fixed delay distributions combined in the passed \code{\link[=dist_ } \examples{ #' # A fixed lognormal distribution with mean 5 and sd 1. -lognormal <- dist_spec( - mean = 1.5, sd = 0.5, max = 20, distribution = "lognormal" -) -print(lognormal) +dist1 <- lognormal(mean = 1.5, sd = 0.5, max = 20) +print(dist1) # An uncertain gamma distribution with mean 3 and sd 2 -gamma <- dist_spec( - mean = 3, sd = 2, mean_sd = 0.5, sd_sd = 0.5, max = 20, - distribution = "gamma" +dist2 <- gamma( + mean = normal(3, 0.5), sd = normal(2, 0.5), max = 20 ) -print(gamma) +print(dist2) } \author{ Sebastian Funk diff --git a/man/sd.dist_spec.Rd b/man/sd.dist_spec.Rd index 6a3f3db29..b7888249e 100644 --- a/man/sd.dist_spec.Rd +++ b/man/sd.dist_spec.Rd @@ -20,20 +20,15 @@ nonparametric) delay distributions combined in the passed \code{\link[=dist_spec } \examples{ # A fixed lognormal distribution with sd 5 and sd 1. -lognormal <- dist_spec( - sd = 5, sd = 1, max = 20, distribution = "lognormal" -) -sd(lognormal) +dist1 <- lognormal(mean = 5, sd = 1, max = 20) +sd(dist1) -# An uncertain gamma distribution with sd 3 and sd 2 -gamma <- dist_spec( - sd = 3, sd = 2, sd_sd = 0.5, sd_sd = 0.5, max = 20, - distribution = "gamma" -) -sd(gamma) +# A gamma distribution with mean 3 and sd 2 +dist2 <- gamma(mean = 3, sd = 2) +sd(dist2) # The sd of the sum of two distributions -sd(lognormal + gamma) +sd(dist1 + dist2) } \author{ Sebastian Funk diff --git a/tests/testthat/setup.R b/tests/testthat/setup.R index 4445d187a..4b63e43af 100644 --- a/tests/testthat/setup.R +++ b/tests/testthat/setup.R @@ -18,4 +18,4 @@ if (identical(Sys.getenv("NOT_CRAN"), "true")) { withr::defer(future::plan("sequential"), teardown_env()) ## process warning once as previous behaviour has been deprecated -empty <- suppressWarnings(fixed(0)) +dummy <- suppressWarnings(dist_spec(mean = 0, sd = 1, max = 5)) diff --git a/tests/testthat/test-adjust_infection_to_report.R b/tests/testthat/test-adjust_infection_to_report.R index 6f73aa227..7b052befd 100644 --- a/tests/testthat/test-adjust_infection_to_report.R +++ b/tests/testthat/test-adjust_infection_to_report.R @@ -3,24 +3,14 @@ cases <- data.table::copy(example_confirmed)[, cases := as.integer(confirm)] # define a single report delay distribution -delay_def <- lognorm_dist_def( - mean = 5, mean_sd = 1, sd = 3, sd_sd = 1, - max_value = 30, samples = 1, to_log = TRUE -) - -# define a single incubation period -incubation_def <- lognorm_dist_def( - mean = incubation_periods[1, ]$mean, - mean_sd = incubation_periods[1, ]$mean_sd, - sd = incubation_periods[1, ]$sd, - sd_sd = incubation_periods[1, ]$sd_sd, - max_value = 30, samples = 1 +delay <- lognormal( + meanlog = normal(1.4, 0.3), sdlog = normal(0.6, 0.2), max = 30 ) test_that("adjust_infection_to_report can correctly handle a simple mapping", { reports <- adjust_infection_to_report( cases, - delay_defs = list(incubation_def, delay_def) + delay_defs = example_incubation_period + delay ) expect_true(nrow(reports) > 80) expect_true(all(!is.infinite(reports$cases))) @@ -31,10 +21,21 @@ test_that("adjust_infection_to_report can correctly handle a mapping with a day of the week effect", { reports <- adjust_infection_to_report( cases, - delay_defs = list(incubation_def, delay_def), + delay_defs = example_incubation_period + delay, reporting_effect = c(1.1, rep(1, 4), 0.95, 0.95) ) expect_true(nrow(reports) > 80) expect_true(all(!is.infinite(reports$cases))) expect_true(all(!is.na(reports$cases))) }) + +test_that("passing data tables to adjust_infection_to_report is deprecated", { + suppressWarnings(delay_def <- lognorm_dist_def( + mean = 5, mean_sd = 1, sd = 3, sd_sd = 1, + max_value = 30, samples = 1, to_log = TRUE + )) + expect_deprecated(adjust_infection_to_report( + cases, + delay_defs = list(delay_def) + )) +}) diff --git a/tests/testthat/test-delays.R b/tests/testthat/test-delays.R index e33e4e620..35b3faea9 100644 --- a/tests/testthat/test-delays.R +++ b/tests/testthat/test-delays.R @@ -21,14 +21,16 @@ test_that("generation times can be specified in different ways", { ) expect_equal( test_stan_delays( - generation_time = generation_time_opts(dist_spec(mean = 3)), + generation_time = generation_time_opts(fixed(value = 3)), params = delay_params ), c(0, 0, 0, 1, 1, 1) ) expect_equal( round(test_stan_delays( - generation_time = generation_time_opts(dist_spec(mean = 3, sd = 1, max = 4)), + generation_time = generation_time_opts( + lognormal(meanlog = 3, sdlog = 1, max = 4) + ), params = delay_params ), digits = 2), c(0.02, 0.11, 0.22, 0.30, 0.35, 1.00, 1.00) @@ -38,14 +40,16 @@ test_that("generation times can be specified in different ways", { test_that("delay parameters can be specified in different ways", { expect_equal( tail(test_stan_delays( - delays = delay_opts(dist_spec(mean = 3)), + delays = delay_opts(fixed(value = 3)), params = delay_params ), n = -2), c(0, 0, 0, 1, 1) ) expect_equal( tail(round(test_stan_delays( - delays = delay_opts(dist_spec(mean = 3, sd = 1, max = 4)), + delays = delay_opts( + lognormal(meanlog = 3, sdlog = 1, max = 4) + ), params = delay_params ), digits = 2), n = -2), c(0.02, 0.11, 0.22, 0.30, 0.35, 1.00) @@ -55,44 +59,20 @@ test_that("delay parameters can be specified in different ways", { test_that("truncation parameters can be specified in different ways", { expect_equal( tail(round(test_stan_delays( - truncation = trunc_opts(dist = dist_spec(mean = 3, sd = 1, max = 4)), + truncation = trunc_opts( + dist = lognormal(meanlog = 3, sdlog = 1, max = 4) + ), params = delay_params ), digits = 2), n = -2), c(1.00, 0.02, 0.11, 0.22, 0.30, 0.35) ) }) -test_that("deprecated arguments are caught", { - options(lifecycle_verbosity = "warning") - expect_warning( - test_stan_delays( - generation_time = generation_time_opts(mean = 3), - params = delay_params - ), "deprecated" - ) - expect_error( - test_stan_delays( - delays = delay_opts(mean = 3), - params = delay_params - ), "named arguments" - ) - expect_warning( - test_stan_delays( - delays = delay_opts(list(mean = 3)), - params = delay_params - ), "deprecated" - ) - expect_warning( - test_stan_delays( - delays = delay_opts(list(mean = 3)), - params = delay_params - ), "deprecated" - ) - expect_warning( - test_stan_delays( - delays = trunc_opts(list(mean = 3)), - params = delay_params - ), "deprecated" - ) - options(lifecycle_verbosity = NULL) +test_that("distributions incompatible with stan models are caught", { + expect_error(generation_time_opts( + gamma(2, 2) + ), "maximum") + expect_error(delay_opts( + normal(2, 2) + ), "lognormal") }) diff --git a/tests/testthat/test-dist.R b/tests/testthat/test-dist.R index 5a505b869..5e0171a23 100644 --- a/tests/testthat/test-dist.R +++ b/tests/testthat/test-dist.R @@ -2,29 +2,28 @@ skip_on_cran() skip_on_os("windows") test_that("distributions are the same in R and stan", { - args <- list(mean = 3, mean_sd = 0, sd = 2, sd_sd = 0, max_value = 15) - lognormal_params <- - do.call(lognorm_dist_def, (c(args, list(samples = 1))))$params[[1]] - gamma_params <- - do.call(gamma_dist_def, (c(args, list(samples = 1))))$params[[1]] - pmf_r_lognormal <- dist_skel( - n = seq_len(args$max_value + 1) - 1, dist = TRUE, cum = FALSE, - model = "lognormal", params = lognormal_params, max_value = args$max_value, - discrete = TRUE - ) - pmf_r_gamma <- dist_skel( - n = seq_len(args$max_value + 1) - 1, dist = TRUE, cum = FALSE, - model = "gamma", params = gamma_params, max_value = args$max_value, - discrete = TRUE - ) + args <- list(mean = 3, sd = 2) + max_args <- c(args, list(max = 15)) - pmf_stan_lognormal <- discretised_pmf( - unlist(lognormal_params), args$max_value + 1, 0 - ) - pmf_stan_gamma <- discretised_pmf( - unlist(gamma_params), args$max_value + 1, 1 - ) + lognormal_params <- do.call(lognormal, args)$params_mean + gamma_params <- do.call(gamma, args)$params_mean + + pmf_r_lognormal <- as.vector(do.call(lognormal, max_args)$np_pmf) + pmf_r_gamma <- as.vector(do.call(gamma, max_args)$np_pmf) + + pmf_stan_lognormal <- discretised_pmf(lognormal_params, max_args$max + 1, 0) + pmf_stan_gamma <- discretised_pmf(gamma_params, max_args$max + 1, 1) expect_equal(pmf_r_lognormal, pmf_stan_lognormal) expect_equal(pmf_r_gamma, pmf_stan_gamma) }) + +test_that("deprecated functions are deprecated", { + args <- list(mean = 3, mean_sd = 0, sd = 2, sd_sd = 0, max_value = 15) + expect_deprecated( + do.call(lognorm_dist_def, (c(args, list(samples = 1))))$params[[1]] + ) + expect_deprecated( + do.call(gamma_dist_def, (c(args, list(samples = 1))))$params[[1]] + ) +}) diff --git a/tests/testthat/test-dist_spec.R b/tests/testthat/test-dist_spec.R index 5c3cd9900..4c3555dc5 100644 --- a/tests/testthat/test-dist_spec.R +++ b/tests/testthat/test-dist_spec.R @@ -1,6 +1,6 @@ test_that("dist_spec returns correct output for fixed lognormal distribution", { - result <- dist_spec(mean = 5, sd = 1, max = 19, distribution = "lognormal") + result <- lognormal(meanlog = 5, sdlog = 1, max = 19) expect_equal(dim(result$params_mean), 0) expect_equal(dim(result$dist), 0) expect_equal(dim(result$max), 0) @@ -14,10 +14,7 @@ test_that("dist_spec returns correct output for fixed lognormal distribution", { }) test_that("dist_spec returns correct output for uncertain gamma distribution", { - result <- dist_spec( - params_mean = c(3, 2), params_sd = c(0.5, 0.5), distribution = "gamma", - max = 19 - ) + result <- gamma(shape = normal(3, 0.5), rate = normal(2, 0.5), max = 19) expect_equal(result$params_mean, array(c(3, 2))) expect_equal(result$params_sd, array(c(0.5, 0.5))) expect_equal(result$dist, array("gamma")) @@ -26,9 +23,7 @@ test_that("dist_spec returns correct output for uncertain gamma distribution", { }) test_that("dist_spec returns correct output for fixed distribution", { - result <- fix_dist(dist_spec( - mean = 5, mean_sd = 3, sd = 1, max = 19, distribution = "lognormal", - )) + result <- fix_dist(lognormal(meanlog = normal(5, 3), sdlog = 1, max = 19)) expect_equal(dim(result$params_mean), 0) expect_equal(result$parametric, array(FALSE)) expect_equal( @@ -39,23 +34,22 @@ test_that("dist_spec returns correct output for fixed distribution", { ) }) -test_that("dist_spec returns error when both pmf and distributional parameters are specified", { - expect_error(dist_spec(mean = 5, sd = 1, max = 20, distribution = "lognormal", pmf = c(0.1, 0.2, 0.3, 0.4)), - "Distributional parameters or a pmf can be specified, but not both.") +test_that("dist_spec returns error when mixed natural and unnatural parameters are specified", { + expect_error( + lognormal(meanlog = 5, sd = 1, max = 20), + "Incompatible combination." + ) }) -test_that("dist_spec returns error when mean is missing but other distributional parameters are given", { - expect_error(dist_spec(sd = 1, max = 20, distribution = "lognormal"), - "is missing.") +test_that("dist_spec returns error when the wrong number of paramters are given", { + expect_error(lognormal(sd = 1, max = 20), "must be specified") + expect_error(gamma(shape = 1, rate = 2, mean = 3), "must be specified") }) test_that("+.dist_spec returns correct output for sum of two distributions", { - lognormal <- dist_spec(mean = 5, sd = 1, max = 19, distribution = "lognormal") - gamma <- dist_spec( - params_mean = c(3, 2), params_sd = c(0.5, 0.5), max = 20, - distribution = "gamma" - ) - result <- lognormal + gamma + dist1 <- lognormal(meanlog = 5, sdlog = 1, max = 19) + dist2 <- gamma(shape = normal(3, 0.5), rate = normal(2, 0.5), max = 20) + result <- dist1 + dist2 expect_equal(result$params_mean, array(c(3, 2))) expect_equal(result$params_sd, array(c(0.5, 0.5))) expect_equal(result$n, 2) @@ -65,13 +59,9 @@ test_that("+.dist_spec returns correct output for sum of two distributions", { }) test_that("+.dist_spec returns correct output for sum of two fixed distributions", { - lognormal <- fix_dist(dist_spec( - mean = 5, sd = 1, max = 19, distribution = "lognormal" - )) - gamma <- fix_dist(dist_spec( - mean = 3, sd = 2, max = 19, distribution = "gamma" - )) - result <- lognormal + gamma + dist1 <- lognormal(meanlog = 5, sdlog = 1, max = 19) + dist2 <- gamma(mean = 3, sd = 2, max = 19) + result <- dist1 + dist2 expect_equal(dim(result$params_mean), 0) expect_equal(result$n, 1) expect_equal(result$n_p, 0) @@ -80,9 +70,9 @@ test_that("+.dist_spec returns correct output for sum of two fixed distributions }) test_that("+.dist_spec returns correct output for sum of two nonparametric distributions", { - lognormal <- dist_spec(pmf = c(0.1, 0.2, 0.3, 0.4)) - gamma <- dist_spec(pmf = c(0.1, 0.2, 0.3, 0.4)) - result <- lognormal + gamma + dist1 <- pmf(c(0.1, 0.2, 0.3, 0.4)) + dist2 <- pmf(c(0.1, 0.2, 0.3, 0.4)) + result <- dist1 + dist2 expect_equal(dim(result$params_mean), 0) expect_equal(result$n, 1) expect_equal(result$n_p, 0) @@ -96,19 +86,15 @@ test_that("+.dist_spec returns correct output for sum of two nonparametric distr test_that("Testing `+.dist_spec` function with tolerance parameter", { # Create distributions - lognormal <- dist_spec( - mean = 1.6, sd = 1, max = 19, distribution = "lognormal" - ) - gamma <- dist_spec( - mean = 3, sd = 2, max = 19, distribution = "gamma" - ) - + dist1 <- lognormal(meanlog = 1.6, sdlog = 1, max = 19) + dist2 <- gamma(mean = 3, sd = 2, max = 19) + # Compute combined distribution with default tolerance - combined_default <- EpiNow2:::`+.dist_spec`(lognormal, gamma) + combined_default <- EpiNow2:::`+.dist_spec`(dist1, dist2) # Compute combined distribution with larger tolerance combined_larger_tolerance <- EpiNow2:::dist_spec_plus( - lognormal, gamma, tolerance = 0.01 + dist1, dist2, tolerance = 0.01 ) # The length of the combined PMF should be greater with default tolerance @@ -128,89 +114,159 @@ test_that("Testing `+.dist_spec` function with tolerance parameter", { ) }) - -test_that("mean.dist_spec returns correct output for fixed lognormal distribution", { - lognormal <- dist_spec( - mean = convert_to_logmean(3, 1), sd = convert_to_logsd(3, 1), - max = 19, distribution = "lognormal" - ) - result <- EpiNow2:::mean.dist_spec(lognormal) - expect_equal(result, 2.49, tolerance = 0.01) # here we can see the bias from +test_that("summary functions return correct output for fixed lognormal distribution", { + dist <- lognormal(mean = 3, sd = 1, max = 19) + ## here we can see the bias from # using this kind of discretisation approach + expect_equal(EpiNow2:::mean.dist_spec(dist), 2.49, tolerance = 0.01) + expect_equal(EpiNow2:::sd.dist_spec(dist), 1.09, tolerance = 0.01) + expect_equal(EpiNow2:::max.dist_spec(dist), 19L) }) -test_that("mean.dist_spec returns correct output for uncertain gamma distribution", { - gamma <- dist_spec(params_mean = c(3, 2), params_sd = c(0.5, 0.5), max = 19, distribution = "gamma") - result <- EpiNow2:::mean.dist_spec(gamma) - expect_equal(result, 1.5) +test_that("summary functions return correct output for uncertain gamma distribution", { + dist <- gamma(shape = normal(3, 0.5), rate = normal(2, 0.5), max = 19) + expect_equal(EpiNow2:::mean.dist_spec(dist), 1.5) + expect_equal(EpiNow2:::max.dist_spec(dist), 19L) }) test_that("mean.dist_spec returns correct output for sum of two distributions", { - lognormal <- dist_spec(mean = 1, sd = 1, max = 19, distribution = "lognormal") - gamma <- dist_spec(mean = 3, sd = 2, max = 19, distribution = "gamma") - result <- EpiNow2:::mean.dist_spec(lognormal + gamma) - expect_equal(result, c(5.84), tolerance = 0.001) + dist1 <- lognormal(meanlog = 1, sdlog = 1, max = 19) + dist2 <- gamma(mean = 3, sd = 2, max = 19) + dist <- dist1 + dist2 + expect_equal(EpiNow2:::mean.dist_spec(dist), c(5.84), tolerance = 0.001) + expect_equal(EpiNow2:::sd.dist_spec(dist), c(16.88), tolerance = 0.001) + ## shortened due to tolerance level + expect_equal(EpiNow2:::max.dist_spec(dist), 24L) +}) + +test_that("sd.dist_spec returns an error when applied to uncertain distributions", { + dist <- gamma(shape = normal(3, 0.5), rate = normal(2, 0.5), max = 19) + expect_error(EpiNow2:::sd.dist_spec(dist), "uncertain") }) test_that("print.dist_spec correctly prints the parameters of the fixed lognormal", { - lognormal <- dist_spec(mean = 1.5, sd = 0.5, max = 19, distribution = "lognormal") + dist <- lognormal(meanlog = 1.5, sdlog = 0.5, max = 19) - expect_output(print(lognormal), "\\n distribution with PMF \\[0\\.0014 0\\.052 0\\.16 0\\.2 0\\.18 0\\.13 0\\.094 0\\.063 0\\.042 0\\.027 0\\.018 0\\.012 0\\.0079 0\\.0052 0\\.0035 0\\.0024 0\\.0016 0\\.0011 0\\.00078 0\\.00055\\]\\.\\n") + expect_output(print(dist), "\\n distribution with PMF \\[0\\.0014 0\\.052 0\\.16 0\\.2 0\\.18 0\\.13 0\\.094 0\\.063 0\\.042 0\\.027 0\\.018 0\\.012 0\\.0079 0\\.0052 0\\.0035 0\\.0024 0\\.0016 0\\.0011 0\\.00078 0\\.00055\\]\\.\\n") }) test_that("print.dist_spec correctly prints the parameters of the uncertain gamma", { - gamma <- dist_spec( - params_mean = c(3, 2), params_sd = c(0.5, 0.5), max = 19, - distribution = "gamma" + gamma <- gamma( + shape = normal(3, 0.5), rate = normal(2, 0.5), max = 19 ) expect_output(print(gamma), "\\n gamma distribution \\(max: 19\\) with uncertain shape \\(mean = 3, sd = 0.5\\) and uncertain rate \\(mean = 2, sd = 0\\.5\\)\\.\\n") }) test_that("print.dist_spec correctly prints the parameters of the uncertain lognormal", { - lognormal_uncertain <- dist_spec(mean = 1.5, sd = 0.5, mean_sd = 0.1, sd_sd = 0.1, max = 19, distribution = "lognormal") + dist <- lognormal( + meanlog = normal(1.5, 0.1), sdlog = normal(0.5, 0.1), max = 19 + ) - expect_output(print(lognormal_uncertain), "\\n lognormal distribution \\(max: 19\\) with uncertain meanlog \\(mean = 1\\.5, sd = 0\\.1\\) and uncertain sdlog \\(mean = 0\\.5, sd = 0\\.1\\)\\.\\n") + expect_output(print(dist), "\\n lognormal distribution \\(max: 19\\) with uncertain meanlog \\(mean = 1\\.5, sd = 0\\.1\\) and uncertain sdlog \\(mean = 0\\.5, sd = 0\\.1\\)\\.\\n") }) test_that("print.dist_spec correctly prints the parameters of a combination of distributions", { - lognormal <- dist_spec(mean = 1.5, sd = 0.5, max = 19, distribution = "lognormal") - gamma <- dist_spec(params_mean = c(3, 2), params_sd = c(0.5, 0.5), max = 19, distribution = "gamma") - combined <- lognormal + gamma + dist1 <- lognormal(meanlog = 1.5, sdlog = 0.5, max = 19) + dist2 <- gamma(shape = normal(3, 0.5), rate = normal(2, 0.5), max = 19) + combined <- dist1 + dist2 expect_output(print(combined), "\\nComposite delay distribution:\\n distribution with PMF \\[0\\.0014 0\\.052 0\\.16 0\\.2 0\\.18 0\\.13 0\\.094 0\\.063 0\\.042 0\\.027 0\\.018 0\\.012 0\\.0079 0\\.0052 0\\.0035 0\\.0024 0\\.0016 0\\.0011 0\\.00078 0\\.00055\\]\\.\\n gamma distribution \\(max: 19\\) with uncertain shape \\(mean = 3, sd = 0\\.5\\) and uncertain rate \\(mean = 2, sd = 0\\.5\\)\\.\\n") }) test_that("plot.dist_spec returns a ggplot object", { - lognormal <- dist_spec(mean = 1.6, sd = 0.5, max = 19, distribution = "lognormal") - plot <- plot(lognormal) + dist <- lognormal(meanlog = 1.6, sdlog = 0.5, max = 19) + plot <- plot(dist) expect_s3_class(plot, "ggplot") }) test_that("plot.dist_spec correctly plots a single distribution", { - lognormal <- dist_spec(mean = 1.6, sd = 0.5, max = 19, distribution = "lognormal") - plot <- plot(lognormal) + dist <- lognormal(meanlog = 1.6, sdlog = 0.5, max = 19) + plot <- plot(dist) expect_equal(length(plot$layers), 2) expect_equal(length(plot$facet$params$facets), 1) }) test_that("plot.dist_spec correctly plots multiple distributions", { - lognormal <- dist_spec(mean = 1.6, sd = 0.5, max = 19, distribution = "lognormal") - gamma <- dist_spec(mean = 3, sd = 2, mean_sd = 0.5, sd_sd = 0.5, max = 19, distribution = "gamma") - combined <- lognormal + gamma + dist1 <- lognormal(meanlog = 1.6, sdlog = 0.5, max = 19) + dist2 <- gamma(shape = normal(3, 5), rate = normal(1, 2), max = 19) + combined <- dist1 + dist2 plot <- plot(combined) expect_equal(length(plot$layers), 2) expect_equal(length(plot$facet$params$facets), 1) }) test_that("plot.dist_spec correctly plots a combination of fixed distributions", { - lognormal <- dist_spec(mean = 1.6, sd = 0.5, max = 19, distribution = "lognormal") - combined <- lognormal + lognormal + dist <- lognormal(meanlog = 1.6, sdlog = 0.5, max = 19) + combined <- dist + dist plot <- plot(combined) expect_equal(length(plot$layers), 2) expect_equal(length(plot$facet$params$facets), 1) }) -test_that("deprecated arguments are caught", { - expect_deprecated(dist_spec(mean = 1.6, sd = 0.6, max = 19, fixed = TRUE)) +test_that("fix_dist works with composite delay distributions", { + dist1 <- lognormal(meanlog = normal(1, 0.1), sdlog = 1, max = 19) + dist2 <- gamma(mean = 3, sd = 2, max = 19) + dist <- dist1 + dist2 + expect_equal(fix_dist(dist)$n, 1L) +}) + +test_that("composite delay distriubtions can be disassembled", { + dist1 <- lognormal(meanlog = normal(1, 0.1), sdlog = 1, max = 19) + dist2 <- gamma(mean = 3, sd = 2, max = 19) + dist <- dist1 + dist2 + expect_equal(EpiNow2:::extract_single_dist(dist, 1), dist1) + expect_equal(EpiNow2:::extract_single_dist(dist, 2), dist2) +}) + +test_that("delay distributions can be specified in different ways", { + expect_equal( + lognormal(mean = 4, sd = 1)$params_mean, array(c(1.4, 0.25)), + tolerance = 0.1 + ) + expect_equal( + round(lognormal(mean = 4, sd = 1, max = 10)$np_pmf, 2), + array(c(0.00, 0.00, 0.14, 0.40, 0.30, 0.11, 0.03, 0.01, 0.00, 0.00, 0.00)) + ) + expect_equal( + gamma(mean = 4, sd = 1)$params_mean, array(c(16, 4)), + tolerance = 0.1 + ) + expect_equal( + round(gamma(mean = 4, sd = 1, max = 7)$np_pmf, 2), + array(c(0.00, 0.01, 0.15, 0.38, 0.31, 0.12, 0.03, 0.00)) + ) + expect_equal( + gamma(shape = normal(16, 2), rate = normal(4, 1))$params_mean, + array(c(16, 4)) + ) + expect_equal( + gamma(shape = normal(16, 2), rate = normal(4, 1))$params_sd, + array(c(2, 1)) + ) + expect_equal( + normal(mean = 4, sd = 1)$params_mean, array(c(4, 1)) + ) + expect_equal( + round(normal(mean = 4, sd = 1, max = 5)$np_pmf, 2), + array(c(0.00, 0.02, 0.14, 0.35, 0.35, 0.14)) + ) + expect_equal( + fixed(value = 3)$np_pmf, array(c(0, 0, 0, 1)) + ) + expect_equal(fixed(value = 3.5)$params_mean, array(3.5)) + expect_equal(pmf(c(0.1, 0.3, 0.2, 0.4))$np_pmf, array(c(0.1, 0.3, 0.2, 0.4))) + expect_equal( + round(pmf(c(0.1, 0.3, 0.2, 0.1, 0.1))$np_pmf, 2), + array(c(0.12, 0.37, 0.25, 0.12, 0.12)) + ) +}) + +test_that("a warning is thrown for non-natural parametrisations", { + expect_warning(lognormal(mean = normal(4, 1), sd = 1, max = 10)) + expect_warning(gamma(mean = normal(4, 1), sd = 1, max = 10)) +}) + +test_that("deprecated functions are deprecated", { + expect_deprecated(dist_spec(params_mean = 1.6, params_sd = 0.6, max = 19)) }) diff --git a/tests/testthat/test-epinow.R b/tests/testthat/test-epinow.R index 68810f5ce..278ade874 100644 --- a/tests/testthat/test-epinow.R +++ b/tests/testthat/test-epinow.R @@ -1,9 +1,9 @@ skip_on_cran() # set example reporting delay -reporting_delay <- dist_spec( - mean = convert_to_logmean(2, 1), mean_sd = 0.1, - sd = convert_to_logsd(2, 1), sd_sd = 0.1, +reporting_delay <- lognormal( + meanlog = normal(0.6, 0.06), + sdlog = normal(0.5, 0.1), max = 10 ) diff --git a/tests/testthat/test-estimate_secondary.R b/tests/testthat/test-estimate_secondary.R index 3f272014d..55f2117ea 100644 --- a/tests/testthat/test-estimate_secondary.R +++ b/tests/testthat/test-estimate_secondary.R @@ -188,8 +188,10 @@ test_that("forecast_secondary can return values from simulated data when using }) test_that("estimate_secondary works with weigh_delay_priors = TRUE", { - delays <- dist_spec( - mean = 2.5, mean_sd = 0.5, sd = 0.47, sd_sd = 0.25, max = 30 + delays <- lognormal( + meanlog = normal(2.5, 0.5), + sdlog = normal(0.47, 0.25), + max = 30 ) inc_weigh <- estimate_secondary( inc_cases[1:60], delays = delay_opts(delays), diff --git a/tests/testthat/test-estimate_truncation.R b/tests/testthat/test-estimate_truncation.R index f0358407d..618725f62 100644 --- a/tests/testthat/test-estimate_truncation.R +++ b/tests/testthat/test-estimate_truncation.R @@ -10,11 +10,9 @@ options(mc.cores = ifelse(interactive(), 4, 1)) reported_cases <- example_confirmed[1:60] # define example truncation distribution (note not integer adjusted) -trunc_dist <- dist_spec( - mean = convert_to_logmean(3, 2), - mean_sd = 0.1, - sd = convert_to_logsd(3, 2), - sd_sd = 0.1, +trunc_dist <- lognormal( + meanlog = normal(0.9, 0.1), + sdlog = normal(0.6, 0.1), max = 10 ) diff --git a/tests/testthat/test-report_cases.R b/tests/testthat/test-report_cases.R index 40506257c..41d8062de 100644 --- a/tests/testthat/test-report_cases.R +++ b/tests/testthat/test-report_cases.R @@ -15,6 +15,6 @@ test_that("report_cases can simulate infections forward", { expect_equal(class(reported_cases), "list") expect_equal(class(reported_cases$samples), c("data.table", "data.frame")) expect_equal(class(reported_cases$summarised), c("data.table", "data.frame")) - expect_equal(nrow(reported_cases$summarised), 9) + expect_equal(nrow(reported_cases$summarised), 10) expect_equal(class(reported_cases$summarised$median), "numeric") }) diff --git a/tests/testthat/test-seeding-time.R b/tests/testthat/test-seeding-time.R index d189192ef..68873b9ed 100644 --- a/tests/testthat/test-seeding-time.R +++ b/tests/testthat/test-seeding-time.R @@ -1,8 +1,8 @@ test_that("Seeding times are correctly calculated", { - gt1 <- dist_spec(mean = 5, sd = 1, max = 9) - gt2 <- dist_spec(mean = 10, sd = 2, max = 14) - delay1 <- dist_spec(mean = 5, sd = 1, max = 9) - delay2 <- dist_spec(mean = 7, sd = 3, max = 14) + gt1 <- lognormal(meanlog = 5, sdlog = 1, max = 9) + gt2 <- lognormal(meanlog = 10, sdlog = 2, max = 14) + delay1 <- lognormal(meanlog = 5, sdlog = 1, max = 9) + delay2 <- lognormal(meanlog = 7, sdlog = 3, max = 14) expect_equal( EpiNow2:::get_seeding_time(delay1, gt1 + gt2), 23L ## 10 + 15 - 1 - 1 ) @@ -12,7 +12,7 @@ test_that("Seeding times are correctly calculated", { }) test_that("Short seeding times are rounded up to 1", { - delay <- dist_spec(mean = 0.5, sd = 1, max = 2) - gt <- dist_spec(mean = 1) + delay <- lognormal(meanlog = 0.5, sdlog = 1, max = 2) + gt <- fixed(value = 1) expect_equal(EpiNow2:::get_seeding_time(delay, gt), 1L) }) diff --git a/vignettes/epinow.Rmd.orig b/vignettes/epinow.Rmd.orig index ad41f91d1..87b30c40b 100644 --- a/vignettes/epinow.Rmd.orig +++ b/vignettes/epinow.Rmd.orig @@ -36,10 +36,7 @@ This should be replaced with parameters relevant to the system that is being stu library("EpiNow2") options(mc.cores = 4) reported_cases <- example_confirmed[1:60] -reporting_delay <- dist_spec( - mean = convert_to_logmean(2, 1), mean_sd = 0, - sd = convert_to_logsd(2, 1), sd_sd = 0, max = 10 -) +reporting_delay <- lognormal(mean = 2, sd = 1, max = 10) delay <- example_incubation_period + reporting_delay rt_prior <- list(mean = 2, sd = 0.1) ``` diff --git a/vignettes/estimate_infections_options.Rmd.orig b/vignettes/estimate_infections_options.Rmd.orig index 0122d28bd..0292ec899 100644 --- a/vignettes/estimate_infections_options.Rmd.orig +++ b/vignettes/estimate_infections_options.Rmd.orig @@ -71,10 +71,7 @@ For the reporting delay, we use a lognormal distribution with mean of 2 days and Note that the mean and standard deviation must be converted to the log scale, which can be done using the `convert_log_logmean()` function. ```{r reporting_delay} -reporting_delay <- dist_spec( - mean = convert_to_logmean(2, 1), mean_sd = 0, - sd = convert_to_logsd(2, 1), sd_sd = 0, max = 10 -) +reporting_delay <- lognormal(mean = 2, sd = 1, max = 10) reporting_delay ``` @@ -172,11 +169,12 @@ We might further want to adjust for right-truncation of recent data estimated us Here, instead of doing so we assume that we know about truncation with mean of 1/2 day, sd 1/2 day, following a lognormal distribution and with a maximum of three days. ```{r define_truncation} -trunc_dist <- dist_spec( - mean = convert_to_logmean(0.5, 0.5), mean_sd = 0.1, - sd = convert_to_logsd(0.5, 0.5), sd_sd = 0.1, +trunc_dist <- lognormal( + mean = normal(0.5, 0.1), + sd = normal(0.5, 0.1), max = 3 ) +trunc_dist ``` We can then use this in the `esimtate_infections()` function using the `truncation` option. diff --git a/vignettes/estimate_infections_workflow.Rmd.orig b/vignettes/estimate_infections_workflow.Rmd.orig index 93b137a82..f4ba771a8 100644 --- a/vignettes/estimate_infections_workflow.Rmd.orig +++ b/vignettes/estimate_infections_workflow.Rmd.orig @@ -65,29 +65,30 @@ As these will affect any results, it is worth spending some time investigating w ## Delay distributions _EpiNow2_ works with different delays that apply to different parts of the infection and observation process. -They are defined using a common interface with the `dist_spec()` function. +They are defined using a common interface that involves functions that are named after the probability distributions, i.e. `lognormal()`, `gamma()`, etc. For help with this function, see its manual page ```{r eval = FALSE} -?EpiNow2::dist_spec +?EpiNow2::Distributions ``` In all cases, the distributions given can be *fixed* (i.e. have no uncertainty) or *variable* (i.e. have associated uncertainty). For example, to define a fixed gamma distribution with mean 3, standard deviation (sd) 1 and maximum value 10, you would write ```{r} -dist_spec(mean = 3, sd = 1, distribution = "gamma", max = 10) +gamma(mean = 3, sd = 1, max = 10) ``` If distributions are variable, the values with uncertainty are treated as [prior probability densities](https://en.wikipedia.org/wiki/Prior_probability) in the Bayesian inference framework used by _EpiNow2_, i.e. they are estimated as part of the inference. For example, to define a variable gamma distribution where uncertainty in the mean is given by a normal distribution with mean 3 and sd 2, and uncertainty in the standard deviation is given by a normal distribution with mean 1 and sd 0.1, with a maximum value 10, you would write ```{r} -dist_spec( - mean = 3, mean_sd = 2, sd = 1, sd_sd = 0.1, distribution = "gamma", max = 10 -) +gamma(mean = normal(3, 2), sd = normal(1, 0.1), max = 10) ``` +Note the warning about parameters. +We used the mean and standard deviation to define this distribution with uncertain parameters, but it would be better to use the "natural" parameters of the gamma distribution, shape and rate, for example using the values estimate and reported back after calling the previous command. + There are various ways the specific delay distributions mentioned below might be obtained. Often, they will come directly from the existing literature reviewed by the user and studies conducted elsewhere. Sometimes it might be possible to obtain them from existing databases, e.g. using the [epiparameter](https://github.com/epiverse-trace/epiparameter) R package. @@ -98,12 +99,12 @@ For a more comprehensive treatment of delays and their estimation avoiding commo ### Generation intervals The generation interval is a delay distribution that describes the amount of time that passes between an individual becoming infected and infecting someone else. -In _EpiNow2_, the generation time distribution is defined by a call to `generation_time_opts()`, a function that takes a single argument defined as a `dist_spec` object (returned by `dist_spec()`). -For example, to define the generation time as gamma distributed with uncertain mean centered on 3 (sd: 2) and sd centered on 1 (sd: 0.1), a maximum value of 10 and weighted by the number of case data points we would use +In _EpiNow2_, the generation time distribution is defined by a call to `generation_time_opts()`, a function that takes a single argument defined as a `dist_spec` object (returned by the function corresponding to the probability distribution, i.e. `lognormal()`, `gamma()`, etc.). +For example, to define the generation time as gamma distributed with uncertain mean centered on 3 (sd: 2) and sd centered on 1 (sd: 0.1), a maximum value of 10 and weighted by the number of case data points we could use the shape and rate parameters obtained above: ```{r, results = 'hide'} -generation_time <- dist_spec( - mean = 3, mean_sd = 2, sd = 1, sd_sd = 0.1, distribution = "gamma", max = 10 +generation_time <- gamma( + shape = normal(15, 15), rate = normal(3.5, 2), max = 10 ) generation_time_opts(generation_time) ``` @@ -115,20 +116,19 @@ Usually this is not observed directly. Instead, we calculate case counts based on, for example, onset of symptoms, lab confirmations, hospitalisations, etc. In order to estimate the trajectory of infection incidence from this we need to either know or estimate the distribution of delays from infection to count. Often, such counts are composed of multiple delays for which we only have separate information, for example the incubation period (time from infection to symptom onset) and reporting delay (time from symptom onset to being a case in the data, e.g. via lab confirmation, if counts are not by the date of symptom onset). -In this case, we can combine multiple delays defined using `dist_spec()` with the plus (`+`) operator, e.g. +In this case, we can combine multiple delays with the plus (`+`) operator, e.g. ```{r} -incubation_period <- dist_spec( - mean = 1.6, mean_sd = 0.05, sd = 0.5, sd_sd = 0.05, - distribution = "lognormal", max = 14 -) -reporting_delay <- dist_spec( - mean = 0.5, sd = 0.5, distribution = "lognormal", max = 10 +incubation_period <- lognormal( + meanlog = normal(1.6, 0.05), + sdlog = normal(0.5, 0.05), + max = 14 ) +reporting_delay <- lognormal(meanlog = 0.5, sdlog = 0.5, max = 10) incubation_period + reporting_delay ``` -In _EpiNow2_, the reporting delay distribution is defined by a call to `delay_opts()`, a function that takes a single argument defined as a `dist_spec` object (returned by `dist_spec()`). +In _EpiNow2_, the reporting delay distribution is defined by a call to `delay_opts()`, a function that takes a single argument defined as a `dist_spec` object (returned by `lognormal()`, `gamma()` etc.). For example, if our observations were by symptom onset we would use ```{r, results = 'hide'} From c6d62be72fc509dbe866022e443f60db4a0ee5a1 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 22 Nov 2023 10:39:52 +0000 Subject: [PATCH 047/129] add news item --- NEWS.md | 1 + 1 file changed, 1 insertion(+) diff --git a/NEWS.md b/NEWS.md index bdb383159..d9321da0f 100644 --- a/NEWS.md +++ b/NEWS.md @@ -7,6 +7,7 @@ * The `fixed` argument to `dist_spec` has been deprecated and replaced by a `fix_dist()` function. By @sbfnk in #503 and reviewed by @seabbs. * Updated `estimate_infections()` so that rather than imputing missing data, it now skips these data points in the likelihood. This is a breaking change as it alters the behaviour of the model when dates are missing from a time series but are known to be zero. We recommend that users check their results when updating to this version but expect this to in most cases improve performance. By @seabbs in #528 and reviewed by @sbfnk. * `simulate_infections` has been renamed to `forecast_infections` in line with `simulate_secondary` and `forecast_secondary`. The terminology is: a forecast is done from a fit to existing data, a simulation from first principles. By @sbfnk in #544 and reviewed by @seabbs. +* The interface to generating delay distributions has been completely overhauled. Instead of calling `dist_spec()` users now specify distributions using functions that represent the available distributions, i.e. `lognormal()`, `gamma()` and `fixed()`. Uncertainty is specified using calls of the same nature, to `normal()`. By @sbfnk in #504. ## Documentation From c95a29654d5e12cea96c5522d503da90832917d7 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 22 Nov 2023 11:04:53 +0000 Subject: [PATCH 048/129] turn sd into an internal function --- NAMESPACE | 4 +--- R/dist.R | 32 ++++++++++++++--------------- man/{sd.dist_spec.Rd => sd_dist.Rd} | 17 +++++++-------- 3 files changed, 25 insertions(+), 28 deletions(-) rename man/{sd.dist_spec.Rd => sd_dist.Rd} (84%) diff --git a/NAMESPACE b/NAMESPACE index f048a0842..cac2a97e7 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -9,8 +9,6 @@ S3method(plot,estimate_infections) S3method(plot,estimate_secondary) S3method(plot,estimate_truncation) S3method(print,dist_spec) -S3method(sd,default) -S3method(sd,dist_spec) S3method(summary,epinow) S3method(summary,estimate_infections) export(R_to_growth) @@ -91,7 +89,7 @@ export(rt_opts) export(sample_approx_dist) export(save_estimate_infections) export(save_input) -export(sd) +export(sd.default) export(secondary_opts) export(set_dt_single_thread) export(setup_default_logging) diff --git a/R/dist.R b/R/dist.R index f63ca1ada..e8c0682aa 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1286,32 +1286,30 @@ mean.dist_spec <- function(x, ...) { return(ret) } -#' @export -sd <- function(x, ...) UseMethod("sd") ##' Returns the standard deviation of one or more delay distribution ##' ##' This works out the standard deviation of all the (parametric / ##' nonparametric) delay distributions combined in the passed [dist_spec()]. ##' ##' @param x The [dist_spec()] to use -##' @param ... Not used ##' @return A vector of standard deviations. ##' @author Sebastian Funk -##' @method sd dist_spec ##' @importFrom utils head -##' @export -#' @examples -#' # A fixed lognormal distribution with sd 5 and sd 1. -#' dist1 <- lognormal(mean = 5, sd = 1, max = 20) -#' sd(dist1) -#' -#' # A gamma distribution with mean 3 and sd 2 -#' dist2 <- gamma(mean = 3, sd = 2) -#' sd(dist2) -#' -#' # The sd of the sum of two distributions -#' sd(dist1 + dist2) -sd.dist_spec <- function(x, ...) { +##' @keywords internal +##' @examples +##' \dontrun{ +##' # A fixed lognormal distribution with sd 5 and sd 1. +##' dist1 <- lognormal(mean = 5, sd = 1, max = 20) +##' sd_dist(dist1) +##' +##' # A gamma distribution with mean 3 and sd 2 +##' dist2 <- gamma(mean = 3, sd = 2) +##' sd_dist(dist2) +##' +##' # The sd of the sum of two distributions +##' sd_dist(dist1 + dist2) +##' } +sd_dist <- function(x) { ret <- rep(.0, x$n) if (x$n_np > 0) { ## nonparametric diff --git a/man/sd.dist_spec.Rd b/man/sd_dist.Rd similarity index 84% rename from man/sd.dist_spec.Rd rename to man/sd_dist.Rd index b7888249e..341e1585d 100644 --- a/man/sd.dist_spec.Rd +++ b/man/sd_dist.Rd @@ -1,15 +1,13 @@ % Generated by roxygen2: do not edit by hand % Please edit documentation in R/dist.R -\name{sd.dist_spec} -\alias{sd.dist_spec} +\name{sd_dist} +\alias{sd_dist} \title{Returns the standard deviation of one or more delay distribution} \usage{ -\method{sd}{dist_spec}(x, ...) +sd_dist(x) } \arguments{ \item{x}{The \code{\link[=dist_spec]{dist_spec()}} to use} - -\item{...}{Not used} } \value{ A vector of standard deviations. @@ -19,17 +17,20 @@ This works out the standard deviation of all the (parametric / nonparametric) delay distributions combined in the passed \code{\link[=dist_spec]{dist_spec()}}. } \examples{ +\dontrun{ # A fixed lognormal distribution with sd 5 and sd 1. dist1 <- lognormal(mean = 5, sd = 1, max = 20) -sd(dist1) +sd_dist(dist1) # A gamma distribution with mean 3 and sd 2 dist2 <- gamma(mean = 3, sd = 2) -sd(dist2) +sd_dist(dist2) # The sd of the sum of two distributions -sd(dist1 + dist2) +sd_dist(dist1 + dist2) +} } \author{ Sebastian Funk } +\keyword{internal} From b3e9001b6313ba89a3fe50a6166afe3994e48dca Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 22 Nov 2023 11:05:11 +0000 Subject: [PATCH 049/129] fix distribution documentation --- R/dist.R | 11 ++++++----- man/Distributions.Rd | 11 +++++++++-- 2 files changed, 15 insertions(+), 7 deletions(-) diff --git a/R/dist.R b/R/dist.R index e8c0682aa..cf9231d23 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1662,6 +1662,7 @@ fix_dist <- function(x, strategy = c("mean", "sample")) { ##' ##' @inheritParams stats::Lognormal ##' @inheritParams .dist_spec +##' @param mean,sd mean and standard deviation of the distribution ##' @return A `dist_spec` representing a distribution of the given ##' specification. ##' @author Sebastian Funk @@ -1678,7 +1679,7 @@ lognormal <- function(meanlog, sdlog, mean, sd, max = Inf) { return(generate_dist_spec(params, "lognormal")) } -##' @inheritParams stats::Gamma +##' @inheritParams stats::GammaDist ##' @author Sebastian Funk ##' @rdname Distributions ##' @title Probability distributions @@ -1726,7 +1727,7 @@ fixed <- function(value) { ##' Generates a nonparametric distribution. ##' -##' @param pmf Probability mass function of the given distribution; this is +##' @param mass Probability mass of the given distribution; this is ##' passed as a zero-indexed numeric vector (i.e. the fist entry represents ##' the probability mass of zero). If not summing to one it will be normalised ##' to sum to one internally. @@ -1737,8 +1738,8 @@ fixed <- function(value) { ##' @examples ##' pmf(c(0.1, 0.3, 0.2, 0.4)) ##' pmf(c(0.1, 0.3, 0.2, 0.1, 0.1)) -pmf <- function(x) { - return(.dist_spec(pmf = x)) +pmf <- function(mass) { + return(.dist_spec(pmf = mass)) } ##' Get the names of the natural parameters of a distribution @@ -1891,7 +1892,7 @@ generate_dist_spec <- function(params, distribution) { } else { converted_params <- list( params_mean = vapply(params, mean, numeric(1), USE.NAMES = FALSE), - params_sd = vapply(params, sd, numeric(1), USE.NAMES = FALSE) + params_sd = vapply(params, sd_dist, numeric(1), USE.NAMES = FALSE) ) } diff --git a/man/Distributions.Rd b/man/Distributions.Rd index 947b4c8c1..d9158d7e9 100644 --- a/man/Distributions.Rd +++ b/man/Distributions.Rd @@ -17,18 +17,25 @@ normal(mean, sd, max = Inf) fixed(value) -pmf(x) +pmf(mass) } \arguments{ \item{meanlog, sdlog}{mean and standard deviation of the distribution on the log scale with default values of \code{0} and \code{1} respectively.} +\item{mean, sd}{mean and standard deviation of the distribution} + \item{max}{Numeric, maximum value of the distribution. The distribution will be truncated at this value. Default: \code{Inf}, i.e. no maximum.} +\item{shape, scale}{shape and scale parameters. Must be positive, + \code{scale} strictly.} + +\item{rate}{an alternative way to specify the scale.} + \item{value}{Value of the fixed (delta) distribution} -\item{pmf}{Probability mass function of the given distribution; this is +\item{mass}{Probability mass of the given distribution; this is passed as a zero-indexed numeric vector (i.e. the fist entry represents the probability mass of zero). If not summing to one it will be normalised to sum to one internally.} From d7fcc60decb0a3133fde78b65227cd0a7df6a8a3 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 22 Nov 2023 12:58:33 +0000 Subject: [PATCH 050/129] remove obselete default --- NAMESPACE | 1 - R/dist.R | 4 ---- 2 files changed, 5 deletions(-) diff --git a/NAMESPACE b/NAMESPACE index cac2a97e7..1cf68d2be 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -89,7 +89,6 @@ export(rt_opts) export(sample_approx_dist) export(save_estimate_infections) export(save_input) -export(sd.default) export(secondary_opts) export(set_dt_single_thread) export(setup_default_logging) diff --git a/R/dist.R b/R/dist.R index cf9231d23..e77e9aba7 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1343,10 +1343,6 @@ sd_dist <- function(x) { } return(ret) } -#' @export -sd.default <- function(x, ...) { - stats::sd(x, ...) -} ##' Returns the maximum of one or more delay distribution ##' From 2fe6f02b7628a5314d6456cc871af70bfc1202ef Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 22 Nov 2023 12:58:55 +0000 Subject: [PATCH 051/129] spell checking --- R/dist.R | 12 ++++++------ man/Distributions.Rd | 2 +- man/convert_to_natural.Rd | 4 ++-- man/generate_dist_spec.Rd | 4 ++-- man/natural_params.Rd | 2 +- 5 files changed, 12 insertions(+), 12 deletions(-) diff --git a/R/dist.R b/R/dist.R index e77e9aba7..db9693924 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1649,7 +1649,7 @@ fix_dist <- function(x, strategy = c("mean", "sample")) { ##' parameters such as the mean or standard deviation of the distribution. If ##' not given as natural parameters then these will be calculated from the given ##' parameters. If they have uncertainty, this will be done by random sampling -##' from the given uncertainty and coverting resulting parameters to their +##' from the given uncertainty and converting resulting parameters to their ##' natural representation. ##' ##' Currently available distributions are lognormal, gamma, normal, fixed @@ -1742,7 +1742,7 @@ pmf <- function(mass) { ##' ##' These are the parameters used in the stan models. All other parameter ##' representations are converted to these using [convert_to_natural()] before -##' being passed to teh stan mnodels. +##' being passed to the stan models. ##' @param distribution Character; the distribution to use. ##' @return A character vector, the natural parameters. ##' @author Sebastian Funk @@ -1808,14 +1808,14 @@ extract_params <- function(params, distribution) { return(params) } -##' Internal function for generating a `dist_spec` given parametrs and a +##' Internal function for generating a `dist_spec` given parameters and a ##' distribution. ##' ##' This will convert all parameters to natural parameters before generating ##' a `dist_spec`. If they have uncertainty this will be done using sampling. ##' @inheritParams extract_params ##' @importFrom purrr walk -##' @return A `dist_spec` of the given specificaiton.` +##' @return A `dist_spec` of the given specification. ##' @author Sebastian Funk generate_dist_spec <- function(params, distribution) { ## process min/max first @@ -1906,10 +1906,10 @@ generate_dist_spec <- function(params, distribution) { ##' Internal function for converting parameters to natural parameters. ##' ##' This is used for preprocessing before generating a `dist_spec` object -##' from a given set of parametrs and distribution +##' from a given set of parameters and distribution ##' @param x A numerical named parameter vector ##' @inheritParams natural_params -##' @return A list with two elements, `params_mean` and `params_sd`, containign +##' @return A list with two elements, `params_mean` and `params_sd`, containing ##' mean and sd of natural parameters. ##' @author Sebastian Funk convert_to_natural <- function(x, distribution) { diff --git a/man/Distributions.Rd b/man/Distributions.Rd index d9158d7e9..7e11c6ea2 100644 --- a/man/Distributions.Rd +++ b/man/Distributions.Rd @@ -67,7 +67,7 @@ ones used in stan) but can sometimes also be specified using other parameters such as the mean or standard deviation of the distribution. If not given as natural parameters then these will be calculated from the given parameters. If they have uncertainty, this will be done by random sampling -from the given uncertainty and coverting resulting parameters to their +from the given uncertainty and converting resulting parameters to their natural representation. Currently available distributions are lognormal, gamma, normal, fixed diff --git a/man/convert_to_natural.Rd b/man/convert_to_natural.Rd index 29d700cae..a6d8ea1b0 100644 --- a/man/convert_to_natural.Rd +++ b/man/convert_to_natural.Rd @@ -12,12 +12,12 @@ convert_to_natural(x, distribution) \item{distribution}{Character; the distribution to use.} } \value{ -A list with two elements, \code{params_mean} and \code{params_sd}, containign +A list with two elements, \code{params_mean} and \code{params_sd}, containing mean and sd of natural parameters. } \description{ This is used for preprocessing before generating a \code{dist_spec} object -from a given set of parametrs and distribution +from a given set of parameters and distribution } \author{ Sebastian Funk diff --git a/man/generate_dist_spec.Rd b/man/generate_dist_spec.Rd index 867ac023e..a7a73fbe8 100644 --- a/man/generate_dist_spec.Rd +++ b/man/generate_dist_spec.Rd @@ -2,7 +2,7 @@ % Please edit documentation in R/dist.R \name{generate_dist_spec} \alias{generate_dist_spec} -\title{Internal function for generating a \code{dist_spec} given parametrs and a +\title{Internal function for generating a \code{dist_spec} given parameters and a distribution.} \usage{ generate_dist_spec(params, distribution) @@ -13,7 +13,7 @@ generate_dist_spec(params, distribution) \item{distribution}{Character; the distribution to use.} } \value{ -A \code{dist_spec} of the given specificaiton.` +A \code{dist_spec} of the given specification. } \description{ This will convert all parameters to natural parameters before generating diff --git a/man/natural_params.Rd b/man/natural_params.Rd index ed7729eeb..e255409e4 100644 --- a/man/natural_params.Rd +++ b/man/natural_params.Rd @@ -15,7 +15,7 @@ A character vector, the natural parameters. \description{ These are the parameters used in the stan models. All other parameter representations are converted to these using \code{\link[=convert_to_natural]{convert_to_natural()}} before -being passed to teh stan mnodels. +being passed to the stan models. } \examples{ \dontrun{ From 6403ff8540af50a5f2f8c34025da2f0de0e0c4b4 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 22 Nov 2023 12:59:03 +0000 Subject: [PATCH 052/129] use correct sd function --- R/dist.R | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/R/dist.R b/R/dist.R index db9693924..ac562989c 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1863,7 +1863,7 @@ generate_dist_spec <- function(params, distribution) { ) } ## sample parameters if they are uncertain - if (any(vapply(params, sd, .0) > 0)) { + if (any(vapply(params, sd_dist, .0) > 0)) { message( "Uncertain ", distribution, " distribution specified in terms of ", "parameters that are not the \"natural\" parameters of the ", @@ -1875,7 +1875,7 @@ generate_dist_spec <- function(params, distribution) { samples <- lapply(names(params), function(x) { rtruncnorm( n = 2000, a = lower_bounds(distribution)[x], - mean = mean(params[[x]]), sd = sd(params[[x]]) + mean = mean(params[[x]]), sd = sd_dist(params[[x]]) ) }) names(samples) <- names(params) From 286108a7ae295a987bc28534f25276e11fbe736a Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 22 Nov 2023 12:55:25 +0000 Subject: [PATCH 053/129] linting --- R/dist.R | 38 ++++++++++++++++++-------------------- 1 file changed, 18 insertions(+), 20 deletions(-) diff --git a/R/dist.R b/R/dist.R index ac562989c..a9a008bae 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1020,8 +1020,8 @@ dist_spec <- function(distribution = c( "The meaning of the 'max' argument has changed compared to", "previous versions. It now indicates the maximum of a distribution", "rather than the length of the probability mass function (including 0)", - "that it represented previously. To replicate previous behaviour reduce", - "max by 1." + "that it represented previously. To replicate previous behaviour ", + "reduce max by 1." ), .frequency = "regularly", .frequency_id = "dist_spec_max" @@ -1158,7 +1158,7 @@ dist_spec_plus <- function(e1, e2, tolerance = 0.001) { delays$np_pmf <- new_pmf delays$np_pmf_length <- length(delays$np_pmf) delays$params_length <- c( - 0, delays$params_length[delays$parametric == TRUE] + 0, delays$params_length[delays$parametric] ) delays$parametric <- array(c(FALSE, rep(TRUE, delays$n_p))) delays$n_np <- 1 @@ -1256,7 +1256,7 @@ c.dist_spec <- function(...) { #' # The mean of the sum of two distributions #' mean(dist1 + dist2) mean.dist_spec <- function(x, ...) { - ret <- rep(.0, x$n) + ret <- rep(0, x$n) if (x$n_np > 0) { ## nonparametric ret[!x$parametric] <- sum((seq_len(x$np_pmf_length) - 1) * x$np_pmf) @@ -1266,22 +1266,20 @@ mean.dist_spec <- function(x, ...) { ret[x$parametric] <- vapply(which(x$parametric), function(id) { single_dist <- extract_single_dist(x, id) if (single_dist$dist == "lognormal") { - ret <- exp( - single_dist$params_mean[[1]] + single_dist$params_mean[[2]]**2 / 2 - ) + exp(single_dist$params_mean[[1]] + single_dist$params_mean[[2]]**2 / 2) } else if (single_dist$dist == "gamma") { - ret <- single_dist$params_mean[[1]] / single_dist$params_mean[[2]] + single_dist$params_mean[[1]] / single_dist$params_mean[[2]] } else if (single_dist$dist == "normal") { - ret <- single_dist$params_mean[[1]] + single_dist$params_mean[[1]] } else if (single_dist$dist == "fixed") { - ret <- single_dist$params_mean[[1]] + single_dist$params_mean[[1]] } else { stop( "Don't know how to calculate mean of ", single_dist$dist, " distribution." ) } - }, .0) + }, numeric(1)) } return(ret) } @@ -1310,7 +1308,7 @@ mean.dist_spec <- function(x, ...) { ##' sd_dist(dist1 + dist2) ##' } sd_dist <- function(x) { - ret <- rep(.0, x$n) + ret <- rep(0, x$n) if (x$n_np > 0) { ## nonparametric mean_pmf <- sum((seq_len(x$np_pmf_length) - 1) * x$np_pmf) @@ -1325,21 +1323,21 @@ sd_dist <- function(x) { ret[x$parametric] <- vapply(which(x$parametric), function(id) { single_dist <- extract_single_dist(x, id) if (single_dist$dist == "lognormal") { - ret <- sqrt(exp(single_dist$params_mean[2]**2) - 1) * + sqrt(exp(single_dist$params_mean[2]**2) - 1) * exp(single_dist$params_mean[1] + 0.5 * single_dist$params_mean[2]**2) } else if (single_dist$dist == "gamma") { - ret <- sqrt(single_dist$params_mean[1] / single_dist$params_mean[2]**2) + sqrt(single_dist$params_mean[1] / single_dist$params_mean[2]**2) } else if (single_dist$dist == "normal") { - ret <- single_dist$params_mean[2] + single_dist$params_mean[2] } else if (single_dist$dist == "fixed") { - ret <- 0 + 0 } else { stop( "Don't know how to calculate standard deviation of ", single_dist$dist, " distribution." ) } - }, .0) + }, numeric(1)) } return(ret) } @@ -1863,11 +1861,11 @@ generate_dist_spec <- function(params, distribution) { ) } ## sample parameters if they are uncertain - if (any(vapply(params, sd_dist, .0) > 0)) { + if (any(vapply(params, sd_dist, numeric(1)) > 0)) { message( "Uncertain ", distribution, " distribution specified in terms of ", "parameters that are not the \"natural\" parameters of the ", - "distribution (", paste(natural_params(distribution), collapse = ", "), + "distribution (", toString(natural_params(distribution)), "). Converting using a finite sample. If possible, it is preferable ", "to specify the distribution direclty in terms of the natural ", "parameters." @@ -1931,7 +1929,7 @@ convert_to_natural <- function(x, distribution) { }, numeric(1))), params_sd = unname(vapply(natural_params(distribution), function(param) { if (length(x[[param]]) == 1) { - .0 + 0 } else { sd(x[[param]]) } From 5636b013bebaf15b229b5f1f87021cc768d05313 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 22 Nov 2023 14:38:42 +0000 Subject: [PATCH 054/129] remove obsolete tests --- tests/testthat/test-dist_spec.R | 13 ++++--------- 1 file changed, 4 insertions(+), 9 deletions(-) diff --git a/tests/testthat/test-dist_spec.R b/tests/testthat/test-dist_spec.R index 4c3555dc5..00b4048b2 100644 --- a/tests/testthat/test-dist_spec.R +++ b/tests/testthat/test-dist_spec.R @@ -119,7 +119,7 @@ test_that("summary functions return correct output for fixed lognormal distribut ## here we can see the bias from # using this kind of discretisation approach expect_equal(EpiNow2:::mean.dist_spec(dist), 2.49, tolerance = 0.01) - expect_equal(EpiNow2:::sd.dist_spec(dist), 1.09, tolerance = 0.01) + expect_equal(EpiNow2:::sd_dist(dist), 1.09, tolerance = 0.01) expect_equal(EpiNow2:::max.dist_spec(dist), 19L) }) @@ -134,14 +134,14 @@ test_that("mean.dist_spec returns correct output for sum of two distributions", dist2 <- gamma(mean = 3, sd = 2, max = 19) dist <- dist1 + dist2 expect_equal(EpiNow2:::mean.dist_spec(dist), c(5.84), tolerance = 0.001) - expect_equal(EpiNow2:::sd.dist_spec(dist), c(16.88), tolerance = 0.001) + expect_equal(EpiNow2:::sd_dist(dist), c(16.88), tolerance = 0.001) ## shortened due to tolerance level expect_equal(EpiNow2:::max.dist_spec(dist), 24L) }) -test_that("sd.dist_spec returns an error when applied to uncertain distributions", { +test_that("sd_dist returns an error when applied to uncertain distributions", { dist <- gamma(shape = normal(3, 0.5), rate = normal(2, 0.5), max = 19) - expect_error(EpiNow2:::sd.dist_spec(dist), "uncertain") + expect_error(EpiNow2:::sd_dist(dist), "uncertain") }) test_that("print.dist_spec correctly prints the parameters of the fixed lognormal", { @@ -262,11 +262,6 @@ test_that("delay distributions can be specified in different ways", { ) }) -test_that("a warning is thrown for non-natural parametrisations", { - expect_warning(lognormal(mean = normal(4, 1), sd = 1, max = 10)) - expect_warning(gamma(mean = normal(4, 1), sd = 1, max = 10)) -}) - test_that("deprecated functions are deprecated", { expect_deprecated(dist_spec(params_mean = 1.6, params_sd = 0.6, max = 19)) }) From a53d80085c6a3601b8249f053bd2f8913a32fed7 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 22 Nov 2023 14:43:52 +0000 Subject: [PATCH 055/129] loop over all parameters --- inst/stan/functions/delays.stan | 9 +++++++-- 1 file changed, 7 insertions(+), 2 deletions(-) diff --git a/inst/stan/functions/delays.stan b/inst/stan/functions/delays.stan index 4e7f3878b..aefeacbfa 100644 --- a/inst/stan/functions/delays.stan +++ b/inst/stan/functions/delays.stan @@ -105,7 +105,12 @@ void delays_lp(vector delay_params, } vector normal_lb_rng(vector mu, vector sigma, vector lb) { - real p = normal_cdf(lb, mu, sigma); // cdf for bounds + int len = num_elements(mu); + vector[len] ret; + for (i in 1:len) { + real p = normal_cdf(lb[i], mu[i], sigma[i]); // cdf for bounds real u = uniform_rng(p, 1); - return (sigma * inv_Phi(u)) + mu; // inverse cdf for value + ret[i] = (sigma[i] * inv_Phi(u)) + mu[i]; // inverse cdf for value + } + return ret; } From 5c1fe7a43cb7cd963576582bd3018f85d8917d2b Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 22 Nov 2023 15:12:00 +0000 Subject: [PATCH 056/129] update touchstone arguments --- touchstone/script.R | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/touchstone/script.R b/touchstone/script.R index 604c8a0fe..5e4095d78 100644 --- a/touchstone/script.R +++ b/touchstone/script.R @@ -10,7 +10,7 @@ touchstone::benchmark_run( default = { epinow( reported_cases = reported_cases, generation_time = generation_time_opts(fixed_generation_time), - delays = fixed_delays, + delays = delay_opts(fixed_delays), rt = rt_opts(prior = list(mean = 2, sd = 0.2)), stan = stan_opts( cores = 2, samples = 500, chains = 2, @@ -39,7 +39,7 @@ touchstone::benchmark_run( # benchmark readme example without delays touchstone::benchmark_run( expr_before_benchmark = { source("touchstone/setup.R") }, - no_delays = { epinow( + delay_opts(no_delays) = { epinow( reported_cases = reported_cases, generation_time = generation_time_opts(fixed_generation_time), rt = rt_opts(prior = list(mean = 2, sd = 0.2)), @@ -57,7 +57,7 @@ touchstone::benchmark_run( stationary = { epinow( reported_cases = reported_cases, generation_time = generation_time_opts(fixed_generation_time), - delays = fixed_delays, + delays = delay_opts(fixed_delays), rt = rt_opts(prior = list(mean = 2, sd = 0.2), gp_on = "R0"), stan = stan_opts( cores = 2, samples = 500, chains = 2, @@ -73,7 +73,7 @@ touchstone::benchmark_run( random_walk = { epinow( reported_cases = reported_cases, generation_time = generation_time_opts(fixed_generation_time), - delays = fixed_delays, + delays = delay_opts(fixed_delays), rt = rt_opts(prior = list(mean = 2, sd = 0.2), rw = 7), gp = NULL, stan = stan_opts( From 65c86fa754162738606515901417971e614a9626 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 22 Nov 2023 15:22:01 +0000 Subject: [PATCH 057/129] linting --- R/adjust.R | 6 ++---- R/dist.R | 6 +++--- R/report.R | 2 +- 3 files changed, 6 insertions(+), 8 deletions(-) diff --git a/R/adjust.R b/R/adjust.R index 172bd4c1f..193f91153 100644 --- a/R/adjust.R +++ b/R/adjust.R @@ -148,12 +148,10 @@ adjust_infection_to_report <- function(infections, delay_defs, deprecate_warn( "2.0.0", "adjust_infection_to_report(delay_defs = 'should be a dist_spec')", - details = c( - "Specifying this as a list of data tables is deprecated." - ) + details = "Specifying this as a list of data tables is deprecated." ) report <- sample_single_dist(infections, delay_defs[[1]]) - if (length(delay_defs ) > 1) { + if (length(delay_defs) > 1) { for (def in 2:length(delay_defs)) { report <- sample_single_dist(report, delay_defs[[def]]) } diff --git a/R/dist.R b/R/dist.R index a9a008bae..64608f983 100644 --- a/R/dist.R +++ b/R/dist.R @@ -127,7 +127,7 @@ dist_skel <- function(n, dist = FALSE, cum = TRUE, model, plnorm(n, params[["meanlog"]], params[["sdlog"]])) / plnorm(max_value + 1, params[["meanlog"]], params[["sdlog"]]) } - } else if (model %in% "normal") { + } else if (model == "normal") { rdist <- function(n) { rnorm(n, params[["mean"]], params[["sd"]]) } @@ -909,7 +909,7 @@ dist_spec <- function(distribution = c( "dist_spec(fixed)", "fix_dist()" ) - params_sd <- c() + params_sd <- NULL } ## check for deprecated parameters if (!all(missing(mean), missing(sd), missing(mean_sd), missing(sd_sd)) && @@ -947,7 +947,7 @@ dist_spec <- function(distribution = c( params_sd <- c(mean = mean_sd, sd = sd_sd) } else if (distribution == "fixed") { params_mean <- mean - params_sd <- c() + params_sd <- NULL } } return(.dist_spec(distribution, params_mean, params_sd, max, pmf)) diff --git a/R/report.R b/R/report.R index 21ae87af0..a055118b1 100644 --- a/R/report.R +++ b/R/report.R @@ -201,7 +201,7 @@ report_summary <- function(summarised_estimates, } if (!is.null(target_folder)) { - saveRDS(summary, paste0(target_folder, "/summary.rds")) + saveRDS(summary, file.path(target_folder, "summary.rds")) } return(summary) } From 502ceb8e85311d4cb0f15473b784d39b24a10a03 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 22 Nov 2023 15:44:24 +0000 Subject: [PATCH 058/129] fix regex search/replace gone wrong --- touchstone/script.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/touchstone/script.R b/touchstone/script.R index 5e4095d78..4f3a85be1 100644 --- a/touchstone/script.R +++ b/touchstone/script.R @@ -39,7 +39,7 @@ touchstone::benchmark_run( # benchmark readme example without delays touchstone::benchmark_run( expr_before_benchmark = { source("touchstone/setup.R") }, - delay_opts(no_delays) = { epinow( + no_delays = { epinow( reported_cases = reported_cases, generation_time = generation_time_opts(fixed_generation_time), rt = rt_opts(prior = list(mean = 2, sd = 0.2)), From 7c72b0f1d2d9227bd56d8a69c43659dd42fb04aa Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Sun, 26 Nov 2023 21:04:50 +0000 Subject: [PATCH 059/129] remove obsolete space --- R/dist.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/dist.R b/R/dist.R index 64608f983..59589ca5f 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1020,7 +1020,7 @@ dist_spec <- function(distribution = c( "The meaning of the 'max' argument has changed compared to", "previous versions. It now indicates the maximum of a distribution", "rather than the length of the probability mass function (including 0)", - "that it represented previously. To replicate previous behaviour ", + "that it represented previously. To replicate previous behaviour", "reduce max by 1." ), .frequency = "regularly", From 88277c5251d15123d7752f17aa7f9318fe0b55a1 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Sun, 26 Nov 2023 21:04:59 +0000 Subject: [PATCH 060/129] update strategy for estimating uncertainty --- R/dist.R | 59 +++++++++++++++++---------------------- man/convert_to_natural.Rd | 6 ++-- 2 files changed, 28 insertions(+), 37 deletions(-) diff --git a/R/dist.R b/R/dist.R index 59589ca5f..02e13a8f4 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1862,27 +1862,18 @@ generate_dist_spec <- function(params, distribution) { } ## sample parameters if they are uncertain if (any(vapply(params, sd_dist, numeric(1)) > 0)) { - message( + warning( "Uncertain ", distribution, " distribution specified in terms of ", "parameters that are not the \"natural\" parameters of the ", "distribution (", toString(natural_params(distribution)), - "). Converting using a finite sample. If possible, it is preferable ", - "to specify the distribution direclty in terms of the natural ", - "parameters." + "). Converting using a crude and very approximate method ", + "that is likely to produce biased results. If possible, ", + "it is preferable to specify the distribution direclty ", + "in terms of the natural parameters." ) - samples <- lapply(names(params), function(x) { - rtruncnorm( - n = 2000, a = lower_bounds(distribution)[x], - mean = mean(params[[x]]), sd = sd_dist(params[[x]]) - ) - }) - names(samples) <- names(params) - } else { - samples <- lapply(params, mean) } - ## generate natural parameters - converted_params <- convert_to_natural(samples, distribution) + converted_params <- convert_to_natural(params, distribution) } else { converted_params <- list( params_mean = vapply(params, mean, numeric(1), USE.NAMES = FALSE), @@ -1910,30 +1901,30 @@ generate_dist_spec <- function(params, distribution) { ##' @return A list with two elements, `params_mean` and `params_sd`, containing ##' mean and sd of natural parameters. ##' @author Sebastian Funk -convert_to_natural <- function(x, distribution) { +convert_to_natural <- function(params, distribution) { + ## unnatural parameter means + ux <- lapply(params, mean) + ## estimate relative uncertainty of parameters + rel_unc <- mean(vapply(params, sd_dist, numeric(1)) / unlist(ux)) + ## store natural parameters + x <- list() if (distribution == "gamma") { - if ("mean" %in% names(x) && "sd" %in% names(x)) { - x$shape <- x$mean**2 / x$sd**2 - x$rate <- x$shape / x$mean - } else if (!("rate" %in% names(x)) && ("scale" %in% names(x))) { - x$rate <- 1 / x$scale + if ("mean" %in% names(ux) && "sd" %in% names(ux)) { + x$shape <- ux$mean**2 / ux$sd**2 + x$rate <- x$shape / ux$mean + } else if (!("rate" %in% names(means)) && ("scale" %in% names(means))) { + x$shape <- ux$shape + x$rate <- 1 / ux$scale } } else if (distribution == "lognormal" && - "mean" %in% names(x) && "sd" %in% names(x)) { - x$meanlog <- convert_to_logmean(x$mean, x$sd) - x$sdlog <- convert_to_logsd(x$mean, x$sd) + "mean" %in% names(params) && "sd" %in% names(params)) { + x$meanlog <- convert_to_logmean(ux$mean, ux$sd) + x$sdlog <- convert_to_logsd(ux$mean, ux$sd) } + natural_means <- unname(unlist(x[natural_params(distribution)])) params <- list( - params_mean = unname(vapply(natural_params(distribution), function(param) { - mean(x[[param]]) - }, numeric(1))), - params_sd = unname(vapply(natural_params(distribution), function(param) { - if (length(x[[param]]) == 1) { - 0 - } else { - sd(x[[param]]) - } - }, numeric(1))) + params_mean = natural_means, + params_sd = natural_means * rel_unc ) return(params) } diff --git a/man/convert_to_natural.Rd b/man/convert_to_natural.Rd index a6d8ea1b0..c2c33937e 100644 --- a/man/convert_to_natural.Rd +++ b/man/convert_to_natural.Rd @@ -4,12 +4,12 @@ \alias{convert_to_natural} \title{Internal function for converting parameters to natural parameters.} \usage{ -convert_to_natural(x, distribution) +convert_to_natural(params, distribution) } \arguments{ -\item{x}{A numerical named parameter vector} - \item{distribution}{Character; the distribution to use.} + +\item{x}{A numerical named parameter vector} } \value{ A list with two elements, \code{params_mean} and \code{params_sd}, containing From cac13ffa4a0d6ac9f92f95ee394e267fd41327ba Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Sun, 26 Nov 2023 21:38:53 +0000 Subject: [PATCH 061/129] update uncertain parameter transformations --- R/epinow.R | 4 ++-- R/estimate_infections.R | 4 ++-- vignettes/estimate_infections_workflow.Rmd.orig | 4 ++-- 3 files changed, 6 insertions(+), 6 deletions(-) diff --git a/R/epinow.R b/R/epinow.R index c49acf8c2..2b76b5a7e 100644 --- a/R/epinow.R +++ b/R/epinow.R @@ -45,8 +45,8 @@ #' # set an example generation time. In practice this should use an estimate #' # from the literature or be estimated from data #' generation_time <- gamma( -#' shape = normal(2, 2.6), -#' rate = normal(0.5, 0.6), +#' shape = normal(1.3, 0.3), +#' rate = normal(0.37, 0.09), #' max = 14 #' ) #' # set an example incubation period. In practice this should use an estimate diff --git a/R/estimate_infections.R b/R/estimate_infections.R index b42a15970..f94b9f72e 100644 --- a/R/estimate_infections.R +++ b/R/estimate_infections.R @@ -78,8 +78,8 @@ #' # set an example generation time. In practice this should use an estimate #' # from the literature or be estimated from data #' generation_time <- gamma( -#' shape = normal(2, 2.6), -#' rate = normal(0.5, 0.6), +#' shape = normal(1.3, 0.3), +#' rate = normal(0.37, 0.09), #' max = 14 #' ) #' # set an example incubation period. In practice this should use an estimate diff --git a/vignettes/estimate_infections_workflow.Rmd.orig b/vignettes/estimate_infections_workflow.Rmd.orig index f4ba771a8..04a408428 100644 --- a/vignettes/estimate_infections_workflow.Rmd.orig +++ b/vignettes/estimate_infections_workflow.Rmd.orig @@ -104,7 +104,7 @@ For example, to define the generation time as gamma distributed with uncertain m ```{r, results = 'hide'} generation_time <- gamma( - shape = normal(15, 15), rate = normal(3.5, 2), max = 10 + shape = normal(9, 3.4), rate = normal(3, 1.2), max = 10 ) generation_time_opts(generation_time) ``` @@ -121,7 +121,7 @@ In this case, we can combine multiple delays with the plus (`+`) operator, e.g. ```{r} incubation_period <- lognormal( meanlog = normal(1.6, 0.05), - sdlog = normal(0.5, 0.05), + sdlog = normal(0.5, 0.05), max = 14 ) reporting_delay <- lognormal(meanlog = 0.5, sdlog = 0.5, max = 10) From d91defd7b3770ff048a5a25ed5ebdf481e57275d Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Mon, 27 Nov 2023 09:13:08 +0000 Subject: [PATCH 062/129] add missing sd to parameter sampling --- R/dist.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/dist.R b/R/dist.R index 02e13a8f4..742fb55b5 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1608,7 +1608,7 @@ fix_dist <- function(x, strategy = c("mean", "sample")) { } else if (strategy == "sample") { lower_bound <- lower_bounds(x$dist)[natural_params(x$dist)] mean <- rtruncnorm( - n = 1, a = lower_bound, mean = x$params_mean + n = 1, a = lower_bound, mean = x$params_mean, sd = x$params_sd ) x <- .dist_spec( params_mean = mean, From e23ac3d9119ada26fe4b9e5ba01aa3b997402599 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Mon, 27 Nov 2023 09:13:23 +0000 Subject: [PATCH 063/129] update / recompile vignettes --- vignettes/epinow.Rmd | 99 ++++---- vignettes/estimate_infections_options.Rmd | 231 +++++++++--------- vignettes/estimate_infections_workflow.Rmd | 68 ++++-- .../estimate_infections_workflow.Rmd.orig | 2 +- vignettes/figure/bp-1.png | Bin 42719 -> 44013 bytes vignettes/figure/default-1.png | Bin 48810 -> 49021 bytes vignettes/figure/fixed-1.png | Bin 36895 -> 37263 bytes vignettes/figure/gp_projection-1.png | Bin 46983 -> 48741 bytes vignettes/figure/lower_accuracy-1.png | Bin 48613 -> 48893 bytes vignettes/figure/no_delays-1.png | Bin 45877 -> 46591 bytes vignettes/figure/nonparametric-1.png | Bin 47471 -> 47131 bytes vignettes/figure/regional_epinow-1.png | Bin 34002 -> 34223 bytes .../figure/regional_epinow_multiple-1.png | Bin 32874 -> 32084 bytes vignettes/figure/results-1.png | Bin 58167 -> 45952 bytes vignettes/figure/susceptible_depletion-1.png | Bin 48920 -> 49521 bytes vignettes/figure/truncation-1.png | Bin 48786 -> 4747 bytes vignettes/figure/weekly_rw-1.png | Bin 47743 -> 48164 bytes 17 files changed, 210 insertions(+), 190 deletions(-) diff --git a/vignettes/epinow.Rmd b/vignettes/epinow.Rmd index 2ad1c5bb0..9e3e683b1 100644 --- a/vignettes/epinow.Rmd +++ b/vignettes/epinow.Rmd @@ -30,10 +30,7 @@ This should be replaced with parameters relevant to the system that is being stu library("EpiNow2") options(mc.cores = 4) reported_cases <- example_confirmed[1:60] -reporting_delay <- dist_spec( - mean = convert_to_logmean(2, 1), mean_sd = 0, - sd = convert_to_logsd(2, 1), sd_sd = 0, max = 10 -) +reporting_delay <- lognormal(mean = 2, sd = 1, max = 10) delay <- example_incubation_period + reporting_delay rt_prior <- list(mean = 2, sd = 0.1) ``` @@ -49,13 +46,13 @@ res <- epinow(reported_cases, target_folder = "results" ) #> Logging threshold set at INFO for the EpiNow2 logger -#> Writing EpiNow2 logs to the console and: /tmp/RtmprzMMcb/regional-epinow/2020-04-21.log +#> Writing EpiNow2 logs to the console and: /tmp/RtmpyrNOVB/regional-epinow/2020-04-21.log #> Logging threshold set at INFO for the EpiNow2.epinow logger -#> Writing EpiNow2.epinow logs to the console and: /tmp/RtmprzMMcb/epinow/2020-04-21.log -#> WARN [2023-10-21 09:32:12] epinow: There were 17 divergent transitions after warmup. See +#> Writing EpiNow2.epinow logs to the console and: /tmp/RtmpyrNOVB/epinow/2020-04-21.log +#> WARN [2023-11-26 21:54:03] epinow: There were 13 divergent transitions after warmup. See #> https://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup #> to find out why this is a problem and how to eliminate them. - -#> WARN [2023-10-21 09:32:12] epinow: Examine the pairs() plot to diagnose sampling problems +#> WARN [2023-11-26 21:54:03] epinow: Examine the pairs() plot to diagnose sampling problems #> - res$plots$R #> NULL @@ -89,41 +86,41 @@ region_rt <- regional_epinow( delays = delay_opts(delay), rt = rt_opts(prior = rt_prior), ) -#> INFO [2023-10-21 09:32:19] Producing following optional outputs: regions, summary, samples, plots, latest +#> INFO [2023-11-26 21:54:10] Producing following optional outputs: regions, summary, samples, plots, latest #> Logging threshold set at INFO for the EpiNow2 logger -#> Writing EpiNow2 logs to the console and: /tmp/RtmprzMMcb/regional-epinow/2020-04-21.log +#> Writing EpiNow2 logs to the console and: /tmp/RtmpyrNOVB/regional-epinow/2020-04-21.log #> Logging threshold set at INFO for the EpiNow2.epinow logger -#> Writing EpiNow2.epinow logs to: /tmp/RtmprzMMcb/epinow/2020-04-21.log -#> INFO [2023-10-21 09:32:19] Reporting estimates using data up to: 2020-04-21 -#> INFO [2023-10-21 09:32:19] No target directory specified so returning output -#> INFO [2023-10-21 09:32:19] Producing estimates for: testland, realland -#> INFO [2023-10-21 09:32:19] Regions excluded: none -#> INFO [2023-10-21 09:33:56] Completed estimates for: testland -#> INFO [2023-10-21 09:35:26] Completed estimates for: realland -#> INFO [2023-10-21 09:35:26] Completed regional estimates -#> INFO [2023-10-21 09:35:26] Regions with estimates: 2 -#> INFO [2023-10-21 09:35:26] Regions with runtime errors: 0 -#> INFO [2023-10-21 09:35:26] Producing summary -#> INFO [2023-10-21 09:35:26] No summary directory specified so returning summary output -#> INFO [2023-10-21 09:35:26] No target directory specified so returning timings +#> Writing EpiNow2.epinow logs to: /tmp/RtmpyrNOVB/epinow/2020-04-21.log +#> INFO [2023-11-26 21:54:10] Reporting estimates using data up to: 2020-04-21 +#> INFO [2023-11-26 21:54:10] No target directory specified so returning output +#> INFO [2023-11-26 21:54:10] Producing estimates for: testland, realland +#> INFO [2023-11-26 21:54:10] Regions excluded: none +#> INFO [2023-11-26 21:59:54] Completed estimates for: testland +#> INFO [2023-11-26 22:33:35] Completed estimates for: realland +#> INFO [2023-11-26 22:33:35] Completed regional estimates +#> INFO [2023-11-26 22:33:35] Regions with estimates: 2 +#> INFO [2023-11-26 22:33:35] Regions with runtime errors: 0 +#> INFO [2023-11-26 22:33:35] Producing summary +#> INFO [2023-11-26 22:33:35] No summary directory specified so returning summary output +#> INFO [2023-11-26 22:33:36] No target directory specified so returning timings ## summary region_rt$summary$summarised_results$table #> Region New confirmed cases by infection date -#> 1: realland 2119 (876 -- 4309) -#> 2: testland 2082 (823 -- 4219) +#> 1: realland 2512 (968 -- 18904) +#> 2: testland 2027 (817 -- 4043) #> Expected change in daily cases Effective reproduction no. -#> 1: Likely decreasing 0.89 (0.61 -- 1.2) -#> 2: Likely decreasing 0.88 (0.6 -- 1.2) +#> 1: Stable 0.95 (0.63 -- 1.5) +#> 2: Likely decreasing 0.87 (0.6 -- 1.1) #> Rate of growth Doubling/halving time (days) -#> 1: -0.033 (-0.14 -- 0.041) -21 (17 -- -5.1) -#> 2: -0.035 (-0.14 -- 0.04) -20 (17 -- -5) +#> 1: -0.016 (-0.12 -- 0.042) -44 (17 -- -5.6) +#> 2: -0.038 (-0.14 -- 0.036) -18 (19 -- -4.9) ## plot region_rt$summary$plots$R ``` ![plot of chunk regional_epinow](figure/regional_epinow-1.png) -If instead, we wanted to use the Gaussian Process for `testland` and a weekly random walk for `realland` we could specify these separately using the `opts_list()` from the package and `modifyList()` from `R`. +If instead, we wanted to use the Gaussian Process for `testland` and a weekly random walk for `realland` we could specify these separately using the `opts_list()` function from the package and `modifyList()` from `R`. ```r @@ -136,34 +133,34 @@ region_separate_rt <- regional_epinow( delays = delay_opts(delay), rt = rt, gp = gp, ) -#> INFO [2023-10-21 09:35:27] Producing following optional outputs: regions, summary, samples, plots, latest +#> INFO [2023-11-26 22:33:36] Producing following optional outputs: regions, summary, samples, plots, latest #> Logging threshold set at INFO for the EpiNow2 logger -#> Writing EpiNow2 logs to the console and: /tmp/RtmprzMMcb/regional-epinow/2020-04-21.log +#> Writing EpiNow2 logs to the console and: /tmp/RtmpyrNOVB/regional-epinow/2020-04-21.log #> Logging threshold set at INFO for the EpiNow2.epinow logger -#> Writing EpiNow2.epinow logs to: /tmp/RtmprzMMcb/epinow/2020-04-21.log -#> INFO [2023-10-21 09:35:27] Reporting estimates using data up to: 2020-04-21 -#> INFO [2023-10-21 09:35:27] No target directory specified so returning output -#> INFO [2023-10-21 09:35:27] Producing estimates for: testland, realland -#> INFO [2023-10-21 09:35:27] Regions excluded: none -#> INFO [2023-10-21 09:37:00] Completed estimates for: testland -#> INFO [2023-10-21 09:37:36] Completed estimates for: realland -#> INFO [2023-10-21 09:37:36] Completed regional estimates -#> INFO [2023-10-21 09:37:36] Regions with estimates: 2 -#> INFO [2023-10-21 09:37:36] Regions with runtime errors: 0 -#> INFO [2023-10-21 09:37:36] Producing summary -#> INFO [2023-10-21 09:37:36] No summary directory specified so returning summary output -#> INFO [2023-10-21 09:37:36] No target directory specified so returning timings +#> Writing EpiNow2.epinow logs to: /tmp/RtmpyrNOVB/epinow/2020-04-21.log +#> INFO [2023-11-26 22:33:36] Reporting estimates using data up to: 2020-04-21 +#> INFO [2023-11-26 22:33:36] No target directory specified so returning output +#> INFO [2023-11-26 22:33:36] Producing estimates for: testland, realland +#> INFO [2023-11-26 22:33:36] Regions excluded: none +#> INFO [2023-11-26 22:39:48] Completed estimates for: testland +#> INFO [2023-11-26 22:40:44] Completed estimates for: realland +#> INFO [2023-11-26 22:40:44] Completed regional estimates +#> INFO [2023-11-26 22:40:44] Regions with estimates: 2 +#> INFO [2023-11-26 22:40:44] Regions with runtime errors: 0 +#> INFO [2023-11-26 22:40:44] Producing summary +#> INFO [2023-11-26 22:40:44] No summary directory specified so returning summary output +#> INFO [2023-11-26 22:40:45] No target directory specified so returning timings ## summary region_separate_rt$summary$summarised_results$table #> Region New confirmed cases by infection date -#> 1: realland 2013 (953 -- 4182) -#> 2: testland 2052 (855 -- 4277) +#> 1: realland 2027 (1002 -- 3958) +#> 2: testland 2100 (841 -- 4030) #> Expected change in daily cases Effective reproduction no. -#> 1: Likely decreasing 0.88 (0.66 -- 1.2) -#> 2: Likely decreasing 0.88 (0.6 -- 1.2) +#> 1: Likely decreasing 0.89 (0.67 -- 1.1) +#> 2: Likely decreasing 0.88 (0.59 -- 1.1) #> Rate of growth Doubling/halving time (days) -#> 1: -0.035 (-0.12 -- 0.04) -20 (17 -- -6) -#> 2: -0.036 (-0.14 -- 0.045) -19 (16 -- -5) +#> 1: -0.035 (-0.11 -- 0.035) -20 (20 -- -6.4) +#> 2: -0.034 (-0.14 -- 0.037) -20 (19 -- -4.9) ## plot region_separate_rt$summary$plots$R ``` diff --git a/vignettes/estimate_infections_options.Rmd b/vignettes/estimate_infections_options.Rmd index 3c5f6cc59..11aa9459e 100644 --- a/vignettes/estimate_infections_options.Rmd +++ b/vignettes/estimate_infections_options.Rmd @@ -26,10 +26,15 @@ We first load the _EpiNow2_ package and also the _rstan_ package that we will us ```r library("EpiNow2") +#> +#> Attaching package: 'EpiNow2' +#> The following object is masked from 'package:base': +#> +#> gamma library("rstan") #> Loading required package: StanHeaders #> -#> rstan version 2.33.1.9000 (Stan version 2.33.0) +#> rstan version 2.32.3 (Stan version 2.26.1) #> For execution on a local, multicore CPU with excess RAM we recommend calling #> options(mc.cores = parallel::detectCores()). #> To avoid recompilation of unchanged Stan programs, we recommend calling @@ -75,7 +80,7 @@ Delays reflect the time that passes between infection and reporting, if these ex ```r example_incubation_period #> -#> Uncertain lognormal distribution with (untruncated) logmean 1.6 (SD 0.064) and logSD 0.42 (SD 0.069) +#> lognormal distribution (max: 14) with uncertain meanlog (mean = 1.6, sd = 0.064) and uncertain sdlog (mean = 0.42, sd = 0.069). ``` For the reporting delay, we use a lognormal distribution with mean of 2 days and standard deviation of 1 day. @@ -83,15 +88,12 @@ Note that the mean and standard deviation must be converted to the log scale, wh ```r -reporting_delay <- dist_spec( - mean = convert_to_logmean(2, 1), mean_sd = 0, - sd = convert_to_logsd(2, 1), sd_sd = 0, max = 10 -) +reporting_delay <- lognormal(mean = 2, sd = 1, max = 10) #> Warning: The meaning of the 'max' argument has changed compared to previous versions. It now indicates the maximum of a distribution rather than the length of the probability mass function (including 0) that it represented previously. To replicate previous behaviour reduce max by 1. #> This warning is displayed once every 8 hours. reporting_delay #> -#> Fixed distribution with PMF [0.11 0.48 0.27 0.093 0.029 0.0096 0.0033 0.0012 0.00045 0.00018 7.4e-05] +#> distribution with PMF [0.11 0.48 0.27 0.093 0.029 0.0096 0.0033 0.0012 0.00045 0.00018 7.4e-05]. ``` _EpiNow2_ provides a feature that allows us to combine these delays into one by summing them up @@ -101,9 +103,9 @@ _EpiNow2_ provides a feature that allows us to combine these delays into one by delay <- example_incubation_period + reporting_delay delay #> -#> Combination of delay distributions: -#> Uncertain lognormal distribution with (untruncated) logmean 1.6 (SD 0.064) and logSD 0.42 (SD 0.069) -#> Fixed distribution with PMF [0.11 0.48 0.27 0.093 0.029 0.0096 0.0033 0.0012 0.00045 0.00018 7.4e-05] +#> Composite delay distribution: +#> lognormal distribution (max: 14) with uncertain meanlog (mean = 1.6, sd = 0.064) and uncertain sdlog (mean = 0.42, sd = 0.069). +#> distribution with PMF [0.11 0.48 0.27 0.093 0.029 0.0096 0.0033 0.0012 0.00045 0.00018 7.4e-05]. ``` ## Generation time @@ -114,7 +116,7 @@ If we want to estimate the reproduction number we need to provide a distribution ```r example_generation_time #> -#> Uncertain gamma distribution with (untruncated) mean 3.6 (SD 0.71) and SD 3.1 (SD 0.77) +#> gamma distribution (max: 14) with uncertain shape (mean = 1.9, sd = 2.2) and uncertain rate (mean = 0.51, sd = 0.54). ``` ## Initial reproduction number @@ -142,25 +144,25 @@ def <- estimate_infections(reported_cases, delays = delay_opts(delay), rt = rt_opts(prior = rt_prior) ) -#> Warning: There were 7 divergent transitions after warmup. See +#> Warning: There were 6 divergent transitions after warmup. See #> https://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup #> to find out why this is a problem and how to eliminate them. #> Warning: Examine the pairs() plot to diagnose sampling problems # summarise results summary(def) -#> measure estimate -#> 1: New confirmed cases by infection date 2326 (1160 -- 4361) -#> 2: Expected change in daily cases Likely decreasing -#> 3: Effective reproduction no. 0.89 (0.62 -- 1.2) -#> 4: Rate of growth -0.024 (-0.094 -- 0.036) -#> 5: Doubling/halving time (days) -29 (19 -- -7.4) +#> measure estimate +#> 1: New confirmed cases by infection date 2195 (1030 -- 4199) +#> 2: Expected change in daily cases Likely decreasing +#> 3: Effective reproduction no. 0.88 (0.6 -- 1.2) +#> 4: Rate of growth -0.03 (-0.11 -- 0.036) +#> 5: Doubling/halving time (days) -23 (19 -- -6.3) # elapsed time (in seconds) get_elapsed_time(def$fit) #> warmup sample -#> chain:1 33.573 24.459 -#> chain:2 27.082 34.938 -#> chain:3 34.183 24.497 -#> chain:4 30.027 31.835 +#> chain:1 32.869 31.472 +#> chain:2 34.072 48.232 +#> chain:3 24.531 41.905 +#> chain:4 40.197 24.689 # summary plot plot(def) ``` @@ -179,25 +181,25 @@ agp <- estimate_infections(reported_cases, rt = rt_opts(prior = rt_prior), gp = gp_opts(basis_prop = 0.1) ) -#> Warning: There were 8 divergent transitions after warmup. See +#> Warning: There were 9 divergent transitions after warmup. See #> https://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup #> to find out why this is a problem and how to eliminate them. #> Warning: Examine the pairs() plot to diagnose sampling problems # summarise results summary(agp) #> measure estimate -#> 1: New confirmed cases by infection date 2343 (1188 -- 4363) +#> 1: New confirmed cases by infection date 2321 (1151 -- 4351) #> 2: Expected change in daily cases Likely decreasing -#> 3: Effective reproduction no. 0.89 (0.63 -- 1.2) -#> 4: Rate of growth -0.024 (-0.091 -- 0.039) -#> 5: Doubling/halving time (days) -29 (18 -- -7.6) +#> 3: Effective reproduction no. 0.89 (0.64 -- 1.2) +#> 4: Rate of growth -0.025 (-0.095 -- 0.036) +#> 5: Doubling/halving time (days) -27 (19 -- -7.3) # elapsed time (in seconds) get_elapsed_time(agp$fit) #> warmup sample -#> chain:1 23.392 23.266 -#> chain:2 18.817 23.019 -#> chain:3 19.906 23.454 -#> chain:4 27.043 23.983 +#> chain:1 21.334 23.803 +#> chain:2 20.714 28.792 +#> chain:3 27.059 44.721 +#> chain:4 24.691 28.737 # summary plot plot(agp) ``` @@ -220,25 +222,25 @@ dep <- estimate_infections(reported_cases, pop = 1000000, future = "latest" ) ) -#> Warning: There were 14 divergent transitions after warmup. See +#> Warning: There were 5 divergent transitions after warmup. See #> https://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup #> to find out why this is a problem and how to eliminate them. #> Warning: Examine the pairs() plot to diagnose sampling problems # summarise results summary(dep) -#> measure estimate -#> 1: New confirmed cases by infection date 2275 (1141 -- 4324) -#> 2: Expected change in daily cases Likely decreasing -#> 3: Effective reproduction no. 0.88 (0.62 -- 1.2) -#> 4: Rate of growth -0.027 (-0.096 -- 0.036) -#> 5: Doubling/halving time (days) -26 (19 -- -7.2) +#> measure estimate +#> 1: New confirmed cases by infection date 2239 (1081 -- 4334) +#> 2: Expected change in daily cases Likely decreasing +#> 3: Effective reproduction no. 0.89 (0.62 -- 1.2) +#> 4: Rate of growth -0.027 (-0.1 -- 0.037) +#> 5: Doubling/halving time (days) -26 (19 -- -6.7) # elapsed time (in seconds) get_elapsed_time(dep$fit) #> warmup sample -#> chain:1 30.522 24.801 -#> chain:2 29.964 24.931 -#> chain:3 33.582 25.698 -#> chain:4 27.050 25.586 +#> chain:1 44.769 36.097 +#> chain:2 35.531 47.282 +#> chain:3 44.366 39.752 +#> chain:4 33.220 44.781 # summary plot plot(dep) ``` @@ -252,11 +254,20 @@ Here, instead of doing so we assume that we know about truncation with mean of 1 ```r -trunc_dist <- dist_spec( - mean = convert_to_logmean(0.5, 0.5), mean_sd = 0.1, - sd = convert_to_logsd(0.5, 0.5), sd_sd = 0.1, +trunc_dist <- lognormal( + mean = normal(0.5, 0.1), + sd = normal(0.5, 0.1), max = 3 ) +#> Warning in generate_dist_spec(params, "lognormal"): Uncertain lognormal +#> distribution specified in terms of parameters that are not the "natural" +#> parameters of the distribution (meanlog, sdlog). Converting using a crude and +#> very approximate method that is likely to produce biased results. If possible, +#> it is preferable to specify the distribution direclty in terms of the natural +#> parameters. +trunc_dist +#> +#> lognormal distribution (max: 3) with meanlog = -1 and uncertain sdlog (mean = 0.83, sd = 0.17). ``` We can then use this in the `esimtate_infections()` function using the `truncation` option. @@ -269,25 +280,17 @@ trunc <- estimate_infections(reported_cases, truncation = trunc_opts(trunc_dist), rt = rt_opts(prior = rt_prior) ) -#> Warning: There were 6 divergent transitions after warmup. See -#> https://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup -#> to find out why this is a problem and how to eliminate them. -#> Warning: Examine the pairs() plot to diagnose sampling problems +#> Error in eval(expr, envir, enclos) : +#> Exception: model_estimate_infections_namespace::model_estimate_infections: delay_params_sd[sym1__] is -0.207944, but must be greater than or equal to 0 (in 'estimate_infections', line 625, column 2 to column 57) +#> failed to create the sampler; sampling not done +#> Error in `fit_model_with_nuts()`: +#> ! model fitting was timed out or failed # summarise results summary(trunc) -#> measure estimate -#> 1: New confirmed cases by infection date 2477 (1311 -- 4653) -#> 2: Expected change in daily cases Likely decreasing -#> 3: Effective reproduction no. 0.91 (0.65 -- 1.2) -#> 4: Rate of growth -0.02 (-0.085 -- 0.044) -#> 5: Doubling/halving time (days) -34 (16 -- -8.2) +#> Error in object[[i]]: object of type 'builtin' is not subsettable # elapsed time (in seconds) get_elapsed_time(trunc$fit) -#> warmup sample -#> chain:1 32.951 25.092 -#> chain:2 33.920 25.699 -#> chain:3 31.455 46.192 -#> chain:4 27.765 26.048 +#> Error in (function (cond) : error in evaluating the argument 'object' in selecting a method for function 'get_elapsed_time': object of type 'builtin' is not subsettable # summary plot plot(trunc) ``` @@ -308,25 +311,25 @@ project_rt <- estimate_infections(reported_cases, prior = rt_prior, future = "project" ) ) -#> Warning: There were 4 divergent transitions after warmup. See +#> Warning: There were 18 divergent transitions after warmup. See #> https://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup #> to find out why this is a problem and how to eliminate them. #> Warning: Examine the pairs() plot to diagnose sampling problems # summarise results summary(project_rt) -#> measure estimate -#> 1: New confirmed cases by infection date 2246 (1150 -- 4539) -#> 2: Expected change in daily cases Likely decreasing -#> 3: Effective reproduction no. 0.87 (0.62 -- 1.2) -#> 4: Rate of growth -0.028 (-0.096 -- 0.042) -#> 5: Doubling/halving time (days) -24 (16 -- -7.2) +#> measure estimate +#> 1: New confirmed cases by infection date 2288 (1037 -- 4391) +#> 2: Expected change in daily cases Likely decreasing +#> 3: Effective reproduction no. 0.89 (0.6 -- 1.2) +#> 4: Rate of growth -0.025 (-0.11 -- 0.04) +#> 5: Doubling/halving time (days) -27 (17 -- -6.5) # elapsed time (in seconds) get_elapsed_time(project_rt$fit) #> warmup sample -#> chain:1 28.858 24.636 -#> chain:2 36.509 47.931 -#> chain:3 32.023 47.087 -#> chain:4 34.074 27.767 +#> chain:1 27.493 41.460 +#> chain:2 35.221 43.828 +#> chain:3 37.618 45.411 +#> chain:4 29.761 35.035 # summary plot plot(project_rt) ``` @@ -346,19 +349,19 @@ fixed <- estimate_infections(reported_cases, ) # summarise results summary(fixed) -#> measure estimate -#> 1: New confirmed cases by infection date 15737 (8930 -- 29454) -#> 2: Expected change in daily cases Increasing -#> 3: Effective reproduction no. 1.2 (1.1 -- 1.3) -#> 4: Rate of growth 0.038 (0.026 -- 0.05) -#> 5: Doubling/halving time (days) 18 (14 -- 27) +#> measure estimate +#> 1: New confirmed cases by infection date 15523 (9069 -- 27937) +#> 2: Expected change in daily cases Increasing +#> 3: Effective reproduction no. 1.2 (1.1 -- 1.3) +#> 4: Rate of growth 0.037 (0.026 -- 0.049) +#> 5: Doubling/halving time (days) 19 (14 -- 27) # elapsed time (in seconds) get_elapsed_time(fixed$fit) #> warmup sample -#> chain:1 2.091 1.127 -#> chain:2 1.884 0.847 -#> chain:3 1.912 0.981 -#> chain:4 1.857 0.900 +#> chain:1 1.608 1.265 +#> chain:2 2.014 1.249 +#> chain:3 1.342 1.265 +#> chain:4 1.299 1.256 # summary plot plot(fixed) ``` @@ -392,18 +395,18 @@ bkp <- estimate_infections(bp_cases, # summarise results summary(bkp) #> measure estimate -#> 1: New confirmed cases by infection date 2468 (2035 -- 2968) +#> 1: New confirmed cases by infection date 2583 (2137 -- 3103) #> 2: Expected change in daily cases Decreasing -#> 3: Effective reproduction no. 0.91 (0.88 -- 0.93) -#> 4: Rate of growth -0.021 (-0.026 -- -0.015) -#> 5: Doubling/halving time (days) -34 (-46 -- -27) +#> 3: Effective reproduction no. 0.9 (0.88 -- 0.93) +#> 4: Rate of growth -0.019 (-0.025 -- -0.013) +#> 5: Doubling/halving time (days) -37 (-51 -- -28) # elapsed time (in seconds) get_elapsed_time(bkp$fit) #> warmup sample -#> chain:1 3.115 2.705 -#> chain:2 2.910 2.433 -#> chain:3 3.695 2.271 -#> chain:4 3.683 2.654 +#> chain:1 3.664 5.156 +#> chain:2 7.443 4.758 +#> chain:3 3.086 4.164 +#> chain:4 3.292 4.891 # summary plot plot(bkp) ``` @@ -426,18 +429,18 @@ rw <- estimate_infections(reported_cases, # summarise results summary(rw) #> measure estimate -#> 1: New confirmed cases by infection date 2168 (1146 -- 4136) +#> 1: New confirmed cases by infection date 2099 (1090 -- 4011) #> 2: Expected change in daily cases Likely decreasing -#> 3: Effective reproduction no. 0.86 (0.63 -- 1.2) -#> 4: Rate of growth -0.031 (-0.091 -- 0.031) -#> 5: Doubling/halving time (days) -22 (22 -- -7.6) +#> 3: Effective reproduction no. 0.87 (0.65 -- 1.1) +#> 4: Rate of growth -0.034 (-0.098 -- 0.028) +#> 5: Doubling/halving time (days) -21 (24 -- -7.1) # elapsed time (in seconds) get_elapsed_time(rw$fit) #> warmup sample -#> chain:1 7.324 9.414 -#> chain:2 9.205 9.808 -#> chain:3 8.057 10.079 -#> chain:4 6.632 7.324 +#> chain:1 7.740 10.294 +#> chain:2 7.820 16.408 +#> chain:3 14.642 10.039 +#> chain:4 8.099 9.983 # summary plot plot(rw) ``` @@ -454,25 +457,25 @@ no_delay <- estimate_infections( reported_cases, generation_time = generation_time_opts(example_generation_time) ) -#> Warning: There were 5 divergent transitions after warmup. See +#> Warning: There were 6 divergent transitions after warmup. See #> https://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup #> to find out why this is a problem and how to eliminate them. #> Warning: Examine the pairs() plot to diagnose sampling problems # summarise results summary(no_delay) #> measure estimate -#> 1: New confirmed cases by infection date 2790 (2313 -- 3329) +#> 1: New confirmed cases by infection date 2760 (2330 -- 3322) #> 2: Expected change in daily cases Decreasing -#> 3: Effective reproduction no. 0.88 (0.76 -- 0.99) -#> 4: Rate of growth -0.026 (-0.055 -- -0.0022) -#> 5: Doubling/halving time (days) -26 (-320 -- -13) +#> 3: Effective reproduction no. 0.89 (0.78 -- 0.99) +#> 4: Rate of growth -0.028 (-0.057 -- -0.0017) +#> 5: Doubling/halving time (days) -25 (-420 -- -12) # elapsed time (in seconds) get_elapsed_time(no_delay$fit) #> warmup sample -#> chain:1 42.446 68.684 -#> chain:2 32.455 34.207 -#> chain:3 42.812 62.019 -#> chain:4 28.186 37.280 +#> chain:1 40.797 40.306 +#> chain:2 38.682 40.881 +#> chain:3 41.781 79.174 +#> chain:4 40.010 46.899 # summary plot plot(no_delay) ``` @@ -498,18 +501,18 @@ non_parametric <- estimate_infections(reported_cases, # summarise results summary(non_parametric) #> measure estimate -#> 1: New confirmed cases by infection date 2361 (1808 -- 3074) +#> 1: New confirmed cases by infection date 2384 (1820 -- 3047) #> 2: Expected change in daily cases Decreasing -#> 3: Effective reproduction no. 0.9 (0.8 -- 0.99) -#> 4: Rate of growth -0.023 (-0.045 -- -0.0014) -#> 5: Doubling/halving time (days) -30 (-510 -- -15) +#> 3: Effective reproduction no. 0.91 (0.69 -- 0.99) +#> 4: Rate of growth -0.021 (-0.044 -- -0.0026) +#> 5: Doubling/halving time (days) -33 (-260 -- -16) # elapsed time (in seconds) get_elapsed_time(non_parametric$fit) #> warmup sample -#> chain:1 2.811 0.823 -#> chain:2 2.688 0.784 -#> chain:3 3.013 0.826 -#> chain:4 3.280 0.805 +#> chain:1 3.023 0.869 +#> chain:2 2.883 0.882 +#> chain:3 2.803 0.844 +#> chain:4 2.471 0.874 # summary plot plot(non_parametric) ``` diff --git a/vignettes/estimate_infections_workflow.Rmd b/vignettes/estimate_infections_workflow.Rmd index d3765c4f9..6a47f51aa 100644 --- a/vignettes/estimate_infections_workflow.Rmd +++ b/vignettes/estimate_infections_workflow.Rmd @@ -69,12 +69,12 @@ As these will affect any results, it is worth spending some time investigating w ## Delay distributions _EpiNow2_ works with different delays that apply to different parts of the infection and observation process. -They are defined using a common interface with the `dist_spec()` function. +They are defined using a common interface that involves functions that are named after the probability distributions, i.e. `lognormal()`, `gamma()`, etc. For help with this function, see its manual page ```r -?EpiNow2::dist_spec +?EpiNow2::Distributions ``` In all cases, the distributions given can be *fixed* (i.e. have no uncertainty) or *variable* (i.e. have associated uncertainty). @@ -82,9 +82,11 @@ For example, to define a fixed gamma distribution with mean 3, standard deviatio ```r -dist_spec(mean = 3, sd = 1, distribution = "gamma", max = 10) +gamma(mean = 3, sd = 1, max = 10) +#> Warning: The meaning of the 'max' argument has changed compared to previous versions. It now indicates the maximum of a distribution rather than the length of the probability mass function (including 0) that it represented previously. To replicate previous behaviour reduce max by 1. +#> This warning is displayed once every 8 hours. #> -#> Fixed distribution with PMF [0.0038 0.15 0.39 0.3 0.12 0.03 0.006 0.00096 0.00013 1.6e-05 1.8e-06] +#> distribution with PMF [0.0038 0.15 0.39 0.3 0.12 0.03 0.006 0.00096 0.00013 1.6e-05 1.8e-06]. ``` If distributions are variable, the values with uncertainty are treated as [prior probability densities](https://en.wikipedia.org/wiki/Prior_probability) in the Bayesian inference framework used by _EpiNow2_, i.e. they are estimated as part of the inference. @@ -92,13 +94,19 @@ For example, to define a variable gamma distribution where uncertainty in the me ```r -dist_spec( - mean = 3, mean_sd = 2, sd = 1, sd_sd = 0.1, distribution = "gamma", max = 10 -) +gamma(mean = normal(3, 2), sd = normal(1, 0.1), max = 10) +#> Warning in generate_dist_spec(params, "gamma"): Uncertain gamma distribution +#> specified in terms of parameters that are not the "natural" parameters of the +#> distribution (shape, rate). Converting using a crude and very approximate +#> method that is likely to produce biased results. If possible, it is preferable +#> to specify the distribution direclty in terms of the natural parameters. #> -#> Uncertain gamma distribution with (untruncated) mean 3 (SD 2) and SD 1 (SD 0.1) +#> gamma distribution (max: 10) with uncertain shape (mean = 9, sd = 3.4) and uncertain rate (mean = 3, sd = 1.2). ``` +Note the warning about parameters. +We used the mean and standard deviation to define this distribution with uncertain parameters, but it would be better to use the "natural" parameters of the gamma distribution, shape and rate, for example using the values estimate and reported back after calling the previous command. + There are various ways the specific delay distributions mentioned below might be obtained. Often, they will come directly from the existing literature reviewed by the user and studies conducted elsewhere. Sometimes it might be possible to obtain them from existing databases, e.g. using the [epiparameter](https://github.com/epiverse-trace/epiparameter) R package. @@ -109,13 +117,13 @@ For a more comprehensive treatment of delays and their estimation avoiding commo ### Generation intervals The generation interval is a delay distribution that describes the amount of time that passes between an individual becoming infected and infecting someone else. -In _EpiNow2_, the generation time distribution is defined by a call to `generation_time_opts()`, a function that takes a single argument defined as a `dist_spec` object (returned by `dist_spec()`). -For example, to define the generation time as gamma distributed with uncertain mean centered on 3 (sd: 2) and sd centered on 1 (sd: 0.1), a maximum value of 10 and weighted by the number of case data points we would use +In _EpiNow2_, the generation time distribution is defined by a call to `generation_time_opts()`, a function that takes a single argument defined as a `dist_spec` object (returned by the function corresponding to the probability distribution, i.e. `lognormal()`, `gamma()`, etc.). +For example, to define the generation time as gamma distributed with uncertain mean centered on 3 and sd centered on 1 with some uncertainty, a maximum value of 10 and weighted by the number of case data points we could use the shape and rate parameters suggested above (though notes that this will only very approximately produce the uncertainty in mean and standard deviation stated there): ```r -generation_time <- dist_spec( - mean = 3, mean_sd = 2, sd = 1, sd_sd = 0.1, distribution = "gamma", max = 10 +generation_time <- gamma( + shape = normal(9, 3.4), rate = normal(3, 1.2), max = 10 ) generation_time_opts(generation_time) ``` @@ -127,25 +135,24 @@ Usually this is not observed directly. Instead, we calculate case counts based on, for example, onset of symptoms, lab confirmations, hospitalisations, etc. In order to estimate the trajectory of infection incidence from this we need to either know or estimate the distribution of delays from infection to count. Often, such counts are composed of multiple delays for which we only have separate information, for example the incubation period (time from infection to symptom onset) and reporting delay (time from symptom onset to being a case in the data, e.g. via lab confirmation, if counts are not by the date of symptom onset). -In this case, we can combine multiple delays defined using `dist_spec()` with the plus (`+`) operator, e.g. +In this case, we can combine multiple delays with the plus (`+`) operator, e.g. ```r -incubation_period <- dist_spec( - mean = 1.6, mean_sd = 0.05, sd = 0.5, sd_sd = 0.05, - distribution = "lognormal", max = 14 -) -reporting_delay <- dist_spec( - mean = 0.5, sd = 0.5, distribution = "lognormal", max = 10 +incubation_period <- lognormal( + meanlog = normal(1.6, 0.05), + sdlog = normal(0.5, 0.05), + max = 14 ) +reporting_delay <- lognormal(meanlog = 0.5, sdlog = 0.5, max = 10) incubation_period + reporting_delay #> -#> Combination of delay distributions: -#> Uncertain lognormal distribution with (untruncated) logmean 1.6 (SD 0.05) and logSD 0.5 (SD 0.05) -#> Fixed distribution with PMF [0.16 0.49 0.23 0.077 0.025 0.0084 0.003 0.0011 0.00045 0.00019 8.2e-05] +#> Composite delay distribution: +#> lognormal distribution (max: 14) with uncertain meanlog (mean = 1.6, sd = 0.05) and uncertain sdlog (mean = 0.5, sd = 0.05). +#> distribution with PMF [0.16 0.49 0.23 0.077 0.025 0.0084 0.003 0.0011 0.00045 0.00019 8.2e-05]. ``` -In _EpiNow2_, the reporting delay distribution is defined by a call to `delay_opts()`, a function that takes a single argument defined as a `dist_spec` object (returned by `dist_spec()`). +In _EpiNow2_, the reporting delay distribution is defined by a call to `delay_opts()`, a function that takes a single argument defined as a `dist_spec` object (returned by `lognormal()`, `gamma()` etc.). For example, if our observations were by symptom onset we would use @@ -230,10 +237,23 @@ def <- estimate_infections( delays = delay_opts(delay), rt = rt_opts(prior = rt_prior) ) -#> Warning: There were 15 divergent transitions after warmup. See +#> Warning: There were 3 divergent transitions after warmup. See #> https://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup #> to find out why this is a problem and how to eliminate them. +#> Warning: There were 1000 transitions after warmup that exceeded the maximum treedepth. Increase max_treedepth above 15. See +#> https://mc-stan.org/misc/warnings.html#maximum-treedepth-exceeded +#> Warning: There were 1 chains where the estimated Bayesian Fraction of Missing Information was low. See +#> https://mc-stan.org/misc/warnings.html#bfmi-low #> Warning: Examine the pairs() plot to diagnose sampling problems +#> Warning: The largest R-hat is NA, indicating chains have not mixed. +#> Running the chains for more iterations may help. See +#> https://mc-stan.org/misc/warnings.html#r-hat +#> Warning: Bulk Effective Samples Size (ESS) is too low, indicating posterior means and medians may be unreliable. +#> Running the chains for more iterations may help. See +#> https://mc-stan.org/misc/warnings.html#bulk-ess +#> Warning: Tail Effective Samples Size (ESS) is too low, indicating posterior variances and tail quantiles may be unreliable. +#> Running the chains for more iterations may help. See +#> https://mc-stan.org/misc/warnings.html#tail-ess ``` Alternatively, for production environments, we recommend using the `epinow()` function. It uses `estimate_infections()` internally and provides functionality for logging and saving results and plots in dedicated directories in the user's file system. diff --git a/vignettes/estimate_infections_workflow.Rmd.orig b/vignettes/estimate_infections_workflow.Rmd.orig index 04a408428..0697b6506 100644 --- a/vignettes/estimate_infections_workflow.Rmd.orig +++ b/vignettes/estimate_infections_workflow.Rmd.orig @@ -100,7 +100,7 @@ For a more comprehensive treatment of delays and their estimation avoiding commo The generation interval is a delay distribution that describes the amount of time that passes between an individual becoming infected and infecting someone else. In _EpiNow2_, the generation time distribution is defined by a call to `generation_time_opts()`, a function that takes a single argument defined as a `dist_spec` object (returned by the function corresponding to the probability distribution, i.e. `lognormal()`, `gamma()`, etc.). -For example, to define the generation time as gamma distributed with uncertain mean centered on 3 (sd: 2) and sd centered on 1 (sd: 0.1), a maximum value of 10 and weighted by the number of case data points we could use the shape and rate parameters obtained above: +For example, to define the generation time as gamma distributed with uncertain mean centered on 3 and sd centered on 1 with some uncertainty, a maximum value of 10 and weighted by the number of case data points we could use the shape and rate parameters suggested above (though notes that this will only very approximately produce the uncertainty in mean and standard deviation stated there): ```{r, results = 'hide'} generation_time <- gamma( diff --git a/vignettes/figure/bp-1.png b/vignettes/figure/bp-1.png index d2c46289c9ca794ce9bac523af59e81c9c2125ec..cd26cbc4cf119e98e241d7f02d1cea8757dc5670 100644 GIT binary patch literal 44013 zcmb@uWl&sQ)GpXaf`$;B;G}U07Tnzl(zv^8a3{eUcXv%=!6i7sEx5Y{4{ibG@P2b| z)!dqYGhNk1({OB^z1LprkrVz|QR)rqdsGkz^hQQnTm=Mzn|^sC!vo)-ODOUIKTsT{ zwOl|TG_035+~kViKM;r^Q~Q~#_~#V+u3HjYs%*;bCTK`XM0z(mwh zg#bNKCY$V^w5C`9nA_-0Y-<1ofk)S0icVzY&f)=a-5rsz3p$BSEgKc50+ip@l_$Xn8=9m%KCr5pMc;4g?$J` z#_$7$$%{eTKJSnbjZuaFKm1DDeYfhlmqidFaP|v3VU7q9KJYd^0GGL(-T%qw_}P8U z*PZR>H(_$j+8j}-b~68eXY1?hRsN5MH>=*`TW9jtIl#FY&#IPQ_}=ZLjPsqgx*pEX z%*{P-y!B6=7No#L{#9N=zE=i2V5n+!9;8Y!B)E=p@Yzbz&`&$EfBExKG5Ow4lm2L7 za!24y25VZ4dO~j2{QW&VJZii{UXGj^lzBS*v16phRzl*HOuWJK{T!}@=i}8J%})y; zFsu=Sr#@y{e#iB5eh*7)uq~hGhc$oTY=(dH0GE?mvF+aeeA_S7z415X4bi0l5tseH zzddh}kdSC|zv0*%XL4W|)eI zqAL>hI}uFoXoh1R2&9*#ylzi?H@5jZn?+N?fbMF+k(>8P!if3a!_T!x3=l0;)?Y5! z3`CBcUy2QbrAvbu@#Lz>M#M+7DrWPe)3IC#LN+{{C>26RW#YeWHNm+s4r?5r)tml;XG?A0NLJ`seuH zanV3)_p^;`f|U8RFqrJr7i9}o$js@D1_Xlp-~`P_*7AFOo?cd2$$UTy!bF7Y`Qe=2 zprS;yjs-}$^ zA!#LJhl}@N2}&rdL1x%GQKk4G{G?p5JjlUjIfd9U{SgA80K^y!AJ-d-Rch+3Bnl9R#b_O1$&}z2MQk=9i@J3Tz?ob;aTTN@jpbWeAZmW^Y z>vNx1A}r=(n%PyXE+H2_Z!*}E_ZXnYHO)DXM;0YHeqLf?VkZc1_U>fkP1g_NM{zfG zKF`CkUSQ&;y?>TGev4kj6&CKJG>-;KGC$N`%cXfoXY-611`lKp){Ecp?Td$~3BAL8 zD(}S+#}s3FDUa%!h2GB}lBvXo;284;W_~m_7u)!jD?RAVt;J7Fs<3K8DXoSh? zMKzMaRW+Zw!GXwQ@M~mC*b(em+apxiJ)vxO-lU0yP)>sv3n?Og6q9G;b3f5-a@
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z-Owi3gz;sYo5;(Nwl+&>0#{A?!r*b3i+$(EldA@Ab8>Qi{3ygVLhxK`iQ@t>fJ?My z4`7kFMG5+so12?CMXx>l2xr(C<)Z;zZ_#N5bq;he@KG2&@m)ls2byU%d+ zW<0<~dcZwoZ2y+87M~Wug!J4^OM7yjlUHMguS5M`-{Ecd%V=<+bSQ=Bk`s}?e+^nI gkN5uH|2z}_oVjhoS}tb=rCx-*w2D-|r187|1+kpVr~m)} From 7e79e6eca0a29f758fcb05e18eb6490af51811bd Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Mon, 27 Nov 2023 12:06:39 +0000 Subject: [PATCH 064/129] update var names --- R/dist.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/dist.R b/R/dist.R index 742fb55b5..9995d1606 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1912,7 +1912,7 @@ convert_to_natural <- function(params, distribution) { if ("mean" %in% names(ux) && "sd" %in% names(ux)) { x$shape <- ux$mean**2 / ux$sd**2 x$rate <- x$shape / ux$mean - } else if (!("rate" %in% names(means)) && ("scale" %in% names(means))) { + } else if (!("rate" %in% names(ux)) && ("scale" %in% names(ux))) { x$shape <- ux$shape x$rate <- 1 / ux$scale } From 30f5aeda577a65a5629edf0339c1c1b99d0a6e69 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Mon, 27 Nov 2023 12:35:04 +0000 Subject: [PATCH 065/129] rename argument in docs --- R/dist.R | 2 +- man/convert_to_natural.Rd | 4 ++-- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/R/dist.R b/R/dist.R index 9995d1606..8d4749cd5 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1896,7 +1896,7 @@ generate_dist_spec <- function(params, distribution) { ##' ##' This is used for preprocessing before generating a `dist_spec` object ##' from a given set of parameters and distribution -##' @param x A numerical named parameter vector +##' @param params A numerical named parameter vector ##' @inheritParams natural_params ##' @return A list with two elements, `params_mean` and `params_sd`, containing ##' mean and sd of natural parameters. diff --git a/man/convert_to_natural.Rd b/man/convert_to_natural.Rd index c2c33937e..6c6c4496c 100644 --- a/man/convert_to_natural.Rd +++ b/man/convert_to_natural.Rd @@ -7,9 +7,9 @@ convert_to_natural(params, distribution) } \arguments{ -\item{distribution}{Character; the distribution to use.} +\item{params}{A numerical named parameter vector} -\item{x}{A numerical named parameter vector} +\item{distribution}{Character; the distribution to use.} } \value{ A list with two elements, \code{params_mean} and \code{params_sd}, containing From 097026032fe9bec6f9cc901deffe211faf03a38a Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Mon, 27 Nov 2023 12:35:14 +0000 Subject: [PATCH 066/129] update man pages --- man/epinow.Rd | 4 ++-- man/estimate_infections.Rd | 4 ++-- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/man/epinow.Rd b/man/epinow.Rd index 1c0d157c7..b7661aaa6 100644 --- a/man/epinow.Rd +++ b/man/epinow.Rd @@ -130,8 +130,8 @@ options(mc.cores = ifelse(interactive(), 4, 1)) # set an example generation time. In practice this should use an estimate # from the literature or be estimated from data generation_time <- gamma( - shape = normal(2, 2.6), - rate = normal(0.5, 0.6), + shape = normal(1.3, 0.3), + rate = normal(0.37, 0.09), max = 14 ) # set an example incubation period. In practice this should use an estimate diff --git a/man/estimate_infections.Rd b/man/estimate_infections.Rd index 487791a50..11201253d 100644 --- a/man/estimate_infections.Rd +++ b/man/estimate_infections.Rd @@ -119,8 +119,8 @@ reported_cases <- example_confirmed[1:60] # set an example generation time. In practice this should use an estimate # from the literature or be estimated from data generation_time <- gamma( - shape = normal(2, 2.6), - rate = normal(0.5, 0.6), + shape = normal(1.3, 0.3), + rate = normal(0.37, 0.09), max = 14 ) # set an example incubation period. In practice this should use an estimate From 322cdd02c51d6e509844dfea6ed7fbf0e7fca2d3 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Mon, 27 Nov 2023 12:37:22 +0000 Subject: [PATCH 067/129] update test result --- tests/testthat/test-report_cases.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/testthat/test-report_cases.R b/tests/testthat/test-report_cases.R index 41d8062de..4888f8145 100644 --- a/tests/testthat/test-report_cases.R +++ b/tests/testthat/test-report_cases.R @@ -15,6 +15,6 @@ test_that("report_cases can simulate infections forward", { expect_equal(class(reported_cases), "list") expect_equal(class(reported_cases$samples), c("data.table", "data.frame")) expect_equal(class(reported_cases$summarised), c("data.table", "data.frame")) - expect_equal(nrow(reported_cases$summarised), 10) + expect_equal(nrow(reported_cases$summarised), 7) expect_equal(class(reported_cases$summarised$median), "numeric") }) From a17e85d3eeee19b7b3cda3b6eb351eeb886249b2 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Thu, 30 Nov 2023 16:08:38 +0000 Subject: [PATCH 068/129] add reviewer Co-authored-by: Sam Abbott --- NEWS.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/NEWS.md b/NEWS.md index d9321da0f..6edcc5363 100644 --- a/NEWS.md +++ b/NEWS.md @@ -7,7 +7,7 @@ * The `fixed` argument to `dist_spec` has been deprecated and replaced by a `fix_dist()` function. By @sbfnk in #503 and reviewed by @seabbs. * Updated `estimate_infections()` so that rather than imputing missing data, it now skips these data points in the likelihood. This is a breaking change as it alters the behaviour of the model when dates are missing from a time series but are known to be zero. We recommend that users check their results when updating to this version but expect this to in most cases improve performance. By @seabbs in #528 and reviewed by @sbfnk. * `simulate_infections` has been renamed to `forecast_infections` in line with `simulate_secondary` and `forecast_secondary`. The terminology is: a forecast is done from a fit to existing data, a simulation from first principles. By @sbfnk in #544 and reviewed by @seabbs. -* The interface to generating delay distributions has been completely overhauled. Instead of calling `dist_spec()` users now specify distributions using functions that represent the available distributions, i.e. `lognormal()`, `gamma()` and `fixed()`. Uncertainty is specified using calls of the same nature, to `normal()`. By @sbfnk in #504. +* The interface to generating delay distributions has been completely overhauled. Instead of calling `dist_spec()` users now specify distributions using functions that represent the available distributions, i.e. `lognormal()`, `gamma()` and `fixed()`. Uncertainty is specified using calls of the same nature, to `normal()`. By @sbfnk in #504 and reviewed by @seabbs. ## Documentation From 136e3037d2eefb8b085224ebad9f87632981185e Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Thu, 30 Nov 2023 14:52:13 +0000 Subject: [PATCH 069/129] base scaling on variance, not sd --- R/dist.R | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/R/dist.R b/R/dist.R index 8d4749cd5..0f2f0b972 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1905,7 +1905,7 @@ convert_to_natural <- function(params, distribution) { ## unnatural parameter means ux <- lapply(params, mean) ## estimate relative uncertainty of parameters - rel_unc <- mean(vapply(params, sd_dist, numeric(1)) / unlist(ux)) + rel_unc <- mean(vapply(params, sd_dist, numeric(1))^2 / unlist(ux)) ## store natural parameters x <- list() if (distribution == "gamma") { @@ -1924,7 +1924,7 @@ convert_to_natural <- function(params, distribution) { natural_means <- unname(unlist(x[natural_params(distribution)])) params <- list( params_mean = natural_means, - params_sd = natural_means * rel_unc + params_sd = sqrt(natural_means * rel_unc) ) return(params) } From f3eeba87de8c539ba2ec5d21eee134eb2941cfb9 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Thu, 30 Nov 2023 16:07:47 +0000 Subject: [PATCH 070/129] re-render vignettes --- vignettes/epinow.Rmd | 92 +++++----- vignettes/estimate_infections_options.Rmd | 166 +++++++++--------- vignettes/estimate_infections_workflow.Rmd | 19 +- .../estimate_infections_workflow.Rmd.orig | 2 +- vignettes/figure/bp-1.png | Bin 44013 -> 44096 bytes vignettes/figure/default-1.png | Bin 49021 -> 49065 bytes vignettes/figure/fixed-1.png | Bin 37263 -> 37436 bytes vignettes/figure/gp_projection-1.png | Bin 48741 -> 48673 bytes vignettes/figure/lower_accuracy-1.png | Bin 48893 -> 48630 bytes vignettes/figure/no_delays-1.png | Bin 46591 -> 45803 bytes vignettes/figure/nonparametric-1.png | Bin 47131 -> 47295 bytes vignettes/figure/regional_epinow-1.png | Bin 34223 -> 33728 bytes .../figure/regional_epinow_multiple-1.png | Bin 32084 -> 32539 bytes vignettes/figure/results-1.png | Bin 45952 -> 57921 bytes vignettes/figure/susceptible_depletion-1.png | Bin 49521 -> 48500 bytes vignettes/figure/weekly_rw-1.png | Bin 48164 -> 47636 bytes 16 files changed, 133 insertions(+), 146 deletions(-) diff --git a/vignettes/epinow.Rmd b/vignettes/epinow.Rmd index 9e3e683b1..60a7d62d0 100644 --- a/vignettes/epinow.Rmd +++ b/vignettes/epinow.Rmd @@ -46,13 +46,13 @@ res <- epinow(reported_cases, target_folder = "results" ) #> Logging threshold set at INFO for the EpiNow2 logger -#> Writing EpiNow2 logs to the console and: /tmp/RtmpyrNOVB/regional-epinow/2020-04-21.log +#> Writing EpiNow2 logs to the console and: /tmp/RtmpBdeheM/regional-epinow/2020-04-21.log #> Logging threshold set at INFO for the EpiNow2.epinow logger -#> Writing EpiNow2.epinow logs to the console and: /tmp/RtmpyrNOVB/epinow/2020-04-21.log -#> WARN [2023-11-26 21:54:03] epinow: There were 13 divergent transitions after warmup. See +#> Writing EpiNow2.epinow logs to the console and: /tmp/RtmpBdeheM/epinow/2020-04-21.log +#> WARN [2023-11-30 15:22:43] epinow: There were 10 divergent transitions after warmup. See #> https://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup #> to find out why this is a problem and how to eliminate them. - -#> WARN [2023-11-26 21:54:03] epinow: Examine the pairs() plot to diagnose sampling problems +#> WARN [2023-11-30 15:22:43] epinow: Examine the pairs() plot to diagnose sampling problems #> - res$plots$R #> NULL @@ -86,34 +86,34 @@ region_rt <- regional_epinow( delays = delay_opts(delay), rt = rt_opts(prior = rt_prior), ) -#> INFO [2023-11-26 21:54:10] Producing following optional outputs: regions, summary, samples, plots, latest +#> INFO [2023-11-30 15:22:50] Producing following optional outputs: regions, summary, samples, plots, latest #> Logging threshold set at INFO for the EpiNow2 logger -#> Writing EpiNow2 logs to the console and: /tmp/RtmpyrNOVB/regional-epinow/2020-04-21.log +#> Writing EpiNow2 logs to the console and: /tmp/RtmpBdeheM/regional-epinow/2020-04-21.log #> Logging threshold set at INFO for the EpiNow2.epinow logger -#> Writing EpiNow2.epinow logs to: /tmp/RtmpyrNOVB/epinow/2020-04-21.log -#> INFO [2023-11-26 21:54:10] Reporting estimates using data up to: 2020-04-21 -#> INFO [2023-11-26 21:54:10] No target directory specified so returning output -#> INFO [2023-11-26 21:54:10] Producing estimates for: testland, realland -#> INFO [2023-11-26 21:54:10] Regions excluded: none -#> INFO [2023-11-26 21:59:54] Completed estimates for: testland -#> INFO [2023-11-26 22:33:35] Completed estimates for: realland -#> INFO [2023-11-26 22:33:35] Completed regional estimates -#> INFO [2023-11-26 22:33:35] Regions with estimates: 2 -#> INFO [2023-11-26 22:33:35] Regions with runtime errors: 0 -#> INFO [2023-11-26 22:33:35] Producing summary -#> INFO [2023-11-26 22:33:35] No summary directory specified so returning summary output -#> INFO [2023-11-26 22:33:36] No target directory specified so returning timings +#> Writing EpiNow2.epinow logs to: /tmp/RtmpBdeheM/epinow/2020-04-21.log +#> INFO [2023-11-30 15:22:50] Reporting estimates using data up to: 2020-04-21 +#> INFO [2023-11-30 15:22:50] No target directory specified so returning output +#> INFO [2023-11-30 15:22:50] Producing estimates for: testland, realland +#> INFO [2023-11-30 15:22:50] Regions excluded: none +#> INFO [2023-11-30 15:56:46] Completed estimates for: testland +#> INFO [2023-11-30 16:03:20] Completed estimates for: realland +#> INFO [2023-11-30 16:03:20] Completed regional estimates +#> INFO [2023-11-30 16:03:20] Regions with estimates: 2 +#> INFO [2023-11-30 16:03:20] Regions with runtime errors: 0 +#> INFO [2023-11-30 16:03:20] Producing summary +#> INFO [2023-11-30 16:03:20] No summary directory specified so returning summary output +#> INFO [2023-11-30 16:03:20] No target directory specified so returning timings ## summary region_rt$summary$summarised_results$table #> Region New confirmed cases by infection date -#> 1: realland 2512 (968 -- 18904) -#> 2: testland 2027 (817 -- 4043) +#> 1: realland 2075 (865 -- 4051) +#> 2: testland 2481 (935 -- 7971) #> Expected change in daily cases Effective reproduction no. -#> 1: Stable 0.95 (0.63 -- 1.5) -#> 2: Likely decreasing 0.87 (0.6 -- 1.1) +#> 1: Likely decreasing 0.88 (0.6 -- 1.1) +#> 2: Stable 0.94 (0.62 -- 1.3) #> Rate of growth Doubling/halving time (days) -#> 1: -0.016 (-0.12 -- 0.042) -44 (17 -- -5.6) -#> 2: -0.038 (-0.14 -- 0.036) -18 (19 -- -4.9) +#> 1: -0.036 (-0.14 -- 0.036) -19 (19 -- -5) +#> 2: -0.016 (-0.13 -- 0.045) -44 (15 -- -5.3) ## plot region_rt$summary$plots$R ``` @@ -133,34 +133,34 @@ region_separate_rt <- regional_epinow( delays = delay_opts(delay), rt = rt, gp = gp, ) -#> INFO [2023-11-26 22:33:36] Producing following optional outputs: regions, summary, samples, plots, latest +#> INFO [2023-11-30 16:03:21] Producing following optional outputs: regions, summary, samples, plots, latest #> Logging threshold set at INFO for the EpiNow2 logger -#> Writing EpiNow2 logs to the console and: /tmp/RtmpyrNOVB/regional-epinow/2020-04-21.log +#> Writing EpiNow2 logs to the console and: /tmp/RtmpBdeheM/regional-epinow/2020-04-21.log #> Logging threshold set at INFO for the EpiNow2.epinow logger -#> Writing EpiNow2.epinow logs to: /tmp/RtmpyrNOVB/epinow/2020-04-21.log -#> INFO [2023-11-26 22:33:36] Reporting estimates using data up to: 2020-04-21 -#> INFO [2023-11-26 22:33:36] No target directory specified so returning output -#> INFO [2023-11-26 22:33:36] Producing estimates for: testland, realland -#> INFO [2023-11-26 22:33:36] Regions excluded: none -#> INFO [2023-11-26 22:39:48] Completed estimates for: testland -#> INFO [2023-11-26 22:40:44] Completed estimates for: realland -#> INFO [2023-11-26 22:40:44] Completed regional estimates -#> INFO [2023-11-26 22:40:44] Regions with estimates: 2 -#> INFO [2023-11-26 22:40:44] Regions with runtime errors: 0 -#> INFO [2023-11-26 22:40:44] Producing summary -#> INFO [2023-11-26 22:40:44] No summary directory specified so returning summary output -#> INFO [2023-11-26 22:40:45] No target directory specified so returning timings +#> Writing EpiNow2.epinow logs to: /tmp/RtmpBdeheM/epinow/2020-04-21.log +#> INFO [2023-11-30 16:03:21] Reporting estimates using data up to: 2020-04-21 +#> INFO [2023-11-30 16:03:21] No target directory specified so returning output +#> INFO [2023-11-30 16:03:21] Producing estimates for: testland, realland +#> INFO [2023-11-30 16:03:21] Regions excluded: none +#> INFO [2023-11-30 16:05:12] Completed estimates for: testland +#> INFO [2023-11-30 16:05:44] Completed estimates for: realland +#> INFO [2023-11-30 16:05:44] Completed regional estimates +#> INFO [2023-11-30 16:05:44] Regions with estimates: 2 +#> INFO [2023-11-30 16:05:44] Regions with runtime errors: 0 +#> INFO [2023-11-30 16:05:44] Producing summary +#> INFO [2023-11-30 16:05:44] No summary directory specified so returning summary output +#> INFO [2023-11-30 16:05:44] No target directory specified so returning timings ## summary region_separate_rt$summary$summarised_results$table #> Region New confirmed cases by infection date -#> 1: realland 2027 (1002 -- 3958) -#> 2: testland 2100 (841 -- 4030) +#> 1: realland 2001 (956 -- 4028) +#> 2: testland 2048 (901 -- 4080) #> Expected change in daily cases Effective reproduction no. -#> 1: Likely decreasing 0.89 (0.67 -- 1.1) -#> 2: Likely decreasing 0.88 (0.59 -- 1.1) +#> 1: Likely decreasing 0.88 (0.66 -- 1.2) +#> 2: Likely decreasing 0.88 (0.61 -- 1.2) #> Rate of growth Doubling/halving time (days) -#> 1: -0.035 (-0.11 -- 0.035) -20 (20 -- -6.4) -#> 2: -0.034 (-0.14 -- 0.037) -20 (19 -- -4.9) +#> 1: -0.035 (-0.12 -- 0.042) -20 (16 -- -6) +#> 2: -0.036 (-0.13 -- 0.04) -19 (17 -- -5.2) ## plot region_separate_rt$summary$plots$R ``` diff --git a/vignettes/estimate_infections_options.Rmd b/vignettes/estimate_infections_options.Rmd index 11aa9459e..8dcca7c64 100644 --- a/vignettes/estimate_infections_options.Rmd +++ b/vignettes/estimate_infections_options.Rmd @@ -144,25 +144,25 @@ def <- estimate_infections(reported_cases, delays = delay_opts(delay), rt = rt_opts(prior = rt_prior) ) -#> Warning: There were 6 divergent transitions after warmup. See +#> Warning: There were 2 divergent transitions after warmup. See #> https://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup #> to find out why this is a problem and how to eliminate them. #> Warning: Examine the pairs() plot to diagnose sampling problems # summarise results summary(def) #> measure estimate -#> 1: New confirmed cases by infection date 2195 (1030 -- 4199) +#> 1: New confirmed cases by infection date 2272 (1082 -- 4222) #> 2: Expected change in daily cases Likely decreasing -#> 3: Effective reproduction no. 0.88 (0.6 -- 1.2) -#> 4: Rate of growth -0.03 (-0.11 -- 0.036) -#> 5: Doubling/halving time (days) -23 (19 -- -6.3) +#> 3: Effective reproduction no. 0.89 (0.61 -- 1.2) +#> 4: Rate of growth -0.027 (-0.1 -- 0.037) +#> 5: Doubling/halving time (days) -26 (19 -- -6.7) # elapsed time (in seconds) get_elapsed_time(def$fit) #> warmup sample -#> chain:1 32.869 31.472 -#> chain:2 34.072 48.232 -#> chain:3 24.531 41.905 -#> chain:4 40.197 24.689 +#> chain:1 39.631 49.732 +#> chain:2 32.870 44.510 +#> chain:3 37.056 45.843 +#> chain:4 41.190 41.020 # summary plot plot(def) ``` @@ -181,25 +181,25 @@ agp <- estimate_infections(reported_cases, rt = rt_opts(prior = rt_prior), gp = gp_opts(basis_prop = 0.1) ) -#> Warning: There were 9 divergent transitions after warmup. See +#> Warning: There were 10 divergent transitions after warmup. See #> https://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup #> to find out why this is a problem and how to eliminate them. #> Warning: Examine the pairs() plot to diagnose sampling problems # summarise results summary(agp) #> measure estimate -#> 1: New confirmed cases by infection date 2321 (1151 -- 4351) +#> 1: New confirmed cases by infection date 2318 (1221 -- 4292) #> 2: Expected change in daily cases Likely decreasing -#> 3: Effective reproduction no. 0.89 (0.64 -- 1.2) -#> 4: Rate of growth -0.025 (-0.095 -- 0.036) -#> 5: Doubling/halving time (days) -27 (19 -- -7.3) +#> 3: Effective reproduction no. 0.9 (0.66 -- 1.2) +#> 4: Rate of growth -0.024 (-0.092 -- 0.036) +#> 5: Doubling/halving time (days) -29 (19 -- -7.5) # elapsed time (in seconds) get_elapsed_time(agp$fit) #> warmup sample -#> chain:1 21.334 23.803 -#> chain:2 20.714 28.792 -#> chain:3 27.059 44.721 -#> chain:4 24.691 28.737 +#> chain:1 21.668 45.690 +#> chain:2 20.766 22.758 +#> chain:3 19.043 35.899 +#> chain:4 18.513 45.408 # summary plot plot(agp) ``` @@ -222,25 +222,25 @@ dep <- estimate_infections(reported_cases, pop = 1000000, future = "latest" ) ) -#> Warning: There were 5 divergent transitions after warmup. See +#> Warning: There were 24 divergent transitions after warmup. See #> https://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup #> to find out why this is a problem and how to eliminate them. #> Warning: Examine the pairs() plot to diagnose sampling problems # summarise results summary(dep) -#> measure estimate -#> 1: New confirmed cases by infection date 2239 (1081 -- 4334) -#> 2: Expected change in daily cases Likely decreasing -#> 3: Effective reproduction no. 0.89 (0.62 -- 1.2) -#> 4: Rate of growth -0.027 (-0.1 -- 0.037) -#> 5: Doubling/halving time (days) -26 (19 -- -6.7) +#> measure estimate +#> 1: New confirmed cases by infection date 2259 (1106 -- 4245) +#> 2: Expected change in daily cases Likely decreasing +#> 3: Effective reproduction no. 0.88 (0.61 -- 1.2) +#> 4: Rate of growth -0.027 (-0.11 -- 0.035) +#> 5: Doubling/halving time (days) -25 (20 -- -6.5) # elapsed time (in seconds) get_elapsed_time(dep$fit) #> warmup sample -#> chain:1 44.769 36.097 -#> chain:2 35.531 47.282 -#> chain:3 44.366 39.752 -#> chain:4 33.220 44.781 +#> chain:1 26.983 25.015 +#> chain:2 32.689 25.745 +#> chain:3 34.598 24.593 +#> chain:4 33.245 25.095 # summary plot plot(dep) ``` @@ -265,9 +265,11 @@ trunc_dist <- lognormal( #> very approximate method that is likely to produce biased results. If possible, #> it is preferable to specify the distribution direclty in terms of the natural #> parameters. +#> Warning in sqrt(natural_means * rel_unc): NaNs produced trunc_dist #> -#> lognormal distribution (max: 3) with meanlog = -1 and uncertain sdlog (mean = 0.83, sd = 0.17). +#> lognormal distribution (max: 3) with +#> Error in if (x$params_sd[pos] > 0) {: missing value where TRUE/FALSE needed ``` We can then use this in the `esimtate_infections()` function using the `truncation` option. @@ -280,9 +282,9 @@ trunc <- estimate_infections(reported_cases, truncation = trunc_opts(trunc_dist), rt = rt_opts(prior = rt_prior) ) -#> Error in eval(expr, envir, enclos) : -#> Exception: model_estimate_infections_namespace::model_estimate_infections: delay_params_sd[sym1__] is -0.207944, but must be greater than or equal to 0 (in 'estimate_infections', line 625, column 2 to column 57) -#> failed to create the sampler; sampling not done +#> Error in FUN(X[[i]], ...) : +#> Stan does not support NA (in delay_params_sd) in data +#> failed to preprocess the data; sampling not done #> Error in `fit_model_with_nuts()`: #> ! model fitting was timed out or failed # summarise results @@ -311,25 +313,25 @@ project_rt <- estimate_infections(reported_cases, prior = rt_prior, future = "project" ) ) -#> Warning: There were 18 divergent transitions after warmup. See +#> Warning: There were 20 divergent transitions after warmup. See #> https://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup #> to find out why this is a problem and how to eliminate them. #> Warning: Examine the pairs() plot to diagnose sampling problems # summarise results summary(project_rt) #> measure estimate -#> 1: New confirmed cases by infection date 2288 (1037 -- 4391) +#> 1: New confirmed cases by infection date 2245 (1119 -- 4319) #> 2: Expected change in daily cases Likely decreasing -#> 3: Effective reproduction no. 0.89 (0.6 -- 1.2) -#> 4: Rate of growth -0.025 (-0.11 -- 0.04) -#> 5: Doubling/halving time (days) -27 (17 -- -6.5) +#> 3: Effective reproduction no. 0.89 (0.61 -- 1.2) +#> 4: Rate of growth -0.026 (-0.1 -- 0.039) +#> 5: Doubling/halving time (days) -26 (18 -- -6.7) # elapsed time (in seconds) get_elapsed_time(project_rt$fit) #> warmup sample -#> chain:1 27.493 41.460 -#> chain:2 35.221 43.828 -#> chain:3 37.618 45.411 -#> chain:4 29.761 35.035 +#> chain:1 35.447 34.177 +#> chain:2 33.563 30.859 +#> chain:3 31.365 24.099 +#> chain:4 34.837 45.162 # summary plot plot(project_rt) ``` @@ -349,19 +351,19 @@ fixed <- estimate_infections(reported_cases, ) # summarise results summary(fixed) -#> measure estimate -#> 1: New confirmed cases by infection date 15523 (9069 -- 27937) -#> 2: Expected change in daily cases Increasing -#> 3: Effective reproduction no. 1.2 (1.1 -- 1.3) -#> 4: Rate of growth 0.037 (0.026 -- 0.049) -#> 5: Doubling/halving time (days) 19 (14 -- 27) +#> measure estimate +#> 1: New confirmed cases by infection date 15440 (8847 -- 27843) +#> 2: Expected change in daily cases Increasing +#> 3: Effective reproduction no. 1.2 (1.1 -- 1.3) +#> 4: Rate of growth 0.037 (0.026 -- 0.05) +#> 5: Doubling/halving time (days) 19 (14 -- 27) # elapsed time (in seconds) get_elapsed_time(fixed$fit) #> warmup sample -#> chain:1 1.608 1.265 -#> chain:2 2.014 1.249 -#> chain:3 1.342 1.265 -#> chain:4 1.299 1.256 +#> chain:1 1.129 1.270 +#> chain:2 1.443 1.295 +#> chain:3 1.569 1.252 +#> chain:4 1.571 1.244 # summary plot plot(fixed) ``` @@ -395,18 +397,18 @@ bkp <- estimate_infections(bp_cases, # summarise results summary(bkp) #> measure estimate -#> 1: New confirmed cases by infection date 2583 (2137 -- 3103) +#> 1: New confirmed cases by infection date 2577 (2146 -- 3130) #> 2: Expected change in daily cases Decreasing #> 3: Effective reproduction no. 0.9 (0.88 -- 0.93) #> 4: Rate of growth -0.019 (-0.025 -- -0.013) -#> 5: Doubling/halving time (days) -37 (-51 -- -28) +#> 5: Doubling/halving time (days) -36 (-52 -- -28) # elapsed time (in seconds) get_elapsed_time(bkp$fit) #> warmup sample -#> chain:1 3.664 5.156 -#> chain:2 7.443 4.758 -#> chain:3 3.086 4.164 -#> chain:4 3.292 4.891 +#> chain:1 2.585 3.471 +#> chain:2 3.000 5.255 +#> chain:3 7.665 4.073 +#> chain:4 3.232 5.177 # summary plot plot(bkp) ``` @@ -429,18 +431,18 @@ rw <- estimate_infections(reported_cases, # summarise results summary(rw) #> measure estimate -#> 1: New confirmed cases by infection date 2099 (1090 -- 4011) +#> 1: New confirmed cases by infection date 2105 (1075 -- 3960) #> 2: Expected change in daily cases Likely decreasing -#> 3: Effective reproduction no. 0.87 (0.65 -- 1.1) -#> 4: Rate of growth -0.034 (-0.098 -- 0.028) -#> 5: Doubling/halving time (days) -21 (24 -- -7.1) +#> 3: Effective reproduction no. 0.86 (0.64 -- 1.1) +#> 4: Rate of growth -0.034 (-0.099 -- 0.032) +#> 5: Doubling/halving time (days) -20 (22 -- -7) # elapsed time (in seconds) get_elapsed_time(rw$fit) #> warmup sample -#> chain:1 7.740 10.294 -#> chain:2 7.820 16.408 -#> chain:3 14.642 10.039 -#> chain:4 8.099 9.983 +#> chain:1 7.975 10.738 +#> chain:2 8.867 10.287 +#> chain:3 7.698 10.673 +#> chain:4 9.396 11.083 # summary plot plot(rw) ``` @@ -457,25 +459,25 @@ no_delay <- estimate_infections( reported_cases, generation_time = generation_time_opts(example_generation_time) ) -#> Warning: There were 6 divergent transitions after warmup. See +#> Warning: There were 3 divergent transitions after warmup. See #> https://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup #> to find out why this is a problem and how to eliminate them. #> Warning: Examine the pairs() plot to diagnose sampling problems # summarise results summary(no_delay) #> measure estimate -#> 1: New confirmed cases by infection date 2760 (2330 -- 3322) +#> 1: New confirmed cases by infection date 2773 (2338 -- 3307) #> 2: Expected change in daily cases Decreasing #> 3: Effective reproduction no. 0.89 (0.78 -- 0.99) -#> 4: Rate of growth -0.028 (-0.057 -- -0.0017) -#> 5: Doubling/halving time (days) -25 (-420 -- -12) +#> 4: Rate of growth -0.026 (-0.056 -- -0.0025) +#> 5: Doubling/halving time (days) -26 (-280 -- -12) # elapsed time (in seconds) get_elapsed_time(no_delay$fit) #> warmup sample -#> chain:1 40.797 40.306 -#> chain:2 38.682 40.881 -#> chain:3 41.781 79.174 -#> chain:4 40.010 46.899 +#> chain:1 42.074 39.484 +#> chain:2 35.120 44.165 +#> chain:3 36.850 70.171 +#> chain:4 39.259 44.068 # summary plot plot(no_delay) ``` @@ -501,18 +503,18 @@ non_parametric <- estimate_infections(reported_cases, # summarise results summary(non_parametric) #> measure estimate -#> 1: New confirmed cases by infection date 2384 (1820 -- 3047) +#> 1: New confirmed cases by infection date 2366 (1813 -- 3047) #> 2: Expected change in daily cases Decreasing -#> 3: Effective reproduction no. 0.91 (0.69 -- 0.99) -#> 4: Rate of growth -0.021 (-0.044 -- -0.0026) -#> 5: Doubling/halving time (days) -33 (-260 -- -16) +#> 3: Effective reproduction no. 0.9 (0.68 -- 0.99) +#> 4: Rate of growth -0.022 (-0.044 -- -0.0026) +#> 5: Doubling/halving time (days) -32 (-270 -- -16) # elapsed time (in seconds) get_elapsed_time(non_parametric$fit) #> warmup sample -#> chain:1 3.023 0.869 -#> chain:2 2.883 0.882 -#> chain:3 2.803 0.844 -#> chain:4 2.471 0.874 +#> chain:1 2.770 0.883 +#> chain:2 3.029 0.813 +#> chain:3 3.299 0.865 +#> chain:4 3.036 0.644 # summary plot plot(non_parametric) ``` diff --git a/vignettes/estimate_infections_workflow.Rmd b/vignettes/estimate_infections_workflow.Rmd index 6a47f51aa..c50adb794 100644 --- a/vignettes/estimate_infections_workflow.Rmd +++ b/vignettes/estimate_infections_workflow.Rmd @@ -83,8 +83,6 @@ For example, to define a fixed gamma distribution with mean 3, standard deviatio ```r gamma(mean = 3, sd = 1, max = 10) -#> Warning: The meaning of the 'max' argument has changed compared to previous versions. It now indicates the maximum of a distribution rather than the length of the probability mass function (including 0) that it represented previously. To replicate previous behaviour reduce max by 1. -#> This warning is displayed once every 8 hours. #> #> distribution with PMF [0.0038 0.15 0.39 0.3 0.12 0.03 0.006 0.00096 0.00013 1.6e-05 1.8e-06]. ``` @@ -101,7 +99,7 @@ gamma(mean = normal(3, 2), sd = normal(1, 0.1), max = 10) #> method that is likely to produce biased results. If possible, it is preferable #> to specify the distribution direclty in terms of the natural parameters. #> -#> gamma distribution (max: 10) with uncertain shape (mean = 9, sd = 3.4) and uncertain rate (mean = 3, sd = 1.2). +#> gamma distribution (max: 10) with uncertain shape (mean = 9, sd = 2.5) and uncertain rate (mean = 3, sd = 1.4). ``` Note the warning about parameters. @@ -123,7 +121,7 @@ For example, to define the generation time as gamma distributed with uncertain m ```r generation_time <- gamma( - shape = normal(9, 3.4), rate = normal(3, 1.2), max = 10 + shape = normal(9, 2.5), rate = normal(3, 1.4), max = 10 ) generation_time_opts(generation_time) ``` @@ -240,20 +238,7 @@ def <- estimate_infections( #> Warning: There were 3 divergent transitions after warmup. See #> https://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup #> to find out why this is a problem and how to eliminate them. -#> Warning: There were 1000 transitions after warmup that exceeded the maximum treedepth. Increase max_treedepth above 15. See -#> https://mc-stan.org/misc/warnings.html#maximum-treedepth-exceeded -#> Warning: There were 1 chains where the estimated Bayesian Fraction of Missing Information was low. See -#> https://mc-stan.org/misc/warnings.html#bfmi-low #> Warning: Examine the pairs() plot to diagnose sampling problems -#> Warning: The largest R-hat is NA, indicating chains have not mixed. -#> Running the chains for more iterations may help. See -#> https://mc-stan.org/misc/warnings.html#r-hat -#> Warning: Bulk Effective Samples Size (ESS) is too low, indicating posterior means and medians may be unreliable. -#> Running the chains for more iterations may help. See -#> https://mc-stan.org/misc/warnings.html#bulk-ess -#> Warning: Tail Effective Samples Size (ESS) is too low, indicating posterior variances and tail quantiles may be unreliable. -#> Running the chains for more iterations may help. See -#> https://mc-stan.org/misc/warnings.html#tail-ess ``` Alternatively, for production environments, we recommend using the `epinow()` function. It uses `estimate_infections()` internally and provides functionality for logging and saving results and plots in dedicated directories in the user's file system. diff --git a/vignettes/estimate_infections_workflow.Rmd.orig b/vignettes/estimate_infections_workflow.Rmd.orig index 0697b6506..3f0d3a889 100644 --- a/vignettes/estimate_infections_workflow.Rmd.orig +++ b/vignettes/estimate_infections_workflow.Rmd.orig @@ -104,7 +104,7 @@ For example, to define the generation time as gamma distributed with uncertain m ```{r, results = 'hide'} generation_time <- gamma( - shape = normal(9, 3.4), rate = normal(3, 1.2), max = 10 + shape = normal(9, 2.5), rate = normal(3, 1.4), max = 10 ) generation_time_opts(generation_time) ``` diff --git a/vignettes/figure/bp-1.png b/vignettes/figure/bp-1.png index cd26cbc4cf119e98e241d7f02d1cea8757dc5670..f40a85c25d5e78036582379de299741eea2dc75a 100644 GIT binary patch literal 44096 zcmbq*Wl$VZyXFK4!QI{6-GaN@;O+!>mq2iLcS#s5Sa1vO4#9&v2_Af#@80`sw`!|) 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capitalisation of distributions --- NEWS.md | 2 +- R/dist.R | 74 ++++++++-------- R/epinow.R | 14 +-- R/estimate_infections.R | 14 +-- R/estimate_secondary.R | 6 +- R/estimate_truncation.R | 10 +-- R/get.R | 18 ++-- R/opts.R | 20 ++--- data-raw/estimate-infections.R | 2 +- data-raw/generation-time.R | 6 +- data-raw/incubation-period.R | 6 +- data-raw/reporting-delay.R | 4 +- man/Distributions.Rd | 30 +++---- man/delay_opts.Rd | 6 +- man/dist_spec.Rd | 4 +- man/epinow.Rd | 14 +-- man/estimate_infections.Rd | 14 +-- man/estimate_secondary.Rd | 2 +- man/estimate_truncation.Rd | 8 +- man/gamma_dist_def.Rd | 2 +- man/generation_time_opts.Rd | 12 +-- man/get_dist.Rd | 2 +- man/get_generation_time.Rd | 2 +- man/get_incubation_period.Rd | 2 +- man/get_seeding_time.Rd | 4 +- man/max.dist_spec.Rd | 4 +- man/mean.dist_spec.Rd | 6 +- man/plot.dist_spec.Rd | 6 +- man/plus-.dist_spec.Rd | 6 +- man/print.dist_spec.Rd | 6 +- man/sd_dist.Rd | 4 +- man/trunc_opts.Rd | 2 +- .../test-adjust_infection_to_report.R | 4 +- tests/testthat/test-delays.R | 14 +-- tests/testthat/test-dist_spec.R | 86 +++++++++---------- tests/testthat/test-epinow.R | 6 +- tests/testthat/test-estimate_secondary.R | 6 +- tests/testthat/test-estimate_truncation.R | 6 +- tests/testthat/test-seeding-time.R | 12 +-- vignettes/epinow.Rmd | 2 +- vignettes/epinow.Rmd.orig | 2 +- vignettes/estimate_infections_options.Rmd | 4 +- .../estimate_infections_options.Rmd.orig | 8 +- vignettes/estimate_infections_workflow.Rmd | 22 ++--- .../estimate_infections_workflow.Rmd.orig | 22 ++--- 45 files changed, 253 insertions(+), 253 deletions(-) diff --git a/NEWS.md b/NEWS.md index 6edcc5363..9a2182bd1 100644 --- a/NEWS.md +++ b/NEWS.md @@ -7,7 +7,7 @@ * The `fixed` argument to `dist_spec` has been deprecated and replaced by a `fix_dist()` function. By @sbfnk in #503 and reviewed by @seabbs. * Updated `estimate_infections()` so that rather than imputing missing data, it now skips these data points in the likelihood. This is a breaking change as it alters the behaviour of the model when dates are missing from a time series but are known to be zero. We recommend that users check their results when updating to this version but expect this to in most cases improve performance. By @seabbs in #528 and reviewed by @sbfnk. * `simulate_infections` has been renamed to `forecast_infections` in line with `simulate_secondary` and `forecast_secondary`. The terminology is: a forecast is done from a fit to existing data, a simulation from first principles. By @sbfnk in #544 and reviewed by @seabbs. -* The interface to generating delay distributions has been completely overhauled. Instead of calling `dist_spec()` users now specify distributions using functions that represent the available distributions, i.e. `lognormal()`, `gamma()` and `fixed()`. Uncertainty is specified using calls of the same nature, to `normal()`. By @sbfnk in #504 and reviewed by @seabbs. +* The interface to generating delay distributions has been completely overhauled. Instead of calling `dist_spec()` users now specify distributions using functions that represent the available distributions, i.e. `LogNormal()`, `Gamma()` and `Fixed()`. Uncertainty is specified using calls of the same nature, to `Normal()`. By @sbfnk in #504 and reviewed by @seabbs. ## Documentation diff --git a/R/dist.R b/R/dist.R index 0f2f0b972..41422ccb4 100644 --- a/R/dist.R +++ b/R/dist.R @@ -309,7 +309,7 @@ dist_fit <- function(values = NULL, samples = 1000, cores = 1, #' Generate a Gamma Distribution Definition Based on Parameter Estimates #' #' @description `r lifecycle::badge("deprecated")` -#' Deprecated; use [gamma()] instead to define a gamma distribution. +#' Deprecated; use [Gamma()] instead to define a gamma distribution. #' #' @param shape Numeric, shape parameter of the gamma distribution. #' @@ -351,7 +351,7 @@ gamma_dist_def <- function(shape, shape_sd, sd, sd_sd, max_value, samples) { lifecycle::deprecate_warn( - "2.0.0", "gamma_dist_def()", "gamma()", + "2.0.0", "gamma_dist_def()", "Gamma()", "The function will be removed completely in version 2.1.0." ) @@ -440,7 +440,7 @@ lognorm_dist_def <- function(mean, mean_sd, max_value, samples, to_log = FALSE) { lifecycle::deprecate_warn( - "2.0.0", "lognorm_dist_def()", "lognormal()", + "2.0.0", "lognorm_dist_def()", "LogNormal()", "The function will be removed completely in version 2.1.0." ) @@ -865,8 +865,8 @@ tune_inv_gamma <- function(lower = 2, upper = 21) { #' @description `r lifecycle::badge("deprecated")` #' This function is deprecated as a user-facing function (while its #' functionality is still used internally). Construct distributions using -#' the corresponding distribution function such as [gamma()], [lognormal()], -#' [normal()] or [fixed()] instead. +#' the corresponding distribution function such as [Gamma()], [LogNormal()], +#' [Normal()] or [Fixed()] instead. #' #' @param mean Deprecated; use `params_mean` instead. #' @@ -923,7 +923,7 @@ dist_spec <- function(distribution = c( deprecate_warn( "2.0.0", "dist_spec(distribution = 'must not be \"empty\"')", - details = "Please use `fixed(0)` instead." + details = "Please use `Fixed(0)` instead." ) } @@ -936,9 +936,9 @@ dist_spec <- function(distribution = c( params_mean <- c(meanlog = mean, sdlog = sd) params_sd <- c(meanlog = mean_sd, sdlog = sd_sd) } else if (distribution == "gamma") { - temp_dist <- gamma( - mean = normal(mean, mean_sd), - sd = normal(sd, sd_sd) + temp_dist <- Gamma( + mean = Normal(mean, mean_sd), + sd = Normal(sd, sd_sd) ) params_mean <- temp_dist$params_mean params_sd <- temp_dist$params_sd @@ -1183,14 +1183,14 @@ dist_spec_plus <- function(e1, e2, tolerance = 0.001) { #' @export #' @examples #' # A fixed lognormal distribution with mean 5 and sd 1. -#' dist1 <- lognormal( +#' dist1 <- LogNormal( #' meanlog = 1.6, sdlog = 1, max = 20 #' ) #' dist1 + dist1 #' #' # An uncertain gamma distribution with mean 3 and sd 2 -#' dist2 <- gamma( -#' mean = normal(3, 0.5), sd = normal(2, 0.5), max = 20 +#' dist2 <- Gamma( +#' mean = Normal(3, 0.5), sd = Normal(2, 0.5), max = 20 #' ) #' dist1 + dist2 #' @@ -1244,12 +1244,12 @@ c.dist_spec <- function(...) { ##' @export #' @examples #' # A fixed lognormal distribution with mean 5 and sd 1. -#' dist1 <- lognormal(mean = 5, sd = 1, max = 20) +#' dist1 <- LogNormal(mean = 5, sd = 1, max = 20) #' mean(dist1) #' #' # An uncertain gamma distribution with mean 3 and sd 2 -#' dist2 <- gamma( -#' mean = normal(3, 0.5), sd = normal(2, 0.5), max = 20 +#' dist2 <- Gamma( +#' mean = Normal(3, 0.5), sd = Normal(2, 0.5), max = 20 #' ) #' mean(dist2) #' @@ -1297,11 +1297,11 @@ mean.dist_spec <- function(x, ...) { ##' @examples ##' \dontrun{ ##' # A fixed lognormal distribution with sd 5 and sd 1. -##' dist1 <- lognormal(mean = 5, sd = 1, max = 20) +##' dist1 <- LogNormal(mean = 5, sd = 1, max = 20) ##' sd_dist(dist1) ##' ##' # A gamma distribution with mean 3 and sd 2 -##' dist2 <- gamma(mean = 3, sd = 2) +##' dist2 <- Gamma(mean = 3, sd = 2) ##' sd_dist(dist2) ##' ##' # The sd of the sum of two distributions @@ -1356,11 +1356,11 @@ sd_dist <- function(x) { ##' @export #' @examples #' # A fixed gamma distribution with mean 5 and sd 1. -#' dist1 <- gamma(mean = 5, sd = 1, max = 20) +#' dist1 <- Gamma(mean = 5, sd = 1, max = 20) #' max(dist1) #' #' # An uncertain lognormal distribution with mean 3 and sd 2 -#' dist2 <- lognormal(mean = normal(3, 0.5), sd = normal(2, 0.5), max = 20) +#' dist2 <- LogNormal(mean = Normal(3, 0.5), sd = Normal(2, 0.5), max = 20) #' max(dist2) #' #' # The mean of the sum of two distributions @@ -1390,12 +1390,12 @@ max.dist_spec <- function(x, ...) { #' @export #' @examples #' #' # A fixed lognormal distribution with mean 5 and sd 1. -#' dist1 <- lognormal(mean = 1.5, sd = 0.5, max = 20) +#' dist1 <- LogNormal(mean = 1.5, sd = 0.5, max = 20) #' print(dist1) #' #' # An uncertain gamma distribution with mean 3 and sd 2 -#' dist2 <- gamma( -#' mean = normal(3, 0.5), sd = normal(2, 0.5), max = 20 +#' dist2 <- Gamma( +#' mean = Normal(3, 0.5), sd = Normal(2, 0.5), max = 20 #' ) #' print(dist2) print.dist_spec <- function(x, ...) { @@ -1478,12 +1478,12 @@ print.dist_spec <- function(x, ...) { #' @author Sam Abbott #' @examples #' #' # A fixed lognormal distribution with mean 5 and sd 1. -#' dist1 <- lognormal(mean = 1.6, sd = 0.5, max = 20) +#' dist1 <- LogNormal(mean = 1.6, sd = 0.5, max = 20) #' plot(dist1) #' #' # An uncertain gamma distribution with mean 3 and sd 2 -#' dist2 <- gamma( -#' mean = normal(3, 0.5), sd = normal(2, 0.5), max = 20 +#' dist2 <- Gamma( +#' mean = Normal(3, 0.5), sd = Normal(2, 0.5), max = 20 #' ) #' plot(dist2) #' @@ -1639,7 +1639,7 @@ fix_dist <- function(x, strategy = c("mean", "sample")) { ## ##' All parameters can be given either as fixed values (a numeric value) or as ##' uncertain values (a `dist_sepc`). If given as uncertain values, currently -##' only normally distributed parameters (generated using `normal()`) are +##' only normally distributed parameters (generated using `Normal()`) are ##' supported. ##' ##' Each distribution has a representation in terms of "natural" parameters (the @@ -1665,9 +1665,9 @@ fix_dist <- function(x, strategy = c("mean", "sample")) { ##' @name Distributions ##' @order 1 ##' @examples -##' lognormal(mean = 4, sd = 1) -##' lognormal(mean = 4, sd = 1, max = 10) -##' lognormal(mean = normal(4, 1), sd = 1, max = 10) +##' LogNormal(mean = 4, sd = 1) +##' LogNormal(mean = 4, sd = 1, max = 10) +##' LogNormal(mean = Normal(4, 1), sd = 1, max = 10) lognormal <- function(meanlog, sdlog, mean, sd, max = Inf) { params <- as.list(environment()) return(generate_dist_spec(params, "lognormal")) @@ -1680,9 +1680,9 @@ lognormal <- function(meanlog, sdlog, mean, sd, max = Inf) { ##' @order 2 ##' @export ##' @examples -##' gamma(mean = 4, sd = 1) -##' gamma(shape = 16, rate = 4) -##' gamma(shape = normal(16, 2), rate = normal(4, 1)) +##' Gamma(mean = 4, sd = 1) +##' Gamma(shape = 16, rate = 4) +##' Gamma(shape = Normal(16, 2), rate = Normal(4, 1)) gamma <- function(shape, rate, scale, mean, sd, max = Inf) { params <- as.list(environment()) return(generate_dist_spec(params, "gamma")) @@ -1693,8 +1693,8 @@ gamma <- function(shape, rate, scale, mean, sd, max = Inf) { ##' @author Sebastian Funk ##' @export ##' @examples -##' normal(mean = 4, sd = 1) -##' normal(mean = 4, sd = 1, max = 10) +##' Normal(mean = 4, sd = 1) +##' Normal(mean = 4, sd = 1, max = 10) normal <- function(mean, sd, max = Inf) { params <- as.list(environment()) return(generate_dist_spec(params, "normal")) @@ -1706,8 +1706,8 @@ normal <- function(mean, sd, max = Inf) { ##' @author Sebastian Funk ##' @export ##' @examples -##' fixed(value = 3) -##' fixed(value = 3.5) +##' Fixed(value = 3) +##' Fixed(value = 3.5) fixed <- function(value) { params <- as.list(environment()) params <- extract_params(params, "fixed") @@ -1831,7 +1831,7 @@ generate_dist_spec <- function(params, distribution) { } x } else if (is.numeric(x)) { - fixed(x) + Fixed(x) } else { stop("Parameter ", x, " must be numeric or normally distributed.") } diff --git a/R/epinow.R b/R/epinow.R index 2b76b5a7e..4524fe22d 100644 --- a/R/epinow.R +++ b/R/epinow.R @@ -44,21 +44,21 @@ #' #' # set an example generation time. In practice this should use an estimate #' # from the literature or be estimated from data -#' generation_time <- gamma( -#' shape = normal(1.3, 0.3), -#' rate = normal(0.37, 0.09), +#' generation_time <- Gamma( +#' shape = Normal(1.3, 0.3), +#' rate = Normal(0.37, 0.09), #' max = 14 #' ) #' # set an example incubation period. In practice this should use an estimate #' # from the literature or be estimated from data -#' incubation_period <- lognormal( -#' meanlog = normal(1.6, 0.06), -#' sdlog = normal(0.4, 0.07), +#' incubation_period <- LogNormal( +#' meanlog = Normal(1.6, 0.06), +#' sdlog = Normal(0.4, 0.07), #' max = 14 #' ) #' # set an example reporting delay. In practice this should use an estimate #' # from the literature or be estimated from data -#' reporting_delay <- lognormal(mean = 2, sd = 1, max = 10) +#' reporting_delay <- LogNormal(mean = 2, sd = 1, max = 10) #' #' # example case data #' reported_cases <- example_confirmed[1:40] diff --git a/R/estimate_infections.R b/R/estimate_infections.R index f94b9f72e..2f84fc904 100644 --- a/R/estimate_infections.R +++ b/R/estimate_infections.R @@ -77,21 +77,21 @@ #' #' # set an example generation time. In practice this should use an estimate #' # from the literature or be estimated from data -#' generation_time <- gamma( -#' shape = normal(1.3, 0.3), -#' rate = normal(0.37, 0.09), +#' generation_time <- Gamma( +#' shape = Normal(1.3, 0.3), +#' rate = Normal(0.37, 0.09), #' max = 14 #' ) #' # set an example incubation period. In practice this should use an estimate #' # from the literature or be estimated from data -#' incubation_period <- lognormal( -#' meanlog = normal(1.6, 0.06), -#' sdlog = normal(0.4, 0.07), +#' incubation_period <- LogNormal( +#' meanlog = Normal(1.6, 0.06), +#' sdlog = Normal(0.4, 0.07), #' max = 14 #' ) #' # set an example reporting delay. In practice this should use an estimate #' # from the literature or be estimated from data -#' reporting_delay <- lognormal(mean = 2, sd = 1, max = 10) +#' reporting_delay <- LogNormal(mean = 2, sd = 1, max = 10) #' #' # for more examples, see the "estimate_infections examples" vignette #' def <- estimate_infections(reported_cases, diff --git a/R/estimate_secondary.R b/R/estimate_secondary.R index c1c69738e..f59d24b5c 100644 --- a/R/estimate_secondary.R +++ b/R/estimate_secondary.R @@ -137,9 +137,9 @@ estimate_secondary <- function(reports, secondary = secondary_opts(), delays = delay_opts( - lognormal( - meanlog = normal(2.5, 0.5), - sdlog = normal(0.47, 0.25), + LogNormal( + meanlog = Normal(2.5, 0.5), + sdlog = Normal(0.47, 0.25), max = 30 ) ), diff --git a/R/estimate_truncation.R b/R/estimate_truncation.R index 3220c7a8b..2e2e7c1c1 100644 --- a/R/estimate_truncation.R +++ b/R/estimate_truncation.R @@ -87,9 +87,9 @@ #' reported_cases <- example_confirmed[1:60] #' #' # define example truncation distribution (note not integer adjusted) -#' trunc <- lognormal( -#' meanlog = normal(0.9, 0.1), -#' sdlog = normal(0.6, 0.1), +#' trunc <- LogNormal( +#' meanlog = Normal(0.9, 0.1), +#' sdlog = Normal(0.6, 0.1), #' max = 10 #' ) #' @@ -140,8 +140,8 @@ #' options(old_opts) estimate_truncation <- function(obs, max_truncation, trunc_max = 10, trunc_dist = "lognormal", - truncation = lognormal( - meanlog = normal(0, 1), sdlog = normal(1, 1), + truncation = LogNormal( + meanlog = Normal(0, 1), sdlog = Normal(1, 1), max = 10 ), model = NULL, diff --git a/R/get.R b/R/get.R index 4a2b739a2..da30af4de 100644 --- a/R/get.R +++ b/R/get.R @@ -161,7 +161,7 @@ get_regional_results <- function(regional_output, #' @description `r lifecycle::badge("deprecated")` #' #' This function has been deprecated. Please specify a distribution -#' using functions such as [gamma()] or [lognormal()] instead. +#' using functions such as [Gamma()] or [LogNormal()] instead. #' #' @param data A `` in the format of `generation_times`. #' @@ -182,8 +182,8 @@ get_dist <- function(data, disease, source, max_value = 14, fixed = FALSE) { lifecycle::deprecate_warn( "2.0.0", "get_dist()", details = c( - paste0( - "Please use distribution functions such as `gamma` or `lognormal` ", + paste( + "Please use distribution functions such as `gamma()` or `lognormal()`", "instead." ), "The function will be removed completely in version 2.1.0." @@ -213,7 +213,7 @@ get_dist <- function(data, disease, source, max_value = 14, fixed = FALSE) { #' #' Extracts a literature distribution from `generation_times`. #' This function has been deprecated. Please specify a distribution -#' using functions such as [gamma()] or [lognormal()] instead. +#' using functions such as [Gamma()] or [LogNormal()] instead. #' #' @inheritParams get_dist #' @inherit get_dist @@ -225,7 +225,7 @@ get_generation_time <- function(disease, source, max_value = 14, "2.0.0", "get_generation_time()", details = c( paste( - "Please use distribution functions such as `gamma` or `lognormal`", + "Please use distribution functions such as `gamma()` or `lognormal()`", "instead." ), "The function will be removed completely in version 2.1.0.", @@ -248,7 +248,7 @@ get_generation_time <- function(disease, source, max_value = 14, #' #' Extracts a literature distribution from `generation_times`. #' This function has been deprecated. Please specify a distribution -#' using functions such as [gamma()] or [lognormal()] instead. +#' using functions such as [Gamma()] or [LogNormal()] instead. #' #' @inheritParams get_dist #' @inherit get_dist @@ -260,7 +260,7 @@ get_incubation_period <- function(disease, source, max_value = 14, "2.0.0", "get_incubation_period()", details = c( paste( - "Please use distribution functions such as `gamma` or `lognormal`", + "Please use distribution functions such as `gamma()` or `lognormal()`", "instead." ), "The function will be removed completely in version 2.1.0.", @@ -321,9 +321,9 @@ get_regions_with_most_reports <- function(reported_cases, ##' The seeding time is set to the mean of the specified delays, constrained ##' to be at least the maximum generation time ##' @param delays Delays specified using distribution functions such as -##' [gamma()] or [lognormal()] +##' [Gamma()] or [LogNormal()] ##' @param generation_time Generation specified using distribution functions -##' such as [gamma()] or [lognormal()] +##' such as [Gamma()] or [LogNormal()] ##' @return An integer seeding time ##' @author Sebastian Funk get_seeding_time <- function(delays, generation_time) { diff --git a/R/opts.R b/R/opts.R index 7a4ff499c..59bf91b73 100644 --- a/R/opts.R +++ b/R/opts.R @@ -19,27 +19,27 @@ #' @author Sebastian Funk #' @author Sam Abbott #' @seealso [convert_to_logmean()] [convert_to_logsd()] -#' [bootstrapped_dist_fit()] [gamma()] [lognormal()] [fixed()] +#' [bootstrapped_dist_fit()] [Gamma()] [LogNormal()] [Fixed()] #' @export #' @examples #' # default settings with a fixed generation time of 1 #' generation_time_opts() #' #' # A fixed gamma distributed generation time -#' generation_time_opts(gamma(mean = 3, sd = 2, max = 14)) +#' generation_time_opts(Gamma(mean = 3, sd = 2, max = 14)) #' #' # An uncertain gamma distributed generation time #' generation_time_opts( -#' gamma( -#' mean = normal(mean = 3, sd = 1), -#' sd = normal(mean = 2, sd = 0.5), +#' Gamma( +#' mean = Normal(mean = 3, sd = 1), +#' sd = Normal(mean = 2, sd = 0.5), #' max = 14 #' ) #' ) #' #' # An example generation time #' generation_time_opts(example_generation_time) -generation_time_opts <- function(dist = fixed(1), ..., +generation_time_opts <- function(dist = Fixed(1), ..., disease, source, max = 14, fixed = FALSE, prior_weight) { deprecated_options_given <- FALSE @@ -123,16 +123,16 @@ generation_time_opts <- function(dist = fixed(1), ..., #' delay_opts() #' #' # A single delay that has uncertainty -#' delay <- lognormal(mean = normal(1, 0.2), sd = normal(0.5, 0.1), max = 14) +#' delay <- LogNormal(mean = Normal(1, 0.2), sd = Normal(0.5, 0.1), max = 14) #' delay_opts(delay) #' #' # A single delay without uncertainty -#' delay <- lognormal(meanlog = 1, sdlog = 0.5, max = 14) +#' delay <- LogNormal(meanlog = 1, sdlog = 0.5, max = 14) #' delay_opts(delay) #' #' # Multiple delays (in this case twice the same) #' delay_opts(delay + delay) -delay_opts <- function(dist = fixed(0), ..., fixed = FALSE) { +delay_opts <- function(dist = Fixed(0), ..., fixed = FALSE) { dot_options <- list(...) if (!is(dist, "dist_spec")) { ## could be old syntax if (is.list(dist)) { @@ -192,7 +192,7 @@ delay_opts <- function(dist = fixed(0), ..., fixed = FALSE) { #' #' # truncation dist #' trunc_opts(dist = dist_spec(mean = 3, sd = 2, max = 10)) -trunc_opts <- function(dist = fixed(0)) { +trunc_opts <- function(dist = Fixed(0)) { if (!is(dist, "dist_spec")) { if (is.list(dist)) { dist <- do.call(dist_spec, dist) diff --git a/data-raw/estimate-infections.R b/data-raw/estimate-infections.R index f01a25dcc..aa278ef8f 100644 --- a/data-raw/estimate-infections.R +++ b/data-raw/estimate-infections.R @@ -7,7 +7,7 @@ options(mc.cores = 4) reported_cases <- example_confirmed[1:60] #' # use example distributions -reporting_delay <- lognormal(mean = 2, sd = 1, max = 10L) +reporting_delay <- LogNormal(mean = 2, sd = 1, max = 10L) example_estimate_infections <- estimate_infections(reported_cases, generation_time = generation_time_opts(example_generation_time), diff --git a/data-raw/generation-time.R b/data-raw/generation-time.R index 734dffacf..3f71e8757 100644 --- a/data-raw/generation-time.R +++ b/data-raw/generation-time.R @@ -10,9 +10,9 @@ library(here) ## Load raw MCMC output gi <- setDT(readRDS(here("data-raw", "gi.rds"))) ## Check mean and standard deviation -example_generation_time <- gamma( - mean = normal(median(gi$mean), sd(gi$mean)), - sd = normal(median(gi$sd), sd(gi$sd)), +example_generation_time <- Gamma( + mean = Normal(median(gi$mean), sd(gi$mean)), + sd = Normal(median(gi$sd), sd(gi$sd)), max = 14L ) diff --git a/data-raw/incubation-period.R b/data-raw/incubation-period.R index 8a234d8a5..97758ef32 100644 --- a/data-raw/incubation-period.R +++ b/data-raw/incubation-period.R @@ -3,9 +3,9 @@ library(EpiNow2) ## COVID-19 incubation period from Lauer et al., ## https://doi.org/10.7326/M20-0504 -example_incubation_period <- lognormal( - meanlog = normal(1.621, 0.0640), - sdlog = normal(0.418, 0.0691), +example_incubation_period <- LogNormal( + meanlog = Normal(1.621, 0.0640), + sdlog = Normal(0.418, 0.0691), max = 14L ) diff --git a/data-raw/reporting-delay.R b/data-raw/reporting-delay.R index b895fea44..e2cc12d33 100644 --- a/data-raw/reporting-delay.R +++ b/data-raw/reporting-delay.R @@ -2,8 +2,8 @@ library(EpiNow2) ## example reporting delay -example_reporting_delay <- lognormal( - meanlog = normal(0.6, 0.06), sdlog = normal(0.5, 0.05), max = 10L +example_reporting_delay <- LogNormal( + meanlog = Normal(0.6, 0.06), sdlog = Normal(0.5, 0.05), max = 10L ) usethis::use_data(example_reporting_delay, overwrite = TRUE) diff --git a/man/Distributions.Rd b/man/Distributions.Rd index 7e11c6ea2..89ec62aa3 100644 --- a/man/Distributions.Rd +++ b/man/Distributions.Rd @@ -9,13 +9,13 @@ \alias{pmf} \title{Probability distributions} \usage{ -lognormal(meanlog, sdlog, mean, sd, max = Inf) +LogNormal(meanlog, sdlog, mean, sd, max = Inf) -gamma(shape, rate, scale, mean, sd, max = Inf) +Gamma(shape, rate, scale, mean, sd, max = Inf) -normal(mean, sd, max = Inf) +Normal(mean, sd, max = Inf) -fixed(value) +Fixed(value) pmf(mass) } @@ -59,7 +59,7 @@ probability distribution that is being used. They generated \code{dist_spec} objects that are then passed to the models underlying EpiNow2. All parameters can be given either as fixed values (a numeric value) or as uncertain values (a \code{dist_sepc}). If given as uncertain values, currently -only normally distributed parameters (generated using \code{normal()}) are +only normally distributed parameters (generated using \code{Normal()}) are supported. Each distribution has a representation in terms of "natural" parameters (the @@ -75,16 +75,16 @@ Currently available distributions are lognormal, gamma, normal, fixed probability mass function is given directly as a numeric vector. } \examples{ -lognormal(mean = 4, sd = 1) -lognormal(mean = 4, sd = 1, max = 10) -lognormal(mean = normal(4, 1), sd = 1, max = 10) -gamma(mean = 4, sd = 1) -gamma(shape = 16, rate = 4) -gamma(shape = normal(16, 2), rate = normal(4, 1)) -normal(mean = 4, sd = 1) -normal(mean = 4, sd = 1, max = 10) -fixed(value = 3) -fixed(value = 3.5) +LogNormal(mean = 4, sd = 1) +LogNormal(mean = 4, sd = 1, max = 10) +LogNormal(mean = Normal(4, 1), sd = 1, max = 10) +Gamma(mean = 4, sd = 1) +Gamma(shape = 16, rate = 4) +Gamma(shape = Normal(16, 2), rate = Normal(4, 1)) +Normal(mean = 4, sd = 1) +Normal(mean = 4, sd = 1, max = 10) +Fixed(value = 3) +Fixed(value = 3.5) pmf(c(0.1, 0.3, 0.2, 0.4)) pmf(c(0.1, 0.3, 0.2, 0.1, 0.1)) } diff --git a/man/delay_opts.Rd b/man/delay_opts.Rd index a0c7360c1..fa2369ab3 100644 --- a/man/delay_opts.Rd +++ b/man/delay_opts.Rd @@ -4,7 +4,7 @@ \alias{delay_opts} \title{Delay Distribution Options} \usage{ -delay_opts(dist = fixed(0), ..., fixed = FALSE) +delay_opts(dist = Fixed(0), ..., fixed = FALSE) } \arguments{ \item{dist}{A delay distribution or series of delay distributions. Default is @@ -27,11 +27,11 @@ functions. delay_opts() # A single delay that has uncertainty -delay <- lognormal(mean = normal(1, 0.2), sd = normal(0.5, 0.1), max = 14) +delay <- LogNormal(mean = Normal(1, 0.2), sd = Normal(0.5, 0.1), max = 14) delay_opts(delay) # A single delay without uncertainty -delay <- lognormal(meanlog = 1, sdlog = 0.5, max = 14) +delay <- LogNormal(meanlog = 1, sdlog = 0.5, max = 14) delay_opts(delay) # Multiple delays (in this case twice the same) diff --git a/man/dist_spec.Rd b/man/dist_spec.Rd index 68a0ee493..e3159d38e 100644 --- a/man/dist_spec.Rd +++ b/man/dist_spec.Rd @@ -54,8 +54,8 @@ A list of distribution options. \ifelse{html}{\href{https://lifecycle.r-lib.org/articles/stages.html#deprecated}{\figure{lifecycle-deprecated.svg}{options: alt='[Deprecated]'}}}{\strong{[Deprecated]}} This function is deprecated as a user-facing function (while its functionality is still used internally). Construct distributions using -the corresponding distribution function such as \code{\link[=gamma]{gamma()}}, \code{\link[=lognormal]{lognormal()}}, -\code{\link[=normal]{normal()}} or \code{\link[=fixed]{fixed()}} instead. +the corresponding distribution function such as \code{\link[=Gamma]{Gamma()}}, \code{\link[=LogNormal]{LogNormal()}}, +\code{\link[=Normal]{Normal()}} or \code{\link[=Fixed]{Fixed()}} instead. } \author{ Sebastian Funk diff --git a/man/epinow.Rd b/man/epinow.Rd index b7661aaa6..513b21b0e 100644 --- a/man/epinow.Rd +++ b/man/epinow.Rd @@ -129,21 +129,21 @@ options(mc.cores = ifelse(interactive(), 4, 1)) # set an example generation time. In practice this should use an estimate # from the literature or be estimated from data -generation_time <- gamma( - shape = normal(1.3, 0.3), - rate = normal(0.37, 0.09), +generation_time <- Gamma( + shape = Normal(1.3, 0.3), + rate = Normal(0.37, 0.09), max = 14 ) # set an example incubation period. In practice this should use an estimate # from the literature or be estimated from data -incubation_period <- lognormal( - meanlog = normal(1.6, 0.06), - sdlog = normal(0.4, 0.07), +incubation_period <- LogNormal( + meanlog = Normal(1.6, 0.06), + sdlog = Normal(0.4, 0.07), max = 14 ) # set an example reporting delay. In practice this should use an estimate # from the literature or be estimated from data -reporting_delay <- lognormal(mean = 2, sd = 1, max = 10) +reporting_delay <- LogNormal(mean = 2, sd = 1, max = 10) # example case data reported_cases <- example_confirmed[1:40] diff --git a/man/estimate_infections.Rd b/man/estimate_infections.Rd index 11201253d..1e6e13074 100644 --- a/man/estimate_infections.Rd +++ b/man/estimate_infections.Rd @@ -118,21 +118,21 @@ reported_cases <- example_confirmed[1:60] # set an example generation time. In practice this should use an estimate # from the literature or be estimated from data -generation_time <- gamma( - shape = normal(1.3, 0.3), - rate = normal(0.37, 0.09), +generation_time <- Gamma( + shape = Normal(1.3, 0.3), + rate = Normal(0.37, 0.09), max = 14 ) # set an example incubation period. In practice this should use an estimate # from the literature or be estimated from data -incubation_period <- lognormal( - meanlog = normal(1.6, 0.06), - sdlog = normal(0.4, 0.07), +incubation_period <- LogNormal( + meanlog = Normal(1.6, 0.06), + sdlog = Normal(0.4, 0.07), max = 14 ) # set an example reporting delay. In practice this should use an estimate # from the literature or be estimated from data -reporting_delay <- lognormal(mean = 2, sd = 1, max = 10) +reporting_delay <- LogNormal(mean = 2, sd = 1, max = 10) # for more examples, see the "estimate_infections examples" vignette def <- estimate_infections(reported_cases, diff --git a/man/estimate_secondary.Rd b/man/estimate_secondary.Rd index d46e22dc3..f7078906e 100644 --- a/man/estimate_secondary.Rd +++ b/man/estimate_secondary.Rd @@ -7,7 +7,7 @@ estimate_secondary( reports, secondary = secondary_opts(), - delays = delay_opts(lognormal(meanlog = normal(2.5, 0.5), sdlog = normal(0.47, 0.25), + delays = delay_opts(LogNormal(meanlog = Normal(2.5, 0.5), sdlog = Normal(0.47, 0.25), max = 30)), truncation = trunc_opts(), obs = obs_opts(), diff --git a/man/estimate_truncation.Rd b/man/estimate_truncation.Rd index 6135e2798..5dfda8fdb 100644 --- a/man/estimate_truncation.Rd +++ b/man/estimate_truncation.Rd @@ -9,7 +9,7 @@ estimate_truncation( max_truncation, trunc_max = 10, trunc_dist = "lognormal", - truncation = lognormal(meanlog = normal(0, 1), sdlog = normal(1, 1), max = 10), + truncation = LogNormal(meanlog = Normal(0, 1), sdlog = Normal(1, 1), max = 10), model = NULL, stan = stan_opts(), CrIs = c(0.2, 0.5, 0.9), @@ -107,9 +107,9 @@ options(mc.cores = ifelse(interactive(), 4, 1)) reported_cases <- example_confirmed[1:60] # define example truncation distribution (note not integer adjusted) -trunc <- lognormal( - meanlog = normal(0.9, 0.1), - sdlog = normal(0.6, 0.1), +trunc <- LogNormal( + meanlog = Normal(0.9, 0.1), + sdlog = Normal(0.6, 0.1), max = 10 ) diff --git a/man/gamma_dist_def.Rd b/man/gamma_dist_def.Rd index bb2a9fce1..f590ac16c 100644 --- a/man/gamma_dist_def.Rd +++ b/man/gamma_dist_def.Rd @@ -44,7 +44,7 @@ A \verb{} defining the distribution as used by \code{\link[=dist_ske } \description{ \ifelse{html}{\href{https://lifecycle.r-lib.org/articles/stages.html#deprecated}{\figure{lifecycle-deprecated.svg}{options: alt='[Deprecated]'}}}{\strong{[Deprecated]}} -Deprecated; use \code{\link[=gamma]{gamma()}} instead to define a gamma distribution. +Deprecated; use \code{\link[=Gamma]{Gamma()}} instead to define a gamma distribution. } \examples{ # using estimated shape and scale diff --git a/man/generation_time_opts.Rd b/man/generation_time_opts.Rd index d3adc7e22..6b605dbb4 100644 --- a/man/generation_time_opts.Rd +++ b/man/generation_time_opts.Rd @@ -5,7 +5,7 @@ \title{Generation Time Distribution Options} \usage{ generation_time_opts( - dist = fixed(1), + dist = Fixed(1), ..., disease, source, @@ -45,13 +45,13 @@ Returns generation time parameters in a format for lower level model use. generation_time_opts() # A fixed gamma distributed generation time -generation_time_opts(gamma(mean = 3, sd = 2, max = 14)) +generation_time_opts(Gamma(mean = 3, sd = 2, max = 14)) # An uncertain gamma distributed generation time generation_time_opts( - gamma( - mean = normal(mean = 3, sd = 1), - sd = normal(mean = 2, sd = 0.5), + Gamma( + mean = Normal(mean = 3, sd = 1), + sd = Normal(mean = 2, sd = 0.5), max = 14 ) ) @@ -61,7 +61,7 @@ generation_time_opts(example_generation_time) } \seealso{ \code{\link[=convert_to_logmean]{convert_to_logmean()}} \code{\link[=convert_to_logsd]{convert_to_logsd()}} -\code{\link[=bootstrapped_dist_fit]{bootstrapped_dist_fit()}} \code{\link[=gamma]{gamma()}} \code{\link[=lognormal]{lognormal()}} \code{\link[=fixed]{fixed()}} +\code{\link[=bootstrapped_dist_fit]{bootstrapped_dist_fit()}} \code{\link[=Gamma]{Gamma()}} \code{\link[=LogNormal]{LogNormal()}} \code{\link[=Fixed]{Fixed()}} } \author{ Sebastian Funk diff --git a/man/get_dist.Rd b/man/get_dist.Rd index 0479dab07..0621d9ddb 100644 --- a/man/get_dist.Rd +++ b/man/get_dist.Rd @@ -25,7 +25,7 @@ A list defining a distribution \ifelse{html}{\href{https://lifecycle.r-lib.org/articles/stages.html#deprecated}{\figure{lifecycle-deprecated.svg}{options: alt='[Deprecated]'}}}{\strong{[Deprecated]}} This function has been deprecated. Please specify a distribution -using functions such as \code{\link[=gamma]{gamma()}} or \code{\link[=lognormal]{lognormal()}} instead. +using functions such as \code{\link[=Gamma]{Gamma()}} or \code{\link[=LogNormal]{LogNormal()}} instead. } \author{ Sam Abbott diff --git a/man/get_generation_time.Rd b/man/get_generation_time.Rd index 12b36076f..aaad142ec 100644 --- a/man/get_generation_time.Rd +++ b/man/get_generation_time.Rd @@ -24,7 +24,7 @@ A list defining a distribution Extracts a literature distribution from \code{generation_times}. This function has been deprecated. Please specify a distribution -using functions such as \code{\link[=gamma]{gamma()}} or \code{\link[=lognormal]{lognormal()}} instead. +using functions such as \code{\link[=Gamma]{Gamma()}} or \code{\link[=LogNormal]{LogNormal()}} instead. } \author{ Sam Abbott diff --git a/man/get_incubation_period.Rd b/man/get_incubation_period.Rd index b1de608f3..2b39aadde 100644 --- a/man/get_incubation_period.Rd +++ b/man/get_incubation_period.Rd @@ -24,7 +24,7 @@ A list defining a distribution Extracts a literature distribution from \code{generation_times}. This function has been deprecated. Please specify a distribution -using functions such as \code{\link[=gamma]{gamma()}} or \code{\link[=lognormal]{lognormal()}} instead. +using functions such as \code{\link[=Gamma]{Gamma()}} or \code{\link[=LogNormal]{LogNormal()}} instead. } \author{ Sam Abbott diff --git a/man/get_seeding_time.Rd b/man/get_seeding_time.Rd index 0f6a8e54a..645020092 100644 --- a/man/get_seeding_time.Rd +++ b/man/get_seeding_time.Rd @@ -8,10 +8,10 @@ get_seeding_time(delays, generation_time) } \arguments{ \item{delays}{Delays specified using distribution functions such as -\code{\link[=gamma]{gamma()}} or \code{\link[=lognormal]{lognormal()}}} +\code{\link[=Gamma]{Gamma()}} or \code{\link[=LogNormal]{LogNormal()}}} \item{generation_time}{Generation specified using distribution functions -such as \code{\link[=gamma]{gamma()}} or \code{\link[=lognormal]{lognormal()}}} +such as \code{\link[=Gamma]{Gamma()}} or \code{\link[=LogNormal]{LogNormal()}}} } \value{ An integer seeding time diff --git a/man/max.dist_spec.Rd b/man/max.dist_spec.Rd index f1d11576e..05887408d 100644 --- a/man/max.dist_spec.Rd +++ b/man/max.dist_spec.Rd @@ -21,11 +21,11 @@ in parameters) } \examples{ # A fixed gamma distribution with mean 5 and sd 1. -dist1 <- gamma(mean = 5, sd = 1, max = 20) +dist1 <- Gamma(mean = 5, sd = 1, max = 20) max(dist1) # An uncertain lognormal distribution with mean 3 and sd 2 -dist2 <- lognormal(mean = normal(3, 0.5), sd = normal(2, 0.5), max = 20) +dist2 <- LogNormal(mean = Normal(3, 0.5), sd = Normal(2, 0.5), max = 20) max(dist2) # The mean of the sum of two distributions diff --git a/man/mean.dist_spec.Rd b/man/mean.dist_spec.Rd index ca4f70c34..e27fdae8a 100644 --- a/man/mean.dist_spec.Rd +++ b/man/mean.dist_spec.Rd @@ -21,12 +21,12 @@ in parameters) } \examples{ # A fixed lognormal distribution with mean 5 and sd 1. -dist1 <- lognormal(mean = 5, sd = 1, max = 20) +dist1 <- LogNormal(mean = 5, sd = 1, max = 20) mean(dist1) # An uncertain gamma distribution with mean 3 and sd 2 -dist2 <- gamma( - mean = normal(3, 0.5), sd = normal(2, 0.5), max = 20 +dist2 <- Gamma( + mean = Normal(3, 0.5), sd = Normal(2, 0.5), max = 20 ) mean(dist2) diff --git a/man/plot.dist_spec.Rd b/man/plot.dist_spec.Rd index 091f7bc88..20383a78e 100644 --- a/man/plot.dist_spec.Rd +++ b/man/plot.dist_spec.Rd @@ -18,12 +18,12 @@ Note that currently uncertainty in distributions is not plot. } \examples{ #' # A fixed lognormal distribution with mean 5 and sd 1. -dist1 <- lognormal(mean = 1.6, sd = 0.5, max = 20) +dist1 <- LogNormal(mean = 1.6, sd = 0.5, max = 20) plot(dist1) # An uncertain gamma distribution with mean 3 and sd 2 -dist2 <- gamma( - mean = normal(3, 0.5), sd = normal(2, 0.5), max = 20 +dist2 <- Gamma( + mean = Normal(3, 0.5), sd = Normal(2, 0.5), max = 20 ) plot(dist2) diff --git a/man/plus-.dist_spec.Rd b/man/plus-.dist_spec.Rd index c768d13b5..453b2b227 100644 --- a/man/plus-.dist_spec.Rd +++ b/man/plus-.dist_spec.Rd @@ -25,14 +25,14 @@ numeric stability. } \examples{ # A fixed lognormal distribution with mean 5 and sd 1. -dist1 <- lognormal( +dist1 <- LogNormal( meanlog = 1.6, sdlog = 1, max = 20 ) dist1 + dist1 # An uncertain gamma distribution with mean 3 and sd 2 -dist2 <- gamma( - mean = normal(3, 0.5), sd = normal(2, 0.5), max = 20 +dist2 <- Gamma( + mean = Normal(3, 0.5), sd = Normal(2, 0.5), max = 20 ) dist1 + dist2 diff --git a/man/print.dist_spec.Rd b/man/print.dist_spec.Rd index b2ebd9b1d..0b3a346a2 100644 --- a/man/print.dist_spec.Rd +++ b/man/print.dist_spec.Rd @@ -20,12 +20,12 @@ functions of fixed delay distributions combined in the passed \code{\link[=dist_ } \examples{ #' # A fixed lognormal distribution with mean 5 and sd 1. -dist1 <- lognormal(mean = 1.5, sd = 0.5, max = 20) +dist1 <- LogNormal(mean = 1.5, sd = 0.5, max = 20) print(dist1) # An uncertain gamma distribution with mean 3 and sd 2 -dist2 <- gamma( - mean = normal(3, 0.5), sd = normal(2, 0.5), max = 20 +dist2 <- Gamma( + mean = Normal(3, 0.5), sd = Normal(2, 0.5), max = 20 ) print(dist2) } diff --git a/man/sd_dist.Rd b/man/sd_dist.Rd index 341e1585d..0751b31d0 100644 --- a/man/sd_dist.Rd +++ b/man/sd_dist.Rd @@ -19,11 +19,11 @@ nonparametric) delay distributions combined in the passed \code{\link[=dist_spec \examples{ \dontrun{ # A fixed lognormal distribution with sd 5 and sd 1. -dist1 <- lognormal(mean = 5, sd = 1, max = 20) +dist1 <- LogNormal(mean = 5, sd = 1, max = 20) sd_dist(dist1) # A gamma distribution with mean 3 and sd 2 -dist2 <- gamma(mean = 3, sd = 2) +dist2 <- Gamma(mean = 3, sd = 2) sd_dist(dist2) # The sd of the sum of two distributions diff --git a/man/trunc_opts.Rd b/man/trunc_opts.Rd index bb38a3fa7..950865386 100644 --- a/man/trunc_opts.Rd +++ b/man/trunc_opts.Rd @@ -4,7 +4,7 @@ \alias{trunc_opts} \title{Truncation Distribution Options} \usage{ -trunc_opts(dist = fixed(0)) +trunc_opts(dist = Fixed(0)) } \arguments{ \item{dist}{A delay distribution or series of delay distributions reflecting diff --git a/tests/testthat/test-adjust_infection_to_report.R b/tests/testthat/test-adjust_infection_to_report.R index 7b052befd..33e8502f4 100644 --- a/tests/testthat/test-adjust_infection_to_report.R +++ b/tests/testthat/test-adjust_infection_to_report.R @@ -3,8 +3,8 @@ cases <- data.table::copy(example_confirmed)[, cases := as.integer(confirm)] # define a single report delay distribution -delay <- lognormal( - meanlog = normal(1.4, 0.3), sdlog = normal(0.6, 0.2), max = 30 +delay <- LogNormal( + meanlog = Normal(1.4, 0.3), sdlog = Normal(0.6, 0.2), max = 30 ) test_that("adjust_infection_to_report can correctly handle a simple mapping", { diff --git a/tests/testthat/test-delays.R b/tests/testthat/test-delays.R index 35b3faea9..57ce46aee 100644 --- a/tests/testthat/test-delays.R +++ b/tests/testthat/test-delays.R @@ -21,7 +21,7 @@ test_that("generation times can be specified in different ways", { ) expect_equal( test_stan_delays( - generation_time = generation_time_opts(fixed(value = 3)), + generation_time = generation_time_opts(Fixed(value = 3)), params = delay_params ), c(0, 0, 0, 1, 1, 1) @@ -29,7 +29,7 @@ test_that("generation times can be specified in different ways", { expect_equal( round(test_stan_delays( generation_time = generation_time_opts( - lognormal(meanlog = 3, sdlog = 1, max = 4) + LogNormal(meanlog = 3, sdlog = 1, max = 4) ), params = delay_params ), digits = 2), @@ -40,7 +40,7 @@ test_that("generation times can be specified in different ways", { test_that("delay parameters can be specified in different ways", { expect_equal( tail(test_stan_delays( - delays = delay_opts(fixed(value = 3)), + delays = delay_opts(Fixed(value = 3)), params = delay_params ), n = -2), c(0, 0, 0, 1, 1) @@ -48,7 +48,7 @@ test_that("delay parameters can be specified in different ways", { expect_equal( tail(round(test_stan_delays( delays = delay_opts( - lognormal(meanlog = 3, sdlog = 1, max = 4) + LogNormal(meanlog = 3, sdlog = 1, max = 4) ), params = delay_params ), digits = 2), n = -2), @@ -60,7 +60,7 @@ test_that("truncation parameters can be specified in different ways", { expect_equal( tail(round(test_stan_delays( truncation = trunc_opts( - dist = lognormal(meanlog = 3, sdlog = 1, max = 4) + dist = LogNormal(meanlog = 3, sdlog = 1, max = 4) ), params = delay_params ), digits = 2), n = -2), @@ -70,9 +70,9 @@ test_that("truncation parameters can be specified in different ways", { test_that("distributions incompatible with stan models are caught", { expect_error(generation_time_opts( - gamma(2, 2) + Gamma(2, 2) ), "maximum") expect_error(delay_opts( - normal(2, 2) + Normal(2, 2) ), "lognormal") }) diff --git a/tests/testthat/test-dist_spec.R b/tests/testthat/test-dist_spec.R index 00b4048b2..d5a5b89a0 100644 --- a/tests/testthat/test-dist_spec.R +++ b/tests/testthat/test-dist_spec.R @@ -1,6 +1,6 @@ test_that("dist_spec returns correct output for fixed lognormal distribution", { - result <- lognormal(meanlog = 5, sdlog = 1, max = 19) + result <- LogNormal(meanlog = 5, sdlog = 1, max = 19) expect_equal(dim(result$params_mean), 0) expect_equal(dim(result$dist), 0) expect_equal(dim(result$max), 0) @@ -14,7 +14,7 @@ test_that("dist_spec returns correct output for fixed lognormal distribution", { }) test_that("dist_spec returns correct output for uncertain gamma distribution", { - result <- gamma(shape = normal(3, 0.5), rate = normal(2, 0.5), max = 19) + result <- Gamma(shape = Normal(3, 0.5), rate = Normal(2, 0.5), max = 19) expect_equal(result$params_mean, array(c(3, 2))) expect_equal(result$params_sd, array(c(0.5, 0.5))) expect_equal(result$dist, array("gamma")) @@ -23,7 +23,7 @@ test_that("dist_spec returns correct output for uncertain gamma distribution", { }) test_that("dist_spec returns correct output for fixed distribution", { - result <- fix_dist(lognormal(meanlog = normal(5, 3), sdlog = 1, max = 19)) + result <- fix_dist(LogNormal(meanlog = Normal(5, 3), sdlog = 1, max = 19)) expect_equal(dim(result$params_mean), 0) expect_equal(result$parametric, array(FALSE)) expect_equal( @@ -36,19 +36,19 @@ test_that("dist_spec returns correct output for fixed distribution", { test_that("dist_spec returns error when mixed natural and unnatural parameters are specified", { expect_error( - lognormal(meanlog = 5, sd = 1, max = 20), + LogNormal(meanlog = 5, sd = 1, max = 20), "Incompatible combination." ) }) test_that("dist_spec returns error when the wrong number of paramters are given", { - expect_error(lognormal(sd = 1, max = 20), "must be specified") - expect_error(gamma(shape = 1, rate = 2, mean = 3), "must be specified") + expect_error(LogNormal(sd = 1, max = 20), "must be specified") + expect_error(Gamma(shape = 1, rate = 2, mean = 3), "must be specified") }) test_that("+.dist_spec returns correct output for sum of two distributions", { - dist1 <- lognormal(meanlog = 5, sdlog = 1, max = 19) - dist2 <- gamma(shape = normal(3, 0.5), rate = normal(2, 0.5), max = 20) + dist1 <- LogNormal(meanlog = 5, sdlog = 1, max = 19) + dist2 <- Gamma(shape = Normal(3, 0.5), rate = Normal(2, 0.5), max = 20) result <- dist1 + dist2 expect_equal(result$params_mean, array(c(3, 2))) expect_equal(result$params_sd, array(c(0.5, 0.5))) @@ -59,8 +59,8 @@ test_that("+.dist_spec returns correct output for sum of two distributions", { }) test_that("+.dist_spec returns correct output for sum of two fixed distributions", { - dist1 <- lognormal(meanlog = 5, sdlog = 1, max = 19) - dist2 <- gamma(mean = 3, sd = 2, max = 19) + dist1 <- LogNormal(meanlog = 5, sdlog = 1, max = 19) + dist2 <- Gamma(mean = 3, sd = 2, max = 19) result <- dist1 + dist2 expect_equal(dim(result$params_mean), 0) expect_equal(result$n, 1) @@ -86,8 +86,8 @@ test_that("+.dist_spec returns correct output for sum of two nonparametric distr test_that("Testing `+.dist_spec` function with tolerance parameter", { # Create distributions - dist1 <- lognormal(meanlog = 1.6, sdlog = 1, max = 19) - dist2 <- gamma(mean = 3, sd = 2, max = 19) + dist1 <- LogNormal(meanlog = 1.6, sdlog = 1, max = 19) + dist2 <- Gamma(mean = 3, sd = 2, max = 19) # Compute combined distribution with default tolerance combined_default <- EpiNow2:::`+.dist_spec`(dist1, dist2) @@ -115,7 +115,7 @@ test_that("Testing `+.dist_spec` function with tolerance parameter", { }) test_that("summary functions return correct output for fixed lognormal distribution", { - dist <- lognormal(mean = 3, sd = 1, max = 19) + dist <- LogNormal(mean = 3, sd = 1, max = 19) ## here we can see the bias from # using this kind of discretisation approach expect_equal(EpiNow2:::mean.dist_spec(dist), 2.49, tolerance = 0.01) @@ -124,14 +124,14 @@ test_that("summary functions return correct output for fixed lognormal distribut }) test_that("summary functions return correct output for uncertain gamma distribution", { - dist <- gamma(shape = normal(3, 0.5), rate = normal(2, 0.5), max = 19) + dist <- Gamma(shape = Normal(3, 0.5), rate = Normal(2, 0.5), max = 19) expect_equal(EpiNow2:::mean.dist_spec(dist), 1.5) expect_equal(EpiNow2:::max.dist_spec(dist), 19L) }) test_that("mean.dist_spec returns correct output for sum of two distributions", { - dist1 <- lognormal(meanlog = 1, sdlog = 1, max = 19) - dist2 <- gamma(mean = 3, sd = 2, max = 19) + dist1 <- LogNormal(meanlog = 1, sdlog = 1, max = 19) + dist2 <- Gamma(mean = 3, sd = 2, max = 19) dist <- dist1 + dist2 expect_equal(EpiNow2:::mean.dist_spec(dist), c(5.84), tolerance = 0.001) expect_equal(EpiNow2:::sd_dist(dist), c(16.88), tolerance = 0.001) @@ -140,56 +140,56 @@ test_that("mean.dist_spec returns correct output for sum of two distributions", }) test_that("sd_dist returns an error when applied to uncertain distributions", { - dist <- gamma(shape = normal(3, 0.5), rate = normal(2, 0.5), max = 19) + dist <- Gamma(shape = Normal(3, 0.5), rate = Normal(2, 0.5), max = 19) expect_error(EpiNow2:::sd_dist(dist), "uncertain") }) test_that("print.dist_spec correctly prints the parameters of the fixed lognormal", { - dist <- lognormal(meanlog = 1.5, sdlog = 0.5, max = 19) + dist <- LogNormal(meanlog = 1.5, sdlog = 0.5, max = 19) expect_output(print(dist), "\\n distribution with PMF \\[0\\.0014 0\\.052 0\\.16 0\\.2 0\\.18 0\\.13 0\\.094 0\\.063 0\\.042 0\\.027 0\\.018 0\\.012 0\\.0079 0\\.0052 0\\.0035 0\\.0024 0\\.0016 0\\.0011 0\\.00078 0\\.00055\\]\\.\\n") }) test_that("print.dist_spec correctly prints the parameters of the uncertain gamma", { - gamma <- gamma( - shape = normal(3, 0.5), rate = normal(2, 0.5), max = 19 + gamma <- Gamma( + shape = Normal(3, 0.5), rate = Normal(2, 0.5), max = 19 ) expect_output(print(gamma), "\\n gamma distribution \\(max: 19\\) with uncertain shape \\(mean = 3, sd = 0.5\\) and uncertain rate \\(mean = 2, sd = 0\\.5\\)\\.\\n") }) test_that("print.dist_spec correctly prints the parameters of the uncertain lognormal", { - dist <- lognormal( - meanlog = normal(1.5, 0.1), sdlog = normal(0.5, 0.1), max = 19 + dist <- LogNormal( + meanlog = Normal(1.5, 0.1), sdlog = Normal(0.5, 0.1), max = 19 ) expect_output(print(dist), "\\n lognormal distribution \\(max: 19\\) with uncertain meanlog \\(mean = 1\\.5, sd = 0\\.1\\) and uncertain sdlog \\(mean = 0\\.5, sd = 0\\.1\\)\\.\\n") }) test_that("print.dist_spec correctly prints the parameters of a combination of distributions", { - dist1 <- lognormal(meanlog = 1.5, sdlog = 0.5, max = 19) - dist2 <- gamma(shape = normal(3, 0.5), rate = normal(2, 0.5), max = 19) + dist1 <- LogNormal(meanlog = 1.5, sdlog = 0.5, max = 19) + dist2 <- Gamma(shape = Normal(3, 0.5), rate = Normal(2, 0.5), max = 19) combined <- dist1 + dist2 expect_output(print(combined), "\\nComposite delay distribution:\\n distribution with PMF \\[0\\.0014 0\\.052 0\\.16 0\\.2 0\\.18 0\\.13 0\\.094 0\\.063 0\\.042 0\\.027 0\\.018 0\\.012 0\\.0079 0\\.0052 0\\.0035 0\\.0024 0\\.0016 0\\.0011 0\\.00078 0\\.00055\\]\\.\\n gamma distribution \\(max: 19\\) with uncertain shape \\(mean = 3, sd = 0\\.5\\) and uncertain rate \\(mean = 2, sd = 0\\.5\\)\\.\\n") }) test_that("plot.dist_spec returns a ggplot object", { - dist <- lognormal(meanlog = 1.6, sdlog = 0.5, max = 19) + dist <- LogNormal(meanlog = 1.6, sdlog = 0.5, max = 19) plot <- plot(dist) expect_s3_class(plot, "ggplot") }) test_that("plot.dist_spec correctly plots a single distribution", { - dist <- lognormal(meanlog = 1.6, sdlog = 0.5, max = 19) + dist <- LogNormal(meanlog = 1.6, sdlog = 0.5, max = 19) plot <- plot(dist) expect_equal(length(plot$layers), 2) expect_equal(length(plot$facet$params$facets), 1) }) test_that("plot.dist_spec correctly plots multiple distributions", { - dist1 <- lognormal(meanlog = 1.6, sdlog = 0.5, max = 19) - dist2 <- gamma(shape = normal(3, 5), rate = normal(1, 2), max = 19) + dist1 <- LogNormal(meanlog = 1.6, sdlog = 0.5, max = 19) + dist2 <- Gamma(shape = Normal(3, 5), rate = Normal(1, 2), max = 19) combined <- dist1 + dist2 plot <- plot(combined) expect_equal(length(plot$layers), 2) @@ -197,7 +197,7 @@ test_that("plot.dist_spec correctly plots multiple distributions", { }) test_that("plot.dist_spec correctly plots a combination of fixed distributions", { - dist <- lognormal(meanlog = 1.6, sdlog = 0.5, max = 19) + dist <- LogNormal(meanlog = 1.6, sdlog = 0.5, max = 19) combined <- dist + dist plot <- plot(combined) expect_equal(length(plot$layers), 2) @@ -205,15 +205,15 @@ test_that("plot.dist_spec correctly plots a combination of fixed distributions", }) test_that("fix_dist works with composite delay distributions", { - dist1 <- lognormal(meanlog = normal(1, 0.1), sdlog = 1, max = 19) - dist2 <- gamma(mean = 3, sd = 2, max = 19) + dist1 <- LogNormal(meanlog = Normal(1, 0.1), sdlog = 1, max = 19) + dist2 <- Gamma(mean = 3, sd = 2, max = 19) dist <- dist1 + dist2 expect_equal(fix_dist(dist)$n, 1L) }) test_that("composite delay distriubtions can be disassembled", { - dist1 <- lognormal(meanlog = normal(1, 0.1), sdlog = 1, max = 19) - dist2 <- gamma(mean = 3, sd = 2, max = 19) + dist1 <- LogNormal(meanlog = Normal(1, 0.1), sdlog = 1, max = 19) + dist2 <- Gamma(mean = 3, sd = 2, max = 19) dist <- dist1 + dist2 expect_equal(EpiNow2:::extract_single_dist(dist, 1), dist1) expect_equal(EpiNow2:::extract_single_dist(dist, 2), dist2) @@ -221,40 +221,40 @@ test_that("composite delay distriubtions can be disassembled", { test_that("delay distributions can be specified in different ways", { expect_equal( - lognormal(mean = 4, sd = 1)$params_mean, array(c(1.4, 0.25)), + LogNormal(mean = 4, sd = 1)$params_mean, array(c(1.4, 0.25)), tolerance = 0.1 ) expect_equal( - round(lognormal(mean = 4, sd = 1, max = 10)$np_pmf, 2), + round(LogNormal(mean = 4, sd = 1, max = 10)$np_pmf, 2), array(c(0.00, 0.00, 0.14, 0.40, 0.30, 0.11, 0.03, 0.01, 0.00, 0.00, 0.00)) ) expect_equal( - gamma(mean = 4, sd = 1)$params_mean, array(c(16, 4)), + Gamma(mean = 4, sd = 1)$params_mean, array(c(16, 4)), tolerance = 0.1 ) expect_equal( - round(gamma(mean = 4, sd = 1, max = 7)$np_pmf, 2), + round(Gamma(mean = 4, sd = 1, max = 7)$np_pmf, 2), array(c(0.00, 0.01, 0.15, 0.38, 0.31, 0.12, 0.03, 0.00)) ) expect_equal( - gamma(shape = normal(16, 2), rate = normal(4, 1))$params_mean, + Gamma(shape = Normal(16, 2), rate = Normal(4, 1))$params_mean, array(c(16, 4)) ) expect_equal( - gamma(shape = normal(16, 2), rate = normal(4, 1))$params_sd, + Gamma(shape = Normal(16, 2), rate = Normal(4, 1))$params_sd, array(c(2, 1)) ) expect_equal( - normal(mean = 4, sd = 1)$params_mean, array(c(4, 1)) + Normal(mean = 4, sd = 1)$params_mean, array(c(4, 1)) ) expect_equal( - round(normal(mean = 4, sd = 1, max = 5)$np_pmf, 2), + round(Normal(mean = 4, sd = 1, max = 5)$np_pmf, 2), array(c(0.00, 0.02, 0.14, 0.35, 0.35, 0.14)) ) expect_equal( - fixed(value = 3)$np_pmf, array(c(0, 0, 0, 1)) + Fixed(value = 3)$np_pmf, array(c(0, 0, 0, 1)) ) - expect_equal(fixed(value = 3.5)$params_mean, array(3.5)) + expect_equal(Fixed(value = 3.5)$params_mean, array(3.5)) expect_equal(pmf(c(0.1, 0.3, 0.2, 0.4))$np_pmf, array(c(0.1, 0.3, 0.2, 0.4))) expect_equal( round(pmf(c(0.1, 0.3, 0.2, 0.1, 0.1))$np_pmf, 2), diff --git a/tests/testthat/test-epinow.R b/tests/testthat/test-epinow.R index 278ade874..882f7a128 100644 --- a/tests/testthat/test-epinow.R +++ b/tests/testthat/test-epinow.R @@ -1,9 +1,9 @@ skip_on_cran() # set example reporting delay -reporting_delay <- lognormal( - meanlog = normal(0.6, 0.06), - sdlog = normal(0.5, 0.1), +reporting_delay <- LogNormal( + meanlog = Normal(0.6, 0.06), + sdlog = Normal(0.5, 0.1), max = 10 ) diff --git a/tests/testthat/test-estimate_secondary.R b/tests/testthat/test-estimate_secondary.R index 55f2117ea..c3ad21880 100644 --- a/tests/testthat/test-estimate_secondary.R +++ b/tests/testthat/test-estimate_secondary.R @@ -188,9 +188,9 @@ test_that("forecast_secondary can return values from simulated data when using }) test_that("estimate_secondary works with weigh_delay_priors = TRUE", { - delays <- lognormal( - meanlog = normal(2.5, 0.5), - sdlog = normal(0.47, 0.25), + delays <- LogNormal( + meanlog = Normal(2.5, 0.5), + sdlog = Normal(0.47, 0.25), max = 30 ) inc_weigh <- estimate_secondary( diff --git a/tests/testthat/test-estimate_truncation.R b/tests/testthat/test-estimate_truncation.R index 618725f62..6e89a1c62 100644 --- a/tests/testthat/test-estimate_truncation.R +++ b/tests/testthat/test-estimate_truncation.R @@ -10,9 +10,9 @@ options(mc.cores = ifelse(interactive(), 4, 1)) reported_cases <- example_confirmed[1:60] # define example truncation distribution (note not integer adjusted) -trunc_dist <- lognormal( - meanlog = normal(0.9, 0.1), - sdlog = normal(0.6, 0.1), +trunc_dist <- LogNormal( + meanlog = Normal(0.9, 0.1), + sdlog = Normal(0.6, 0.1), max = 10 ) diff --git a/tests/testthat/test-seeding-time.R b/tests/testthat/test-seeding-time.R index 68873b9ed..b6e99796c 100644 --- a/tests/testthat/test-seeding-time.R +++ b/tests/testthat/test-seeding-time.R @@ -1,8 +1,8 @@ test_that("Seeding times are correctly calculated", { - gt1 <- lognormal(meanlog = 5, sdlog = 1, max = 9) - gt2 <- lognormal(meanlog = 10, sdlog = 2, max = 14) - delay1 <- lognormal(meanlog = 5, sdlog = 1, max = 9) - delay2 <- lognormal(meanlog = 7, sdlog = 3, max = 14) + gt1 <- LogNormal(meanlog = 5, sdlog = 1, max = 9) + gt2 <- LogNormal(meanlog = 10, sdlog = 2, max = 14) + delay1 <- LogNormal(meanlog = 5, sdlog = 1, max = 9) + delay2 <- LogNormal(meanlog = 7, sdlog = 3, max = 14) expect_equal( EpiNow2:::get_seeding_time(delay1, gt1 + gt2), 23L ## 10 + 15 - 1 - 1 ) @@ -12,7 +12,7 @@ test_that("Seeding times are correctly calculated", { }) test_that("Short seeding times are rounded up to 1", { - delay <- lognormal(meanlog = 0.5, sdlog = 1, max = 2) - gt <- fixed(value = 1) + delay <- LogNormal(meanlog = 0.5, sdlog = 1, max = 2) + gt <- Fixed(value = 1) expect_equal(EpiNow2:::get_seeding_time(delay, gt), 1L) }) diff --git a/vignettes/epinow.Rmd b/vignettes/epinow.Rmd index 60a7d62d0..ee6bb0524 100644 --- a/vignettes/epinow.Rmd +++ b/vignettes/epinow.Rmd @@ -30,7 +30,7 @@ This should be replaced with parameters relevant to the system that is being stu library("EpiNow2") options(mc.cores = 4) reported_cases <- example_confirmed[1:60] -reporting_delay <- lognormal(mean = 2, sd = 1, max = 10) +reporting_delay <- LogNormal(mean = 2, sd = 1, max = 10) delay <- example_incubation_period + reporting_delay rt_prior <- list(mean = 2, sd = 0.1) ``` diff --git a/vignettes/epinow.Rmd.orig b/vignettes/epinow.Rmd.orig index 87b30c40b..b0b2fb782 100644 --- a/vignettes/epinow.Rmd.orig +++ b/vignettes/epinow.Rmd.orig @@ -36,7 +36,7 @@ This should be replaced with parameters relevant to the system that is being stu library("EpiNow2") options(mc.cores = 4) reported_cases <- example_confirmed[1:60] -reporting_delay <- lognormal(mean = 2, sd = 1, max = 10) +reporting_delay <- LogNormal(mean = 2, sd = 1, max = 10) delay <- example_incubation_period + reporting_delay rt_prior <- list(mean = 2, sd = 0.1) ``` diff --git a/vignettes/estimate_infections_options.Rmd b/vignettes/estimate_infections_options.Rmd index 8dcca7c64..fe39d08ba 100644 --- a/vignettes/estimate_infections_options.Rmd +++ b/vignettes/estimate_infections_options.Rmd @@ -88,7 +88,7 @@ Note that the mean and standard deviation must be converted to the log scale, wh ```r -reporting_delay <- lognormal(mean = 2, sd = 1, max = 10) +reporting_delay <- LogNormal(mean = 2, sd = 1, max = 10) #> Warning: The meaning of the 'max' argument has changed compared to previous versions. It now indicates the maximum of a distribution rather than the length of the probability mass function (including 0) that it represented previously. To replicate previous behaviour reduce max by 1. #> This warning is displayed once every 8 hours. reporting_delay @@ -254,7 +254,7 @@ Here, instead of doing so we assume that we know about truncation with mean of 1 ```r -trunc_dist <- lognormal( +trunc_dist <- LogNormal( mean = normal(0.5, 0.1), sd = normal(0.5, 0.1), max = 3 diff --git a/vignettes/estimate_infections_options.Rmd.orig b/vignettes/estimate_infections_options.Rmd.orig index 0292ec899..f1339b6ec 100644 --- a/vignettes/estimate_infections_options.Rmd.orig +++ b/vignettes/estimate_infections_options.Rmd.orig @@ -71,7 +71,7 @@ For the reporting delay, we use a lognormal distribution with mean of 2 days and Note that the mean and standard deviation must be converted to the log scale, which can be done using the `convert_log_logmean()` function. ```{r reporting_delay} -reporting_delay <- lognormal(mean = 2, sd = 1, max = 10) +reporting_delay <- LogNormal(mean = 2, sd = 1, max = 10) reporting_delay ``` @@ -169,9 +169,9 @@ We might further want to adjust for right-truncation of recent data estimated us Here, instead of doing so we assume that we know about truncation with mean of 1/2 day, sd 1/2 day, following a lognormal distribution and with a maximum of three days. ```{r define_truncation} -trunc_dist <- lognormal( - mean = normal(0.5, 0.1), - sd = normal(0.5, 0.1), +trunc_dist <- LogNormal( + mean = Normal(0.5, 0.1), + sd = Normal(0.5, 0.1), max = 3 ) trunc_dist diff --git a/vignettes/estimate_infections_workflow.Rmd b/vignettes/estimate_infections_workflow.Rmd index c50adb794..7e1b9b88f 100644 --- a/vignettes/estimate_infections_workflow.Rmd +++ b/vignettes/estimate_infections_workflow.Rmd @@ -69,7 +69,7 @@ As these will affect any results, it is worth spending some time investigating w ## Delay distributions _EpiNow2_ works with different delays that apply to different parts of the infection and observation process. -They are defined using a common interface that involves functions that are named after the probability distributions, i.e. `lognormal()`, `gamma()`, etc. +They are defined using a common interface that involves functions that are named after the probability distributions, i.e. `LogNormal()`, `Gamma()`, etc. For help with this function, see its manual page @@ -82,7 +82,7 @@ For example, to define a fixed gamma distribution with mean 3, standard deviatio ```r -gamma(mean = 3, sd = 1, max = 10) +Gamma(mean = 3, sd = 1, max = 10) #> #> distribution with PMF [0.0038 0.15 0.39 0.3 0.12 0.03 0.006 0.00096 0.00013 1.6e-05 1.8e-06]. ``` @@ -92,7 +92,7 @@ For example, to define a variable gamma distribution where uncertainty in the me ```r -gamma(mean = normal(3, 2), sd = normal(1, 0.1), max = 10) +Gamma(mean = Normal(3, 2), sd = Normal(1, 0.1), max = 10) #> Warning in generate_dist_spec(params, "gamma"): Uncertain gamma distribution #> specified in terms of parameters that are not the "natural" parameters of the #> distribution (shape, rate). Converting using a crude and very approximate @@ -115,13 +115,13 @@ For a more comprehensive treatment of delays and their estimation avoiding commo ### Generation intervals The generation interval is a delay distribution that describes the amount of time that passes between an individual becoming infected and infecting someone else. -In _EpiNow2_, the generation time distribution is defined by a call to `generation_time_opts()`, a function that takes a single argument defined as a `dist_spec` object (returned by the function corresponding to the probability distribution, i.e. `lognormal()`, `gamma()`, etc.). +In _EpiNow2_, the generation time distribution is defined by a call to `generation_time_opts()`, a function that takes a single argument defined as a `dist_spec` object (returned by the function corresponding to the probability distribution, i.e. `LogNormal()`, `Gamma()`, etc.). For example, to define the generation time as gamma distributed with uncertain mean centered on 3 and sd centered on 1 with some uncertainty, a maximum value of 10 and weighted by the number of case data points we could use the shape and rate parameters suggested above (though notes that this will only very approximately produce the uncertainty in mean and standard deviation stated there): ```r -generation_time <- gamma( - shape = normal(9, 2.5), rate = normal(3, 1.4), max = 10 +generation_time <- Gamma( + shape = Normal(9, 2.5), rate = Normal(3, 1.4), max = 10 ) generation_time_opts(generation_time) ``` @@ -137,12 +137,12 @@ In this case, we can combine multiple delays with the plus (`+`) operator, e.g. ```r -incubation_period <- lognormal( - meanlog = normal(1.6, 0.05), - sdlog = normal(0.5, 0.05), +incubation_period <- LogNormal( + meanlog = Normal(1.6, 0.05), + sdlog = Normal(0.5, 0.05), max = 14 ) -reporting_delay <- lognormal(meanlog = 0.5, sdlog = 0.5, max = 10) +reporting_delay <- LogNormal(meanlog = 0.5, sdlog = 0.5, max = 10) incubation_period + reporting_delay #> #> Composite delay distribution: @@ -150,7 +150,7 @@ incubation_period + reporting_delay #> distribution with PMF [0.16 0.49 0.23 0.077 0.025 0.0084 0.003 0.0011 0.00045 0.00019 8.2e-05]. ``` -In _EpiNow2_, the reporting delay distribution is defined by a call to `delay_opts()`, a function that takes a single argument defined as a `dist_spec` object (returned by `lognormal()`, `gamma()` etc.). +In _EpiNow2_, the reporting delay distribution is defined by a call to `delay_opts()`, a function that takes a single argument defined as a `dist_spec` object (returned by `LogNormal()`, `Gamma()` etc.). For example, if our observations were by symptom onset we would use diff --git a/vignettes/estimate_infections_workflow.Rmd.orig b/vignettes/estimate_infections_workflow.Rmd.orig index 3f0d3a889..2effddff5 100644 --- a/vignettes/estimate_infections_workflow.Rmd.orig +++ b/vignettes/estimate_infections_workflow.Rmd.orig @@ -65,7 +65,7 @@ As these will affect any results, it is worth spending some time investigating w ## Delay distributions _EpiNow2_ works with different delays that apply to different parts of the infection and observation process. -They are defined using a common interface that involves functions that are named after the probability distributions, i.e. `lognormal()`, `gamma()`, etc. +They are defined using a common interface that involves functions that are named after the probability distributions, i.e. `LogNormal()`, `Gamma()`, etc. For help with this function, see its manual page ```{r eval = FALSE} @@ -76,14 +76,14 @@ In all cases, the distributions given can be *fixed* (i.e. have no uncertainty) For example, to define a fixed gamma distribution with mean 3, standard deviation (sd) 1 and maximum value 10, you would write ```{r} -gamma(mean = 3, sd = 1, max = 10) +Gamma(mean = 3, sd = 1, max = 10) ``` If distributions are variable, the values with uncertainty are treated as [prior probability densities](https://en.wikipedia.org/wiki/Prior_probability) in the Bayesian inference framework used by _EpiNow2_, i.e. they are estimated as part of the inference. For example, to define a variable gamma distribution where uncertainty in the mean is given by a normal distribution with mean 3 and sd 2, and uncertainty in the standard deviation is given by a normal distribution with mean 1 and sd 0.1, with a maximum value 10, you would write ```{r} -gamma(mean = normal(3, 2), sd = normal(1, 0.1), max = 10) +Gamma(mean = Normal(3, 2), sd = Normal(1, 0.1), max = 10) ``` Note the warning about parameters. @@ -99,12 +99,12 @@ For a more comprehensive treatment of delays and their estimation avoiding commo ### Generation intervals The generation interval is a delay distribution that describes the amount of time that passes between an individual becoming infected and infecting someone else. -In _EpiNow2_, the generation time distribution is defined by a call to `generation_time_opts()`, a function that takes a single argument defined as a `dist_spec` object (returned by the function corresponding to the probability distribution, i.e. `lognormal()`, `gamma()`, etc.). +In _EpiNow2_, the generation time distribution is defined by a call to `generation_time_opts()`, a function that takes a single argument defined as a `dist_spec` object (returned by the function corresponding to the probability distribution, i.e. `LogNormal()`, `Gamma()`, etc.). For example, to define the generation time as gamma distributed with uncertain mean centered on 3 and sd centered on 1 with some uncertainty, a maximum value of 10 and weighted by the number of case data points we could use the shape and rate parameters suggested above (though notes that this will only very approximately produce the uncertainty in mean and standard deviation stated there): ```{r, results = 'hide'} -generation_time <- gamma( - shape = normal(9, 2.5), rate = normal(3, 1.4), max = 10 +generation_time <- Gamma( + shape = Normal(9, 2.5), rate = Normal(3, 1.4), max = 10 ) generation_time_opts(generation_time) ``` @@ -119,16 +119,16 @@ Often, such counts are composed of multiple delays for which we only have separa In this case, we can combine multiple delays with the plus (`+`) operator, e.g. ```{r} -incubation_period <- lognormal( - meanlog = normal(1.6, 0.05), - sdlog = normal(0.5, 0.05), +incubation_period <- LogNormal( + meanlog = Normal(1.6, 0.05), + sdlog = Normal(0.5, 0.05), max = 14 ) -reporting_delay <- lognormal(meanlog = 0.5, sdlog = 0.5, max = 10) +reporting_delay <- LogNormal(meanlog = 0.5, sdlog = 0.5, max = 10) incubation_period + reporting_delay ``` -In _EpiNow2_, the reporting delay distribution is defined by a call to `delay_opts()`, a function that takes a single argument defined as a `dist_spec` object (returned by `lognormal()`, `gamma()` etc.). +In _EpiNow2_, the reporting delay distribution is defined by a call to `delay_opts()`, a function that takes a single argument defined as a `dist_spec` object (returned by `LogNormal()`, `Gamma()` etc.). For example, if our observations were by symptom onset we would use ```{r, results = 'hide'} From ac5b20015d4a584421f35af5ba58f58dd48d0e75 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Thu, 11 Jan 2024 15:14:38 +0000 Subject: [PATCH 072/129] separate dist_spec from stan model --- R/create.R | 83 +++++-- R/dist.R | 703 ++++++++++++++++++++++++++++------------------------- 2 files changed, 429 insertions(+), 357 deletions(-) diff --git a/R/create.R b/R/create.R index c40824fd1..9fffeb130 100644 --- a/R/create.R +++ b/R/create.R @@ -708,26 +708,47 @@ create_stan_args <- function(stan = stan_opts(), ##' @param ... Named delay distributions. The names are assigned to IDs ##' @param weight Numeric, weight associated with delay priors; default: 1 ##' @return A list of variables as expected by the stan model -##' @importFrom purrr list_transpose map +##' @importFrom purrr transpose map flatten ##' @author Sebastian Funk -create_stan_delays <- function(..., weight = 1) { - dot_args <- list(...) - ## combine delays - combined_delays <- unclass(c(...)) +create_stan_delays <- function(..., weight = 1, tolerance = 0.001) { + ## discretise + delays <- lapply(list(...), discretise) + ## convolve where appropriate + delays <- lapply(delays, collapse) + ## apply tolerance + delays <- lapply(delays, apply_tolerance, tolerance = tolerance) + ## get maximum delays + max_delay <- unname(as.numeric(flatten(map(delays, max)))) ## number of different non-empty types - type_n <- unlist(purrr::list_transpose(dot_args, simplify = FALSE)$n) + type_n <- vapply(delays, length, numeric(1)) ## assign ID values to each type ids <- rep(0L, length(type_n)) ids[type_n > 0] <- seq_len(sum(type_n > 0)) names(ids) <- paste(names(type_n), "id", sep = "_") - ## start consructing stan object - ret <- unclass(combined_delays) - ## construct additional variables - ret <- c(ret, list( - types = sum(type_n > 0), - types_p = array(as.integer(combined_delays$parametric)) + delays <- flatten(delays) + parametric <- unname( + vapply(delays, function(x) x$distribution != "nonparametric", logical(1)) + ) + param_length <- unname(vapply(delays[parametric], function(x) { + length(x$parameters) + }, numeric(1))) + nonparam_length <- unname(vapply(delays[!parametric], function(x) { + length(x$pmf) + }, numeric(1))) + distributions <- unname(as.character( + map(delays[parametric], ~ .x$distribution) )) + + ## create stan object + ret <- list( + n = length(delays), + n_p = sum(parametric), + n_np = sum(!parametric), + types = sum(type_n > 0), + types_p = array(as.integer(parametric)) + ) + ## delay identifiers ret$types_id <- integer(0) ret$types_id[ret$types_p == 1] <- seq_len(ret$n_p) @@ -735,28 +756,36 @@ create_stan_delays <- function(..., weight = 1) { ret$types_id <- array(ret$types_id) ## map delays to identifiers ret$types_groups <- array(c(0, cumsum(unname(type_n[type_n > 0]))) + 1) + + ret$params_mean <- array(unname(as.numeric( + map(flatten(map(delays[parametric], ~ .x$parameters)), mean) + ))) + ret$params_sd <- array(unname(as.numeric( + map(flatten(map(delays[parametric], ~ .x$parameters)), sd_dist) + ))) + ret$max <- array(max_delay[parametric]) + + ret$np_pmf <- array(unname(as.numeric( + flatten(map(delays[!parametric], ~ .x$pmf)) + ))) ## get non zero length delay pmf lengths - ret$np_pmf_groups <- array( - c(0, cumsum( - combined_delays$np_pmf_length[combined_delays$np_pmf_length > 0]) - ) + 1 - ) + ret$np_pmf_groups <- array(c(0, cumsum(nonparam_length)) + 1) ## calculate total np pmf length - ret$np_pmf_length <- sum(combined_delays$np_pmf_length) + ret$np_pmf_length <- sum(nonparam_length) ## get non zero length param lengths - ret$params_groups <- array( - c(0, cumsum( - combined_delays$params_length[combined_delays$params_length > 0]) - ) + 1 - ) + ret$params_groups <- array(c(0, cumsum(param_length)) + 1) ## calculate total param length - ret$params_length <- sum(combined_delays$params_length) + ret$params_length <- sum(param_length) + ## set lower bounds + ret$params_lower <- array(unname(as.numeric(flatten( + map(delays[parametric], function(x) { + lower_bounds(x$distribution)[names(x$parameters)] + }) + )))) ## assign prior weights ret$weight <- array(rep(weight, ret$n_p)) ## assign distribution - ret$dist <- array(match(c(ret$dist), c("lognormal", "gamma")) - 1L) - ## remove auxiliary variables - ret$fixed <- NULL + ret$dist <- array(match(distributions, c("lognormal", "gamma")) - 1L) names(ret) <- paste("delay", names(ret), sep = "_") ret <- c(ret, ids) diff --git a/R/dist.R b/R/dist.R index 41422ccb4..98439e200 100644 --- a/R/dist.R +++ b/R/dist.R @@ -140,13 +140,25 @@ dist_skel <- function(n, dist = FALSE, cum = TRUE, model, pnorm(n, params[["mean"]], params[["sd"]])) / pnorm(max_value + 1, params[["mean"]], params[["sd"]]) } + } else if (model == "fixed") { + rdist <- function(n) { + rep(params[["value"]], n) + } + pdist <- function(n) { + as.integer(n > params[["value"]]) + } + ddist <- function(n) { + as.integer(n == params[["value"]]) + } } if (discrete) { cmf <- c(0, pdist(seq_len(max_value + 1))) pmf <- diff(cmf) rdist <- function(n) { - sample(x = seq_len(max_value + 1) - 1, size = n, prob = pmf) + sample( + x = seq_len(max_value + 1) - 1, size = n, prob = pmf, replace = TRUE + ) } pdist <- function(n) { cmf[n + 1] @@ -1105,79 +1117,19 @@ dist_spec <- function(distribution = c( ret$np_pmf_length <- length(ret$np_pmf) ret$params_length <- length(ret$params_mean) ret[sum_args] <- purrr::map(ret[sum_args], sum) - attr(ret, "class") <- c("list", "dist_spec") + attr(ret, "class") <- c("dist_spec", class(ret)) return(ret) } -#' Creates a delay distribution as the sum of two other delay distributions -#' -#' This is done via convolution with [stats::convolve()]. Nonparametric delays -#' that can be combined are processed together, and their cumulative -#' distribution function is truncated at a specified tolerance level, ensuring -#' numeric stability. +#' Creates a delay distribution as the sum of two other delay distributions. #' +#' @return A delay distribution representing the sum of the two delays +#' (with class [dist_spec()]) #' @param e1 The first delay distribution (of type [dist_spec()]) to #' combine. #' #' @param e2 The second delay distribution (of type [dist_spec()]) to #' combine. -#' -#' @param tolerance A numeric value that sets the cumulative probability -#' to retain when truncating the cumulative distribution function of the -#' combined nonparametric delays. The default value is 0.001 with this retaining -#' 0.999 of the cumulative probability. Note that using a larger tolerance may -#' result in a smaller number of points in the combined nonparametric delay but -#' may also impact the accuracy of the combined delay (i.e., change the mean -#' and standard deviation). -#' -#' @return A delay distribution representing the sum of the two delays -#' (with class [dist_spec()]) -#' -#' @author Sebastian Funk -#' @author Sam Abbott -#' @importFrom stats convolve -dist_spec_plus <- function(e1, e2, tolerance = 0.001) { - ## process delay distributions - delays <- c(e1, e2) - ## combine any nonparametric delays that can be combined - if (sum(!delays$parametric) > 1) { - new_pmf <- 1L - group_starts <- c(1L, cumsum(delays$np_pmf_length) + 1L) - for (i in seq_len(length(group_starts) - 1L)) { - new_pmf <- stats::convolve( - new_pmf, - rev(delays$np_pmf[seq(group_starts[i], group_starts[i + 1L] - 1L)]), - type = "open" - ) - } - if (tolerance > 0 && length(new_pmf) > 1) { - cdf <- cumsum(new_pmf) - new_pmf <- new_pmf[c(TRUE, (1 - cdf[-length(cdf)]) >= tolerance)] - new_pmf <- new_pmf / sum(new_pmf) - } - delays$np_pmf <- new_pmf - delays$np_pmf_length <- length(delays$np_pmf) - delays$params_length <- c( - 0, delays$params_length[delays$parametric] - ) - delays$parametric <- array(c(FALSE, rep(TRUE, delays$n_p))) - delays$n_np <- 1 - delays$n <- delays$n_p + 1 - } - delays$np_pmf_length <- length(delays$np_pmf) - return(delays) -} - -#' Creates a delay distribution as the sum of two other delay distributions -#' -#' This is done via convolution with [stats::convolve()]. Nonparametric delays -#' that can be combined are processed together, and their cumulative -#' distribution function is truncated at a specified tolerance level, ensuring -#' numeric stability. -#' -#' @return A delay distribution representing the sum of the two delays -#' (with class [dist_spec()]) -#' @inheritParams dist_spec_plus #' @author Sebastian Funk #' @method + dist_spec #' @export @@ -1193,11 +1145,8 @@ dist_spec_plus <- function(e1, e2, tolerance = 0.001) { #' mean = Normal(3, 0.5), sd = Normal(2, 0.5), max = 20 #' ) #' dist1 + dist2 -#' -#' # Using tolerance parameter -#' EpiNow2:::dist_spec_plus(dist1, dist1, tolerance = 0.5) `+.dist_spec` <- function(e1, e2) { - dist_spec_plus(e1, e2, tolerance = 0.001) + c(e1, e2) } #' Combines multiple delay distributions for further processing @@ -1209,24 +1158,19 @@ dist_spec_plus <- function(e1, e2, tolerance = 0.001) { #' @return Combined delay distributions (with class ``) #' @author Sebastian Funk #' @method c dist_spec -#' @importFrom purrr list_transpose map +#' @export c.dist_spec <- function(...) { ## process delay distributions - delays <- list(...) - if (!(all(vapply(delays, is, FALSE, "dist_spec")))) { + dist_specs <- list(...) + if (!(all(vapply(dist_specs, is, FALSE, "dist_spec")))) { stop( - "Delay distribution can only be concatenated with other delay ", + "Distribution can only be concatenated with other delay ", "distributions." ) } - ## transpose delays - delays <- purrr::list_transpose(delays, simplify = FALSE) - ## convert back to arrays - delays <- purrr::map(delays, function(x) array(unlist(x))) - sum_args <- grep("^n($|_)", names(delays)) - delays[sum_args] <- purrr::map(delays[sum_args], sum) - attr(delays, "class") <- c("list", "dist_spec") - return(delays) + dist_specs <- do.call(c, lapply(dist_specs, unclass)) + attr(dist_specs, "class") <- c("dist_spec", "list") + return(dist_specs) } ##' Returns the mean of one or more delay distribution @@ -1237,7 +1181,9 @@ c.dist_spec <- function(...) { ##' ##' @param x The `` to use ##' @param ... Not used -##' @return A vector of means. +##' @param ignore_uncertainty Logical; whether to ignore any uncertainty in +##' parameters. If set to FALSE (the default) then the mean of any uncertain +##' parameters will be returned as NA. ##' @author Sebastian Funk ##' @method mean dist_spec ##' @importFrom utils head @@ -1255,32 +1201,39 @@ c.dist_spec <- function(...) { #' #' # The mean of the sum of two distributions #' mean(dist1 + dist2) -mean.dist_spec <- function(x, ...) { - ret <- rep(0, x$n) - if (x$n_np > 0) { - ## nonparametric - ret[!x$parametric] <- sum((seq_len(x$np_pmf_length) - 1) * x$np_pmf) - } - if (x$n_p > 0) { - ## parametric - ret[x$parametric] <- vapply(which(x$parametric), function(id) { - single_dist <- extract_single_dist(x, id) - if (single_dist$dist == "lognormal") { - exp(single_dist$params_mean[[1]] + single_dist$params_mean[[2]]**2 / 2) - } else if (single_dist$dist == "gamma") { - single_dist$params_mean[[1]] / single_dist$params_mean[[2]] - } else if (single_dist$dist == "normal") { - single_dist$params_mean[[1]] - } else if (single_dist$dist == "fixed") { - single_dist$params_mean[[1]] +mean.dist_spec <- function(x, ..., ignore_uncertainty = FALSE) { + ret <- vapply(x, function(y) { + if (is.numeric(y)) { + return(y) + } + ## y is a dist_spec + if (y$distribution == "nonparametric") { + ## nonparametric + return(sum((seq_along(y$pmf) - 1) * y$pmf)) + } else { + if (!all(vapply(y$parameters, is.numeric, logical(1)))) { + if (ignore_uncertainty) { + y$parameters <- lapply(y$parameters, mean, ignore_uncertainty = TRUE) + } else { + return(NA_real_) + } + } + if (y$distribution == "lognormal") { + return(exp(y$parameters$meanlog + y$parameters$sdlog**2 / 2)) + } else if (y$distribution == "gamma") { + return(y$parameters$shape / y$parameters$rate) + } else if (y$distribution == "normal") { + return(y$parameters$mean) + } else if (y$distribution == "fixed") { + return(y$parameters$value) } else { stop( "Don't know how to calculate mean of ", single_dist$dist, " distribution." ) } - }, numeric(1)) - } + } + }, numeric(1)) return(ret) } @@ -1308,28 +1261,28 @@ mean.dist_spec <- function(x, ...) { ##' sd_dist(dist1 + dist2) ##' } sd_dist <- function(x) { - ret <- rep(0, x$n) - if (x$n_np > 0) { - ## nonparametric - mean_pmf <- sum((seq_len(x$np_pmf_length) - 1) * x$np_pmf) - ret[!x$parametric] <- sum((seq_len(x$np_pmf_length) - 1)**2 * x$np_pmf) - - mean_pmf^2 - } - if (x$n_p > 0) { - ## parametric - if (any(x$params_sd > 0)) { - stop("Cannot calculate standard deviation of uncertain distribution") + ret <- vapply(x, function(y) { + if (is.numeric(y)) { + return(0) } - ret[x$parametric] <- vapply(which(x$parametric), function(id) { - single_dist <- extract_single_dist(x, id) - if (single_dist$dist == "lognormal") { - sqrt(exp(single_dist$params_mean[2]**2) - 1) * - exp(single_dist$params_mean[1] + 0.5 * single_dist$params_mean[2]**2) - } else if (single_dist$dist == "gamma") { - sqrt(single_dist$params_mean[1] / single_dist$params_mean[2]**2) - } else if (single_dist$dist == "normal") { - single_dist$params_mean[2] - } else if (single_dist$dist == "fixed") { + ## y is a dist_spec + if (y$distribution == "nonparametric") { + ## nonparametric + mean_pmf <- sum((seq_along(y$pmf) - 1) * y$pmf) + return(sum((seq_along(y$pmf) - 1)**2 * y$pmf) - mean_pmf^2) + } else { + ## parametric + if (!all(vapply(y$parameters, is.numeric, logical(1)))) { + return(NA_real_) + } + if (y$distribution == "lognormal") { + sqrt(exp(y$parameters$sdlog**2) - 1) * + exp(y$parameters$meanlog + 0.5 * y$parameters$sdlog**2) + } else if (y$distribution == "gamma") { + sqrt(y$parameters$shape / y$parameters$rate**2) + } else if (y$distribution == "normal") { + y$parameters$sd + } else if (y$distribution == "fixed") { 0 } else { stop( @@ -1337,8 +1290,8 @@ sd_dist <- function(x) { single_dist$dist, " distribution." ) } - }, numeric(1)) - } + } + }, numeric(1)) return(ret) } @@ -1363,21 +1316,142 @@ sd_dist <- function(x) { #' dist2 <- LogNormal(mean = Normal(3, 0.5), sd = Normal(2, 0.5), max = 20) #' max(dist2) #' -#' # The mean of the sum of two distributions -#' mean(dist1 + dist2) +#' # The maxf the sum of two distributions +#' max(dist1 + dist2) max.dist_spec <- function(x, ...) { - ret <- rep(0L, x$n) - if (x$n_np > 0) { - ## nonparametric - ret[!x$parametric] <- x$np_pmf_length - 1 + ret <- vapply(x, function(y) { + ## y is a dist_spec + if (y$distribution == "nonparametric") { + ## nonparametric + return(length(y$pmf) - 1) + } else if (y$distribution == "fixed") { + return(y$parameters$value) + } else { + return(y$max) + } + }, numeric(1)) + return(ret) +} +## +##' Discretise a +##' +##' By default it will discretise all the distributions it can discretise +##' (i.e. those with finite support and constant parameters). +##' @title Discretise a +##' @param x A `` +##' @param silent Logical; if `TRUE` then any distribution that can't be +##' discretised will be returned as is. If `FALSE` then an error will be +##' thrown. +##' @return A `` where all distributions with constant parameters are +##' nonparametric. +##' @author Sebastian Funk +##' @export +discretise <- function(x, silent = TRUE) { + if (!is(x, "dist_spec")) { + stop("Can only discretise a .") } - if (x$n_p > 0) { - ## parametric - ret[x$parametric] <- x$max + ## check max + max_x <- max(x) + if (any(is.infinite(max_x)) && !silent) { + stop("Cannot discretise a distribution with infinite support.") } + ## discretise + ret <- lapply(seq_along(x), function(id) { + y <- x[[id]] + if (y$distribution == "nonparametric") { + return(y) + } else { + if (all(vapply(y$parameters, is.numeric, logical(1))) && + is.finite(max_x[id])) { + z <- list(pmf = dist_skel( + n = seq_len(max_x[id] + 1) - 1, dist = TRUE, cum = FALSE, + model = y$distribution, params = y$parameters, + max_value = max_x[id], discrete = TRUE + )) + z$distribution <- "nonparametric" + return(z) + } else if (silent) { + return(y) + } else { + stop( + "Cannot discretise a distribution with uncertain parameters." + ) + } + } + }) + attr(ret, "class") <- c("dist_spec", "list") return(ret) } +##' Collapse nonparametric distributions in a +##' +##' This convolves any consecutive nonparametric distributions contained +##' in the . +##' @param x A `` +##' @return A `` where consecutive nonparametric distributions +##' have been convolved +##' @importFrom stats convolve +##' @author Sebastian Funk +##' @export +collapse <- function(x) { + if (!is(x, "dist_spec")) { + stop("Can only convolve distributions in a .") + } + ## get nonparametric distributions + nonparametric <- unname(unlist(map(x, "distribution"))) == "nonparametric" + ## find consecutive nonparametric distributions + consecutive <- rle(nonparametric) + ids <- unique(c(1, cumsum(consecutive$lengths[-length(consecutive$lengths)]))) + ## find ids of nonparametric distributions that are collapsable + ## (i.e. have other nonparametric distributions followign them) + collapseable <- ids[consecutive$values == TRUE & consecutive$length > 1] + ## identify ids of distributions that follow the collapseable distributions + next_ids <- lapply(collapseable, function(id) { + ids[id] + seq_len(consecutive$lengths[id] - 1) + }) + for (id in collapseable) { + ## collapse distributions + for (next_id in next_ids[id]) { + x[[ids[id]]]$pmf <- convolve( + x[[ids[id]]]$pmf, rev(x[[next_id]]$pmf), type = "open" + ) + } + } + ## remove collapsed pmfs + x[unlist(next_ids)] <- NULL + + return(x) +} + +##' Applies a threshold to all nonparametric distributions in a +##' +##' This removes any part of the tail of the nonparametric distributions in the +##' where the probability mass is below the threshold level. +##' @param x A `` +##' @param tolerance Numeric; the desired tolerance level. +##' @return A `` where probability masses below the threshold level +##' have been removed +##' @author Sebastian Funk, Sam Abbott +##' @export +apply_tolerance <- function(x, tolerance) { + if (!is(x, "dist_spec")) { + stop("Can only apply tolerance to distributions in a .") + } + x <- lapply(x, function(x) { + if (x$distribution == "nonparametric") { + cmf <- cumsum(x$pmf) + new_pmf <- x$pmf[c(TRUE, (1 - cmf[-length(cmf)]) >= tolerance)] + x$pmf <- new_pmf / sum(new_pmf) + return(x) + } else { + return(x) + } + }) + + attr(x, "class") <- c("dist_spec", "list") + return(x) +} + #' Prints the parameters of one or more delay distributions #' #' This displays the parameters of the uncertain and probability mass @@ -1399,70 +1473,54 @@ max.dist_spec <- function(x, ...) { #' ) #' print(dist2) print.dist_spec <- function(x, ...) { - cat("\n") - if (x$n > 1) { - cat("Composite delay distribution:\n") + .print.dist_spec(x, indent = 0, ...) +} + +.print.dist_spec <- function(x, indent, ...) { + indent_str <- strrep(" ", indent) + if (length(x) > 1) { + cat(indent_str, "Composite distribution:\n", sep = "") } - nonparametric_id <- 1 - nonparametric_pos <- 1 - parametric_id <- 1 - parametric_pos <- 1 - for (i in 1:x$n) { - cat(" ") - if (!is.null(x$names) && nchar(x$names[i]) > 0) { - cat(x$names[i], ": ", sep = "") - } - if (x$parametric[i] > 0) { - dist <- x$dist[parametric_id] - cat(dist, " distribution", sep = "") - if (is.finite(x$max[parametric_id])) { - cat(" (max: ", x$max[parametric_id], ")", sep = "") + for (i in seq_along(x)) { + if (x[[i]]$distribution == "nonparametric") { + ## nonparametric + cat( + indent_str, "- nonparametric distribution\n", indent_str, " PMF: [", + paste(signif(x[[i]]$pmf, digits = 2), collapse = " "), "]\n", + sep = "" + ) + } else if (x[[i]]$distribution == "fixed") { + ## fixed + cat(indent_str, "- fixed value:\n", sep = "") + if (is.numeric(x[[i]]$parameters$value)) { + cat(indent_str, " ", x[[i]]$parameters$value, "\n", sep = "") + } else { + .print.dist_spec(x[[i]]$parameters$value, indent = indent + 4) + } + } else { + ## parametric + cat(indent_str, "- ", x[[i]]$distribution, " distribution", sep = "") + if (is.finite(x[[i]]$max)) { + cat(" (max: ", x[[i]]$max, ")", sep = "") } - cat(" with ", sep = "") + cat(":\n") ## loop over natural parameters and print - for (id in seq(1, x$params_length[i])) { - pos <- parametric_pos - 1 + id - if (id > 1) { - if (id == x$params_length[i]) { - cat(" and ") - } else { - cat(", ") - } - } - if (x$params_sd[pos] > 0) { - cat("uncertain ") - } - cat(natural_params(dist)[id]) - if (x$params_sd[pos] > 0) { + for (param in names(x[[i]]$parameters)) { + cat( + indent_str, " ", param, ":\n", sep = "" + ) + if (is.numeric(x[[i]]$parameters[[param]])) { cat( - " (mean = ", signif(x$params_mean[pos], digits = 2), ", ", - "sd = ", signif(x$params_sd[pos], digits = 2), ")", + indent_str, " ", + signif(x[[i]]$parameters[[param]], digits = 2), "\n", sep = "" ) } else { - cat(" = ", signif(x$params_mean[pos], digits = 2), sep = "") + .print.dist_spec(x[[i]]$parameters[[param]], indent = indent + 4) } } - parametric_id <- parametric_id + 1 - parametric_pos <- parametric_pos + x$params_length[i] - } else { - cat( - "distribution with PMF [", - paste(signif( - x$np_pmf[seq( - nonparametric_pos, length.out = x$np_pmf_length[nonparametric_id] - )], - digits = 2 - ), collapse = " "), - "]", - sep = "" - ) - nonparametric_id <- nonparametric_id + 1 - nonparametric_pos <- nonparametric_pos + x$np_pmf_length[i] } - cat(".\n") } - cat("\n") } #' Plot PMF and CDF for a dist_spec object @@ -1503,21 +1561,19 @@ plot.dist_spec <- function(x, ...) { value = numeric(), cdf = numeric(), distribution = factor() ) - parametric_id <- 1 - nonparametric_id <- 1 group_starts <- c(1L, cumsum(x$np_pmf_length) + 1L) - for (i in 1:x$n) { - if (x$parametric[i]) { - # Uncertain distribution - c_dist <- fix_dist(extract_single_dist(x, i)) - pmf <- c_dist$np_pmf - parametric_id <- parametric_id + 1 - dist_name <- paste0("Uncertain ", x$dist[parametric_id], " (ID: ", i, ")") - } else { + for (i in seq_along(x)) { + if (x[[i]]$distribution == "nonparametric") { # Fixed distribution - pmf <- x$np_pmf[seq(group_starts[i], group_starts[i + 1L] - 1L)] + pmf <- x$pmf[seq(group_starts[i], group_starts[i + 1L] - 1L)] dist_name <- paste0("Fixed", " (ID: ", i, ")") - nonparametric_id <- nonparametric_id + 1 + } else { + # Uncertain distribution + c_dist <- discretise(fix_dist(extract_single_dist(x, i))) + pmf <- c_dist[[1]]$pmf + dist_name <- paste0( + "Uncertain ", x[[i]]$distribution, " (ID: ", i, ")" + ) } pmf_data <- rbind( pmf_data, @@ -1554,27 +1610,11 @@ plot.dist_spec <- function(x, ...) { ##' @keywords internal ##' @author Sebastian Funk extract_single_dist <- function(x, i) { - if (i > x$n) { + if (i > length(x)) { stop("i can't be greater than the number of distributions.") } - if (x$parametric[i]) { - parametric_id <- cumsum(x$parametric)[i] - params_start_id <- cumsum(c(0, x$params_length))[i] + 1 - params_id <- seq(params_start_id, length.out = x$params_length[i]) - ret <- .dist_spec( - params_mean = x$params_mean[params_id], - params_sd = x$params_sd[params_id], - max = x$max[parametric_id], - distribution = x$dist[parametric_id] - ) - } else { - nonparametric_id <- cumsum(!x$parametric)[i] - pmf_start_id <- cumsum(c(0, x$np_pmf_length))[nonparametric_id] + 1 - pmf_id <- seq(pmf_start_id, length.out = x$np_pmf_length[nonparametric_id]) - ret <- .dist_spec( - pmf = x$np_pmf[pmf_id] - ) - } + ret <- list(x[[i]]) + attr(ret, "class") <- c("dist_spec", class(ret)) return(ret) } @@ -1592,39 +1632,38 @@ extract_single_dist <- function(x, i) { ##' @importFrom truncnorm rtruncnorm ##' @importFrom rlang arg_match fix_dist <- function(x, strategy = c("mean", "sample")) { - ## match strategy argument to options + if (!is(x, "dist_spec")) { + stop("Can only fix distributions in a .") + } + ## match strategy argument to options strategy <- arg_match(strategy) - fix_single_dist <- function(x) { + ret <- lapply(x, function(x) { ## if x is fixed already we don't have to do anything - if (!x$parametric || all(x$params_sd == 0)) return(x) + if ( + x$distribution == "nonparametric" || + all(vapply(x$parameters, is.numeric, logical(1)) == TRUE) + ) { + return(x) + } ## apply strategy depending on choice if (strategy == "mean") { - x <- .dist_spec( - params_mean = x$params_mean, - distribution = x$dist, - max = as.vector(x$max) - ) + x$parameters <- lapply(x$parameters, mean) } else if (strategy == "sample") { - lower_bound <- lower_bounds(x$dist)[natural_params(x$dist)] - mean <- rtruncnorm( - n = 1, a = lower_bound, mean = x$params_mean, sd = x$params_sd - ) - x <- .dist_spec( - params_mean = mean, - distribution = x$dist, - max = as.vector(x$max) - ) + lower_bound <- + lower_bounds(x$distribution)[natural_params(x$distribution)] + mean <- as.list(rtruncnorm( + n = 1, a = lower_bound, + mean = vapply(x$parameters, mean, numeric(1)), + sd = vapply(x$parameters, sd_dist, numeric(1)) + )) + names(mean) <- names(x$parameters) + x$parameters <- mean } return(x) - } + }) - ret <- fix_single_dist(extract_single_dist(x, 1)) - if (x$n > 1) { - for (i in 2:x$n) { - ret <- ret + fix_single_dist(extract_single_dist(x, i)) - } - } + attr(ret, "class") <- c("dist_spec", "list") return(ret) } @@ -1668,9 +1707,9 @@ fix_dist <- function(x, strategy = c("mean", "sample")) { ##' LogNormal(mean = 4, sd = 1) ##' LogNormal(mean = 4, sd = 1, max = 10) ##' LogNormal(mean = Normal(4, 1), sd = 1, max = 10) -lognormal <- function(meanlog, sdlog, mean, sd, max = Inf) { +LogNormal <- function(meanlog, sdlog, mean, sd, max = Inf) { params <- as.list(environment()) - return(generate_dist_spec(params, "lognormal")) + return(new_dist_spec(params, "lognormal")) } ##' @inheritParams stats::GammaDist @@ -1683,9 +1722,9 @@ lognormal <- function(meanlog, sdlog, mean, sd, max = Inf) { ##' Gamma(mean = 4, sd = 1) ##' Gamma(shape = 16, rate = 4) ##' Gamma(shape = Normal(16, 2), rate = Normal(4, 1)) -gamma <- function(shape, rate, scale, mean, sd, max = Inf) { +Gamma <- function(shape, rate, scale, mean, sd, max = Inf) { params <- as.list(environment()) - return(generate_dist_spec(params, "gamma")) + return(new_dist_spec(params, "gamma")) } ##' @rdname Distributions @@ -1695,9 +1734,9 @@ gamma <- function(shape, rate, scale, mean, sd, max = Inf) { ##' @examples ##' Normal(mean = 4, sd = 1) ##' Normal(mean = 4, sd = 1, max = 10) -normal <- function(mean, sd, max = Inf) { +Normal <- function(mean, sd, max = Inf) { params <- as.list(environment()) - return(generate_dist_spec(params, "normal")) + return(new_dist_spec(params, "normal")) } ##' @rdname Distributions @@ -1708,15 +1747,9 @@ normal <- function(mean, sd, max = Inf) { ##' @examples ##' Fixed(value = 3) ##' Fixed(value = 3.5) -fixed <- function(value) { +Fixed <- function(value, max = Inf) { params <- as.list(environment()) - params <- extract_params(params, "fixed") - if (is(params$value, "dist_spec")) { - return(params) - } else if (is.numeric(params$value)) { - fixed_value <- params$value - } - return(.dist_spec(params_mean = fixed_value, distribution = "fixed")) + return(new_dist_spec(params, "fixed")) } ##' Generates a nonparametric distribution. @@ -1733,7 +1766,7 @@ fixed <- function(value) { ##' pmf(c(0.1, 0.3, 0.2, 0.4)) ##' pmf(c(0.1, 0.3, 0.2, 0.1, 0.1)) pmf <- function(mass) { - return(.dist_spec(pmf = mass)) + return(new_dist_spec(params = mass / sum(mass), "nonparametric")) } ##' Get the names of the natural parameters of a distribution @@ -1811,85 +1844,92 @@ extract_params <- function(params, distribution) { ##' ##' This will convert all parameters to natural parameters before generating ##' a `dist_spec`. If they have uncertainty this will be done using sampling. +##' @param params Parameters of the distribution (including `max`) ##' @inheritParams extract_params ##' @importFrom purrr walk ##' @return A `dist_spec` of the given specification. ##' @author Sebastian Funk -generate_dist_spec <- function(params, distribution) { - ## process min/max first - max <- params$max - params$max <- NULL - ## extract parameters and convert all to dist_spec - params <- extract_params(params, distribution) - params <- lapply(params, function(x) { - if (is(x, "dist_spec") && x$dist == "normal") { - if (any(x$params_sd > 0)) { - stop( - "Normal distribution indicating uncertainty cannot itself ", - "be uncertain." - ) - } - x - } else if (is.numeric(x)) { - Fixed(x) +##' @keywords internal +new_dist_spec <- function(params, distribution) { + if (distribution == "nonparametric") { + ## nonparametric distribution + ret <- list( + pmf = params, + distribution = "nonparametric" + ) + } else { + ## process min/max first + max <- params$max + params$max <- NULL + ## extract parameters and convert all to dist_spec + params <- extract_params(params, distribution) + ## fixed distribution + if (distribution == "fixed") { + ret <- list( + parameters = params, + distribution = "fixed" + ) } else { - stop("Parameter ", x, " must be numeric or normally distributed.") - } - }) + ## parametric probability distribution + ## check bounds + for (param_name in names(params)) { + lb <- lower_bounds(distribution)[param_name] + if (is.numeric(params[[param_name]]) && params[[param_name]] < lb) { + stop( + "Parameter ", param_name, " is less than its lower bound ", lb, + "." + ) + } else if ( + is(params[[param_name]], "dist") && params[[param_name]]$max < lb + ) { + stop( + "Maximum of parameter ", param_name, " is less than its ", + "lower bound ", lb, "." + ) + } + } - ## check bounds - for (param_name in names(params)) { - if (!params[[param_name]]$parametric || - params[[param_name]]$dist == "fixed") { - ## no uncertainty, so check if within range - lb <- lower_bounds(distribution)[param_name] - if (mean(params[[param_name]]) < lb) { - stop( - "Parameter ", param_name, " is less than its lower bound ", lb, "." + ## convert any unnatural parameters + unnatural_params <- setdiff(names(params), natural_params(distribution)) + if (length(unnatural_params) > 0) { + if (length(unnatural_params) < length(params)) { + stop( + "Incompatible combination of parameters of a ", distribution, + " distribution specified." + ) + } + ## sample parameters if they are uncertain + if (any(vapply(params, sd_dist, numeric(1)) > 0)) { + warning( + "Uncertain ", distribution, " distribution specified in terms of ", + "parameters that are not the \"natural\" parameters of the ", + "distribution (", toString(natural_params(distribution)), + "). Converting using a crude and very approximate method ", + "that is likely to produce biased results. If possible, ", + "it is preferable to specify the distribution directly ", + "in terms of the natural parameters." + ) + } + ## generate natural parameters + params <- convert_to_natural(params, distribution) + } + ## convert normal with sd == 0 to fixed + if (distribution == "normal" && is.numeric(params$sd) && params$sd == 0) { + rQet <- list( + parameters = list(value = params$mean), distribution = "fixed" ) + } else { + ret <- list(parameters = params, distribution = distribution) } } + ret <- c(ret, list(max = max)) } - - ## convert any unnatural parameters - unnatural_params <- setdiff(names(params), natural_params(distribution)) - if (length(unnatural_params) > 0) { - if (length(unnatural_params) < length(params)) { - stop( - "Incompatible combination of parameters of a ", distribution, - " distribution specified." - ) - } - ## sample parameters if they are uncertain - if (any(vapply(params, sd_dist, numeric(1)) > 0)) { - warning( - "Uncertain ", distribution, " distribution specified in terms of ", - "parameters that are not the \"natural\" parameters of the ", - "distribution (", toString(natural_params(distribution)), - "). Converting using a crude and very approximate method ", - "that is likely to produce biased results. If possible, ", - "it is preferable to specify the distribution direclty ", - "in terms of the natural parameters." - ) - } - ## generate natural parameters - converted_params <- convert_to_natural(params, distribution) - } else { - converted_params <- list( - params_mean = vapply(params, mean, numeric(1), USE.NAMES = FALSE), - params_sd = vapply(params, sd_dist, numeric(1), USE.NAMES = FALSE) - ) - } - - dist <- .dist_spec( - distribution = distribution, - params_mean = converted_params$params_mean, - params_sd = converted_params$params_sd, - max = max - ) + ## join and wrap in another list to make concatenating easier + ret <- list(ret) + attr(ret, "class") <- c("dist_spec", "list") ## now we have a distribution with natural parameters - return dist_spec - return(dist) + return(ret) } ##' Internal function for converting parameters to natural parameters. @@ -1918,13 +1958,16 @@ convert_to_natural <- function(params, distribution) { } } else if (distribution == "lognormal" && "mean" %in% names(params) && "sd" %in% names(params)) { - x$meanlog <- convert_to_logmean(ux$mean, ux$sd) + x$meanlog <- log(ux$mean^2 / sqrt(ux$sd^2 + ux$mean^2)) x$sdlog <- convert_to_logsd(ux$mean, ux$sd) } - natural_means <- unname(unlist(x[natural_params(distribution)])) - params <- list( - params_mean = natural_means, - params_sd = sqrt(natural_means * rel_unc) - ) + if (rel_unc > 0) { + params <- lapply(names(x), function (param_name) { + Normal(mean = x[[param_name]], sd = sqrt(x[[param_name]] * rel_unc)) + }) + names(params) <- names(x) + } else { + params <- x + } return(params) } From 5daa83bee2ea1c64cd6dc510a5da1a97480bef91 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Thu, 11 Jan 2024 15:15:04 +0000 Subject: [PATCH 073/129] adjust tests/code for new dist_spec set up --- R/adjust.R | 10 +++++----- R/checks.R | 34 +++++++++++++++++++++++++++++----- R/estimate_infections.R | 2 +- R/get.R | 2 +- R/opts.R | 6 +++--- 5 files changed, 39 insertions(+), 15 deletions(-) diff --git a/R/adjust.R b/R/adjust.R index 193f91153..a20ea0bb6 100644 --- a/R/adjust.R +++ b/R/adjust.R @@ -116,11 +116,11 @@ adjust_infection_to_report <- function(infections, delay_defs, sample_dist_spec <- function(input, delay_def) { ## Define sample delay fn sample_delay_fn <- function(n, dist, cum, ...) { - fixed_dist <- fix_dist(delay_def, strategy = "sample") + fixed_dist <- discretise(fix_dist(delay_def, strategy = "sample")) if (dist) { - fixed_dist$np_pmf[n + 1] + fixed_dist[[1]]$pmf[n + 1] } else { - sample(seq_along(fixed_dist$np_pmf) - 1, size = n, replace = TRUE) + sample(seq_along(fixed_dist[[1]]$pmf) - 1, size = n, replace = TRUE) } } @@ -139,8 +139,8 @@ adjust_infection_to_report <- function(infections, delay_defs, if (is(delay_defs, "dist_spec")) { report <- sample_dist_spec(infections, extract_single_dist(delay_defs, 1)) - if (delay_defs$n > 1) { - for (def in 2:delay_defs$n) { + if (length(delay_defs) > 1) { + for (def in seq(2, length(delay_defs))) { report <- sample_dist_spec(report, extract_single_dist(delay_defs, def)) } } diff --git a/R/checks.R b/R/checks.R index 5e5a5bbc8..671e69da4 100644 --- a/R/checks.R +++ b/R/checks.R @@ -58,8 +58,8 @@ check_reports_valid <- function(reports, model) { #' Validate probability distribution for passing to stan #' #' @description -#' `check_stan_dist()` checks that the supplied data is a ``, -#' and that it can be further processed by stan. +#' `check_stan_delay()` checks that the supplied data is a ``, +#' that it is lognormal or gamma, and that it has a finite maximum. #' #' @param dist A `dist_spec` object.` #' @importFrom checkmate assert_class @@ -67,16 +67,40 @@ check_reports_valid <- function(reports, model) { #' @return Called for its side effects. #' @author Sebastian Funk #' @keywords internal -check_stan_dist <- function(dist) { +check_stan_delay <- function(dist) { # Check that `dist` is a `dist_spec` assert_class(dist, "dist_spec") # Check that `dist` is lognormal or gamma or nonparametric - if (!all(dist$dist %in% c("lognormal", "gamma"))) { + distributions <- vapply(dist, function(x) x$distribution, character(1)) + if ( + !all(distributions %in% c("lognormal", "gamma", "fixed", "nonparametric")) + ) { stop( - "Distributions passed to the model need to be lognormal, gamma or ", + "Distributions passed to the model need to be lognormal, gamma, fixed or ", "nonparametric (i.e., have no uncertainty)." ) } + # Check that `dist` has parameters that are either numeric or normal + # distributions with numeric parameters and infinite maximum + numeric_parameters <- vapply(dist$parameters, is.numeric, logical(1)) + normal_parameters <- vapply( + dist$parameters, + function(x) { + is(x, "dist_spec") && + x$distribution == "normal" && + all(vapply(x$parameters, is.numeric, logical(1))) && + is.infinite(x$max) + }, + logical(1) + ) + if (!all(numeric_parameters | normal_parameters)) { + stop( + "Delay distributions passed to the model need to have parameters that ", + "are either numeric or normally distributed with numeric parameters ", + "and infinite maximum." + ) + } + # Check that `dist` has a finite maximum if (any(is.infinite(max(dist)))) { stop("All distribution passed to the model need to have a finite maximum") } diff --git a/R/estimate_infections.R b/R/estimate_infections.R index 2f84fc904..1167f8049 100644 --- a/R/estimate_infections.R +++ b/R/estimate_infections.R @@ -243,7 +243,7 @@ estimate_infections <- function(reported_cases, ) ## Add prior infections - if (delays$n > 0) { + if (length(delays) > 0) { out$prior_infections <- shifted_cases[ , .( diff --git a/R/get.R b/R/get.R index da30af4de..971da6895 100644 --- a/R/get.R +++ b/R/get.R @@ -328,7 +328,7 @@ get_regions_with_most_reports <- function(reported_cases, ##' @author Sebastian Funk get_seeding_time <- function(delays, generation_time) { # Estimate the mean delay ----------------------------------------------- - seeding_time <- sum(mean(delays)) + seeding_time <- sum(mean(delays, ignore_uncertainty = TRUE)) if (seeding_time < 1) { seeding_time <- 1 } else { diff --git a/R/opts.R b/R/opts.R index 59bf91b73..51bea375c 100644 --- a/R/opts.R +++ b/R/opts.R @@ -98,7 +98,7 @@ generation_time_opts <- function(dist = Fixed(1), ..., "information, see the relevant documentation pages using ", "`?generation_time_opts`") } - check_stan_dist(dist) + check_stan_delay(dist) attr(dist, "class") <- c("generation_time_opts", class(dist)) return(dist) } @@ -163,7 +163,7 @@ delay_opts <- function(dist = Fixed(0), ..., fixed = FALSE) { ## can be removed once dot options are hard deprecated stop("Unknown named arguments passed to `delay_opts`") } - check_stan_dist(dist) + check_stan_delay(dist) attr(dist, "class") <- c("delay_opts", class(dist)) return(dist) } @@ -208,7 +208,7 @@ trunc_opts <- function(dist = Fixed(0)) { "`?trunc_opts`" ) } - check_stan_dist(dist) + check_stan_delay(dist) attr(dist, "class") <- c("trunc_opts", class(dist)) return(dist) } From d5e4ddf1bf2bd262d6261a40eba73e04a6516bca Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Thu, 11 Jan 2024 15:15:20 +0000 Subject: [PATCH 074/129] re-create examples --- data/example_generation_time.rda | Bin 340 -> 322 bytes data/example_incubation_period.rda | Bin 357 -> 323 bytes data/example_reporting_delay.rda | Bin 327 -> 309 bytes 3 files changed, 0 insertions(+), 0 deletions(-) diff --git a/data/example_generation_time.rda b/data/example_generation_time.rda index 2e60aab54e8039f8f827d587a84938135dbb11e6..21dae53513ebc799a8876d4ada6db4cc040e04b3 100644 GIT binary patch literal 322 zcmV-I0lof0T4*^jL0KkKS;^<5i2wm2|G)n~NQ3}D5(LBm5Xipg-avpTC;$K;00KZ^ zC;&kLumKoK8Bw6r(-6=!0MktYpc;BlQKpA5089V`zyJUM0V0}$Wj(2)G6A3i)BtD$ zL8!X*P3?~HLV-?XC{k9~NeJNkv)SNd{azo*u(J#gBTHp?#4FXRMaW{JSfNOch}9X{ z00^a|FBEpDF<7L=tyvUS1q@4dAutkYjSZB@0;Y->s9+(s(Z<9ge3D)55)xenmHc)| zpaK3dEpks??1nlE6q+-*Bc$taB&fJ~XcC@g7hZzO0tz8)v#m{sh`ZJi UmBGhLS^twFL@cx@tQy(HwsaHAue$1dEX%6d!owvvFEfBV0D?duZ~#C6 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zxr>Hu$3Ajw*)~>5A_TGq{EQqOoLGRS^UL7d5LIA}t*nbu28nK)B7f7udLWnrQwl#R zv6+y|1cEGi8B_%jE~OX&aFcw=BtcY>DS?~-kr4n7tZRktfJ8fbT|+mwYI literal 327 zcmV-N0l5A`T4*^jL0KkKS$?;-j{pG{@A>~fNP!ptga9x=ujkz00ssIo03iTCNC-dy zumLbcH8fN7nkGzX4@r;>Gy$U~O$3PuMD(6e0BF!XO)(lhL(~}1(9i*p&;S4c3t;{G zaQI2ITG269u5>g^Cst}FMDw)>Y$|2-&RKsYgOM$yTbol*-7H83j%Gn18NG%Qi}l%z zz!63ve9wOEb$n2Cify|6_f=>a+6^fK01RLuFdth28a)__N)RU0Gs028#02(63$ZIE3PXYN@E{+CVMj4eKRc;tOcmTOWd@2yZd$gqM(LTM|qw z`b`XiIMX&+RQPxj2C`x2WC73DWQ~a?q*8qCZ439MF64@Ep& Date: Thu, 11 Jan 2024 15:15:36 +0000 Subject: [PATCH 075/129] re-doc --- NAMESPACE | 13 +++++-- man/Distributions.Rd | 10 ++--- man/apply_tolerance.Rd | 24 ++++++++++++ ...check_stan_dist.Rd => check_stan_delay.Rd} | 10 ++--- man/collapse.Rd | 22 +++++++++++ man/create_stan_delays.Rd | 2 +- man/discretise.Rd | 29 ++++++++++++++ man/dist_spec_plus.Rd | 38 ------------------- man/max.dist_spec.Rd | 4 +- man/mean.dist_spec.Rd | 9 +++-- ...generate_dist_spec.Rd => new_dist_spec.Rd} | 9 +++-- man/plus-.dist_spec.Rd | 10 +---- 12 files changed, 109 insertions(+), 71 deletions(-) create mode 100644 man/apply_tolerance.Rd rename man/{check_stan_dist.Rd => check_stan_delay.Rd} (59%) create mode 100644 man/collapse.Rd create mode 100644 man/discretise.Rd delete mode 100644 man/dist_spec_plus.Rd rename man/{generate_dist_spec.Rd => new_dist_spec.Rd} (74%) diff --git a/NAMESPACE b/NAMESPACE index 1cf68d2be..d127387f3 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -1,6 +1,7 @@ # Generated by roxygen2: do not edit by hand S3method("+",dist_spec) +S3method(c,dist_spec) S3method(max,dist_spec) S3method(mean,dist_spec) S3method(plot,dist_spec) @@ -11,9 +12,14 @@ S3method(plot,estimate_truncation) S3method(print,dist_spec) S3method(summary,epinow) S3method(summary,estimate_infections) +export(Fixed) +export(Gamma) +export(LogNormal) +export(Normal) export(R_to_growth) export(add_day_of_week) export(adjust_infection_to_report) +export(apply_tolerance) export(backcalc_opts) export(bootstrapped_dist_fit) export(calc_CrI) @@ -21,6 +27,7 @@ export(calc_CrIs) export(calc_summary_measures) export(calc_summary_stats) export(clean_nowcasts) +export(collapse) export(construct_output) export(convert_to_logmean) export(convert_to_logsd) @@ -35,6 +42,7 @@ export(create_shifted_cases) export(create_stan_args) export(create_stan_data) export(delay_opts) +export(discretise) export(dist_fit) export(dist_skel) export(dist_spec) @@ -51,9 +59,7 @@ export(extract_samples) export(extract_stan_param) export(fix_dist) export(forecast_infections) -export(fixed) export(forecast_secondary) -export(gamma) export(gamma_dist_def) export(generation_time_opts) export(get_dist) @@ -66,10 +72,8 @@ export(get_regions_with_most_reports) export(gp_opts) export(growth_to_R) export(lognorm_dist_def) -export(lognormal) export(make_conf) export(map_prob_change) -export(normal) export(obs_opts) export(opts_list) export(package_model) @@ -200,6 +204,7 @@ importFrom(posterior,mcse_mean) importFrom(progressr,progressor) importFrom(progressr,with_progress) importFrom(purrr,compact) +importFrom(purrr,flatten) importFrom(purrr,keep) importFrom(purrr,list_transpose) importFrom(purrr,map) diff --git a/man/Distributions.Rd b/man/Distributions.Rd index 89ec62aa3..008a5d381 100644 --- a/man/Distributions.Rd +++ b/man/Distributions.Rd @@ -2,10 +2,10 @@ % Please edit documentation in R/dist.R \name{Distributions} \alias{Distributions} -\alias{lognormal} -\alias{gamma} -\alias{normal} -\alias{fixed} +\alias{LogNormal} +\alias{Gamma} +\alias{Normal} +\alias{Fixed} \alias{pmf} \title{Probability distributions} \usage{ @@ -15,7 +15,7 @@ Gamma(shape, rate, scale, mean, sd, max = Inf) Normal(mean, sd, max = Inf) -Fixed(value) +Fixed(value, max = Inf) pmf(mass) } diff --git a/man/apply_tolerance.Rd b/man/apply_tolerance.Rd new file mode 100644 index 000000000..49f4a4338 --- /dev/null +++ b/man/apply_tolerance.Rd @@ -0,0 +1,24 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/dist.R +\name{apply_tolerance} +\alias{apply_tolerance} +\title{Applies a threshold to all nonparametric distributions in a } +\usage{ +apply_tolerance(x, tolerance) +} +\arguments{ +\item{x}{A \verb{}} + +\item{tolerance}{Numeric; the desired tolerance level.} +} +\value{ +A \verb{} where probability masses below the threshold level +have been removed +} +\description{ +This removes any part of the tail of the nonparametric distributions in the + where the probability mass is below the threshold level. +} +\author{ +Sebastian Funk, Sam Abbott +} diff --git a/man/check_stan_dist.Rd b/man/check_stan_delay.Rd similarity index 59% rename from man/check_stan_dist.Rd rename to man/check_stan_delay.Rd index 8ad5cdb50..e1e3f763d 100644 --- a/man/check_stan_dist.Rd +++ b/man/check_stan_delay.Rd @@ -1,10 +1,10 @@ % Generated by roxygen2: do not edit by hand % Please edit documentation in R/checks.R -\name{check_stan_dist} -\alias{check_stan_dist} +\name{check_stan_delay} +\alias{check_stan_delay} \title{Validate probability distribution for passing to stan} \usage{ -check_stan_dist(dist) +check_stan_delay(dist) } \arguments{ \item{dist}{A \code{dist_spec} object.`} @@ -13,8 +13,8 @@ check_stan_dist(dist) Called for its side effects. } \description{ -\code{check_stan_dist()} checks that the supplied data is a \verb{}, -and that it can be further processed by stan. +\code{check_stan_delay()} checks that the supplied data is a \verb{}, +that it is lognormal or gamma, and that it has a finite maximum. } \author{ Sebastian Funk diff --git a/man/collapse.Rd b/man/collapse.Rd new file mode 100644 index 000000000..63e35492f --- /dev/null +++ b/man/collapse.Rd @@ -0,0 +1,22 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/dist.R +\name{collapse} +\alias{collapse} +\title{Collapse nonparametric distributions in a } +\usage{ +collapse(x) +} +\arguments{ +\item{x}{A \verb{}} +} +\value{ +A \verb{} where consecutive nonparametric distributions +have been convolved +} +\description{ +This convolves any consecutive nonparametric distributions contained +in the . +} +\author{ +Sebastian Funk +} diff --git a/man/create_stan_delays.Rd b/man/create_stan_delays.Rd index 5c6519e10..958c475fc 100644 --- a/man/create_stan_delays.Rd +++ b/man/create_stan_delays.Rd @@ -4,7 +4,7 @@ \alias{create_stan_delays} \title{Create delay variables for stan} \usage{ -create_stan_delays(..., weight = 1) +create_stan_delays(..., weight = 1, tolerance = 0.001) } \arguments{ \item{...}{Named delay distributions. The names are assigned to IDs} diff --git a/man/discretise.Rd b/man/discretise.Rd new file mode 100644 index 000000000..f942c69f6 --- /dev/null +++ b/man/discretise.Rd @@ -0,0 +1,29 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/dist.R +\name{discretise} +\alias{discretise} +\title{Discretise a } +\usage{ +discretise(x, silent = TRUE) +} +\arguments{ +\item{x}{A \verb{}} + +\item{silent}{Logical; if \code{TRUE} then any distribution that can't be +discretised will be returned as is. If \code{FALSE} then an error will be +thrown.} +} +\value{ +A \verb{} where all distributions with constant parameters are +nonparametric. +} +\description{ +Discretise a +} +\details{ +By default it will discretise all the distributions it can discretise +(i.e. those with finite support and constant parameters). +} +\author{ +Sebastian Funk +} diff --git a/man/dist_spec_plus.Rd b/man/dist_spec_plus.Rd deleted file mode 100644 index 12a774c99..000000000 --- a/man/dist_spec_plus.Rd +++ /dev/null @@ -1,38 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/dist.R -\name{dist_spec_plus} -\alias{dist_spec_plus} -\title{Creates a delay distribution as the sum of two other delay distributions} -\usage{ -dist_spec_plus(e1, e2, tolerance = 0.001) -} -\arguments{ -\item{e1}{The first delay distribution (of type \code{\link[=dist_spec]{dist_spec()}}) to -combine.} - -\item{e2}{The second delay distribution (of type \code{\link[=dist_spec]{dist_spec()}}) to -combine.} - -\item{tolerance}{A numeric value that sets the cumulative probability -to retain when truncating the cumulative distribution function of the -combined nonparametric delays. The default value is 0.001 with this retaining -0.999 of the cumulative probability. Note that using a larger tolerance may -result in a smaller number of points in the combined nonparametric delay but -may also impact the accuracy of the combined delay (i.e., change the mean -and standard deviation).} -} -\value{ -A delay distribution representing the sum of the two delays -(with class \code{\link[=dist_spec]{dist_spec()}}) -} -\description{ -This is done via convolution with \code{\link[stats:convolve]{stats::convolve()}}. Nonparametric delays -that can be combined are processed together, and their cumulative -distribution function is truncated at a specified tolerance level, ensuring -numeric stability. -} -\author{ -Sebastian Funk - -Sam Abbott -} diff --git a/man/max.dist_spec.Rd b/man/max.dist_spec.Rd index 05887408d..0ae753635 100644 --- a/man/max.dist_spec.Rd +++ b/man/max.dist_spec.Rd @@ -28,8 +28,8 @@ max(dist1) dist2 <- LogNormal(mean = Normal(3, 0.5), sd = Normal(2, 0.5), max = 20) max(dist2) -# The mean of the sum of two distributions -mean(dist1 + dist2) +# The maxf the sum of two distributions +max(dist1 + dist2) } \author{ Sebastian Funk diff --git a/man/mean.dist_spec.Rd b/man/mean.dist_spec.Rd index e27fdae8a..aa71f0288 100644 --- a/man/mean.dist_spec.Rd +++ b/man/mean.dist_spec.Rd @@ -4,15 +4,16 @@ \alias{mean.dist_spec} \title{Returns the mean of one or more delay distribution} \usage{ -\method{mean}{dist_spec}(x, ...) +\method{mean}{dist_spec}(x, ..., ignore_uncertainty = FALSE) } \arguments{ \item{x}{The \verb{} to use} \item{...}{Not used} -} -\value{ -A vector of means. + +\item{ignore_uncertainty}{Logical; whether to ignore any uncertainty in +parameters. If set to FALSE (the default) then the mean of any uncertain +parameters will be returned as NA.} } \description{ This works out the mean of all the (parametric / nonparametric) delay diff --git a/man/generate_dist_spec.Rd b/man/new_dist_spec.Rd similarity index 74% rename from man/generate_dist_spec.Rd rename to man/new_dist_spec.Rd index a7a73fbe8..943b1fdfb 100644 --- a/man/generate_dist_spec.Rd +++ b/man/new_dist_spec.Rd @@ -1,14 +1,14 @@ % Generated by roxygen2: do not edit by hand % Please edit documentation in R/dist.R -\name{generate_dist_spec} -\alias{generate_dist_spec} +\name{new_dist_spec} +\alias{new_dist_spec} \title{Internal function for generating a \code{dist_spec} given parameters and a distribution.} \usage{ -generate_dist_spec(params, distribution) +new_dist_spec(params, distribution) } \arguments{ -\item{params}{Given parameters (obtained using \code{as.list(environment())})} +\item{params}{Parameters of the distribution (including \code{max})} \item{distribution}{Character; the distribution to use.} } @@ -22,3 +22,4 @@ a \code{dist_spec}. If they have uncertainty this will be done using sampling. \author{ Sebastian Funk } +\keyword{internal} diff --git a/man/plus-.dist_spec.Rd b/man/plus-.dist_spec.Rd index 453b2b227..c26ee45c3 100644 --- a/man/plus-.dist_spec.Rd +++ b/man/plus-.dist_spec.Rd @@ -2,7 +2,7 @@ % Please edit documentation in R/dist.R \name{+.dist_spec} \alias{+.dist_spec} -\title{Creates a delay distribution as the sum of two other delay distributions} +\title{Creates a delay distribution as the sum of two other delay distributions.} \usage{ \method{+}{dist_spec}(e1, e2) } @@ -18,10 +18,7 @@ A delay distribution representing the sum of the two delays (with class \code{\link[=dist_spec]{dist_spec()}}) } \description{ -This is done via convolution with \code{\link[stats:convolve]{stats::convolve()}}. Nonparametric delays -that can be combined are processed together, and their cumulative -distribution function is truncated at a specified tolerance level, ensuring -numeric stability. +Creates a delay distribution as the sum of two other delay distributions. } \examples{ # A fixed lognormal distribution with mean 5 and sd 1. @@ -35,9 +32,6 @@ dist2 <- Gamma( mean = Normal(3, 0.5), sd = Normal(2, 0.5), max = 20 ) dist1 + dist2 - -# Using tolerance parameter -EpiNow2:::dist_spec_plus(dist1, dist1, tolerance = 0.5) } \author{ Sebastian Funk From fff4c99eb71417facb515f3320118cb95dbab474 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Thu, 11 Jan 2024 15:15:46 +0000 Subject: [PATCH 076/129] update tests --- tests/testthat/test-delays.R | 2 +- tests/testthat/test-dist.R | 14 +-- tests/testthat/test-dist_spec.R | 182 ++++++++++++++++---------------- tests/testthat/test-epinow.R | 2 +- 4 files changed, 101 insertions(+), 99 deletions(-) diff --git a/tests/testthat/test-delays.R b/tests/testthat/test-delays.R index 57ce46aee..dc70059ce 100644 --- a/tests/testthat/test-delays.R +++ b/tests/testthat/test-delays.R @@ -73,6 +73,6 @@ test_that("distributions incompatible with stan models are caught", { Gamma(2, 2) ), "maximum") expect_error(delay_opts( - Normal(2, 2) + Normal(2, 2, max = 10) ), "lognormal") }) diff --git a/tests/testthat/test-dist.R b/tests/testthat/test-dist.R index 5e0171a23..7e507400f 100644 --- a/tests/testthat/test-dist.R +++ b/tests/testthat/test-dist.R @@ -2,14 +2,16 @@ skip_on_cran() skip_on_os("windows") test_that("distributions are the same in R and stan", { - args <- list(mean = 3, sd = 2) - max_args <- c(args, list(max = 15)) + args <- list(mean = 3, sd = 2, max = 15) - lognormal_params <- do.call(lognormal, args)$params_mean - gamma_params <- do.call(gamma, args)$params_mean + lognormal_dist <- do.call(LogNormal, args) + gamma_dist <- do.call(Gamma, args) - pmf_r_lognormal <- as.vector(do.call(lognormal, max_args)$np_pmf) - pmf_r_gamma <- as.vector(do.call(gamma, max_args)$np_pmf) + lognormal_params <- unname(as.numeric(lognormal_dist[[1]]$parameters)) + gamma_params <- unname(as.numeric(gamma_dist[[1]]$parameters)) + + pmf_r_lognormal <- discretise(lognormal_dist)[[1]]$pmf + pmf_r_gamma <- discretise(gamma_dist)[[1]]$pmf pmf_stan_lognormal <- discretised_pmf(lognormal_params, max_args$max + 1, 0) pmf_stan_gamma <- discretised_pmf(gamma_params, max_args$max + 1, 1) diff --git a/tests/testthat/test-dist_spec.R b/tests/testthat/test-dist_spec.R index d5a5b89a0..f5c2f1e1b 100644 --- a/tests/testthat/test-dist_spec.R +++ b/tests/testthat/test-dist_spec.R @@ -1,12 +1,11 @@ test_that("dist_spec returns correct output for fixed lognormal distribution", { - result <- LogNormal(meanlog = 5, sdlog = 1, max = 19) - expect_equal(dim(result$params_mean), 0) - expect_equal(dim(result$dist), 0) - expect_equal(dim(result$max), 0) - expect_equal(result$parametric, array(FALSE)) + result <- discretise(LogNormal(meanlog = 5, sdlog = 1, max = 19)) + expect_null(result[[1]]$parameters) + expect_equal(result[[1]]$distribution, "nonparametric") + expect_null(result[[1]]$max) expect_equal( - as.vector(round(result$np_pmf, 2)), + as.vector(round(result[[1]]$pmf, 2)), c(0.00, 0.00, 0.00, 0.00, 0.01, 0.01, 0.02, 0.03, 0.03, 0.04, 0.05, 0.06, 0.07, 0.07, 0.08, 0.09, 0.10, 0.10, 0.11, 0.12) @@ -14,20 +13,26 @@ test_that("dist_spec returns correct output for fixed lognormal distribution", { }) test_that("dist_spec returns correct output for uncertain gamma distribution", { - result <- Gamma(shape = Normal(3, 0.5), rate = Normal(2, 0.5), max = 19) - expect_equal(result$params_mean, array(c(3, 2))) - expect_equal(result$params_sd, array(c(0.5, 0.5))) - expect_equal(result$dist, array("gamma")) - expect_equal(result$max, array(19)) - expect_equal(result$parametric, array(TRUE)) + result <- discretise( + Gamma(shape = Normal(3, 0.5), rate = Normal(2, 0.5), max = 19) + ) + expect_equal(result[[1]]$parameters$shape[[1]]$parameters$mean, 3) + expect_equal(result[[1]]$parameters$shape[[1]]$parameters$sd, 0.5) + expect_equal(result[[1]]$parameters$rate[[1]]$parameters$mean, 2) + expect_equal(result[[1]]$parameters$rate[[1]]$parameters$sd, 0.5) + expect_equal(result[[1]]$distribution, "gamma") + expect_equal(result[[1]]$max, 19) }) test_that("dist_spec returns correct output for fixed distribution", { - result <- fix_dist(LogNormal(meanlog = Normal(5, 3), sdlog = 1, max = 19)) - expect_equal(dim(result$params_mean), 0) - expect_equal(result$parametric, array(FALSE)) + result <- discretise( + fix_dist(LogNormal(meanlog = Normal(5, 3), sdlog = 1, max = 19)) + ) + expect_null(result[[1]]$parameters) + expect_equal(result[[1]]$distribution, "nonparametric") + expect_null(result[[1]]$max) expect_equal( - as.vector(round(result$np_pmf, 2)), + as.vector(round(result[[1]]$pmf, 2)), c(0.00, 0.00, 0.00, 0.00, 0.01, 0.01, 0.02, 0.03, 0.03, 0.04, 0.05, 0.06, 0.07, 0.07, 0.08, 0.09, 0.10, 0.10, 0.11, 0.12) @@ -46,76 +51,58 @@ test_that("dist_spec returns error when the wrong number of paramters are given" expect_error(Gamma(shape = 1, rate = 2, mean = 3), "must be specified") }) -test_that("+.dist_spec returns correct output for sum of two distributions", { +test_that("c.dist_spec returns correct output for sum of two distributions", { dist1 <- LogNormal(meanlog = 5, sdlog = 1, max = 19) dist2 <- Gamma(shape = Normal(3, 0.5), rate = Normal(2, 0.5), max = 20) result <- dist1 + dist2 - expect_equal(result$params_mean, array(c(3, 2))) - expect_equal(result$params_sd, array(c(0.5, 0.5))) - expect_equal(result$n, 2) - expect_equal(result$n_p, 1) - expect_equal(result$n_np, 1) - expect_equal(result$np_pmf_length, 20) + expect_equal(result[[1]]$parameters$meanlog, 5) + expect_equal(result[[1]]$parameters$sdlog, 1) + expect_equal(result[[2]]$parameters$shape[[1]]$parameters$mean, 3) + expect_equal(result[[2]]$parameters$shape[[1]]$parameters$sd, 0.5) + expect_equal(result[[2]]$parameters$rate[[1]]$parameters$mean, 2) + expect_equal(result[[2]]$parameters$rate[[1]]$parameters$sd, 0.5) + expect_equal(length(result), 2) }) -test_that("+.dist_spec returns correct output for sum of two fixed distributions", { - dist1 <- LogNormal(meanlog = 5, sdlog = 1, max = 19) - dist2 <- Gamma(mean = 3, sd = 2, max = 19) - result <- dist1 + dist2 - expect_equal(dim(result$params_mean), 0) - expect_equal(result$n, 1) - expect_equal(result$n_p, 0) - expect_equal(result$n_np, 1) - expect_equal(result$np_pmf_length, 30) -}) - -test_that("+.dist_spec returns correct output for sum of two nonparametric distributions", { +test_that("collapse returns correct output for sum of two nonparametric distributions", { dist1 <- pmf(c(0.1, 0.2, 0.3, 0.4)) dist2 <- pmf(c(0.1, 0.2, 0.3, 0.4)) - result <- dist1 + dist2 - expect_equal(dim(result$params_mean), 0) - expect_equal(result$n, 1) - expect_equal(result$n_p, 0) - expect_equal(result$n_np, 1) - expect_equal(result$np_pmf_length, 7) + result <- collapse(c(dist1, dist2)) + expect_null(result[[1]]$parameters) + expect_equal(result[[1]]$distribution, "nonparametric") + expect_null(result[[1]]$max) + expect_equal(length(result), 1) expect_equal( - as.vector(round(result$np_pmf, 2)), + round(result[[1]]$pmf, 2), c(0.01, 0.04, 0.10, 0.20, 0.25, 0.24, 0.16) ) }) -test_that("Testing `+.dist_spec` function with tolerance parameter", { +test_that("Testing `apply_tolerance` function applied to a convolution", { # Create distributions dist1 <- LogNormal(meanlog = 1.6, sdlog = 1, max = 19) dist2 <- Gamma(mean = 3, sd = 2, max = 19) # Compute combined distribution with default tolerance - combined_default <- EpiNow2:::`+.dist_spec`(dist1, dist2) + combined <- collapse(discretise(c(dist1, dist2))) # Compute combined distribution with larger tolerance - combined_larger_tolerance <- EpiNow2:::dist_spec_plus( - dist1, dist2, tolerance = 0.01 - ) + combined_tolerance <- apply_tolerance(combined, tolerance = 0.001) # The length of the combined PMF should be greater with default tolerance - expect_true( - length(combined_default$np_pmf) > length(combined_larger_tolerance$np_pmf) - ) + expect_true(length(combined[[1]]$pmf) > length(combined_tolerance[[1]]$pmf)) # Both should sum to 1 - expect_equal(sum(combined_default$np_pmf), 1) - expect_equal(sum(combined_larger_tolerance$np_pmf), 1) + expect_equal(sum(combined[[1]]$pmf), 1) + expect_equal(sum(combined_tolerance[[1]]$pmf), 1) # The first 5 entries should be within 0.01 of each other expect_equal( - combined_default$np_pmf[1:5], combined_larger_tolerance$np_pmf[1:5], - tolerance = 0.01 - ) - expect_equal( - mean(combined_default), mean(combined_larger_tolerance), tolerance = 0.1 + combined[[1]]$pmf[1:5], combined_tolerance[[1]]$pmf[1:5], tolerance = 0.01 ) + expect_equal(mean(combined), mean(combined_tolerance), tolerance = 0.1) }) test_that("summary functions return correct output for fixed lognormal distribution", { - dist <- LogNormal(mean = 3, sd = 1, max = 19) + dist <- discretise(LogNormal(mean = 3, sd = 1, max = 19)) ## here we can see the bias from # using this kind of discretisation approach expect_equal(EpiNow2:::mean.dist_spec(dist), 2.49, tolerance = 0.01) @@ -125,7 +112,7 @@ test_that("summary functions return correct output for fixed lognormal distribut test_that("summary functions return correct output for uncertain gamma distribution", { dist <- Gamma(shape = Normal(3, 0.5), rate = Normal(2, 0.5), max = 19) - expect_equal(EpiNow2:::mean.dist_spec(dist), 1.5) + expect_equal(EpiNow2:::mean.dist_spec(dist, ignore_uncertainty = TRUE), 1.5) expect_equal(EpiNow2:::max.dist_spec(dist), 19L) }) @@ -133,21 +120,26 @@ test_that("mean.dist_spec returns correct output for sum of two distributions", dist1 <- LogNormal(meanlog = 1, sdlog = 1, max = 19) dist2 <- Gamma(mean = 3, sd = 2, max = 19) dist <- dist1 + dist2 - expect_equal(EpiNow2:::mean.dist_spec(dist), c(5.84), tolerance = 0.001) - expect_equal(EpiNow2:::sd_dist(dist), c(16.88), tolerance = 0.001) + expect_equal(EpiNow2:::mean.dist_spec(dist), c(4.48, 3), tolerance = 0.001) + expect_equal(EpiNow2:::sd_dist(dist), c(5.87, 2), tolerance = 0.001) ## shortened due to tolerance level - expect_equal(EpiNow2:::max.dist_spec(dist), 24L) + expect_equal(EpiNow2:::max.dist_spec(dist), c(19L, 19L)) +}) + +test_that("mean returns NA when applied to uncertain distributions", { + dist <- Gamma(shape = Normal(3, 0.5), rate = Normal(2, 0.5), max = 19) + expect_true(is.na(EpiNow2:::mean.dist_spec(dist))) }) -test_that("sd_dist returns an error when applied to uncertain distributions", { +test_that("sd_dist returns NA when applied to uncertain distributions", { dist <- Gamma(shape = Normal(3, 0.5), rate = Normal(2, 0.5), max = 19) - expect_error(EpiNow2:::sd_dist(dist), "uncertain") + expect_true(is.na(EpiNow2:::sd_dist(dist))) }) test_that("print.dist_spec correctly prints the parameters of the fixed lognormal", { - dist <- LogNormal(meanlog = 1.5, sdlog = 0.5, max = 19) + dist <- discretise(LogNormal(meanlog = 1.5, sdlog = 0.5, max = 19)) - expect_output(print(dist), "\\n distribution with PMF \\[0\\.0014 0\\.052 0\\.16 0\\.2 0\\.18 0\\.13 0\\.094 0\\.063 0\\.042 0\\.027 0\\.018 0\\.012 0\\.0079 0\\.0052 0\\.0035 0\\.0024 0\\.0016 0\\.0011 0\\.00078 0\\.00055\\]\\.\\n") + expect_output(print(dist), "- nonparametric distribution\\n PMF: \\[0\\.0014 0\\.052 0\\.16 0\\.2 0\\.18 0\\.13 0\\.094 0\\.063 0\\.042 0\\.027 0\\.018 0\\.012 0\\.0079 0\\.0052 0\\.0035 0\\.0024 0\\.0016 0\\.0011 0\\.00078 0\\.00055\\]") }) test_that("print.dist_spec correctly prints the parameters of the uncertain gamma", { @@ -155,7 +147,7 @@ test_that("print.dist_spec correctly prints the parameters of the uncertain gamm shape = Normal(3, 0.5), rate = Normal(2, 0.5), max = 19 ) - expect_output(print(gamma), "\\n gamma distribution \\(max: 19\\) with uncertain shape \\(mean = 3, sd = 0.5\\) and uncertain rate \\(mean = 2, sd = 0\\.5\\)\\.\\n") + expect_output(print(gamma), "- gamma distribution \\(max: 19\\):\\n shape:\\n - normal distribution:\\n mean:\\n 3\\n sd:\\n 0\\.5\\n rate:\\n - normal distribution:\\n mean:\\n 2\\n sd:\\n 0\\.5") }) test_that("print.dist_spec correctly prints the parameters of the uncertain lognormal", { @@ -163,7 +155,7 @@ test_that("print.dist_spec correctly prints the parameters of the uncertain logn meanlog = Normal(1.5, 0.1), sdlog = Normal(0.5, 0.1), max = 19 ) - expect_output(print(dist), "\\n lognormal distribution \\(max: 19\\) with uncertain meanlog \\(mean = 1\\.5, sd = 0\\.1\\) and uncertain sdlog \\(mean = 0\\.5, sd = 0\\.1\\)\\.\\n") + expect_output(print(dist), "- lognormal distribution \\(max: 19\\):\\n meanlog:\\n - normal distribution:\\n mean:\\n 1\\.5\\n sd:\\n 0\\.1\\n sdlog:\\n - normal distribution:\\n mean:\\n 0\\.5\\n sd:\\n 0\\.1") }) test_that("print.dist_spec correctly prints the parameters of a combination of distributions", { @@ -171,7 +163,7 @@ test_that("print.dist_spec correctly prints the parameters of a combination of d dist2 <- Gamma(shape = Normal(3, 0.5), rate = Normal(2, 0.5), max = 19) combined <- dist1 + dist2 - expect_output(print(combined), "\\nComposite delay distribution:\\n distribution with PMF \\[0\\.0014 0\\.052 0\\.16 0\\.2 0\\.18 0\\.13 0\\.094 0\\.063 0\\.042 0\\.027 0\\.018 0\\.012 0\\.0079 0\\.0052 0\\.0035 0\\.0024 0\\.0016 0\\.0011 0\\.00078 0\\.00055\\]\\.\\n gamma distribution \\(max: 19\\) with uncertain shape \\(mean = 3, sd = 0\\.5\\) and uncertain rate \\(mean = 2, sd = 0\\.5\\)\\.\\n") + expect_output(print(combined), "Composite distribution:\\n- lognormal distribution \\(max: 19\\):\\n meanlog:\\n 1\\.5\\n sdlog:\\n 0\\.5\\n- gamma distribution \\(max: 19\\):\\n shape:\\n - normal distribution:\\n mean:\\n 3\\n sd:\\n 0\\.5\\n rate:\\n - normal distribution:\\n mean:\\n 2\\n sd:\\n 0\\.5") }) test_that("plot.dist_spec returns a ggplot object", { @@ -208,10 +200,10 @@ test_that("fix_dist works with composite delay distributions", { dist1 <- LogNormal(meanlog = Normal(1, 0.1), sdlog = 1, max = 19) dist2 <- Gamma(mean = 3, sd = 2, max = 19) dist <- dist1 + dist2 - expect_equal(fix_dist(dist)$n, 1L) + expect_equal(length(collapse(discretise(fix_dist(dist)))), 1L) }) -test_that("composite delay distriubtions can be disassembled", { +test_that("composite delay distributions can be disassembled", { dist1 <- LogNormal(meanlog = Normal(1, 0.1), sdlog = 1, max = 19) dist2 <- Gamma(mean = 3, sd = 2, max = 19) dist <- dist1 + dist2 @@ -221,44 +213,52 @@ test_that("composite delay distriubtions can be disassembled", { test_that("delay distributions can be specified in different ways", { expect_equal( - LogNormal(mean = 4, sd = 1)$params_mean, array(c(1.4, 0.25)), + unname(as.numeric(LogNormal(mean = 4, sd = 1)[[1]]$parameters)), + c(1.4, 0.25), tolerance = 0.1 ) expect_equal( - round(LogNormal(mean = 4, sd = 1, max = 10)$np_pmf, 2), - array(c(0.00, 0.00, 0.14, 0.40, 0.30, 0.11, 0.03, 0.01, 0.00, 0.00, 0.00)) + round(discretise(LogNormal(mean = 4, sd = 1, max = 10))[[1]]$pmf, 2), + c(0.00, 0.00, 0.14, 0.40, 0.30, 0.11, 0.03, 0.01, 0.00, 0.00, 0.00) ) expect_equal( - Gamma(mean = 4, sd = 1)$params_mean, array(c(16, 4)), + unname(as.numeric(Gamma(mean = 4, sd = 1)[[1]]$parameters)), + c(16, 4), tolerance = 0.1 ) expect_equal( - round(Gamma(mean = 4, sd = 1, max = 7)$np_pmf, 2), - array(c(0.00, 0.01, 0.15, 0.38, 0.31, 0.12, 0.03, 0.00)) - ) - expect_equal( - Gamma(shape = Normal(16, 2), rate = Normal(4, 1))$params_mean, - array(c(16, 4)) + round(discretise(Gamma(mean = 4, sd = 1, max = 7))[[1]]$pmf, 2), + c(0.00, 0.01, 0.15, 0.38, 0.31, 0.12, 0.03, 0.00) ) expect_equal( - Gamma(shape = Normal(16, 2), rate = Normal(4, 1))$params_sd, - array(c(2, 1)) + unname(as.numeric( + Gamma( + shape = Normal(16, 2), rate = Normal(4, 1) + )[[1]]$parameters$shape[[1]]$parameters + )), + c(16, 2) ) expect_equal( - Normal(mean = 4, sd = 1)$params_mean, array(c(4, 1)) + unname(as.numeric( + Gamma( + shape = Normal(16, 2), rate = Normal(4, 1) + )[[1]]$parameters$rate[[1]]$parameters + )), + c(4, 1) ) expect_equal( - round(Normal(mean = 4, sd = 1, max = 5)$np_pmf, 2), - array(c(0.00, 0.02, 0.14, 0.35, 0.35, 0.14)) + unname(as.numeric(Normal(mean = 4, sd = 1)[[1]]$parameters)), c(4, 1) ) expect_equal( - Fixed(value = 3)$np_pmf, array(c(0, 0, 0, 1)) + round(discretise(Normal(mean = 4, sd = 1, max = 5))[[1]]$pmf, 2), + c(0.00, 0.02, 0.14, 0.35, 0.35, 0.14) ) - expect_equal(Fixed(value = 3.5)$params_mean, array(3.5)) - expect_equal(pmf(c(0.1, 0.3, 0.2, 0.4))$np_pmf, array(c(0.1, 0.3, 0.2, 0.4))) + expect_equal(discretise(Fixed(value = 3))[[1]]$pmf, c(0, 0, 0, 1)) + expect_equal(Fixed(value = 3.5)[[1]]$parameters$value, 3.5) + expect_equal(pmf(c(0.1, 0.3, 0.2, 0.4))[[1]]$pmf, c(0.1, 0.3, 0.2, 0.4)) expect_equal( - round(pmf(c(0.1, 0.3, 0.2, 0.1, 0.1))$np_pmf, 2), - array(c(0.12, 0.37, 0.25, 0.12, 0.12)) + round(pmf(c(0.1, 0.3, 0.2, 0.1, 0.1))[[1]]$pmf, 2), + c(0.12, 0.37, 0.25, 0.12, 0.12) ) }) diff --git a/tests/testthat/test-epinow.R b/tests/testthat/test-epinow.R index 882f7a128..74fa057e8 100644 --- a/tests/testthat/test-epinow.R +++ b/tests/testthat/test-epinow.R @@ -20,7 +20,7 @@ test_that("epinow produces expected output when run with default settings", { out <- suppressWarnings(epinow( reported_cases = reported_cases, generation_time = generation_time_opts(example_generation_time), - delays = delay_opts(example_incubation_period + reporting_delay), + delays = delay_opts(c(example_incubation_period, reporting_delay)), stan = stan_opts( samples = 25, warmup = 25, cores = 1, chains = 2, From 64f8e21f575591e4b212ed85ca5f435bc3ebba34 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Thu, 11 Jan 2024 15:34:14 +0000 Subject: [PATCH 077/129] new dist_spec in estimate_truncation example --- R/estimate_truncation.R | 22 ++++++++++++++-------- man/estimate_truncation.Rd | 22 ++++++++++++++-------- 2 files changed, 28 insertions(+), 16 deletions(-) diff --git a/R/estimate_truncation.R b/R/estimate_truncation.R index 2e2e7c1c1..5a6dfe6c7 100644 --- a/R/estimate_truncation.R +++ b/R/estimate_truncation.R @@ -96,18 +96,24 @@ #' # apply truncation to example data #' construct_truncation <- function(index, cases, dist) { #' set.seed(index) -#' if (dist$dist == 0) { +#' if (dist[[1]]$distribution == 0) { #' dfunc <- dlnorm #' } else { #' dfunc <- dgamma #' } -#' cmf <- cumsum( -#' dfunc( -#' 1:(dist$max + 1), -#' rnorm(1, dist$params_mean[1], dist$params_sd[1]), -#' rnorm(1, dist$params_mean[2], dist$params_sd[2]) -#' ) -#' ) +#' cmf <- cumsum( +#' dlnorm( +#' seq_len(max(dist) + 1), +#' rnorm(1, +#' dist[[1]]$parameters$meanlog[[1]]$parameters$mean, +#' dist[[1]]$parameters$meanlog[[1]]$parameters$sd +#' ), +#' rnorm(1, +#' dist[[1]]$parameters$sdlog[[1]]$parameters$mean, +#' dist[[1]]$parameters$sdlog[[1]]$parameters$sd +#' ) +#' ) +#' ) #' cmf <- cmf / cmf[dist$max + 1] #' cmf <- rev(cmf)[-1] #' trunc_cases <- data.table::copy(cases)[1:(.N - index)] diff --git a/man/estimate_truncation.Rd b/man/estimate_truncation.Rd index 5dfda8fdb..c38730153 100644 --- a/man/estimate_truncation.Rd +++ b/man/estimate_truncation.Rd @@ -116,18 +116,24 @@ trunc <- LogNormal( # apply truncation to example data construct_truncation <- function(index, cases, dist) { set.seed(index) - if (dist$dist == 0) { + if (dist[[1]]$distribution == 0) { dfunc <- dlnorm } else { dfunc <- dgamma } - cmf <- cumsum( - dfunc( - 1:(dist$max + 1), - rnorm(1, dist$params_mean[1], dist$params_sd[1]), - rnorm(1, dist$params_mean[2], dist$params_sd[2]) - ) - ) + cmf <- cumsum( + dlnorm( + seq_len(max(dist) + 1), + rnorm(1, + dist[[1]]$parameters$meanlog[[1]]$parameters$mean, + dist[[1]]$parameters$meanlog[[1]]$parameters$sd + ), + rnorm(1, + dist[[1]]$parameters$sdlog[[1]]$parameters$mean, + dist[[1]]$parameters$sdlog[[1]]$parameters$sd + ) + ) + ) cmf <- cmf / cmf[dist$max + 1] cmf <- rev(cmf)[-1] trunc_cases <- data.table::copy(cases)[1:(.N - index)] From 9a301ec161bbd8609a5b67e9f578a7d9f4c6150d Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Thu, 11 Jan 2024 15:34:24 +0000 Subject: [PATCH 078/129] update get_seeding_time with updated dist_spec --- R/get.R | 8 ++------ 1 file changed, 2 insertions(+), 6 deletions(-) diff --git a/R/get.R b/R/get.R index 971da6895..a154e90c9 100644 --- a/R/get.R +++ b/R/get.R @@ -332,13 +332,9 @@ get_seeding_time <- function(delays, generation_time) { if (seeding_time < 1) { seeding_time <- 1 } else { - seeding_time <- as.integer(seeding_time) + seeding_time <- round(seeding_time) } ## make sure we have at least (length of total gt pmf - 1) seeding time - seeding_time <- max( - seeding_time, - sum(generation_time$max - 1) + sum(generation_time$np_pmf_length) - - length(generation_time$max) - length(generation_time$np_pmf_length) - ) + seeding_time <- max(seeding_time, sum(max(generation_time))) return(seeding_time) } From ee008dbccf852a175715400f65df88c22c2d63dd Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Thu, 11 Jan 2024 15:35:07 +0000 Subject: [PATCH 079/129] estimate_truncation and seeding time tests --- tests/testthat/test-estimate_truncation.R | 14 ++++++++++---- tests/testthat/test-seeding-time.R | 12 ++++++------ 2 files changed, 16 insertions(+), 10 deletions(-) diff --git a/tests/testthat/test-estimate_truncation.R b/tests/testthat/test-estimate_truncation.R index 6e89a1c62..7f13a7091 100644 --- a/tests/testthat/test-estimate_truncation.R +++ b/tests/testthat/test-estimate_truncation.R @@ -21,12 +21,18 @@ construct_truncation <- function(index, cases, dist) { set.seed(index) cmf <- cumsum( dlnorm( - 1:(dist$max + 1), - rnorm(1, dist$params_mean[1], dist$params_sd[1]), - rnorm(1, dist$params_mean[2], dist$params_sd[2]) + seq_len(max(dist) + 1), + rnorm(1, + dist[[1]]$parameters$meanlog[[1]]$parameters$mean, + dist[[1]]$parameters$meanlog[[1]]$parameters$sd + ), + rnorm(1, + dist[[1]]$parameters$sdlog[[1]]$parameters$mean, + dist[[1]]$parameters$sdlog[[1]]$parameters$sd + ) ) ) - cmf <- cmf / cmf[dist$max + 1] + cmf <- cmf / cmf[max(dist) + 1] cmf <- rev(cmf)[-1] trunc_cases <- data.table::copy(cases)[1:(.N - index)] trunc_cases[(.N - length(cmf) + 1):.N, confirm := as.integer(confirm * cmf)] diff --git a/tests/testthat/test-seeding-time.R b/tests/testthat/test-seeding-time.R index b6e99796c..746a5dfda 100644 --- a/tests/testthat/test-seeding-time.R +++ b/tests/testthat/test-seeding-time.R @@ -1,10 +1,10 @@ test_that("Seeding times are correctly calculated", { - gt1 <- LogNormal(meanlog = 5, sdlog = 1, max = 9) - gt2 <- LogNormal(meanlog = 10, sdlog = 2, max = 14) - delay1 <- LogNormal(meanlog = 5, sdlog = 1, max = 9) - delay2 <- LogNormal(meanlog = 7, sdlog = 3, max = 14) + gt1 <- LogNormal(mean = 5, sd = 1, max = 9) + gt2 <- LogNormal(mean = 10, sd = 2, max = 14) + delay1 <- LogNormal(mean = 5, sd = 1, max = 9) + delay2 <- LogNormal(mean = 7, sd = 3, max = 14) expect_equal( - EpiNow2:::get_seeding_time(delay1, gt1 + gt2), 23L ## 10 + 15 - 1 - 1 + EpiNow2:::get_seeding_time(delay1, gt1 + gt2), 23L ## 9 + 14 ) expect_equal( EpiNow2:::get_seeding_time(delay1 + delay2, gt1), 12L ## 5 + 7 @@ -12,7 +12,7 @@ test_that("Seeding times are correctly calculated", { }) test_that("Short seeding times are rounded up to 1", { - delay <- LogNormal(meanlog = 0.5, sdlog = 1, max = 2) + delay <- LogNormal(mean = 0.5, sd = 1, max = 2) gt <- Fixed(value = 1) expect_equal(EpiNow2:::get_seeding_time(delay, gt), 1L) }) From ae59fdbbeef9aaa2f7cde17f83d4da60807867a0 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Thu, 11 Jan 2024 15:47:39 +0000 Subject: [PATCH 080/129] update truncation dist in estimate_truncation --- R/estimate_truncation.R | 29 ++++++++++++++++++----------- 1 file changed, 18 insertions(+), 11 deletions(-) diff --git a/R/estimate_truncation.R b/R/estimate_truncation.R index 5a6dfe6c7..58c055192 100644 --- a/R/estimate_truncation.R +++ b/R/estimate_truncation.R @@ -224,11 +224,16 @@ estimate_truncation <- function(obs, max_truncation, trunc_max = 10, construct_trunc <- TRUE } if (construct_trunc) { - truncation <- .dist_spec( - params_mean = c(0, 1), - params_sd = c(1, 1), - distribution = trunc_dist, - max = trunc_max + params_mean <- c(0, 1) + params_sd <- c(1, 1) + parameters <- lapply(seq_along(params_mean), function (id) { + Normal(params_mean, params_sd) + }) + names(parameters) <- natural_params(trunc_dist) + parameters$max <- trunc_max + truncation <- new_dist_spec( + parameters = parameters, + distribution = trunc_dist ) } @@ -278,12 +283,14 @@ estimate_truncation <- function(obs, max_truncation, trunc_max = 10, out <- list() # Summarise fit truncation distribution for downstream usage delay_params <- extract_stan_param(fit, params = "delay_params") - out$dist <- .dist_spec( - params_mean = round(delay_params$mean, 3), - params_sd = round(delay_params$sd, 3), - max = truncation$max - ) - out$dist$dist <- truncation$dist + params_mean <- round(delay_params$mean, 3) + params_sd <- round(delay_params$sd, 3) + parameters <- lapply(seq_along(params_mean), function (id) { + Normal(params_mean[id], params_sd[id]) + }) + names(parameters) <- natural_params(truncation[[1]]$distribution) + out$dist <- truncation + out$dist$parameters <- parameters # summarise reconstructed observations recon_obs <- extract_stan_param(fit, "recon_obs", From 4d3e8d966711bff086b1aea43ab27c047fecc988 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Thu, 11 Jan 2024 16:15:15 +0000 Subject: [PATCH 081/129] remove more uses of old dist_spec --- R/dist.R | 198 +++++++++---------------------------------- R/get.R | 28 +++--- man/dot-dist_spec.Rd | 69 --------------- man/new_dist_spec.Rd | 6 +- 4 files changed, 57 insertions(+), 244 deletions(-) delete mode 100644 man/dot-dist_spec.Rd diff --git a/R/dist.R b/R/dist.R index 98439e200..4815e7fda 100644 --- a/R/dist.R +++ b/R/dist.R @@ -880,6 +880,20 @@ tune_inv_gamma <- function(lower = 2, upper = 21) { #' the corresponding distribution function such as [Gamma()], [LogNormal()], #' [Normal()] or [Fixed()] instead. #' +#' @param distribution Character, defaults to "lognormal". The (discretised) +#' distribution to be used. Can be "lognormal", "gamma", "normal" or "fixed". +#' The corresponding parameters (defined in [natural_params()]) are passed +#' as `params_mean`, and their uncertainty as `params_sd`. +#' +#' @param params_mean Numeric. Central values of the parameters of the +#' distribution as defined in [natural_params(). +#' +#' @param params_sd Numeric. Standard deviations of the parameters of the +#' distribution as defined in [natural_params(). +#' +#' @param max Numeric, maximum value of the distribution. The distribution will +#' be truncated at this value. Default: `Inf`, i.e. no maximum. +#' #' @param mean Deprecated; use `params_mean` instead. #' #' @param sd Deprecated; use `params_mean` instead. @@ -888,13 +902,15 @@ tune_inv_gamma <- function(lower = 2, upper = 21) { #' #' @param sd_sd Deprecated; use `params_sd` instead. #' +#' @param pmf Numeric, a vector of values that represent the (nonparametric) +#' probability mass function of the delay (starting with 0); defaults to an +#' empty vector corresponding to a parametric specification of the distribution +#' (using \code{params_mean}, and \code{params_sd}. #' @param fixed Deprecated, use [fix_dist()] instead. #' @return A list of distribution options. -#' #' @author Sebastian Funk #' @author Sam Abbott #' @importFrom rlang warn arg_match -#' @inheritParams .dist_spec #' @export dist_spec <- function(distribution = c( "lognormal", "normal", "gamma", "fixed", "empty" @@ -962,163 +978,22 @@ dist_spec <- function(distribution = c( params_sd <- NULL } } - return(.dist_spec(distribution, params_mean, params_sd, max, pmf)) -} - -#' Specify a distribution. -#' -#' @description `r lifecycle::badge("stable")` -#' Defines the parameters of a supported distribution for use in onward -#' modelling. Multiple distribution families are supported - see the -#' documentation for `family` for details. Alternatively, a nonparametric -#' distribution can be specified using the \code{pmf} argument. -#' This function provides distribution -#' functionality in [delay_opts()], [generation_time_opts()], and -#' [trunc_opts()]. -#' -#' @param params_mean Numeric. Central values of the parameters of the -#' distribution as defined in [natural_params(). -#' -#' @param params_sd Numeric. Standard deviations of the parameters of the -#' distribution as defined in [natural_params(). -#' -#' @param distribution Character, defaults to "lognormal". The (discretised) -#' distribution to be used. Can be "lognormal", "gamma", "normal" or "fixed". -#' The corresponding parameters (defined in [natural_params()]) are passed -#' as `params_mean`, and their uncertainty as `params_sd`. -#' -#' @param max Numeric, maximum value of the distribution. The distribution will -#' be truncated at this value. Default: `Inf`, i.e. no maximum. -#' -#' @param pmf Numeric, a vector of values that represent the (nonparametric) -#' probability mass function of the delay (starting with 0); defaults to an -#' empty vector corresponding to a parametric specification of the distribution -#' (using \code{params_mean}, and \code{params_sd}. -#' -#' @return A `dist_spec` object defining the distribution. -#' -#' @author Sebastian Funk -#' @author Sam Abbott -#' @importFrom rlang warn -#' @keywords internal -#' @examples -#' \dontrun{ -#' # A fixed lognormal distribution with mean 5 and sd 1. -#' .dist_spec( -#' params_mean = c(meanlog = 5, sdlog = 1), max = 20, -#' distribution = "lognormal" -#' ) -#' -#' # An uncertain gamma distribution with mean 3 and sd 2 -#' .dist_spec( -#' params_mean = c(alpha = 3, beta = 0.5), -#' params_sd = c(alpha = 0.75, beta = 0.25), -#' distribution = "gamma" -#' ) -#' } -.dist_spec <- function(distribution = c( - "lognormal", "normal", "gamma", "fixed" - ), - params_mean = numeric(0), params_sd = numeric(0), - max = Inf, pmf = numeric(0)) { - if (length(pmf) > 0 && - !(length(params_mean) == 0 && length(params_sd) == 0)) { - stop("Distributional parameters or a pmf can be specified, but not both.") - } - - if (is.finite(max)) { - warn( - message = paste( - "The meaning of the 'max' argument has changed compared to", - "previous versions. It now indicates the maximum of a distribution", - "rather than the length of the probability mass function (including 0)", - "that it represented previously. To replicate previous behaviour", - "reduce max by 1." - ), - .frequency = "regularly", - .frequency_id = "dist_spec_max" - ) - } - - ## deprecate previous behaviour - if (length(params_sd) == 0) { - params_sd <- rep(0, length(params_mean)) - } - - distribution <- match.arg(distribution) - - if (distribution == "fixed") { - ## if integer fixed then can write the PMF - if (as.integer(params_mean) == params_mean && params_mean >= 0) { - max <- params_mean - parametric <- FALSE - } else { - parametric <- TRUE - } - if (any(params_sd > 0)) { - stop("Fixed parameters cannot have a nonzero standard deviation.") + if (length(pmf) > 0) { + if (!all( + missing(mean), missing(sd), missing(mean_sd), missing(sd_sd), + missing(params_mean), missing(params_sd) + )) { + stop("Distributional parameters should not be given in addition to `pmf`") } + distribution <- "nonparametric" + parameters <- list(pmf = pmf) } else { - ## if PMF is given, set max - if (is.infinite(max) && length(pmf) > 0) { - max <- length(pmf) - 1 - } - parametric <- any(params_sd > 0) || is.infinite(max) - } - if (parametric) { ## calculate pmf - ret <- list( - params_mean = params_mean, - params_sd = params_sd, - dist = distribution, - max = max, - n = 1, - n_p = 1, - n_np = 0, - np_pmf = numeric(0), - parametric = TRUE, - params_lower = lower_bounds(distribution)[natural_params(distribution)] - ) - } else { - ret <- list( - params_mean = numeric(0), - params_sd = numeric(0), - dist = character(0), - max = integer(0), - parametric = FALSE, - params_lower = numeric(0) - ) - if (length(pmf) == 0) { - if (distribution == "fixed") { ## delta - pmf <- c(rep(0, params_mean), 1) - } else { - params <- params_mean - names(params) <- natural_params(distribution) - pmf <- dist_skel( - n = seq_len(max + 1) - 1, dist = TRUE, cum = FALSE, - model = distribution, params = params, max_value = max, - discrete = TRUE - ) - } - } else { ## nonparametric fixed - pmf <- pmf[1:(max + 1)] - pmf <- pmf / sum(pmf) - } - if (length(pmf) > 0) { - ret <- c(ret, list( - n = 1, - n_p = 0, - n_np = 1, - np_pmf = pmf - )) - } + parameters <- lapply(seq_along(params_mean), function(id) { + Normal(params_mean[id], params_sd[id]) + }) + parameters$max <- max } - ret <- purrr::map(ret, array) - sum_args <- grep("(^n$|^n_$)", names(ret)) - ret$np_pmf_length <- length(ret$np_pmf) - ret$params_length <- length(ret$params_mean) - ret[sum_args] <- purrr::map(ret[sum_args], sum) - attr(ret, "class") <- c("dist_spec", class(ret)) - return(ret) + return(new_dist_spec(distribution, parameters)) } #' Creates a delay distribution as the sum of two other delay distributions. @@ -1694,8 +1569,9 @@ fix_dist <- function(x, strategy = c("mean", "sample")) { ##' probability mass function is given directly as a numeric vector. ##' ##' @inheritParams stats::Lognormal -##' @inheritParams .dist_spec ##' @param mean,sd mean and standard deviation of the distribution +##' @param max Numeric, maximum value of the distribution. The distribution will +##' be truncated at this value. Default: `Inf`, i.e. no maximum. ##' @return A `dist_spec` representing a distribution of the given ##' specification. ##' @author Sebastian Funk @@ -1766,7 +1642,9 @@ Fixed <- function(value, max = Inf) { ##' pmf(c(0.1, 0.3, 0.2, 0.4)) ##' pmf(c(0.1, 0.3, 0.2, 0.1, 0.1)) pmf <- function(mass) { - return(new_dist_spec(params = mass / sum(mass), "nonparametric")) + return( + new_dist_spec(parameters = list(pmf = mass / sum(mass)), "nonparametric") + ) } ##' Get the names of the natural parameters of a distribution @@ -1850,11 +1728,11 @@ extract_params <- function(params, distribution) { ##' @return A `dist_spec` of the given specification. ##' @author Sebastian Funk ##' @keywords internal -new_dist_spec <- function(params, distribution) { +new_dist_spec <- function(param, distribution) { if (distribution == "nonparametric") { ## nonparametric distribution ret <- list( - pmf = params, + pmf = params$pmf, distribution = "nonparametric" ) } else { diff --git a/R/get.R b/R/get.R index a154e90c9..65ab63201 100644 --- a/R/get.R +++ b/R/get.R @@ -192,20 +192,24 @@ get_dist <- function(data, disease, source, max_value = 14, fixed = FALSE) { target_disease <- disease target_source <- source data <- data[disease == target_disease][source == target_source] - dist <- as.list( - data[, .(mean, mean_sd, sd, sd_sd, max = max_value, distribution = dist)] - ) if (fixed) { - dist$mean_sd <- 0 - dist$sd_sd <- 0 + data$sd <- 0 + data$sd_sd <- 0 + } + parameters <- list( + Normal(data$mean, data$mean_sd), + Normal(data$sd, data$sd_sd) + ) + if (data$dist == "gamma") { + names(parameters) <- c("mean", "sd") + } else { + names(parameters) <- c("meanlog", "sdlog") } - dist$params_mean <- c(dist$mean, dist$sd) - dist$params_sd <- c(dist$mean_sd, dist$sd_sd) - dist$mean <- NULL - dist$sd <- NULL - dist$mean_sd <- NULL - dist$sd_sd <- NULL - return(do.call(.dist_spec, dist)) + parameters$max <- max_value + return(new_dist_spec( + params = parameters, + distribution = data$dist + )) } #' Get a Literature Distribution for the Generation Time #' diff --git a/man/dot-dist_spec.Rd b/man/dot-dist_spec.Rd deleted file mode 100644 index fa810b91c..000000000 --- a/man/dot-dist_spec.Rd +++ /dev/null @@ -1,69 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/dist.R -\name{.dist_spec} -\alias{.dist_spec} -\title{Specify a distribution.} -\usage{ -.dist_spec( - distribution = c("lognormal", "normal", "gamma", "fixed"), - params_mean = numeric(0), - params_sd = numeric(0), - max = Inf, - pmf = numeric(0) -) -} -\arguments{ -\item{distribution}{Character, defaults to "lognormal". The (discretised) -distribution to be used. Can be "lognormal", "gamma", "normal" or "fixed". -The corresponding parameters (defined in \code{\link[=natural_params]{natural_params()}}) are passed -as \code{params_mean}, and their uncertainty as \code{params_sd}.} - -\item{params_mean}{Numeric. Central values of the parameters of the -distribution as defined in [natural_params().} - -\item{params_sd}{Numeric. Standard deviations of the parameters of the -distribution as defined in [natural_params().} - -\item{max}{Numeric, maximum value of the distribution. The distribution will -be truncated at this value. Default: \code{Inf}, i.e. no maximum.} - -\item{pmf}{Numeric, a vector of values that represent the (nonparametric) -probability mass function of the delay (starting with 0); defaults to an -empty vector corresponding to a parametric specification of the distribution -(using \code{params_mean}, and \code{params_sd}.} -} -\value{ -A \code{dist_spec} object defining the distribution. -} -\description{ -\ifelse{html}{\href{https://lifecycle.r-lib.org/articles/stages.html#stable}{\figure{lifecycle-stable.svg}{options: alt='[Stable]'}}}{\strong{[Stable]}} -Defines the parameters of a supported distribution for use in onward -modelling. Multiple distribution families are supported - see the -documentation for \code{family} for details. Alternatively, a nonparametric -distribution can be specified using the \code{pmf} argument. -This function provides distribution -functionality in \code{\link[=delay_opts]{delay_opts()}}, \code{\link[=generation_time_opts]{generation_time_opts()}}, and -\code{\link[=trunc_opts]{trunc_opts()}}. -} -\examples{ -\dontrun{ -# A fixed lognormal distribution with mean 5 and sd 1. -.dist_spec( - params_mean = c(meanlog = 5, sdlog = 1), max = 20, - distribution = "lognormal" -) - -# An uncertain gamma distribution with mean 3 and sd 2 -.dist_spec( - params_mean = c(alpha = 3, beta = 0.5), - params_sd = c(alpha = 0.75, beta = 0.25), - distribution = "gamma" -) -} -} -\author{ -Sebastian Funk - -Sam Abbott -} -\keyword{internal} diff --git a/man/new_dist_spec.Rd b/man/new_dist_spec.Rd index 943b1fdfb..2122ac2b1 100644 --- a/man/new_dist_spec.Rd +++ b/man/new_dist_spec.Rd @@ -5,12 +5,12 @@ \title{Internal function for generating a \code{dist_spec} given parameters and a distribution.} \usage{ -new_dist_spec(params, distribution) +new_dist_spec(param, distribution) } \arguments{ -\item{params}{Parameters of the distribution (including \code{max})} - \item{distribution}{Character; the distribution to use.} + +\item{params}{Parameters of the distribution (including \code{max})} } \value{ A \code{dist_spec} of the given specification. From 11872019074d81f64bba58b926f5b06ccfdd8d9d Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Thu, 11 Jan 2024 16:24:55 +0000 Subject: [PATCH 082/129] SD explicitly to zero for fixed --- R/dist.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/dist.R b/R/dist.R index 4815e7fda..e2f338943 100644 --- a/R/dist.R +++ b/R/dist.R @@ -975,7 +975,7 @@ dist_spec <- function(distribution = c( params_sd <- c(mean = mean_sd, sd = sd_sd) } else if (distribution == "fixed") { params_mean <- mean - params_sd <- NULL + params_sd <- 0 } } if (length(pmf) > 0) { From 5173586ad9f3f0e2f03a4e26c4096f401a81eaba Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Thu, 11 Jan 2024 16:25:32 +0000 Subject: [PATCH 083/129] give names --- R/dist.R | 1 + 1 file changed, 1 insertion(+) diff --git a/R/dist.R b/R/dist.R index e2f338943..d57ea269d 100644 --- a/R/dist.R +++ b/R/dist.R @@ -991,6 +991,7 @@ dist_spec <- function(distribution = c( parameters <- lapply(seq_along(params_mean), function(id) { Normal(params_mean[id], params_sd[id]) }) + names(parameters) <- natural_parameters(distribution) parameters$max <- max } return(new_dist_spec(distribution, parameters)) From 96a12779774897d1f4cf0075d54f66b389f6ed9e Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Thu, 11 Jan 2024 16:25:39 +0000 Subject: [PATCH 084/129] fix typo --- R/dist.R | 2 +- man/new_dist_spec.Rd | 6 +++--- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/R/dist.R b/R/dist.R index d57ea269d..80f77c438 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1729,7 +1729,7 @@ extract_params <- function(params, distribution) { ##' @return A `dist_spec` of the given specification. ##' @author Sebastian Funk ##' @keywords internal -new_dist_spec <- function(param, distribution) { +new_dist_spec <- function(params, distribution) { if (distribution == "nonparametric") { ## nonparametric distribution ret <- list( diff --git a/man/new_dist_spec.Rd b/man/new_dist_spec.Rd index 2122ac2b1..943b1fdfb 100644 --- a/man/new_dist_spec.Rd +++ b/man/new_dist_spec.Rd @@ -5,12 +5,12 @@ \title{Internal function for generating a \code{dist_spec} given parameters and a distribution.} \usage{ -new_dist_spec(param, distribution) +new_dist_spec(params, distribution) } \arguments{ -\item{distribution}{Character; the distribution to use.} - \item{params}{Parameters of the distribution (including \code{max})} + +\item{distribution}{Character; the distribution to use.} } \value{ A \code{dist_spec} of the given specification. From c92fb21806b4537043711e758d79704ef81acee5 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Thu, 11 Jan 2024 16:25:48 +0000 Subject: [PATCH 085/129] fix indent --- R/dist.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/dist.R b/R/dist.R index 80f77c438..86d38aa3d 100644 --- a/R/dist.R +++ b/R/dist.R @@ -989,7 +989,7 @@ dist_spec <- function(distribution = c( parameters <- list(pmf = pmf) } else { parameters <- lapply(seq_along(params_mean), function(id) { - Normal(params_mean[id], params_sd[id]) + Normal(params_mean[id], params_sd[id]) }) names(parameters) <- natural_parameters(distribution) parameters$max <- max From e03f365617ce0deb1f730e9c45513dd1f12e245f Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Thu, 11 Jan 2024 16:26:44 +0000 Subject: [PATCH 086/129] fix another typo --- R/dist.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/dist.R b/R/dist.R index 86d38aa3d..c3c39ebb3 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1794,7 +1794,7 @@ new_dist_spec <- function(params, distribution) { } ## convert normal with sd == 0 to fixed if (distribution == "normal" && is.numeric(params$sd) && params$sd == 0) { - rQet <- list( + ret <- list( parameters = list(value = params$mean), distribution = "fixed" ) } else { From 9c4f45a9044deaba3098d61627fedd1da195f8f7 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Thu, 11 Jan 2024 16:37:53 +0000 Subject: [PATCH 087/129] squash bugs highlighted by tests --- R/dist.R | 13 +++++++------ tests/testthat/test-dist_spec.R | 2 +- 2 files changed, 8 insertions(+), 7 deletions(-) diff --git a/R/dist.R b/R/dist.R index c3c39ebb3..9f8414e26 100644 --- a/R/dist.R +++ b/R/dist.R @@ -975,7 +975,6 @@ dist_spec <- function(distribution = c( params_sd <- c(mean = mean_sd, sd = sd_sd) } else if (distribution == "fixed") { params_mean <- mean - params_sd <- 0 } } if (length(pmf) > 0) { @@ -988,13 +987,16 @@ dist_spec <- function(distribution = c( distribution <- "nonparametric" parameters <- list(pmf = pmf) } else { + if (length(params_sd) == 0) { + params_sd <- rep(0, length(params_mean)) + } parameters <- lapply(seq_along(params_mean), function(id) { Normal(params_mean[id], params_sd[id]) }) - names(parameters) <- natural_parameters(distribution) + names(parameters) <- natural_params(distribution) parameters$max <- max } - return(new_dist_spec(distribution, parameters)) + return(new_dist_spec(parameters, distribution)) } #' Creates a delay distribution as the sum of two other delay distributions. @@ -1643,9 +1645,8 @@ Fixed <- function(value, max = Inf) { ##' pmf(c(0.1, 0.3, 0.2, 0.4)) ##' pmf(c(0.1, 0.3, 0.2, 0.1, 0.1)) pmf <- function(mass) { - return( - new_dist_spec(parameters = list(pmf = mass / sum(mass)), "nonparametric") - ) + params <- list(pmf = mass / sum(mass)) + return(new_dist_spec(params, "nonparametric")) } ##' Get the names of the natural parameters of a distribution diff --git a/tests/testthat/test-dist_spec.R b/tests/testthat/test-dist_spec.R index f5c2f1e1b..1c02badee 100644 --- a/tests/testthat/test-dist_spec.R +++ b/tests/testthat/test-dist_spec.R @@ -263,5 +263,5 @@ test_that("delay distributions can be specified in different ways", { }) test_that("deprecated functions are deprecated", { - expect_deprecated(dist_spec(params_mean = 1.6, params_sd = 0.6, max = 19)) + expect_deprecated(dist_spec(params_mean = c(1.6, 0.6), max = 19)) }) From 52eeaf123b0e7270a4d52c5237a1f5d5b6c5bd60 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Fri, 12 Jan 2024 09:58:38 +0000 Subject: [PATCH 088/129] remove missing variable --- R/dist.R | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/R/dist.R b/R/dist.R index 9f8414e26..d5b813897 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1106,7 +1106,7 @@ mean.dist_spec <- function(x, ..., ignore_uncertainty = FALSE) { return(y$parameters$value) } else { stop( - "Don't know how to calculate mean of ", single_dist$dist, + "Don't know how to calculate mean of ", y$distribution, " distribution." ) } @@ -1165,7 +1165,7 @@ sd_dist <- function(x) { } else { stop( "Don't know how to calculate standard deviation of ", - single_dist$dist, " distribution." + y$distribution, " distribution." ) } } From a47549953db165db4d9a5fffe140e4126cd3ef0f Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Fri, 12 Jan 2024 09:59:15 +0000 Subject: [PATCH 089/129] linting --- R/checks.R | 4 ++-- R/create.R | 2 +- R/dist.R | 4 ++-- 3 files changed, 5 insertions(+), 5 deletions(-) diff --git a/R/checks.R b/R/checks.R index 671e69da4..7982705ca 100644 --- a/R/checks.R +++ b/R/checks.R @@ -76,8 +76,8 @@ check_stan_delay <- function(dist) { !all(distributions %in% c("lognormal", "gamma", "fixed", "nonparametric")) ) { stop( - "Distributions passed to the model need to be lognormal, gamma, fixed or ", - "nonparametric (i.e., have no uncertainty)." + "Distributions passed to the model need to be lognormal, gamma, fixed ", + "or nonparametric." ) } # Check that `dist` has parameters that are either numeric or normal diff --git a/R/create.R b/R/create.R index 9fffeb130..2e1227612 100644 --- a/R/create.R +++ b/R/create.R @@ -720,7 +720,7 @@ create_stan_delays <- function(..., weight = 1, tolerance = 0.001) { ## get maximum delays max_delay <- unname(as.numeric(flatten(map(delays, max)))) ## number of different non-empty types - type_n <- vapply(delays, length, numeric(1)) + type_n <- lengths(delays) ## assign ID values to each type ids <- rep(0L, length(type_n)) ids[type_n > 0] <- seq_len(sum(type_n > 0)) diff --git a/R/dist.R b/R/dist.R index d5b813897..a033ee0e1 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1282,7 +1282,7 @@ collapse <- function(x) { ids <- unique(c(1, cumsum(consecutive$lengths[-length(consecutive$lengths)]))) ## find ids of nonparametric distributions that are collapsable ## (i.e. have other nonparametric distributions followign them) - collapseable <- ids[consecutive$values == TRUE & consecutive$length > 1] + collapseable <- ids[consecutive$values & (consecutive$length > 1)] ## identify ids of distributions that follow the collapseable distributions next_ids <- lapply(collapseable, function(id) { ids[id] + seq_len(consecutive$lengths[id] - 1) @@ -1520,7 +1520,7 @@ fix_dist <- function(x, strategy = c("mean", "sample")) { ## if x is fixed already we don't have to do anything if ( x$distribution == "nonparametric" || - all(vapply(x$parameters, is.numeric, logical(1)) == TRUE) + all(vapply(x$parameters, is.numeric, logical(1))) ) { return(x) } From f4f43d4cb5031fb8c13ad2a6c9b0dfc2682f88ff Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Fri, 12 Jan 2024 09:59:31 +0000 Subject: [PATCH 090/129] add missing docs --- R/create.R | 1 + man/create_stan_delays.Rd | 2 ++ 2 files changed, 3 insertions(+) diff --git a/R/create.R b/R/create.R index 2e1227612..4c37e2f68 100644 --- a/R/create.R +++ b/R/create.R @@ -707,6 +707,7 @@ create_stan_args <- function(stan = stan_opts(), ##' ##' @param ... Named delay distributions. The names are assigned to IDs ##' @param weight Numeric, weight associated with delay priors; default: 1 +##' @inheritParams apply_tolerance ##' @return A list of variables as expected by the stan model ##' @importFrom purrr transpose map flatten ##' @author Sebastian Funk diff --git a/man/create_stan_delays.Rd b/man/create_stan_delays.Rd index 958c475fc..d31cc7012 100644 --- a/man/create_stan_delays.Rd +++ b/man/create_stan_delays.Rd @@ -10,6 +10,8 @@ create_stan_delays(..., weight = 1, tolerance = 0.001) \item{...}{Named delay distributions. The names are assigned to IDs} \item{weight}{Numeric, weight associated with delay priors; default: 1} + +\item{tolerance}{Numeric; the desired tolerance level.} } \value{ A list of variables as expected by the stan model From 6ec6394f2a80d30e711beaa6dc18a38db2376015 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Fri, 12 Jan 2024 09:59:39 +0000 Subject: [PATCH 091/129] import transpose --- NAMESPACE | 1 + 1 file changed, 1 insertion(+) diff --git a/NAMESPACE b/NAMESPACE index d127387f3..196f4d8eb 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -216,6 +216,7 @@ importFrom(purrr,pmap_dbl) importFrom(purrr,quietly) importFrom(purrr,reduce) importFrom(purrr,safely) +importFrom(purrr,transpose) importFrom(purrr,walk) importFrom(rlang,abort) importFrom(rlang,arg_match) From a35933a48ec0917e082f5fd9c769458944b783b3 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Fri, 12 Jan 2024 09:59:58 +0000 Subject: [PATCH 092/129] ensure sd is positive --- R/dist.R | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/R/dist.R b/R/dist.R index a033ee0e1..ef00fc55a 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1842,8 +1842,8 @@ convert_to_natural <- function(params, distribution) { x$sdlog <- convert_to_logsd(ux$mean, ux$sd) } if (rel_unc > 0) { - params <- lapply(names(x), function (param_name) { - Normal(mean = x[[param_name]], sd = sqrt(x[[param_name]] * rel_unc)) + params <- lapply(names(x), function(param_name) { + Normal(mean = x[[param_name]], sd = sqrt(abs(x[[param_name]]) * rel_unc)) }) names(params) <- names(x) } else { From 8b95ccf054cf51e9409d2cd004a4116ddd775307 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Fri, 12 Jan 2024 10:00:06 +0000 Subject: [PATCH 093/129] fix estimate_truncation example --- R/estimate_truncation.R | 8 ++++---- man/estimate_truncation.Rd | 2 +- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/R/estimate_truncation.R b/R/estimate_truncation.R index 58c055192..8ee3640c0 100644 --- a/R/estimate_truncation.R +++ b/R/estimate_truncation.R @@ -114,7 +114,7 @@ #' ) #' ) #' ) -#' cmf <- cmf / cmf[dist$max + 1] +#' cmf <- cmf / cmf[max(dist) + 1] #' cmf <- rev(cmf)[-1] #' trunc_cases <- data.table::copy(cases)[1:(.N - index)] #' trunc_cases[ @@ -226,13 +226,13 @@ estimate_truncation <- function(obs, max_truncation, trunc_max = 10, if (construct_trunc) { params_mean <- c(0, 1) params_sd <- c(1, 1) - parameters <- lapply(seq_along(params_mean), function (id) { + parameters <- lapply(seq_along(params_mean), function(id) { Normal(params_mean, params_sd) }) names(parameters) <- natural_params(trunc_dist) parameters$max <- trunc_max truncation <- new_dist_spec( - parameters = parameters, + params = parameters, distribution = trunc_dist ) } @@ -290,7 +290,7 @@ estimate_truncation <- function(obs, max_truncation, trunc_max = 10, }) names(parameters) <- natural_params(truncation[[1]]$distribution) out$dist <- truncation - out$dist$parameters <- parameters + out$dist[[1]]$parameters <- parameters # summarise reconstructed observations recon_obs <- extract_stan_param(fit, "recon_obs", diff --git a/man/estimate_truncation.Rd b/man/estimate_truncation.Rd index c38730153..8f7605746 100644 --- a/man/estimate_truncation.Rd +++ b/man/estimate_truncation.Rd @@ -134,7 +134,7 @@ construct_truncation <- function(index, cases, dist) { ) ) ) - cmf <- cmf / cmf[dist$max + 1] + cmf <- cmf / cmf[max(dist) + 1] cmf <- rev(cmf)[-1] trunc_cases <- data.table::copy(cases)[1:(.N - index)] trunc_cases[ From 9a6922185834ccfd33f56a44af16c8b0d1755aab Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Fri, 12 Jan 2024 10:20:18 +0000 Subject: [PATCH 094/129] make tolerance user-settable --- R/create.R | 11 ++++++----- R/opts.R | 12 +++++++++--- man/create_stan_delays.Rd | 4 +--- man/delay_opts.Rd | 4 +++- man/generation_time_opts.Rd | 5 ++++- man/trunc_opts.Rd | 4 +++- 6 files changed, 26 insertions(+), 14 deletions(-) diff --git a/R/create.R b/R/create.R index 4c37e2f68..c1ee305eb 100644 --- a/R/create.R +++ b/R/create.R @@ -707,17 +707,18 @@ create_stan_args <- function(stan = stan_opts(), ##' ##' @param ... Named delay distributions. The names are assigned to IDs ##' @param weight Numeric, weight associated with delay priors; default: 1 -##' @inheritParams apply_tolerance ##' @return A list of variables as expected by the stan model ##' @importFrom purrr transpose map flatten ##' @author Sebastian Funk -create_stan_delays <- function(..., weight = 1, tolerance = 0.001) { +create_stan_delays <- function(..., weight = 1) { ## discretise - delays <- lapply(list(...), discretise) + delays <- map(list(...), discretise) ## convolve where appropriate - delays <- lapply(delays, collapse) + delays <- map(delays, collapse) ## apply tolerance - delays <- lapply(delays, apply_tolerance, tolerance = tolerance) + delays <- map(delays, function(x) { + apply_tolerance(x, tolerance = attr(x, "tolerance")) + }) ## get maximum delays max_delay <- unname(as.numeric(flatten(map(delays, max)))) ## number of different non-empty types diff --git a/R/opts.R b/R/opts.R index 51bea375c..4c6ae7223 100644 --- a/R/opts.R +++ b/R/opts.R @@ -14,6 +14,7 @@ #' @param prior_weight deprecated; prior weights are now specified as a #' model option. Use the `weigh_delay_priors` argument of #' [estimate_infections()] instead. +#' @inheritParams apply_tolerance #' @return A `` object summarising the input delay #' distributions. #' @author Sebastian Funk @@ -41,7 +42,7 @@ #' generation_time_opts(example_generation_time) generation_time_opts <- function(dist = Fixed(1), ..., disease, source, max = 14, fixed = FALSE, - prior_weight) { + prior_weight, tolerance = 0.001) { deprecated_options_given <- FALSE dot_options <- list(...) @@ -99,6 +100,7 @@ generation_time_opts <- function(dist = Fixed(1), ..., "`?generation_time_opts`") } check_stan_delay(dist) + attr(dist, "tolerance") <- tolerance attr(dist, "class") <- c("generation_time_opts", class(dist)) return(dist) } @@ -112,6 +114,7 @@ generation_time_opts <- function(dist = Fixed(1), ..., #' a fixed distribution with all mass at 0, i.e. no delay. #' @param ... deprecated; use `dist` instead #' @param fixed deprecated; use `dist` instead +#' @inheritParams apply_tolerance #' @return A `` object summarising the input delay distributions. #' @author Sam Abbott #' @author Sebastian Funk @@ -132,7 +135,7 @@ generation_time_opts <- function(dist = Fixed(1), ..., #' #' # Multiple delays (in this case twice the same) #' delay_opts(delay + delay) -delay_opts <- function(dist = Fixed(0), ..., fixed = FALSE) { +delay_opts <- function(dist = Fixed(0), ..., fixed = FALSE, tolerance = 0.001) { dot_options <- list(...) if (!is(dist, "dist_spec")) { ## could be old syntax if (is.list(dist)) { @@ -164,6 +167,7 @@ delay_opts <- function(dist = Fixed(0), ..., fixed = FALSE) { stop("Unknown named arguments passed to `delay_opts`") } check_stan_delay(dist) + attr(dist, "tolerance") <- tolerance attr(dist, "class") <- c("delay_opts", class(dist)) return(dist) } @@ -178,6 +182,7 @@ delay_opts <- function(dist = Fixed(0), ..., fixed = FALSE) { #' @param dist A delay distribution or series of delay distributions reflecting #' the truncation generated using [dist_spec()] or [estimate_truncation()]. #' Default is fixed distribution with maximum 0, i.e. no truncation +#' @inheritParams apply_tolerance #' @return A `` object summarising the input truncation #' distribution. #' @@ -192,7 +197,7 @@ delay_opts <- function(dist = Fixed(0), ..., fixed = FALSE) { #' #' # truncation dist #' trunc_opts(dist = dist_spec(mean = 3, sd = 2, max = 10)) -trunc_opts <- function(dist = Fixed(0)) { +trunc_opts <- function(dist = Fixed(0), tolerance = 0.001) { if (!is(dist, "dist_spec")) { if (is.list(dist)) { dist <- do.call(dist_spec, dist) @@ -209,6 +214,7 @@ trunc_opts <- function(dist = Fixed(0)) { ) } check_stan_delay(dist) + attr(dist, "tolerance") <- tolerance attr(dist, "class") <- c("trunc_opts", class(dist)) return(dist) } diff --git a/man/create_stan_delays.Rd b/man/create_stan_delays.Rd index d31cc7012..5c6519e10 100644 --- a/man/create_stan_delays.Rd +++ b/man/create_stan_delays.Rd @@ -4,14 +4,12 @@ \alias{create_stan_delays} \title{Create delay variables for stan} \usage{ -create_stan_delays(..., weight = 1, tolerance = 0.001) +create_stan_delays(..., weight = 1) } \arguments{ \item{...}{Named delay distributions. The names are assigned to IDs} \item{weight}{Numeric, weight associated with delay priors; default: 1} - -\item{tolerance}{Numeric; the desired tolerance level.} } \value{ A list of variables as expected by the stan model diff --git a/man/delay_opts.Rd b/man/delay_opts.Rd index fa2369ab3..236bb0b60 100644 --- a/man/delay_opts.Rd +++ b/man/delay_opts.Rd @@ -4,7 +4,7 @@ \alias{delay_opts} \title{Delay Distribution Options} \usage{ -delay_opts(dist = Fixed(0), ..., fixed = FALSE) +delay_opts(dist = Fixed(0), ..., fixed = FALSE, tolerance = 0.001) } \arguments{ \item{dist}{A delay distribution or series of delay distributions. Default is @@ -13,6 +13,8 @@ a fixed distribution with all mass at 0, i.e. no delay.} \item{...}{deprecated; use \code{dist} instead} \item{fixed}{deprecated; use \code{dist} instead} + +\item{tolerance}{Numeric; the desired tolerance level.} } \value{ A \verb{} object summarising the input delay distributions. diff --git a/man/generation_time_opts.Rd b/man/generation_time_opts.Rd index 6b605dbb4..9bce3587e 100644 --- a/man/generation_time_opts.Rd +++ b/man/generation_time_opts.Rd @@ -11,7 +11,8 @@ generation_time_opts( source, max = 14, fixed = FALSE, - prior_weight + prior_weight, + tolerance = 0.001 ) } \arguments{ @@ -31,6 +32,8 @@ distribution is given a fixed generation time of 1 will be assumed.} \item{prior_weight}{deprecated; prior weights are now specified as a model option. Use the \code{weigh_delay_priors} argument of \code{\link[=estimate_infections]{estimate_infections()}} instead.} + +\item{tolerance}{Numeric; the desired tolerance level.} } \value{ A \verb{} object summarising the input delay diff --git a/man/trunc_opts.Rd b/man/trunc_opts.Rd index 950865386..736c7e3ea 100644 --- a/man/trunc_opts.Rd +++ b/man/trunc_opts.Rd @@ -4,12 +4,14 @@ \alias{trunc_opts} \title{Truncation Distribution Options} \usage{ -trunc_opts(dist = Fixed(0)) +trunc_opts(dist = Fixed(0), tolerance = 0.001) } \arguments{ \item{dist}{A delay distribution or series of delay distributions reflecting the truncation generated using \code{\link[=dist_spec]{dist_spec()}} or \code{\link[=estimate_truncation]{estimate_truncation()}}. Default is fixed distribution with maximum 0, i.e. no truncation} + +\item{tolerance}{Numeric; the desired tolerance level.} } \value{ A \verb{} object summarising the input truncation From 4c8626d3598b793c9ffc1c42d65991855dea5725 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Fri, 12 Jan 2024 10:49:39 +0000 Subject: [PATCH 095/129] use purrr::map instead of lapply --- R/estimate_truncation.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/estimate_truncation.R b/R/estimate_truncation.R index 8ee3640c0..36446cd01 100644 --- a/R/estimate_truncation.R +++ b/R/estimate_truncation.R @@ -285,7 +285,7 @@ estimate_truncation <- function(obs, max_truncation, trunc_max = 10, delay_params <- extract_stan_param(fit, params = "delay_params") params_mean <- round(delay_params$mean, 3) params_sd <- round(delay_params$sd, 3) - parameters <- lapply(seq_along(params_mean), function (id) { + parameters <- purrr::map(seq_along(params_mean), function (id) { Normal(params_mean[id], params_sd[id]) }) names(parameters) <- natural_params(truncation[[1]]$distribution) From 46e1f8c6ed9b9090e64597a57badce9a7eb6e2c2 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Fri, 12 Jan 2024 11:41:11 +0000 Subject: [PATCH 096/129] fix stan dist test --- tests/testthat/test-dist.R | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tests/testthat/test-dist.R b/tests/testthat/test-dist.R index 7e507400f..c54f1ec22 100644 --- a/tests/testthat/test-dist.R +++ b/tests/testthat/test-dist.R @@ -13,8 +13,8 @@ test_that("distributions are the same in R and stan", { pmf_r_lognormal <- discretise(lognormal_dist)[[1]]$pmf pmf_r_gamma <- discretise(gamma_dist)[[1]]$pmf - pmf_stan_lognormal <- discretised_pmf(lognormal_params, max_args$max + 1, 0) - pmf_stan_gamma <- discretised_pmf(gamma_params, max_args$max + 1, 1) + pmf_stan_lognormal <- discretised_pmf(lognormal_params, args$max + 1, 0) + pmf_stan_gamma <- discretised_pmf(gamma_params, args$max + 1, 1) expect_equal(pmf_r_lognormal, pmf_stan_lognormal) expect_equal(pmf_r_gamma, pmf_stan_gamma) From 2becf787d042bed93f1343594fc4c61b891760dd Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Tue, 16 Jan 2024 12:34:22 +0000 Subject: [PATCH 097/129] fix plotting --- R/dist.R | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/R/dist.R b/R/dist.R index ef00fc55a..454830d6e 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1439,18 +1439,19 @@ plot.dist_spec <- function(x, ...) { value = numeric(), cdf = numeric(), distribution = factor() ) - group_starts <- c(1L, cumsum(x$np_pmf_length) + 1L) + dist_sd <- sd_dist(x) for (i in seq_along(x)) { if (x[[i]]$distribution == "nonparametric") { # Fixed distribution - pmf <- x$pmf[seq(group_starts[i], group_starts[i + 1L] - 1L)] - dist_name <- paste0("Fixed", " (ID: ", i, ")") + pmf <- x[[i]]$pmf + dist_name <- paste0("Nonparametric", " (ID: ", i, ")") } else { # Uncertain distribution c_dist <- discretise(fix_dist(extract_single_dist(x, i))) pmf <- c_dist[[1]]$pmf dist_name <- paste0( - "Uncertain ", x[[i]]$distribution, " (ID: ", i, ")" + ifelse(is.na(dist_sd[i]), "Uncertain ", ""), + x[[i]]$distribution, " (ID: ", i, ")" ) } pmf_data <- rbind( From 748a62c016d1c2a2869de7fff815afe6b0f1b957 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Tue, 20 Feb 2024 12:05:38 +0000 Subject: [PATCH 098/129] Apply suggestions from code review Co-authored-by: Sam Abbott --- R/get.R | 7 ++++--- R/opts.R | 2 +- 2 files changed, 5 insertions(+), 4 deletions(-) diff --git a/R/get.R b/R/get.R index 65ab63201..ae5afcbe8 100644 --- a/R/get.R +++ b/R/get.R @@ -183,7 +183,8 @@ get_dist <- function(data, disease, source, max_value = 14, fixed = FALSE) { "2.0.0", "get_dist()", details = c( paste( - "Please use distribution functions such as `gamma()` or `lognormal()`", + "Please use distribution functions such as `Gamma()` or `Lognormal()`", +`` "instead." ), "The function will be removed completely in version 2.1.0." @@ -229,7 +230,7 @@ get_generation_time <- function(disease, source, max_value = 14, "2.0.0", "get_generation_time()", details = c( paste( - "Please use distribution functions such as `gamma()` or `lognormal()`", + "Please use distribution functions such as `Gamma()` or `Lognormal()`", "instead." ), "The function will be removed completely in version 2.1.0.", @@ -264,7 +265,7 @@ get_incubation_period <- function(disease, source, max_value = 14, "2.0.0", "get_incubation_period()", details = c( paste( - "Please use distribution functions such as `gamma()` or `lognormal()`", + "Please use distribution functions such as `Gamma()` or `Lognormal()`", "instead." ), "The function will be removed completely in version 2.1.0.", diff --git a/R/opts.R b/R/opts.R index 4c6ae7223..2af6740e2 100644 --- a/R/opts.R +++ b/R/opts.R @@ -196,7 +196,7 @@ delay_opts <- function(dist = Fixed(0), ..., fixed = FALSE, tolerance = 0.001) { #' trunc_opts() #' #' # truncation dist -#' trunc_opts(dist = dist_spec(mean = 3, sd = 2, max = 10)) +#' trunc_opts(dist = LogNormal(mean = 3, sd = 2, max = 10)) trunc_opts <- function(dist = Fixed(0), tolerance = 0.001) { if (!is(dist, "dist_spec")) { if (is.list(dist)) { From 57dce2ba63678013681cdd492b8d3e3fe249a132 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Tue, 20 Feb 2024 12:29:33 +0000 Subject: [PATCH 099/129] rate and scale examples for Gamma Co-authored-by: Sam Abbott --- R/dist.R | 1 + 1 file changed, 1 insertion(+) diff --git a/R/dist.R b/R/dist.R index 454830d6e..3789d448d 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1602,6 +1602,7 @@ LogNormal <- function(meanlog, sdlog, mean, sd, max = Inf) { ##' Gamma(mean = 4, sd = 1) ##' Gamma(shape = 16, rate = 4) ##' Gamma(shape = Normal(16, 2), rate = Normal(4, 1)) +##' Gamma(shape = Normal(16, 2), scale = Normal(1/4, 1)) Gamma <- function(shape, rate, scale, mean, sd, max = Inf) { params <- as.list(environment()) return(new_dist_spec(params, "gamma")) From 7a7d29e833e908a971d4496b7f132721723b0291 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Tue, 20 Feb 2024 12:30:07 +0000 Subject: [PATCH 100/129] capitalise gamma and lognormal Co-authored-by: Sam Abbott --- R/dist.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/dist.R b/R/dist.R index 3789d448d..398a9dd09 100644 --- a/R/dist.R +++ b/R/dist.R @@ -924,7 +924,7 @@ dist_spec <- function(distribution = c( "dist_spec()", details = c( paste0( - "Please use distribution functions such as `gamma` or `lognormal` ", + "Please use distribution functions such as `Gamma()` or `Lognormal()` ", "instead." ), "The function will become internal only in version 2.1.0." From e01b874a2a531079f06eaab38eee2cc1d1f2c16f Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Tue, 20 Feb 2024 12:31:26 +0000 Subject: [PATCH 101/129] change to single hash --- R/dist.R | 468 +++++++++++++++++++++++++++---------------------------- 1 file changed, 234 insertions(+), 234 deletions(-) diff --git a/R/dist.R b/R/dist.R index 398a9dd09..1d0a46e58 100644 --- a/R/dist.R +++ b/R/dist.R @@ -1051,21 +1051,21 @@ c.dist_spec <- function(...) { return(dist_specs) } -##' Returns the mean of one or more delay distribution -##' -##' This works out the mean of all the (parametric / nonparametric) delay -##' distributions combined in the passed [dist_spec()] (ignoring any uncertainty -##' in parameters) -##' -##' @param x The `` to use -##' @param ... Not used -##' @param ignore_uncertainty Logical; whether to ignore any uncertainty in -##' parameters. If set to FALSE (the default) then the mean of any uncertain -##' parameters will be returned as NA. -##' @author Sebastian Funk -##' @method mean dist_spec -##' @importFrom utils head -##' @export +#' Returns the mean of one or more delay distribution +#' +#' This works out the mean of all the (parametric / nonparametric) delay +#' distributions combined in the passed [dist_spec()] (ignoring any uncertainty +#' in parameters) +#' +#' @param x The `` to use +#' @param ... Not used +#' @param ignore_uncertainty Logical; whether to ignore any uncertainty in +#' parameters. If set to FALSE (the default) then the mean of any uncertain +#' parameters will be returned as NA. +#' @author Sebastian Funk +#' @method mean dist_spec +#' @importFrom utils head +#' @export #' @examples #' # A fixed lognormal distribution with mean 5 and sd 1. #' dist1 <- LogNormal(mean = 5, sd = 1, max = 20) @@ -1115,29 +1115,29 @@ mean.dist_spec <- function(x, ..., ignore_uncertainty = FALSE) { return(ret) } -##' Returns the standard deviation of one or more delay distribution -##' -##' This works out the standard deviation of all the (parametric / -##' nonparametric) delay distributions combined in the passed [dist_spec()]. -##' -##' @param x The [dist_spec()] to use -##' @return A vector of standard deviations. -##' @author Sebastian Funk -##' @importFrom utils head -##' @keywords internal -##' @examples -##' \dontrun{ -##' # A fixed lognormal distribution with sd 5 and sd 1. -##' dist1 <- LogNormal(mean = 5, sd = 1, max = 20) -##' sd_dist(dist1) -##' -##' # A gamma distribution with mean 3 and sd 2 -##' dist2 <- Gamma(mean = 3, sd = 2) -##' sd_dist(dist2) -##' -##' # The sd of the sum of two distributions -##' sd_dist(dist1 + dist2) -##' } +#' Returns the standard deviation of one or more delay distribution +#' +#' This works out the standard deviation of all the (parametric / +#' nonparametric) delay distributions combined in the passed [dist_spec()]. +#' +#' @param x The [dist_spec()] to use +#' @return A vector of standard deviations. +#' @author Sebastian Funk +#' @importFrom utils head +#' @keywords internal +#' @examples +#' \dontrun{ +#' # A fixed lognormal distribution with sd 5 and sd 1. +#' dist1 <- LogNormal(mean = 5, sd = 1, max = 20) +#' sd_dist(dist1) +#' +#' # A gamma distribution with mean 3 and sd 2 +#' dist2 <- Gamma(mean = 3, sd = 2) +#' sd_dist(dist2) +#' +#' # The sd of the sum of two distributions +#' sd_dist(dist1 + dist2) +#' } sd_dist <- function(x) { ret <- vapply(x, function(y) { if (is.numeric(y)) { @@ -1173,18 +1173,18 @@ sd_dist <- function(x) { return(ret) } -##' Returns the maximum of one or more delay distribution -##' -##' This works out the maximum of all the (parametric / nonparametric) delay -##' distributions combined in the passed [dist_spec()] (ignoring any uncertainty -##' in parameters) -##' -##' @param x The [dist_spec()] to use -##' @param ... Not used -##' @return A vector of means. -##' @author Sebastian Funk -##' @method max dist_spec -##' @export +#' Returns the maximum of one or more delay distribution +#' +#' This works out the maximum of all the (parametric / nonparametric) delay +#' distributions combined in the passed [dist_spec()] (ignoring any uncertainty +#' in parameters) +#' +#' @param x The [dist_spec()] to use +#' @param ... Not used +#' @return A vector of means. +#' @author Sebastian Funk +#' @method max dist_spec +#' @export #' @examples #' # A fixed gamma distribution with mean 5 and sd 1. #' dist1 <- Gamma(mean = 5, sd = 1, max = 20) @@ -1211,19 +1211,19 @@ max.dist_spec <- function(x, ...) { return(ret) } ## -##' Discretise a -##' -##' By default it will discretise all the distributions it can discretise -##' (i.e. those with finite support and constant parameters). -##' @title Discretise a -##' @param x A `` -##' @param silent Logical; if `TRUE` then any distribution that can't be -##' discretised will be returned as is. If `FALSE` then an error will be -##' thrown. -##' @return A `` where all distributions with constant parameters are -##' nonparametric. -##' @author Sebastian Funk -##' @export +#' Discretise a +#' +#' By default it will discretise all the distributions it can discretise +#' (i.e. those with finite support and constant parameters). +#' @title Discretise a +#' @param x A `` +#' @param silent Logical; if `TRUE` then any distribution that can't be +#' discretised will be returned as is. If `FALSE` then an error will be +#' thrown. +#' @return A `` where all distributions with constant parameters are +#' nonparametric. +#' @author Sebastian Funk +#' @export discretise <- function(x, silent = TRUE) { if (!is(x, "dist_spec")) { stop("Can only discretise a .") @@ -1261,16 +1261,16 @@ discretise <- function(x, silent = TRUE) { return(ret) } -##' Collapse nonparametric distributions in a -##' -##' This convolves any consecutive nonparametric distributions contained -##' in the . -##' @param x A `` -##' @return A `` where consecutive nonparametric distributions -##' have been convolved -##' @importFrom stats convolve -##' @author Sebastian Funk -##' @export +#' Collapse nonparametric distributions in a +#' +#' This convolves any consecutive nonparametric distributions contained +#' in the . +#' @param x A `` +#' @return A `` where consecutive nonparametric distributions +#' have been convolved +#' @importFrom stats convolve +#' @author Sebastian Funk +#' @export collapse <- function(x) { if (!is(x, "dist_spec")) { stop("Can only convolve distributions in a .") @@ -1301,16 +1301,16 @@ collapse <- function(x) { return(x) } -##' Applies a threshold to all nonparametric distributions in a -##' -##' This removes any part of the tail of the nonparametric distributions in the -##' where the probability mass is below the threshold level. -##' @param x A `` -##' @param tolerance Numeric; the desired tolerance level. -##' @return A `` where probability masses below the threshold level -##' have been removed -##' @author Sebastian Funk, Sam Abbott -##' @export +#' Applies a threshold to all nonparametric distributions in a +#' +#' This removes any part of the tail of the nonparametric distributions in the +#' where the probability mass is below the threshold level. +#' @param x A `` +#' @param tolerance Numeric; the desired tolerance level. +#' @return A `` where probability masses below the threshold level +#' have been removed +#' @author Sebastian Funk, Sam Abbott +#' @export apply_tolerance <- function(x, tolerance) { if (!is(x, "dist_spec")) { stop("Can only apply tolerance to distributions in a .") @@ -1481,13 +1481,13 @@ plot.dist_spec <- function(x, ...) { return(plot) } -##' Extract a single element of a composite `` -##' -##' @param x A composite `dist_spec` object -##' @param i The index to extract -##' @return A single `dist_spec` object -##' @keywords internal -##' @author Sebastian Funk +#' Extract a single element of a composite `` +#' +#' @param x A composite `dist_spec` object +#' @param i The index to extract +#' @return A single `dist_spec` object +#' @keywords internal +#' @author Sebastian Funk extract_single_dist <- function(x, i) { if (i > length(x)) { stop("i can't be greater than the number of distributions.") @@ -1497,19 +1497,19 @@ extract_single_dist <- function(x, i) { return(ret) } -##' Fix the parameters of a `` -##' -##' If the given `` has any uncertainty, it is removed and the -##' corresponding distribution converted into a fixed one. -##' @return A `` object without uncertainty -##' @author Sebastian Funk -##' @export -##' @param x A `` -##' @param strategy Character; either "mean" (use the mean estimates of the -##' mean and standard deviation) or "sample" (randomly sample mean and -##' standard deviation from uncertainty given in the `` -##' @importFrom truncnorm rtruncnorm -##' @importFrom rlang arg_match +#' Fix the parameters of a `` +#' +#' If the given `` has any uncertainty, it is removed and the +#' corresponding distribution converted into a fixed one. +#' @return A `` object without uncertainty +#' @author Sebastian Funk +#' @export +#' @param x A `` +#' @param strategy Character; either "mean" (use the mean estimates of the +#' mean and standard deviation) or "sample" (randomly sample mean and +#' standard deviation from uncertainty given in the `` +#' @importFrom truncnorm rtruncnorm +#' @importFrom rlang arg_match fix_dist <- function(x, strategy = c("mean", "sample")) { if (!is(x, "dist_spec")) { stop("Can only fix distributions in a .") @@ -1546,124 +1546,124 @@ fix_dist <- function(x, strategy = c("mean", "sample")) { return(ret) } -##' @details -##' Probability distributions are ubiquitous in EpiNow2, usually representing -##' epidemiological delays (e.g., the generation time for delays between -##' becoming infecting and infecting others; or reporting delays) -##' -##' They are generated using functions that have a name corresponding to the -##' probability distribution that is being used. They generated `dist_spec` -##' objects that are then passed to the models underlying EpiNow2. +#' @details +#' Probability distributions are ubiquitous in EpiNow2, usually representing +#' epidemiological delays (e.g., the generation time for delays between +#' becoming infecting and infecting others; or reporting delays) +#' +#' They are generated using functions that have a name corresponding to the +#' probability distribution that is being used. They generated `dist_spec` +#' objects that are then passed to the models underlying EpiNow2. ## -##' All parameters can be given either as fixed values (a numeric value) or as -##' uncertain values (a `dist_sepc`). If given as uncertain values, currently -##' only normally distributed parameters (generated using `Normal()`) are -##' supported. -##' -##' Each distribution has a representation in terms of "natural" parameters (the -##' ones used in stan) but can sometimes also be specified using other -##' parameters such as the mean or standard deviation of the distribution. If -##' not given as natural parameters then these will be calculated from the given -##' parameters. If they have uncertainty, this will be done by random sampling -##' from the given uncertainty and converting resulting parameters to their -##' natural representation. -##' -##' Currently available distributions are lognormal, gamma, normal, fixed -##' (delta) and nonparametric. The nonparametric is a special case where the -##' probability mass function is given directly as a numeric vector. -##' -##' @inheritParams stats::Lognormal -##' @param mean,sd mean and standard deviation of the distribution -##' @param max Numeric, maximum value of the distribution. The distribution will -##' be truncated at this value. Default: `Inf`, i.e. no maximum. -##' @return A `dist_spec` representing a distribution of the given -##' specification. -##' @author Sebastian Funk -##' @export -##' @rdname Distributions -##' @name Distributions -##' @order 1 -##' @examples -##' LogNormal(mean = 4, sd = 1) -##' LogNormal(mean = 4, sd = 1, max = 10) -##' LogNormal(mean = Normal(4, 1), sd = 1, max = 10) +#' All parameters can be given either as fixed values (a numeric value) or as +#' uncertain values (a `dist_sepc`). If given as uncertain values, currently +#' only normally distributed parameters (generated using `Normal()`) are +#' supported. +#' +#' Each distribution has a representation in terms of "natural" parameters (the +#' ones used in stan) but can sometimes also be specified using other +#' parameters such as the mean or standard deviation of the distribution. If +#' not given as natural parameters then these will be calculated from the given +#' parameters. If they have uncertainty, this will be done by random sampling +#' from the given uncertainty and converting resulting parameters to their +#' natural representation. +#' +#' Currently available distributions are lognormal, gamma, normal, fixed +#' (delta) and nonparametric. The nonparametric is a special case where the +#' probability mass function is given directly as a numeric vector. +#' +#' @inheritParams stats::Lognormal +#' @param mean,sd mean and standard deviation of the distribution +#' @param max Numeric, maximum value of the distribution. The distribution will +#' be truncated at this value. Default: `Inf`, i.e. no maximum. +#' @return A `dist_spec` representing a distribution of the given +#' specification. +#' @author Sebastian Funk +#' @export +#' @rdname Distributions +#' @name Distributions +#' @order 1 +#' @examples +#' LogNormal(mean = 4, sd = 1) +#' LogNormal(mean = 4, sd = 1, max = 10) +#' LogNormal(mean = Normal(4, 1), sd = 1, max = 10) LogNormal <- function(meanlog, sdlog, mean, sd, max = Inf) { params <- as.list(environment()) return(new_dist_spec(params, "lognormal")) } -##' @inheritParams stats::GammaDist -##' @author Sebastian Funk -##' @rdname Distributions -##' @title Probability distributions -##' @order 2 -##' @export -##' @examples -##' Gamma(mean = 4, sd = 1) -##' Gamma(shape = 16, rate = 4) -##' Gamma(shape = Normal(16, 2), rate = Normal(4, 1)) -##' Gamma(shape = Normal(16, 2), scale = Normal(1/4, 1)) +#' @inheritParams stats::GammaDist +#' @author Sebastian Funk +#' @rdname Distributions +#' @title Probability distributions +#' @order 2 +#' @export +#' @examples +#' Gamma(mean = 4, sd = 1) +#' Gamma(shape = 16, rate = 4) +#' Gamma(shape = Normal(16, 2), rate = Normal(4, 1)) +#' Gamma(shape = Normal(16, 2), scale = Normal(1/4, 1)) Gamma <- function(shape, rate, scale, mean, sd, max = Inf) { params <- as.list(environment()) return(new_dist_spec(params, "gamma")) } -##' @rdname Distributions -##' @order 3 -##' @author Sebastian Funk -##' @export -##' @examples -##' Normal(mean = 4, sd = 1) -##' Normal(mean = 4, sd = 1, max = 10) +#' @rdname Distributions +#' @order 3 +#' @author Sebastian Funk +#' @export +#' @examples +#' Normal(mean = 4, sd = 1) +#' Normal(mean = 4, sd = 1, max = 10) Normal <- function(mean, sd, max = Inf) { params <- as.list(environment()) return(new_dist_spec(params, "normal")) } -##' @rdname Distributions -##' @order 4 -##' @param value Value of the fixed (delta) distribution -##' @author Sebastian Funk -##' @export -##' @examples -##' Fixed(value = 3) -##' Fixed(value = 3.5) +#' @rdname Distributions +#' @order 4 +#' @param value Value of the fixed (delta) distribution +#' @author Sebastian Funk +#' @export +#' @examples +#' Fixed(value = 3) +#' Fixed(value = 3.5) Fixed <- function(value, max = Inf) { params <- as.list(environment()) return(new_dist_spec(params, "fixed")) } -##' Generates a nonparametric distribution. -##' -##' @param mass Probability mass of the given distribution; this is -##' passed as a zero-indexed numeric vector (i.e. the fist entry represents -##' the probability mass of zero). If not summing to one it will be normalised -##' to sum to one internally. -##' @author Sebastian Funk -##' @rdname Distributions -##' @order 5 -##' @export -##' @examples -##' pmf(c(0.1, 0.3, 0.2, 0.4)) -##' pmf(c(0.1, 0.3, 0.2, 0.1, 0.1)) +#' Generates a nonparametric distribution. +#' +#' @param mass Probability mass of the given distribution; this is +#' passed as a zero-indexed numeric vector (i.e. the fist entry represents +#' the probability mass of zero). If not summing to one it will be normalised +#' to sum to one internally. +#' @author Sebastian Funk +#' @rdname Distributions +#' @order 5 +#' @export +#' @examples +#' pmf(c(0.1, 0.3, 0.2, 0.4)) +#' pmf(c(0.1, 0.3, 0.2, 0.1, 0.1)) pmf <- function(mass) { params <- list(pmf = mass / sum(mass)) return(new_dist_spec(params, "nonparametric")) } -##' Get the names of the natural parameters of a distribution -##' -##' These are the parameters used in the stan models. All other parameter -##' representations are converted to these using [convert_to_natural()] before -##' being passed to the stan models. -##' @param distribution Character; the distribution to use. -##' @return A character vector, the natural parameters. -##' @author Sebastian Funk -##' @keywords internal -##' @examples -##' \dontrun{ -##' natural_params("gamma") -##' } +#' Get the names of the natural parameters of a distribution +#' +#' These are the parameters used in the stan models. All other parameter +#' representations are converted to these using [convert_to_natural()] before +#' being passed to the stan models. +#' @param distribution Character; the distribution to use. +#' @return A character vector, the natural parameters. +#' @author Sebastian Funk +#' @keywords internal +#' @examples +#' \dontrun{ +#' natural_params("gamma") +#' } natural_params <- function(distribution) { if (distribution == "gamma") { ret <- c("shape", "rate") @@ -1677,17 +1677,17 @@ natural_params <- function(distribution) { return(ret) } -##' Get the lower bounds of the parameters of a distribution -##' -##' This is used to avoid sampling parameter values that have no support. -##' @return A numeric vector, the lower bounds. -##' @inheritParams natural_params -##' @author Sebastian Funk -##' @keywords internal -##' @examples -##' \dontrun{ -##' lower_bounds("lognormal") -##' } +#' Get the lower bounds of the parameters of a distribution +#' +#' This is used to avoid sampling parameter values that have no support. +#' @return A numeric vector, the lower bounds. +#' @inheritParams natural_params +#' @author Sebastian Funk +#' @keywords internal +#' @examples +#' \dontrun{ +#' lower_bounds("lognormal") +#' } lower_bounds <- function(distribution) { if (distribution == "gamma") { ret <- c(shape = 0, rate = 0, scale = 0, mean = 0, sd = 0) @@ -1701,14 +1701,14 @@ lower_bounds <- function(distribution) { return(ret) } -##' Internal function for extracting given parameter names of a distribution -##' from the environment -##' -##' @param params Given parameters (obtained using `as.list(environment())`) -##' @return A character vector of parameters and their values. -##' @inheritParams natural_params -##' @author Sebastian Funk -##' @keywords internal +#' Internal function for extracting given parameter names of a distribution +#' from the environment +#' +#' @param params Given parameters (obtained using `as.list(environment())`) +#' @return A character vector of parameters and their values. +#' @inheritParams natural_params +#' @author Sebastian Funk +#' @keywords internal extract_params <- function(params, distribution) { params <- params[!vapply(params, inherits, "name", FUN.VALUE = TRUE)] n_params <- length(natural_params(distribution)) @@ -1721,17 +1721,17 @@ extract_params <- function(params, distribution) { return(params) } -##' Internal function for generating a `dist_spec` given parameters and a -##' distribution. -##' -##' This will convert all parameters to natural parameters before generating -##' a `dist_spec`. If they have uncertainty this will be done using sampling. -##' @param params Parameters of the distribution (including `max`) -##' @inheritParams extract_params -##' @importFrom purrr walk -##' @return A `dist_spec` of the given specification. -##' @author Sebastian Funk -##' @keywords internal +#' Internal function for generating a `dist_spec` given parameters and a +#' distribution. +#' +#' This will convert all parameters to natural parameters before generating +#' a `dist_spec`. If they have uncertainty this will be done using sampling. +#' @param params Parameters of the distribution (including `max`) +#' @inheritParams extract_params +#' @importFrom purrr walk +#' @return A `dist_spec` of the given specification. +#' @author Sebastian Funk +#' @keywords internal new_dist_spec <- function(params, distribution) { if (distribution == "nonparametric") { ## nonparametric distribution @@ -1814,15 +1814,15 @@ new_dist_spec <- function(params, distribution) { return(ret) } -##' Internal function for converting parameters to natural parameters. -##' -##' This is used for preprocessing before generating a `dist_spec` object -##' from a given set of parameters and distribution -##' @param params A numerical named parameter vector -##' @inheritParams natural_params -##' @return A list with two elements, `params_mean` and `params_sd`, containing -##' mean and sd of natural parameters. -##' @author Sebastian Funk +#' Internal function for converting parameters to natural parameters. +#' +#' This is used for preprocessing before generating a `dist_spec` object +#' from a given set of parameters and distribution +#' @param params A numerical named parameter vector +#' @inheritParams natural_params +#' @return A list with two elements, `params_mean` and `params_sd`, containing +#' mean and sd of natural parameters. +#' @author Sebastian Funk convert_to_natural <- function(params, distribution) { ## unnatural parameter means ux <- lapply(params, mean) From 9374acd7cf5f8ca8aa0f1d0c4e34564d1a8d0353 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Tue, 20 Feb 2024 12:51:53 +0000 Subject: [PATCH 102/129] use bar in normal_cdf --- inst/stan/functions/delays.stan | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/inst/stan/functions/delays.stan b/inst/stan/functions/delays.stan index aefeacbfa..dcc17f1b0 100644 --- a/inst/stan/functions/delays.stan +++ b/inst/stan/functions/delays.stan @@ -108,7 +108,7 @@ vector normal_lb_rng(vector mu, vector sigma, vector lb) { int len = num_elements(mu); vector[len] ret; for (i in 1:len) { - real p = normal_cdf(lb[i], mu[i], sigma[i]); // cdf for bounds + real p = normal_cdf(lb[i] | mu[i], sigma[i]); // cdf for bounds real u = uniform_rng(p, 1); ret[i] = (sigma[i] * inv_Phi(u)) + mu[i]; // inverse cdf for value } From 2a3495f7be7bff70375d096602ee53778451bf6c Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Tue, 20 Feb 2024 12:52:29 +0000 Subject: [PATCH 103/129] remove estraneous backticks --- R/get.R | 1 - 1 file changed, 1 deletion(-) diff --git a/R/get.R b/R/get.R index ae5afcbe8..395e2beed 100644 --- a/R/get.R +++ b/R/get.R @@ -184,7 +184,6 @@ get_dist <- function(data, disease, source, max_value = 14, fixed = FALSE) { details = c( paste( "Please use distribution functions such as `Gamma()` or `Lognormal()`", -`` "instead." ), "The function will be removed completely in version 2.1.0." From 204feff5181c7a67de9039537610ffcaae0868e9 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Tue, 20 Feb 2024 13:42:29 +0000 Subject: [PATCH 104/129] remove space before left parenthesis --- R/estimate_truncation.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/estimate_truncation.R b/R/estimate_truncation.R index 36446cd01..aa2148f49 100644 --- a/R/estimate_truncation.R +++ b/R/estimate_truncation.R @@ -285,7 +285,7 @@ estimate_truncation <- function(obs, max_truncation, trunc_max = 10, delay_params <- extract_stan_param(fit, params = "delay_params") params_mean <- round(delay_params$mean, 3) params_sd <- round(delay_params$sd, 3) - parameters <- purrr::map(seq_along(params_mean), function (id) { + parameters <- purrr::map(seq_along(params_mean), function(id) { Normal(params_mean[id], params_sd[id]) }) names(parameters) <- natural_params(truncation[[1]]$distribution) From ca47727c61fdb49de71bfb68f614ba074af47f25 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 21 Feb 2024 14:42:44 +0000 Subject: [PATCH 105/129] split up dist.R --- R/adjust.R | 185 +++++++++++ R/deprecated.R | 215 ++++++++++++ R/{dist.R => dist_spec.R} | 670 -------------------------------------- R/estimate_delay.R | 268 +++++++++++++++ 4 files changed, 668 insertions(+), 670 deletions(-) create mode 100644 R/deprecated.R rename R/{dist.R => dist_spec.R} (65%) create mode 100644 R/estimate_delay.R diff --git a/R/adjust.R b/R/adjust.R index a20ea0bb6..7335f487c 100644 --- a/R/adjust.R +++ b/R/adjust.R @@ -184,3 +184,188 @@ adjust_infection_to_report <- function(infections, delay_defs, } return(report) } + +#' Approximate Sampling a Distribution using Counts +#' +#' @description `r lifecycle::badge("soft-deprecated")` +#' Convolves cases by a PMF function. This function will soon be removed or +#' replaced with a more robust stan implementation. +#' +#' @param cases A `` of cases (in date order) with the following +#' variables: `date` and `cases`. +#' +#' @param max_value Numeric, maximum value to allow. Defaults to 120 days +#' +#' @param direction Character string, defato "backwards". Direction in which to +#' map cases. Supports either "backwards" or "forwards". +#' +#' @param dist_fn Function that takes two arguments with the first being +#' numeric and the second being logical (and defined as `dist`). Should return +#' the probability density or a sample from the defined distribution. See +#' the examples for more. +#' +#' @param earliest_allowed_mapped A character string representing a date +#' ("2020-01-01"). Indicates the earliest allowed mapped value. +#' +#' @param type Character string indicating the method to use to transform +#' counts. Supports either "sample" which approximates sampling or "median" +#' would shift by the median of the distribution. +#' +#' @param truncate_future Logical, should cases be truncated if they occur +#' after the first date reported in the data. Defaults to `TRUE`. +#' +#' @return A `` of cases by date of onset +#' @export +#' @importFrom purrr map_dfc +#' @importFrom data.table data.table setorder +#' @importFrom lubridate days +#' @examples +#' \donttest{ +#' cases <- example_confirmed +#' cases <- cases[, cases := as.integer(confirm)] +#' print(cases) +#' +#' # total cases +#' sum(cases$cases) +#' +#' delay_fn <- function(n, dist, cum) { +#' if (dist) { +#' pgamma(n + 0.9999, 2, 1) - pgamma(n - 1e-5, 2, 1) +#' } else { +#' as.integer(rgamma(n, 2, 1)) +#' } +#' } +#' +#' onsets <- sample_approx_dist( +#' cases = cases, +#' dist_fn = delay_fn +#' ) +#' +#' # estimated onset distribution +#' print(onsets) +#' +#' # check that sum is equal to reported cases +#' total_onsets <- median( +#' purrr::map_dbl( +#' 1:10, +#' ~ sum(sample_approx_dist( +#' cases = cases, +#' dist_fn = delay_fn +#' )$cases) +#' ) +#' ) +#' total_onsets +#' +#' +#' # map from onset cases to reported +#' reports <- sample_approx_dist( +#' cases = cases, +#' dist_fn = delay_fn, +#' direction = "forwards" +#' ) +#' +#' +#' # map from onset cases to reported using a mean shift +#' reports <- sample_approx_dist( +#' cases = cases, +#' dist_fn = delay_fn, +#' direction = "forwards", +#' type = "median" +#' ) +#' } +sample_approx_dist <- function(cases = NULL, + dist_fn = NULL, + max_value = 120, + earliest_allowed_mapped = NULL, + direction = "backwards", + type = "sample", + truncate_future = TRUE) { + if (type == "sample") { + if (direction == "backwards") { + direction_fn <- rev + } else if (direction == "forwards") { + direction_fn <- function(x) { + x + } + } + # reverse cases so starts with current first + reversed_cases <- direction_fn(cases$cases) + reversed_cases[is.na(reversed_cases)] <- 0 + # draw from the density fn of the dist + draw <- dist_fn(0:max_value, dist = TRUE, cum = FALSE) + + # approximate cases + mapped_cases <- suppressMessages(purrr::map_dfc( + seq_along(reversed_cases), + ~ c( + rep(0, . - 1), + stats::rbinom( + length(draw), + rep(reversed_cases[.], length(draw)), + draw + ), + rep(0, length(reversed_cases) - .) + ) + )) + + + # set dates order based on direction mapping + if (direction == "backwards") { + dates <- seq(min(cases$date) - lubridate::days(length(draw) - 1), + max(cases$date), + by = "days" + ) + } else if (direction == "forwards") { + dates <- seq(min(cases$date), + max(cases$date) + lubridate::days(length(draw) - 1), + by = "days" + ) + } + + # summarises movements and sample for placement of non-integer cases + case_sum <- direction_fn(rowSums(mapped_cases)) + floor_case_sum <- floor(case_sum) + sample_cases <- floor_case_sum + + as.numeric((runif(seq_along(case_sum)) < (case_sum - floor_case_sum))) + + # summarise imputed onsets and build output data.table + mapped_cases <- data.table::data.table( + date = dates, + cases = sample_cases + ) + + # filter out all zero cases until first recorded case + mapped_cases <- data.table::setorder(mapped_cases, date) + mapped_cases <- mapped_cases[ + , + cum_cases := cumsum(cases) + ][cum_cases != 0][, cum_cases := NULL] + } else if (type == "median") { + shift <- as.integer( + median(as.integer(dist_fn(1000, dist = FALSE)), na.rm = TRUE) + ) + + if (direction == "backwards") { + mapped_cases <- data.table::copy(cases)[ + , + date := date - lubridate::days(shift) + ] + } else if (direction == "forwards") { + mapped_cases <- data.table::copy(cases)[ + , + date := date + lubridate::days(shift) + ] + } + } + + if (!is.null(earliest_allowed_mapped)) { + mapped_cases <- mapped_cases[date >= as.Date(earliest_allowed_mapped)] + } + + # filter out future cases + if (direction == "forwards" && truncate_future) { + max_date <- max(cases$date) + mapped_cases <- mapped_cases[date <= max_date] + } + return(mapped_cases) +} diff --git a/R/deprecated.R b/R/deprecated.R new file mode 100644 index 000000000..874871a6b --- /dev/null +++ b/R/deprecated.R @@ -0,0 +1,215 @@ +#' Generate a Gamma Distribution Definition Based on Parameter Estimates +#' +#' @description `r lifecycle::badge("deprecated")` +#' Deprecated; use [Gamma()] instead to define a gamma distribution. +#' +#' @param shape Numeric, shape parameter of the gamma distribution. +#' +#' @param shape_sd Numeric, standard deviation of the shape parameter. +#' +#' @param scale Numeric, scale parameter of the gamma distribution. +#' +#' @param scale_sd Numeric, standard deviation of the scale parameter. +#' +#' @param samples Numeric, number of sample distributions to generate. +#' +#' @importFrom truncnorm rtruncnorm +#' @return A `` defining the distribution as used by [dist_skel()] +#' @export +#' @inheritParams dist_skel +#' @inheritParams lognorm_dist_def +#' @author Sam Abbott +#' @examples +#' # using estimated shape and scale +#' def <- gamma_dist_def( +#' shape = 5.807, shape_sd = 0.2, +#' scale = 0.9, scale_sd = 0.05, +#' max_value = 20, samples = 10 +#' ) +#' print(def) +#' def$params[[1]] +#' +#' # using mean and sd +#' def <- gamma_dist_def( +#' mean = 3, mean_sd = 0.5, +#' sd = 3, sd_sd = 0.1, +#' max_value = 20, samples = 10 +#' ) +#' print(def) +#' def$params[[1]] +gamma_dist_def <- function(shape, shape_sd, + scale, scale_sd, + mean, mean_sd, + sd, sd_sd, + max_value, samples) { + lifecycle::deprecate_warn( + "2.0.0", "gamma_dist_def()", "Gamma()", + "The function will be removed completely in version 2.1.0." + ) + + if (missing(shape) && missing(scale) && !missing(mean) && !missing(sd)) { + if (!missing(mean_sd)) { + mean <- truncnorm::rtruncnorm(samples, a = 0, mean = mean, sd = mean_sd) + } + if (!missing(sd_sd)) { + sd <- truncnorm::rtruncnorm(samples, a = 0, mean = sd, sd = sd_sd) + } + scale <- sd^2 / mean + shape <- mean / scale + } else { + if (!missing(shape_sd)) { + shape <- truncnorm::rtruncnorm( + samples, + a = 0, mean = shape, sd = shape_sd + ) + } + if (!missing(scale_sd)) { + scale <- 1 / truncnorm::rtruncnorm( + samples, + a = 0, mean = scale, sd = scale_sd + ) + } + } + + rate <- 1 / scale + + dist <- data.table::data.table( + model = rep("gamma", samples), + params = purrr::list_transpose( + list( + shape = shape, + rate = rate + ) + ), + max_value = rep(max_value, samples) + ) + return(dist) +} + +#' Generate a Log Normal Distribution Definition Based on Parameter Estimates +#' +#' @description `r lifecycle::badge("deprecated")` +#' Generates a distribution definition when only parameter estimates +#' are available for log normal distributed parameters. See [rlnorm()] for +#' distribution information. +#' +#' @param mean Numeric, log mean parameter of the gamma distribution. +#' +#' @param mean_sd Numeric, standard deviation of the log mean parameter. +#' +#' @param sd Numeric, log sd parameter of the gamma distribution. +#' +#' @param sd_sd Numeric, standard deviation of the log sd parameter. +#' +#' @param samples Numeric, number of sample distributions to generate. +#' +#' @param to_log Logical, should parameters be logged before use. +#' +#' @return A `` defining the distribution as used by [dist_skel()] +#' @author Sam Abbott +#' @importFrom truncnorm rtruncnorm +#' @export +#' @inheritParams dist_skel +#' @examples +#' def <- lognorm_dist_def( +#' mean = 1.621, mean_sd = 0.0640, +#' sd = 0.418, sd_sd = 0.0691, +#' max_value = 20, samples = 10 +#' ) +#' print(def) +#' def$params[[1]] +#' +#' def <- lognorm_dist_def( +#' mean = 5, mean_sd = 1, +#' sd = 3, sd_sd = 1, +#' max_value = 20, samples = 10, +#' to_log = TRUE +#' ) +#' print(def) +#' def$params[[1]] +lognorm_dist_def <- function(mean, mean_sd, + sd, sd_sd, + max_value, samples, + to_log = FALSE) { + lifecycle::deprecate_warn( + "2.0.0", "lognorm_dist_def()", "LogNormal()", + "The function will be removed completely in version 2.1.0." + ) + + transform_mean <- function(mu, sig) { + mean_location <- log(mu^2 / sqrt(sig^2 + mu^2)) + mean_location + } + + transform_sd <- function(mu, sig) { + mean_shape <- sqrt(log(1 + (sig^2 / mu^2))) + mean_shape + } + + if (missing(mean_sd)) { + sampled_means <- mean + } else { + sampled_means <- truncnorm::rtruncnorm( + samples, + a = 0, mean = mean, sd = mean_sd + ) + } + + if (missing(sd_sd)) { + sampled_sds <- sd + } else { + sampled_sds <- truncnorm::rtruncnorm(samples, a = 0, mean = sd, sd = sd_sd) + } + means <- sampled_means + sds <- sampled_sds + + if (to_log) { + means <- mapply(transform_mean, sampled_means, sampled_sds) + sds <- mapply(transform_sd, sampled_means, sampled_sds) + } + + dist <- data.table::data.table( + model = rep("lognormal", samples), + params = purrr::list_transpose( + list( + meanlog = means, + sdlog = sds + ) + ), + max_value = rep(max_value, samples) + ) + return(dist) +} + +#' Tune an Inverse Gamma to Achieve the Target Truncation +#' +#' @description `r lifecycle::badge("deprecated")` +#' Allows an inverse gamma distribution to be. tuned so that less than 0.01 of +#' its probability mass function falls outside of the specified bounds. This is +#' required when using an inverse gamma prior, for example for a Gaussian +#' process. As no inverse gamma priors are currently in use and this function +#' has some stability issues it has been deprecated. +#' +#' @param lower Numeric, defaults to 2. Lower truncation bound. +#' +#' @param upper Numeric, defaults to 21. Upper truncation bound. +#' +#' @return A list of alpha and beta values that describe a inverse gamma +#' distribution that achieves the target truncation. +#' @export +#' +#' @keywords internal +#' +tune_inv_gamma <- function(lower = 2, upper = 21) { + lifecycle::deprecate_stop( + "1.3.6", "tune_inv_gamma()", + details = paste0( + "As no inverse gamma priors are currently in use and this function has ", + "some stability issues it has been deprecated. Please let the package ", + "authors know if deprecating this function has caused any issues. ", + "For the last active version of the function see the one contained ", + "in version 1.3.5 at ", + "https://github.com/epiforecasts/EpiNow2/blob/bad836ebd650ace73ad1ead887fd0eae98c52dd6/R/dist.R#L739" # nolint + ) + ) +} diff --git a/R/dist.R b/R/dist_spec.R similarity index 65% rename from R/dist.R rename to R/dist_spec.R index 1d0a46e58..8ab0de03e 100644 --- a/R/dist.R +++ b/R/dist_spec.R @@ -202,676 +202,6 @@ dist_skel <- function(n, dist = FALSE, cum = TRUE, model, } -#' Fit an Integer Adjusted Exponential, Gamma or Lognormal distributions -#' -#' @description `r lifecycle::badge("stable")` -#' Fits an integer adjusted exponential, gamma or lognormal distribution using -#' stan. -#' @param values Numeric vector of values -#' -#' @param samples Numeric, number of samples to take. Must be >= 1000. -#' Defaults to 1000. -#' -#' @param dist Character string, which distribution to fit. Defaults to -#' exponential (`"exp"`) but gamma (`"gamma"`) and lognormal (`"lognormal"`) are -#' also supported. -#' -#' @param cores Numeric, defaults to 1. Number of CPU cores to use (no effect -#' if greater than the number of chains). -#' -#' @param chains Numeric, defaults to 2. Number of MCMC chains to use. More is -#' better with the minimum being two. -#' -#' @param verbose Logical, defaults to FALSE. Should verbose progress messages -#' be printed. -#' -#' @return A stan fit of an interval censored distribution -#' @author Sam Abbott -#' @export -#' @inheritParams stan_opts -#' @examples -#' \donttest{ -#' # integer adjusted exponential model -#' dist_fit(rexp(1:100, 2), -#' samples = 1000, dist = "exp", -#' cores = ifelse(interactive(), 4, 1), verbose = TRUE -#' ) -#' -#' -#' # integer adjusted gamma model -#' dist_fit(rgamma(1:100, 5, 5), -#' samples = 1000, dist = "gamma", -#' cores = ifelse(interactive(), 4, 1), verbose = TRUE -#' ) -#' -#' # integer adjusted lognormal model -#' dist_fit(rlnorm(1:100, log(5), 0.2), -#' samples = 1000, dist = "lognormal", -#' cores = ifelse(interactive(), 4, 1), verbose = TRUE -#' ) -#' } -dist_fit <- function(values = NULL, samples = 1000, cores = 1, - chains = 2, dist = "exp", verbose = FALSE, - backend = "rstan") { - if (samples < 1000) { - samples <- 1000 - warning(sprintf("%s %s", "`samples` must be at least 1000.", - "Now setting it to 1000 internally." - ) - ) - } - # model parameters - lows <- values - 1 - lows <- ifelse(lows <= 0, 1e-6, lows) - ups <- values + 1 - - data <- list( - N = length(values), - low = lows, - up = ups, - lam_mean = numeric(0), - prior_mean = numeric(0), - prior_sd = numeric(0), - par_sigma = numeric(0) - ) - - model <- stan_model(backend, "dist_fit") - - if (dist == "exp") { - data$dist <- 0 - data$lam_mean <- array(mean(values)) - } else if (dist == "lognormal") { - data$dist <- 1 - data$prior_mean <- array(log(mean(values))) - data$prior_sd <- array(log(sd(values))) - } else if (dist == "gamma") { - data$dist <- 2 - data$prior_mean <- array(mean(values)) - data$prior_sd <- array(sd(values)) - data$par_sigma <- array(1.0) - } - - # set adapt delta based on the sample size - if (length(values) <= 30) { - adapt_delta <- 0.999 - } else { - adapt_delta <- 0.9 - } - - # fit model - args <- create_stan_args( - stan = stan_opts( - model, - samples = samples, - warmup = 1000, - control = list(adapt_delta = adapt_delta), - chains = chains, - cores = cores, - backend = backend - ), - data = data, verbose = verbose, model = "dist_fit" - ) - - fit <- fit_model(args, id = "dist_fit") - - return(fit) -} - - -#' Generate a Gamma Distribution Definition Based on Parameter Estimates -#' -#' @description `r lifecycle::badge("deprecated")` -#' Deprecated; use [Gamma()] instead to define a gamma distribution. -#' -#' @param shape Numeric, shape parameter of the gamma distribution. -#' -#' @param shape_sd Numeric, standard deviation of the shape parameter. -#' -#' @param scale Numeric, scale parameter of the gamma distribution. -#' -#' @param scale_sd Numeric, standard deviation of the scale parameter. -#' -#' @param samples Numeric, number of sample distributions to generate. -#' -#' @importFrom truncnorm rtruncnorm -#' @return A `` defining the distribution as used by [dist_skel()] -#' @export -#' @inheritParams dist_skel -#' @inheritParams lognorm_dist_def -#' @author Sam Abbott -#' @examples -#' # using estimated shape and scale -#' def <- gamma_dist_def( -#' shape = 5.807, shape_sd = 0.2, -#' scale = 0.9, scale_sd = 0.05, -#' max_value = 20, samples = 10 -#' ) -#' print(def) -#' def$params[[1]] -#' -#' # using mean and sd -#' def <- gamma_dist_def( -#' mean = 3, mean_sd = 0.5, -#' sd = 3, sd_sd = 0.1, -#' max_value = 20, samples = 10 -#' ) -#' print(def) -#' def$params[[1]] -gamma_dist_def <- function(shape, shape_sd, - scale, scale_sd, - mean, mean_sd, - sd, sd_sd, - max_value, samples) { - lifecycle::deprecate_warn( - "2.0.0", "gamma_dist_def()", "Gamma()", - "The function will be removed completely in version 2.1.0." - ) - - if (missing(shape) && missing(scale) && !missing(mean) && !missing(sd)) { - if (!missing(mean_sd)) { - mean <- truncnorm::rtruncnorm(samples, a = 0, mean = mean, sd = mean_sd) - } - if (!missing(sd_sd)) { - sd <- truncnorm::rtruncnorm(samples, a = 0, mean = sd, sd = sd_sd) - } - scale <- sd^2 / mean - shape <- mean / scale - } else { - if (!missing(shape_sd)) { - shape <- truncnorm::rtruncnorm( - samples, - a = 0, mean = shape, sd = shape_sd - ) - } - if (!missing(scale_sd)) { - scale <- 1 / truncnorm::rtruncnorm( - samples, - a = 0, mean = scale, sd = scale_sd - ) - } - } - - rate <- 1 / scale - - dist <- data.table::data.table( - model = rep("gamma", samples), - params = purrr::list_transpose( - list( - shape = shape, - rate = rate - ) - ), - max_value = rep(max_value, samples) - ) - return(dist) -} - -#' Generate a Log Normal Distribution Definition Based on Parameter Estimates -#' -#' @description `r lifecycle::badge("deprecated")` -#' Generates a distribution definition when only parameter estimates -#' are available for log normal distributed parameters. See [rlnorm()] for -#' distribution information. -#' -#' @param mean Numeric, log mean parameter of the gamma distribution. -#' -#' @param mean_sd Numeric, standard deviation of the log mean parameter. -#' -#' @param sd Numeric, log sd parameter of the gamma distribution. -#' -#' @param sd_sd Numeric, standard deviation of the log sd parameter. -#' -#' @param samples Numeric, number of sample distributions to generate. -#' -#' @param to_log Logical, should parameters be logged before use. -#' -#' @return A `` defining the distribution as used by [dist_skel()] -#' @author Sam Abbott -#' @importFrom truncnorm rtruncnorm -#' @export -#' @inheritParams dist_skel -#' @examples -#' def <- lognorm_dist_def( -#' mean = 1.621, mean_sd = 0.0640, -#' sd = 0.418, sd_sd = 0.0691, -#' max_value = 20, samples = 10 -#' ) -#' print(def) -#' def$params[[1]] -#' -#' def <- lognorm_dist_def( -#' mean = 5, mean_sd = 1, -#' sd = 3, sd_sd = 1, -#' max_value = 20, samples = 10, -#' to_log = TRUE -#' ) -#' print(def) -#' def$params[[1]] -lognorm_dist_def <- function(mean, mean_sd, - sd, sd_sd, - max_value, samples, - to_log = FALSE) { - lifecycle::deprecate_warn( - "2.0.0", "lognorm_dist_def()", "LogNormal()", - "The function will be removed completely in version 2.1.0." - ) - - transform_mean <- function(mu, sig) { - mean_location <- log(mu^2 / sqrt(sig^2 + mu^2)) - mean_location - } - - transform_sd <- function(mu, sig) { - mean_shape <- sqrt(log(1 + (sig^2 / mu^2))) - mean_shape - } - - if (missing(mean_sd)) { - sampled_means <- mean - } else { - sampled_means <- truncnorm::rtruncnorm( - samples, - a = 0, mean = mean, sd = mean_sd - ) - } - - if (missing(sd_sd)) { - sampled_sds <- sd - } else { - sampled_sds <- truncnorm::rtruncnorm(samples, a = 0, mean = sd, sd = sd_sd) - } - means <- sampled_means - sds <- sampled_sds - - if (to_log) { - means <- mapply(transform_mean, sampled_means, sampled_sds) - sds <- mapply(transform_sd, sampled_means, sampled_sds) - } - - dist <- data.table::data.table( - model = rep("lognormal", samples), - params = purrr::list_transpose( - list( - meanlog = means, - sdlog = sds - ) - ), - max_value = rep(max_value, samples) - ) - return(dist) -} - -#' Fit a Subsampled Bootstrap to Integer Values and Summarise Distribution -#' Parameters -#' -#' @description `r lifecycle::badge("stable")` -#' Fits an integer adjusted distribution to a subsampled bootstrap of data and -#' then integrates the posterior samples into a single set of summary -#' statistics. Can be used to generate a robust reporting delay that accounts -#' for the fact the underlying delay likely varies over time or that the size -#' of the available reporting delay sample may not be representative of the -#' current case load. -#' -#' @param values Integer vector of values. -#' -#' @param dist Character string, which distribution to fit. Defaults to -#' lognormal (`"lognormal"`) but gamma (`"gamma"`) is also supported. -#' -#' @param verbose Logical, defaults to `FALSE`. Should progress messages be -#' printed. -#' -#' @param samples Numeric, number of samples to take overall from the -#' bootstrapped posteriors. -#' -#' @param bootstraps Numeric, defaults to 1. The number of bootstrap samples -#' (with replacement) of the delay distribution to take. -#' -#' @param bootstrap_samples Numeric, defaults to 100. The number of samples to -#' take in each bootstrap. When the sample size of the supplied delay -#' distribution is less than 100 this is used instead. -#' -#' @param max_value Numeric, defaults to the maximum value in the observed -#' data. Maximum delay to allow (added to output but does impact fitting). -#' -#' @return A `` object summarising the bootstrapped distribution -#' @author Sam Abbott -#' @importFrom purrr list_transpose -#' @importFrom future.apply future_lapply -#' @importFrom rstan extract -#' @importFrom data.table data.table rbindlist -#' @export -#' @examples -#' \donttest{ -#' # lognormal -#' delays <- rlnorm(500, log(5), 1) -#' out <- bootstrapped_dist_fit(delays, -#' samples = 1000, bootstraps = 10, -#' dist = "lognormal" -#' ) -#' out -#' } -bootstrapped_dist_fit <- function(values, dist = "lognormal", - samples = 2000, bootstraps = 10, - bootstrap_samples = 250, max_value, - verbose = FALSE) { - if (!dist %in% c("gamma", "lognormal")) { - stop("Only lognormal and gamma distributions are supported") - } - - if (samples < bootstraps) { - samples <- bootstraps - } - ## Make values integer if not - values <- as.integer(values) - ## Remove NA values - values <- values[!is.na(values)] - ## Filter out negative values - values <- values[values >= 0] - - get_single_dist <- function(values, samples = 1) { - set_dt_single_thread() - - fit <- EpiNow2::dist_fit(values, samples = samples, dist = dist) - - - out <- list() - if (dist == "lognormal") { - out$mean_samples <- sample(extract(fit)$mu, samples) - out$sd_samples <- sample(extract(fit)$sigma, samples) - } else if (dist == "gamma") { - alpha_samples <- sample(extract(fit)$alpha, samples) - beta_samples <- sample(extract(fit)$beta, samples) - out$mean_samples <- alpha_samples / beta_samples - out$sd_samples <- sqrt(alpha_samples) / beta_samples - } - return(out) - } - - if (bootstraps == 1) { - dist_samples <- get_single_dist(values, samples = samples) - } else { - ## Fit each sub sample - dist_samples <- future.apply::future_lapply(1:bootstraps, - function(boot) { - get_single_dist( - sample(values, - min(length(values), bootstrap_samples), - replace = TRUE - ), - samples = ceiling(samples / bootstraps) - ) - }, - future.scheduling = Inf, - future.globals = c( - "values", "bootstraps", "samples", - "bootstrap_samples", "get_single_dist" - ), - future.packages = "data.table", future.seed = TRUE - ) - - - dist_samples <- purrr::list_transpose(dist_samples, simplify = FALSE) - dist_samples <- purrr::map(dist_samples, unlist) - } - - out <- list() - out$mean <- mean(dist_samples$mean_samples) - out$mean_sd <- sd(dist_samples$mean_samples) - out$sd <- mean(dist_samples$sd_sample) - out$sd_sd <- sd(dist_samples$sd_samples) - if (!missing(max_value)) { - out$max <- max_value - } else { - out$max <- max(values) - } - return(do.call(dist_spec, out)) -} - -#' Estimate a Delay Distribution -#' -#' @description `r lifecycle::badge("maturing")` -#' Estimate a log normal delay distribution from a vector of integer delays. -#' Currently this function is a simple wrapper for [bootstrapped_dist_fit()]. -#' -#' @param delays Integer vector of delays -#' -#' @param ... Arguments to pass to internal methods. -#' -#' @return A `` summarising the bootstrapped distribution -#' @author Sam Abbott -#' @export -#' @seealso [bootstrapped_dist_fit()] -#' @examples -#' \donttest{ -#' delays <- rlnorm(500, log(5), 1) -#' estimate_delay(delays, samples = 1000, bootstraps = 10) -#' } -estimate_delay <- function(delays, ...) { - fit <- bootstrapped_dist_fit( - values = delays, - dist = "lognormal", ... - ) - return(fit) -} - -#' Approximate Sampling a Distribution using Counts -#' -#' @description `r lifecycle::badge("soft-deprecated")` -#' Convolves cases by a PMF function. This function will soon be removed or -#' replaced with a more robust stan implementation. -#' -#' @param cases A `` of cases (in date order) with the following -#' variables: `date` and `cases`. -#' -#' @param max_value Numeric, maximum value to allow. Defaults to 120 days -#' -#' @param direction Character string, defato "backwards". Direction in which to -#' map cases. Supports either "backwards" or "forwards". -#' -#' @param dist_fn Function that takes two arguments with the first being -#' numeric and the second being logical (and defined as `dist`). Should return -#' the probability density or a sample from the defined distribution. See -#' the examples for more. -#' -#' @param earliest_allowed_mapped A character string representing a date -#' ("2020-01-01"). Indicates the earliest allowed mapped value. -#' -#' @param type Character string indicating the method to use to transform -#' counts. Supports either "sample" which approximates sampling or "median" -#' would shift by the median of the distribution. -#' -#' @param truncate_future Logical, should cases be truncated if they occur -#' after the first date reported in the data. Defaults to `TRUE`. -#' -#' @return A `` of cases by date of onset -#' @export -#' @importFrom purrr map_dfc -#' @importFrom data.table data.table setorder -#' @importFrom lubridate days -#' @examples -#' \donttest{ -#' cases <- example_confirmed -#' cases <- cases[, cases := as.integer(confirm)] -#' print(cases) -#' -#' # total cases -#' sum(cases$cases) -#' -#' delay_fn <- function(n, dist, cum) { -#' if (dist) { -#' pgamma(n + 0.9999, 2, 1) - pgamma(n - 1e-5, 2, 1) -#' } else { -#' as.integer(rgamma(n, 2, 1)) -#' } -#' } -#' -#' onsets <- sample_approx_dist( -#' cases = cases, -#' dist_fn = delay_fn -#' ) -#' -#' # estimated onset distribution -#' print(onsets) -#' -#' # check that sum is equal to reported cases -#' total_onsets <- median( -#' purrr::map_dbl( -#' 1:10, -#' ~ sum(sample_approx_dist( -#' cases = cases, -#' dist_fn = delay_fn -#' )$cases) -#' ) -#' ) -#' total_onsets -#' -#' -#' # map from onset cases to reported -#' reports <- sample_approx_dist( -#' cases = cases, -#' dist_fn = delay_fn, -#' direction = "forwards" -#' ) -#' -#' -#' # map from onset cases to reported using a mean shift -#' reports <- sample_approx_dist( -#' cases = cases, -#' dist_fn = delay_fn, -#' direction = "forwards", -#' type = "median" -#' ) -#' } -sample_approx_dist <- function(cases = NULL, - dist_fn = NULL, - max_value = 120, - earliest_allowed_mapped = NULL, - direction = "backwards", - type = "sample", - truncate_future = TRUE) { - if (type == "sample") { - if (direction == "backwards") { - direction_fn <- rev - } else if (direction == "forwards") { - direction_fn <- function(x) { - x - } - } - # reverse cases so starts with current first - reversed_cases <- direction_fn(cases$cases) - reversed_cases[is.na(reversed_cases)] <- 0 - # draw from the density fn of the dist - draw <- dist_fn(0:max_value, dist = TRUE, cum = FALSE) - - # approximate cases - mapped_cases <- suppressMessages(purrr::map_dfc( - seq_along(reversed_cases), - ~ c( - rep(0, . - 1), - stats::rbinom( - length(draw), - rep(reversed_cases[.], length(draw)), - draw - ), - rep(0, length(reversed_cases) - .) - ) - )) - - - # set dates order based on direction mapping - if (direction == "backwards") { - dates <- seq(min(cases$date) - lubridate::days(length(draw) - 1), - max(cases$date), - by = "days" - ) - } else if (direction == "forwards") { - dates <- seq(min(cases$date), - max(cases$date) + lubridate::days(length(draw) - 1), - by = "days" - ) - } - - # summarises movements and sample for placement of non-integer cases - case_sum <- direction_fn(rowSums(mapped_cases)) - floor_case_sum <- floor(case_sum) - sample_cases <- floor_case_sum + - as.numeric((runif(seq_along(case_sum)) < (case_sum - floor_case_sum))) - - # summarise imputed onsets and build output data.table - mapped_cases <- data.table::data.table( - date = dates, - cases = sample_cases - ) - - # filter out all zero cases until first recorded case - mapped_cases <- data.table::setorder(mapped_cases, date) - mapped_cases <- mapped_cases[ - , - cum_cases := cumsum(cases) - ][cum_cases != 0][, cum_cases := NULL] - } else if (type == "median") { - shift <- as.integer( - median(as.integer(dist_fn(1000, dist = FALSE)), na.rm = TRUE) - ) - - if (direction == "backwards") { - mapped_cases <- data.table::copy(cases)[ - , - date := date - lubridate::days(shift) - ] - } else if (direction == "forwards") { - mapped_cases <- data.table::copy(cases)[ - , - date := date + lubridate::days(shift) - ] - } - } - - if (!is.null(earliest_allowed_mapped)) { - mapped_cases <- mapped_cases[date >= as.Date(earliest_allowed_mapped)] - } - - # filter out future cases - if (direction == "forwards" && truncate_future) { - max_date <- max(cases$date) - mapped_cases <- mapped_cases[date <= max_date] - } - return(mapped_cases) -} - -#' Tune an Inverse Gamma to Achieve the Target Truncation -#' -#' @description `r lifecycle::badge("deprecated")` -#' Allows an inverse gamma distribution to be. tuned so that less than 0.01 of -#' its probability mass function falls outside of the specified bounds. This is -#' required when using an inverse gamma prior, for example for a Gaussian -#' process. As no inverse gamma priors are currently in use and this function -#' has some stability issues it has been deprecated. -#' -#' @param lower Numeric, defaults to 2. Lower truncation bound. -#' -#' @param upper Numeric, defaults to 21. Upper truncation bound. -#' -#' @return A list of alpha and beta values that describe a inverse gamma -#' distribution that achieves the target truncation. -#' @export -#' -#' @keywords internal -#' -tune_inv_gamma <- function(lower = 2, upper = 21) { - lifecycle::deprecate_stop( - "1.3.6", "tune_inv_gamma()", - details = paste0( - "As no inverse gamma priors are currently in use and this function has ", - "some stability issues it has been deprecated. Please let the package ", - "authors know if deprecating this function has caused any issues. ", - "For the last active version of the function see the one contained ", - "in version 1.3.5 at ", - "https://github.com/epiforecasts/EpiNow2/blob/bad836ebd650ace73ad1ead887fd0eae98c52dd6/R/dist.R#L739" # nolint - ) - ) -} - #' Specify a distribution. #' #' @description `r lifecycle::badge("deprecated")` diff --git a/R/estimate_delay.R b/R/estimate_delay.R new file mode 100644 index 000000000..67c4254c7 --- /dev/null +++ b/R/estimate_delay.R @@ -0,0 +1,268 @@ +#' Fit an Integer Adjusted Exponential, Gamma or Lognormal distributions +#' +#' @description `r lifecycle::badge("stable")` +#' Fits an integer adjusted exponential, gamma or lognormal distribution using +#' stan. +#' @param values Numeric vector of values +#' +#' @param samples Numeric, number of samples to take. Must be >= 1000. +#' Defaults to 1000. +#' +#' @param dist Character string, which distribution to fit. Defaults to +#' exponential (`"exp"`) but gamma (`"gamma"`) and lognormal (`"lognormal"`) are +#' also supported. +#' +#' @param cores Numeric, defaults to 1. Number of CPU cores to use (no effect +#' if greater than the number of chains). +#' +#' @param chains Numeric, defaults to 2. Number of MCMC chains to use. More is +#' better with the minimum being two. +#' +#' @param verbose Logical, defaults to FALSE. Should verbose progress messages +#' be printed. +#' +#' @return A stan fit of an interval censored distribution +#' @author Sam Abbott +#' @export +#' @inheritParams stan_opts +#' @examples +#' \donttest{ +#' # integer adjusted exponential model +#' dist_fit(rexp(1:100, 2), +#' samples = 1000, dist = "exp", +#' cores = ifelse(interactive(), 4, 1), verbose = TRUE +#' ) +#' +#' +#' # integer adjusted gamma model +#' dist_fit(rgamma(1:100, 5, 5), +#' samples = 1000, dist = "gamma", +#' cores = ifelse(interactive(), 4, 1), verbose = TRUE +#' ) +#' +#' # integer adjusted lognormal model +#' dist_fit(rlnorm(1:100, log(5), 0.2), +#' samples = 1000, dist = "lognormal", +#' cores = ifelse(interactive(), 4, 1), verbose = TRUE +#' ) +#' } +dist_fit <- function(values = NULL, samples = 1000, cores = 1, + chains = 2, dist = "exp", verbose = FALSE, + backend = "rstan") { + if (samples < 1000) { + samples <- 1000 + warning(sprintf("%s %s", "`samples` must be at least 1000.", + "Now setting it to 1000 internally." + ) + ) + } + # model parameters + lows <- values - 1 + lows <- ifelse(lows <= 0, 1e-6, lows) + ups <- values + 1 + + data <- list( + N = length(values), + low = lows, + up = ups, + lam_mean = numeric(0), + prior_mean = numeric(0), + prior_sd = numeric(0), + par_sigma = numeric(0) + ) + + model <- stan_model(backend, "dist_fit") + + if (dist == "exp") { + data$dist <- 0 + data$lam_mean <- array(mean(values)) + } else if (dist == "lognormal") { + data$dist <- 1 + data$prior_mean <- array(log(mean(values))) + data$prior_sd <- array(log(sd(values))) + } else if (dist == "gamma") { + data$dist <- 2 + data$prior_mean <- array(mean(values)) + data$prior_sd <- array(sd(values)) + data$par_sigma <- array(1.0) + } + + # set adapt delta based on the sample size + if (length(values) <= 30) { + adapt_delta <- 0.999 + } else { + adapt_delta <- 0.9 + } + + # fit model + args <- create_stan_args( + stan = stan_opts( + model, + samples = samples, + warmup = 1000, + control = list(adapt_delta = adapt_delta), + chains = chains, + cores = cores, + backend = backend + ), + data = data, verbose = verbose, model = "dist_fit" + ) + + fit <- fit_model(args, id = "dist_fit") + + return(fit) +} + + +#' Fit a Subsampled Bootstrap to Integer Values and Summarise Distribution +#' Parameters +#' +#' @description `r lifecycle::badge("stable")` +#' Fits an integer adjusted distribution to a subsampled bootstrap of data and +#' then integrates the posterior samples into a single set of summary +#' statistics. Can be used to generate a robust reporting delay that accounts +#' for the fact the underlying delay likely varies over time or that the size +#' of the available reporting delay sample may not be representative of the +#' current case load. +#' +#' @param values Integer vector of values. +#' +#' @param dist Character string, which distribution to fit. Defaults to +#' lognormal (`"lognormal"`) but gamma (`"gamma"`) is also supported. +#' +#' @param verbose Logical, defaults to `FALSE`. Should progress messages be +#' printed. +#' +#' @param samples Numeric, number of samples to take overall from the +#' bootstrapped posteriors. +#' +#' @param bootstraps Numeric, defaults to 1. The number of bootstrap samples +#' (with replacement) of the delay distribution to take. +#' +#' @param bootstrap_samples Numeric, defaults to 100. The number of samples to +#' take in each bootstrap. When the sample size of the supplied delay +#' distribution is less than 100 this is used instead. +#' +#' @param max_value Numeric, defaults to the maximum value in the observed +#' data. Maximum delay to allow (added to output but does impact fitting). +#' +#' @return A `` object summarising the bootstrapped distribution +#' @author Sam Abbott +#' @importFrom purrr list_transpose +#' @importFrom future.apply future_lapply +#' @importFrom rstan extract +#' @importFrom data.table data.table rbindlist +#' @export +#' @examples +#' \donttest{ +#' # lognormal +#' delays <- rlnorm(500, log(5), 1) +#' out <- bootstrapped_dist_fit(delays, +#' samples = 1000, bootstraps = 10, +#' dist = "lognormal" +#' ) +#' out +#' } +bootstrapped_dist_fit <- function(values, dist = "lognormal", + samples = 2000, bootstraps = 10, + bootstrap_samples = 250, max_value, + verbose = FALSE) { + if (!dist %in% c("gamma", "lognormal")) { + stop("Only lognormal and gamma distributions are supported") + } + + if (samples < bootstraps) { + samples <- bootstraps + } + ## Make values integer if not + values <- as.integer(values) + ## Remove NA values + values <- values[!is.na(values)] + ## Filter out negative values + values <- values[values >= 0] + + get_single_dist <- function(values, samples = 1) { + set_dt_single_thread() + + fit <- EpiNow2::dist_fit(values, samples = samples, dist = dist) + + + out <- list() + if (dist == "lognormal") { + out$mean_samples <- sample(extract(fit)$mu, samples) + out$sd_samples <- sample(extract(fit)$sigma, samples) + } else if (dist == "gamma") { + alpha_samples <- sample(extract(fit)$alpha, samples) + beta_samples <- sample(extract(fit)$beta, samples) + out$mean_samples <- alpha_samples / beta_samples + out$sd_samples <- sqrt(alpha_samples) / beta_samples + } + return(out) + } + + if (bootstraps == 1) { + dist_samples <- get_single_dist(values, samples = samples) + } else { + ## Fit each sub sample + dist_samples <- future.apply::future_lapply(1:bootstraps, + function(boot) { + get_single_dist( + sample(values, + min(length(values), bootstrap_samples), + replace = TRUE + ), + samples = ceiling(samples / bootstraps) + ) + }, + future.scheduling = Inf, + future.globals = c( + "values", "bootstraps", "samples", + "bootstrap_samples", "get_single_dist" + ), + future.packages = "data.table", future.seed = TRUE + ) + + + dist_samples <- purrr::list_transpose(dist_samples, simplify = FALSE) + dist_samples <- purrr::map(dist_samples, unlist) + } + + out <- list() + out$mean <- mean(dist_samples$mean_samples) + out$mean_sd <- sd(dist_samples$mean_samples) + out$sd <- mean(dist_samples$sd_sample) + out$sd_sd <- sd(dist_samples$sd_samples) + if (!missing(max_value)) { + out$max <- max_value + } else { + out$max <- max(values) + } + return(do.call(dist_spec, out)) +} + +#' Estimate a Delay Distribution +#' +#' @description `r lifecycle::badge("maturing")` +#' Estimate a log normal delay distribution from a vector of integer delays. +#' Currently this function is a simple wrapper for [bootstrapped_dist_fit()]. +#' +#' @param delays Integer vector of delays +#' +#' @param ... Arguments to pass to internal methods. +#' +#' @return A `` summarising the bootstrapped distribution +#' @author Sam Abbott +#' @export +#' @seealso [bootstrapped_dist_fit()] +#' @examples +#' \donttest{ +#' delays <- rlnorm(500, log(5), 1) +#' estimate_delay(delays, samples = 1000, bootstraps = 10) +#' } +estimate_delay <- function(delays, ...) { + fit <- bootstrapped_dist_fit( + values = delays, + dist = "lognormal", ... + ) + return(fit) +} From 4cb0108eeab3b6b27e61037e6420e0d2c6e8ae09 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 21 Feb 2024 14:56:29 +0000 Subject: [PATCH 106/129] move deprecated `dist_spec` function --- R/deprecated.R | 127 ++++++++++++++++++++++++++++++++++++++++++++++++ R/dist_spec.R | 128 ------------------------------------------------- 2 files changed, 127 insertions(+), 128 deletions(-) diff --git a/R/deprecated.R b/R/deprecated.R index 874871a6b..ab28bed15 100644 --- a/R/deprecated.R +++ b/R/deprecated.R @@ -213,3 +213,130 @@ tune_inv_gamma <- function(lower = 2, upper = 21) { ) ) } + +#' Specify a distribution. +#' +#' @description `r lifecycle::badge("deprecated")` +#' This function is deprecated as a user-facing function (while its +#' functionality is still used internally). Construct distributions using +#' the corresponding distribution function such as [Gamma()], [LogNormal()], +#' [Normal()] or [Fixed()] instead. +#' +#' @param distribution Character, defaults to "lognormal". The (discretised) +#' distribution to be used. Can be "lognormal", "gamma", "normal" or "fixed". +#' The corresponding parameters (defined in [natural_params()]) are passed +#' as `params_mean`, and their uncertainty as `params_sd`. +#' +#' @param params_mean Numeric. Central values of the parameters of the +#' distribution as defined in [natural_params(). +#' +#' @param params_sd Numeric. Standard deviations of the parameters of the +#' distribution as defined in [natural_params(). +#' +#' @param max Numeric, maximum value of the distribution. The distribution will +#' be truncated at this value. Default: `Inf`, i.e. no maximum. +#' +#' @param mean Deprecated; use `params_mean` instead. +#' +#' @param sd Deprecated; use `params_mean` instead. +#' +#' @param mean_sd Deprecated; use `params_sd` instead. +#' +#' @param sd_sd Deprecated; use `params_sd` instead. +#' +#' @param pmf Numeric, a vector of values that represent the (nonparametric) +#' probability mass function of the delay (starting with 0); defaults to an +#' empty vector corresponding to a parametric specification of the distribution +#' (using \code{params_mean}, and \code{params_sd}. +#' @param fixed Deprecated, use [fix_dist()] instead. +#' @return A list of distribution options. +#' @author Sebastian Funk +#' @author Sam Abbott +#' @importFrom rlang warn arg_match +#' @export +dist_spec <- function(distribution = c( + "lognormal", "normal", "gamma", "fixed", "empty" + ), + params_mean = numeric(0), params_sd = numeric(0), + mean, sd = 0, mean_sd = 0, sd_sd = 0, + max = Inf, pmf = numeric(0), fixed = FALSE) { + + lifecycle::deprecate_warn( + "2.0.0", + "dist_spec()", + details = c( + paste0( + "Please use distribution functions such as `Gamma()` or `Lognormal()` ", + "instead." + ), + "The function will become internal only in version 2.1.0." + ) + ) + ## check for deprecated parameters + if (!missing(fixed)) { + lifecycle::deprecate_warn( + "2.0.0", + "dist_spec(fixed)", + "fix_dist()" + ) + params_sd <- NULL + } + ## check for deprecated parameters + if (!all(missing(mean), missing(sd), missing(mean_sd), missing(sd_sd)) && + (length(params_mean) > 0 || length(params_sd) > 0)) { + stop("Distributional parameters should not be given as `mean`, `sd`, etc. ", + "in addition to `params_mean` or `params_sd`") + } + distribution <- match.arg(distribution) + ## check if distribution is given as empty and warn about deprecation if so + if (distribution == "empty") { + deprecate_warn( + "2.0.0", + "dist_spec(distribution = 'must not be \"empty\"')", + details = "Please use `Fixed(0)` instead." + ) + } + + if (!all(missing(mean), missing(sd), missing(mean_sd), missing(sd_sd))) { + if (sd == 0 && mean_sd == 0 && sd_sd == 0) { + distribution <- "fixed" + } + ## deprecated arguments given + if (distribution == "lognormal") { + params_mean <- c(meanlog = mean, sdlog = sd) + params_sd <- c(meanlog = mean_sd, sdlog = sd_sd) + } else if (distribution == "gamma") { + temp_dist <- Gamma( + mean = Normal(mean, mean_sd), + sd = Normal(sd, sd_sd) + ) + params_mean <- temp_dist$params_mean + params_sd <- temp_dist$params_sd + } else if (distribution == "normal") { + params_mean <- c(mean = mean, sd = sd) + params_sd <- c(mean = mean_sd, sd = sd_sd) + } else if (distribution == "fixed") { + params_mean <- mean + } + } + if (length(pmf) > 0) { + if (!all( + missing(mean), missing(sd), missing(mean_sd), missing(sd_sd), + missing(params_mean), missing(params_sd) + )) { + stop("Distributional parameters should not be given in addition to `pmf`") + } + distribution <- "nonparametric" + parameters <- list(pmf = pmf) + } else { + if (length(params_sd) == 0) { + params_sd <- rep(0, length(params_mean)) + } + parameters <- lapply(seq_along(params_mean), function(id) { + Normal(params_mean[id], params_sd[id]) + }) + names(parameters) <- natural_params(distribution) + parameters$max <- max + } + return(new_dist_spec(parameters, distribution)) +} diff --git a/R/dist_spec.R b/R/dist_spec.R index 8ab0de03e..7ed13a503 100644 --- a/R/dist_spec.R +++ b/R/dist_spec.R @@ -201,134 +201,6 @@ dist_skel <- function(n, dist = FALSE, cum = TRUE, model, return(sample) } - -#' Specify a distribution. -#' -#' @description `r lifecycle::badge("deprecated")` -#' This function is deprecated as a user-facing function (while its -#' functionality is still used internally). Construct distributions using -#' the corresponding distribution function such as [Gamma()], [LogNormal()], -#' [Normal()] or [Fixed()] instead. -#' -#' @param distribution Character, defaults to "lognormal". The (discretised) -#' distribution to be used. Can be "lognormal", "gamma", "normal" or "fixed". -#' The corresponding parameters (defined in [natural_params()]) are passed -#' as `params_mean`, and their uncertainty as `params_sd`. -#' -#' @param params_mean Numeric. Central values of the parameters of the -#' distribution as defined in [natural_params(). -#' -#' @param params_sd Numeric. Standard deviations of the parameters of the -#' distribution as defined in [natural_params(). -#' -#' @param max Numeric, maximum value of the distribution. The distribution will -#' be truncated at this value. Default: `Inf`, i.e. no maximum. -#' -#' @param mean Deprecated; use `params_mean` instead. -#' -#' @param sd Deprecated; use `params_mean` instead. -#' -#' @param mean_sd Deprecated; use `params_sd` instead. -#' -#' @param sd_sd Deprecated; use `params_sd` instead. -#' -#' @param pmf Numeric, a vector of values that represent the (nonparametric) -#' probability mass function of the delay (starting with 0); defaults to an -#' empty vector corresponding to a parametric specification of the distribution -#' (using \code{params_mean}, and \code{params_sd}. -#' @param fixed Deprecated, use [fix_dist()] instead. -#' @return A list of distribution options. -#' @author Sebastian Funk -#' @author Sam Abbott -#' @importFrom rlang warn arg_match -#' @export -dist_spec <- function(distribution = c( - "lognormal", "normal", "gamma", "fixed", "empty" - ), - params_mean = numeric(0), params_sd = numeric(0), - mean, sd = 0, mean_sd = 0, sd_sd = 0, - max = Inf, pmf = numeric(0), fixed = FALSE) { - - lifecycle::deprecate_warn( - "2.0.0", - "dist_spec()", - details = c( - paste0( - "Please use distribution functions such as `Gamma()` or `Lognormal()` ", - "instead." - ), - "The function will become internal only in version 2.1.0." - ) - ) - ## check for deprecated parameters - if (!missing(fixed)) { - lifecycle::deprecate_warn( - "2.0.0", - "dist_spec(fixed)", - "fix_dist()" - ) - params_sd <- NULL - } - ## check for deprecated parameters - if (!all(missing(mean), missing(sd), missing(mean_sd), missing(sd_sd)) && - (length(params_mean) > 0 || length(params_sd) > 0)) { - stop("Distributional parameters should not be given as `mean`, `sd`, etc. ", - "in addition to `params_mean` or `params_sd`") - } - distribution <- match.arg(distribution) - ## check if distribution is given as empty and warn about deprecation if so - if (distribution == "empty") { - deprecate_warn( - "2.0.0", - "dist_spec(distribution = 'must not be \"empty\"')", - details = "Please use `Fixed(0)` instead." - ) - } - - if (!all(missing(mean), missing(sd), missing(mean_sd), missing(sd_sd))) { - if (sd == 0 && mean_sd == 0 && sd_sd == 0) { - distribution <- "fixed" - } - ## deprecated arguments given - if (distribution == "lognormal") { - params_mean <- c(meanlog = mean, sdlog = sd) - params_sd <- c(meanlog = mean_sd, sdlog = sd_sd) - } else if (distribution == "gamma") { - temp_dist <- Gamma( - mean = Normal(mean, mean_sd), - sd = Normal(sd, sd_sd) - ) - params_mean <- temp_dist$params_mean - params_sd <- temp_dist$params_sd - } else if (distribution == "normal") { - params_mean <- c(mean = mean, sd = sd) - params_sd <- c(mean = mean_sd, sd = sd_sd) - } else if (distribution == "fixed") { - params_mean <- mean - } - } - if (length(pmf) > 0) { - if (!all( - missing(mean), missing(sd), missing(mean_sd), missing(sd_sd), - missing(params_mean), missing(params_sd) - )) { - stop("Distributional parameters should not be given in addition to `pmf`") - } - distribution <- "nonparametric" - parameters <- list(pmf = pmf) - } else { - if (length(params_sd) == 0) { - params_sd <- rep(0, length(params_mean)) - } - parameters <- lapply(seq_along(params_mean), function(id) { - Normal(params_mean[id], params_sd[id]) - }) - names(parameters) <- natural_params(distribution) - parameters$max <- max - } - return(new_dist_spec(parameters, distribution)) -} - #' Creates a delay distribution as the sum of two other delay distributions. #' #' @return A delay distribution representing the sum of the two delays From e8e6623f5ff9a6c831bf1da18f616577710d8ca6 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 21 Feb 2024 15:06:47 +0000 Subject: [PATCH 107/129] add examples --- R/dist_spec.R | 73 ++++++++++++++++++++++++++++++++++-- man/Distributions.Rd | 3 +- man/apply_tolerance.Rd | 6 ++- man/bootstrapped_dist_fit.Rd | 2 +- man/c.dist_spec.Rd | 15 +++++++- man/collapse.Rd | 12 +++++- man/convert_to_natural.Rd | 17 ++++++++- man/discretise.Rd | 12 +++++- man/dist_fit.Rd | 2 +- man/dist_skel.Rd | 2 +- man/dist_spec.Rd | 2 +- man/estimate_delay.Rd | 2 +- man/extract_params.Rd | 6 +-- man/extract_single_dist.Rd | 14 ++++++- man/fix_dist.Rd | 10 ++++- man/gamma_dist_def.Rd | 2 +- man/lognorm_dist_def.Rd | 2 +- man/lower_bounds.Rd | 2 +- man/max.dist_spec.Rd | 4 +- man/mean.dist_spec.Rd | 2 +- man/natural_params.Rd | 2 +- man/new_dist_spec.Rd | 10 ++++- man/plot.dist_spec.Rd | 2 +- man/plus-.dist_spec.Rd | 3 +- man/print.dist_spec.Rd | 2 +- man/sample_approx_dist.Rd | 2 +- man/sd_dist.Rd | 2 +- man/trunc_opts.Rd | 2 +- man/tune_inv_gamma.Rd | 2 +- 29 files changed, 181 insertions(+), 36 deletions(-) diff --git a/R/dist_spec.R b/R/dist_spec.R index 7ed13a503..62dd4aa69 100644 --- a/R/dist_spec.R +++ b/R/dist_spec.R @@ -204,7 +204,7 @@ dist_skel <- function(n, dist = FALSE, cum = TRUE, model, #' Creates a delay distribution as the sum of two other delay distributions. #' #' @return A delay distribution representing the sum of the two delays -#' (with class [dist_spec()]) + #' @param e1 The first delay distribution (of type [dist_spec()]) to #' combine. #' @@ -239,6 +239,18 @@ dist_skel <- function(n, dist = FALSE, cum = TRUE, model, #' @author Sebastian Funk #' @method c dist_spec #' @export +#' @examples +#' # A fixed lognormal distribution with mean 5 and sd 1. +#' dist1 <- LogNormal( +#' meanlog = 1.6, sdlog = 1, max = 20 +#' ) +#' dist1 + dist1 +#' +#' # An uncertain gamma distribution with mean 3 and sd 2 +#' dist2 <- Gamma( +#' mean = Normal(3, 0.5), sd = Normal(2, 0.5), max = 20 +#' ) +#' c(dist1, dist2) c.dist_spec <- function(...) { ## process delay distributions dist_specs <- list(...) @@ -396,7 +408,7 @@ sd_dist <- function(x) { #' dist2 <- LogNormal(mean = Normal(3, 0.5), sd = Normal(2, 0.5), max = 20) #' max(dist2) #' -#' # The maxf the sum of two distributions +#' # The max the sum of two distributions #' max(dist1 + dist2) max.dist_spec <- function(x, ...) { ret <- vapply(x, function(y) { @@ -412,7 +424,7 @@ max.dist_spec <- function(x, ...) { }, numeric(1)) return(ret) } -## + #' Discretise a #' #' By default it will discretise all the distributions it can discretise @@ -426,6 +438,15 @@ max.dist_spec <- function(x, ...) { #' nonparametric. #' @author Sebastian Funk #' @export +#' @examples +#' # A fixed gamma distribution with mean 5 and sd 1. +#' dist1 <- Gamma(mean = 5, sd = 1, max = 20) +#' +#' # An uncertain lognormal distribution with mean 3 and sd 2 +#' dist2 <- LogNormal(mean = Normal(3, 0.5), sd = Normal(2, 0.5), max = 20) +#' +#' # The maxf the sum of two distributions +#' discretise(dist1 + dist2) discretise <- function(x, silent = TRUE) { if (!is(x, "dist_spec")) { stop("Can only discretise a .") @@ -473,6 +494,15 @@ discretise <- function(x, silent = TRUE) { #' @importFrom stats convolve #' @author Sebastian Funk #' @export +#' @examples +#' # A fixed gamma distribution with mean 5 and sd 1. +#' dist1 <- Gamma(mean = 5, sd = 1, max = 20) +#' +#' # An uncertain lognormal distribution with mean 3 and sd 2 +#' dist2 <- LogNormal(mean = 3, sd = 2, max = 20) +#' +#' # The maxf the sum of two distributions +#' collapse(discretise(dist1 + dist2)) collapse <- function(x) { if (!is(x, "dist_spec")) { stop("Can only convolve distributions in a .") @@ -513,6 +543,9 @@ collapse <- function(x) { #' have been removed #' @author Sebastian Funk, Sam Abbott #' @export +#' @examples +#' dist <- discretise(Gamma(mean = 5, sd = 1, max = 20)) +#' apply_tolerance(dist, 0.01) apply_tolerance <- function(x, tolerance) { if (!is(x, "dist_spec")) { stop("Can only apply tolerance to distributions in a .") @@ -690,6 +723,17 @@ plot.dist_spec <- function(x, ...) { #' @return A single `dist_spec` object #' @keywords internal #' @author Sebastian Funk +#' @examples +#' dist1 <- LogNormal(mean = 1.6, sd = 0.5, max = 20) +#' +#' # An uncertain gamma distribution with mean 3 and sd 2 +#' dist2 <- Gamma( +#' mean = Normal(3, 0.5), sd = Normal(2, 0.5), max = 20 +#' ) +#' +#' # Multiple distributions +#' dist <- dist1 + dist2 +#' extract_single_dist(dist, 2) extract_single_dist <- function(x, i) { if (i > length(x)) { stop("i can't be greater than the number of distributions.") @@ -712,6 +756,13 @@ extract_single_dist <- function(x, i) { #' standard deviation from uncertainty given in the `` #' @importFrom truncnorm rtruncnorm #' @importFrom rlang arg_match +#' @examples +#' # An uncertain gamma distribution with mean 3 and sd 2 +#' dist <- LogNormal( +#' meanlog = Normal(3, 0.5), sdlog = Normal(2, 0.5), max = 20 +#' ) +#' +#' fix_dist(dist) fix_dist <- function(x, strategy = c("mean", "sample")) { if (!is(x, "dist_spec")) { stop("Can only fix distributions in a .") @@ -904,7 +955,7 @@ lower_bounds <- function(distribution) { } #' Internal function for extracting given parameter names of a distribution -#' from the environment +#' from the environment. Called by `new_dist_spec` #' #' @param params Given parameters (obtained using `as.list(environment())`) #' @return A character vector of parameters and their values. @@ -934,6 +985,13 @@ extract_params <- function(params, distribution) { #' @return A `dist_spec` of the given specification. #' @author Sebastian Funk #' @keywords internal +#' @examples +#' \dontrun{ +#' new_dist_spec( +#' params = list(mean = 2, sd = 1, max = Inf), +#' distribution = "normal" +#' ) +#' } new_dist_spec <- function(params, distribution) { if (distribution == "nonparametric") { ## nonparametric distribution @@ -1025,6 +1083,13 @@ new_dist_spec <- function(params, distribution) { #' @return A list with two elements, `params_mean` and `params_sd`, containing #' mean and sd of natural parameters. #' @author Sebastian Funk +#' @keywords internal +#' \dontrun{ +#' convert_to_natural( +#' params = list(mean = 2, sd = 1, max = Inf), +#' distribution = "gamma" +#' ) +#' } convert_to_natural <- function(params, distribution) { ## unnatural parameter means ux <- lapply(params, mean) diff --git a/man/Distributions.Rd b/man/Distributions.Rd index 008a5d381..4510f4721 100644 --- a/man/Distributions.Rd +++ b/man/Distributions.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/dist.R +% Please edit documentation in R/dist_spec.R \name{Distributions} \alias{Distributions} \alias{LogNormal} @@ -81,6 +81,7 @@ LogNormal(mean = Normal(4, 1), sd = 1, max = 10) Gamma(mean = 4, sd = 1) Gamma(shape = 16, rate = 4) Gamma(shape = Normal(16, 2), rate = Normal(4, 1)) +Gamma(shape = Normal(16, 2), scale = Normal(1/4, 1)) Normal(mean = 4, sd = 1) Normal(mean = 4, sd = 1, max = 10) Fixed(value = 3) diff --git a/man/apply_tolerance.Rd b/man/apply_tolerance.Rd index 49f4a4338..17ed41947 100644 --- a/man/apply_tolerance.Rd +++ b/man/apply_tolerance.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/dist.R +% Please edit documentation in R/dist_spec.R \name{apply_tolerance} \alias{apply_tolerance} \title{Applies a threshold to all nonparametric distributions in a } @@ -19,6 +19,10 @@ have been removed This removes any part of the tail of the nonparametric distributions in the where the probability mass is below the threshold level. } +\examples{ +dist <- discretise(Gamma(mean = 5, sd = 1, max = 20)) +apply_tolerance(dist, 0.01) +} \author{ Sebastian Funk, Sam Abbott } diff --git a/man/bootstrapped_dist_fit.Rd b/man/bootstrapped_dist_fit.Rd index 00a19ff9c..ecd6981da 100644 --- a/man/bootstrapped_dist_fit.Rd +++ b/man/bootstrapped_dist_fit.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/dist.R +% Please edit documentation in R/estimate_delay.R \name{bootstrapped_dist_fit} \alias{bootstrapped_dist_fit} \title{Fit a Subsampled Bootstrap to Integer Values and Summarise Distribution diff --git a/man/c.dist_spec.Rd b/man/c.dist_spec.Rd index 728fecc9d..ba71af809 100644 --- a/man/c.dist_spec.Rd +++ b/man/c.dist_spec.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/dist.R +% Please edit documentation in R/dist_spec.R \name{c.dist_spec} \alias{c.dist_spec} \title{Combines multiple delay distributions for further processing} @@ -16,6 +16,19 @@ Combined delay distributions (with class \verb{}) This combines the parameters so that they can be fed as multiple delay distributions to \code{\link[=epinow]{epinow()}} or \code{\link[=estimate_infections]{estimate_infections()}}. } +\examples{ +# A fixed lognormal distribution with mean 5 and sd 1. +dist1 <- LogNormal( + meanlog = 1.6, sdlog = 1, max = 20 +) +dist1 + dist1 + +# An uncertain gamma distribution with mean 3 and sd 2 +dist2 <- Gamma( + mean = Normal(3, 0.5), sd = Normal(2, 0.5), max = 20 +) +c(dist1, dist2) +} \author{ Sebastian Funk } diff --git a/man/collapse.Rd b/man/collapse.Rd index 63e35492f..eb588ffc9 100644 --- a/man/collapse.Rd +++ b/man/collapse.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/dist.R +% Please edit documentation in R/dist_spec.R \name{collapse} \alias{collapse} \title{Collapse nonparametric distributions in a } @@ -17,6 +17,16 @@ have been convolved This convolves any consecutive nonparametric distributions contained in the . } +\examples{ +# A fixed gamma distribution with mean 5 and sd 1. +dist1 <- Gamma(mean = 5, sd = 1, max = 20) + +# An uncertain lognormal distribution with mean 3 and sd 2 +dist2 <- LogNormal(mean = 3, sd = 2, max = 20) + +# The maxf the sum of two distributions +collapse(discretise(dist1 + dist2)) +} \author{ Sebastian Funk } diff --git a/man/convert_to_natural.Rd b/man/convert_to_natural.Rd index 6c6c4496c..b324d9682 100644 --- a/man/convert_to_natural.Rd +++ b/man/convert_to_natural.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/dist.R +% Please edit documentation in R/dist_spec.R \name{convert_to_natural} \alias{convert_to_natural} \title{Internal function for converting parameters to natural parameters.} @@ -22,3 +22,18 @@ from a given set of parameters and distribution \author{ Sebastian Funk } +\keyword{"gamma"} +\keyword{)} +\keyword{1,} +\keyword{2,} +\keyword{=} +\keyword{Inf),} +\keyword{\dontrun{} +\keyword{convert_to_natural(} +\keyword{distribution} +\keyword{internal} +\keyword{list(mean} +\keyword{max} +\keyword{params} +\keyword{sd} +\keyword{}} diff --git a/man/discretise.Rd b/man/discretise.Rd index f942c69f6..d8ee31d16 100644 --- a/man/discretise.Rd +++ b/man/discretise.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/dist.R +% Please edit documentation in R/dist_spec.R \name{discretise} \alias{discretise} \title{Discretise a } @@ -24,6 +24,16 @@ Discretise a By default it will discretise all the distributions it can discretise (i.e. those with finite support and constant parameters). } +\examples{ +# A fixed gamma distribution with mean 5 and sd 1. +dist1 <- Gamma(mean = 5, sd = 1, max = 20) + +# An uncertain lognormal distribution with mean 3 and sd 2 +dist2 <- LogNormal(mean = Normal(3, 0.5), sd = Normal(2, 0.5), max = 20) + +# The maxf the sum of two distributions +discretise(dist1 + dist2) +} \author{ Sebastian Funk } diff --git a/man/dist_fit.Rd b/man/dist_fit.Rd index a61b95e75..404aa605d 100644 --- a/man/dist_fit.Rd +++ b/man/dist_fit.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/dist.R +% Please edit documentation in R/estimate_delay.R \name{dist_fit} \alias{dist_fit} \title{Fit an Integer Adjusted Exponential, Gamma or Lognormal distributions} diff --git a/man/dist_skel.Rd b/man/dist_skel.Rd index 1edd0743c..e05d0d55f 100644 --- a/man/dist_skel.Rd +++ b/man/dist_skel.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/dist.R +% Please edit documentation in R/dist_spec.R \name{dist_skel} \alias{dist_skel} \title{Distribution Skeleton} diff --git a/man/dist_spec.Rd b/man/dist_spec.Rd index e3159d38e..713eaa4ef 100644 --- a/man/dist_spec.Rd +++ b/man/dist_spec.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/dist.R +% Please edit documentation in R/deprecated.R \name{dist_spec} \alias{dist_spec} \title{Specify a distribution.} diff --git a/man/estimate_delay.Rd b/man/estimate_delay.Rd index cea324b92..89412f985 100644 --- a/man/estimate_delay.Rd +++ b/man/estimate_delay.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/dist.R +% Please edit documentation in R/estimate_delay.R \name{estimate_delay} \alias{estimate_delay} \title{Estimate a Delay Distribution} diff --git a/man/extract_params.Rd b/man/extract_params.Rd index fe5b0d834..6f7e254cc 100644 --- a/man/extract_params.Rd +++ b/man/extract_params.Rd @@ -1,9 +1,9 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/dist.R +% Please edit documentation in R/dist_spec.R \name{extract_params} \alias{extract_params} \title{Internal function for extracting given parameter names of a distribution -from the environment} +from the environment. Called by \code{new_dist_spec}} \usage{ extract_params(params, distribution) } @@ -17,7 +17,7 @@ A character vector of parameters and their values. } \description{ Internal function for extracting given parameter names of a distribution -from the environment +from the environment. Called by \code{new_dist_spec} } \author{ Sebastian Funk diff --git a/man/extract_single_dist.Rd b/man/extract_single_dist.Rd index 6ed137e1c..05f94e402 100644 --- a/man/extract_single_dist.Rd +++ b/man/extract_single_dist.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/dist.R +% Please edit documentation in R/dist_spec.R \name{extract_single_dist} \alias{extract_single_dist} \title{Extract a single element of a composite \verb{}} @@ -17,6 +17,18 @@ A single \code{dist_spec} object \description{ Extract a single element of a composite \verb{} } +\examples{ +dist1 <- LogNormal(mean = 1.6, sd = 0.5, max = 20) + +# An uncertain gamma distribution with mean 3 and sd 2 +dist2 <- Gamma( + mean = Normal(3, 0.5), sd = Normal(2, 0.5), max = 20 +) + +# Multiple distributions +dist <- dist1 + dist2 +extract_single_dist(dist, 2) +} \author{ Sebastian Funk } diff --git a/man/fix_dist.Rd b/man/fix_dist.Rd index a11ffbd8d..32b277111 100644 --- a/man/fix_dist.Rd +++ b/man/fix_dist.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/dist.R +% Please edit documentation in R/dist_spec.R \name{fix_dist} \alias{fix_dist} \title{Fix the parameters of a \verb{}} @@ -20,6 +20,14 @@ A \verb{} object without uncertainty If the given \verb{} has any uncertainty, it is removed and the corresponding distribution converted into a fixed one. } +\examples{ +# An uncertain gamma distribution with mean 3 and sd 2 +dist <- LogNormal( + meanlog = Normal(3, 0.5), sdlog = Normal(2, 0.5), max = 20 +) + +fix_dist(dist) +} \author{ Sebastian Funk } diff --git a/man/gamma_dist_def.Rd b/man/gamma_dist_def.Rd index f590ac16c..454985adf 100644 --- a/man/gamma_dist_def.Rd +++ b/man/gamma_dist_def.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/dist.R +% Please edit documentation in R/deprecated.R \name{gamma_dist_def} \alias{gamma_dist_def} \title{Generate a Gamma Distribution Definition Based on Parameter Estimates} diff --git a/man/lognorm_dist_def.Rd b/man/lognorm_dist_def.Rd index 11db86014..d2bdafbda 100644 --- a/man/lognorm_dist_def.Rd +++ b/man/lognorm_dist_def.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/dist.R +% Please edit documentation in R/deprecated.R \name{lognorm_dist_def} \alias{lognorm_dist_def} \title{Generate a Log Normal Distribution Definition Based on Parameter Estimates} diff --git a/man/lower_bounds.Rd b/man/lower_bounds.Rd index d1f757905..2f1cb643e 100644 --- a/man/lower_bounds.Rd +++ b/man/lower_bounds.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/dist.R +% Please edit documentation in R/dist_spec.R \name{lower_bounds} \alias{lower_bounds} \title{Get the lower bounds of the parameters of a distribution} diff --git a/man/max.dist_spec.Rd b/man/max.dist_spec.Rd index 0ae753635..f4d4154f1 100644 --- a/man/max.dist_spec.Rd +++ b/man/max.dist_spec.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/dist.R +% Please edit documentation in R/dist_spec.R \name{max.dist_spec} \alias{max.dist_spec} \title{Returns the maximum of one or more delay distribution} @@ -28,7 +28,7 @@ max(dist1) dist2 <- LogNormal(mean = Normal(3, 0.5), sd = Normal(2, 0.5), max = 20) max(dist2) -# The maxf the sum of two distributions +# The max the sum of two distributions max(dist1 + dist2) } \author{ diff --git a/man/mean.dist_spec.Rd b/man/mean.dist_spec.Rd index aa71f0288..dfd14eb9d 100644 --- a/man/mean.dist_spec.Rd +++ b/man/mean.dist_spec.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/dist.R +% Please edit documentation in R/dist_spec.R \name{mean.dist_spec} \alias{mean.dist_spec} \title{Returns the mean of one or more delay distribution} diff --git a/man/natural_params.Rd b/man/natural_params.Rd index e255409e4..1ed380306 100644 --- a/man/natural_params.Rd +++ b/man/natural_params.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/dist.R +% Please edit documentation in R/dist_spec.R \name{natural_params} \alias{natural_params} \title{Get the names of the natural parameters of a distribution} diff --git a/man/new_dist_spec.Rd b/man/new_dist_spec.Rd index 943b1fdfb..3f7aa1859 100644 --- a/man/new_dist_spec.Rd +++ b/man/new_dist_spec.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/dist.R +% Please edit documentation in R/dist_spec.R \name{new_dist_spec} \alias{new_dist_spec} \title{Internal function for generating a \code{dist_spec} given parameters and a @@ -19,6 +19,14 @@ A \code{dist_spec} of the given specification. This will convert all parameters to natural parameters before generating a \code{dist_spec}. If they have uncertainty this will be done using sampling. } +\examples{ +\dontrun{ +new_dist_spec( + params = list(mean = 2, sd = 1, max = Inf), + distribution = "normal" +) +} +} \author{ Sebastian Funk } diff --git a/man/plot.dist_spec.Rd b/man/plot.dist_spec.Rd index 20383a78e..ac15d043e 100644 --- a/man/plot.dist_spec.Rd +++ b/man/plot.dist_spec.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/dist.R +% Please edit documentation in R/dist_spec.R \name{plot.dist_spec} \alias{plot.dist_spec} \title{Plot PMF and CDF for a dist_spec object} diff --git a/man/plus-.dist_spec.Rd b/man/plus-.dist_spec.Rd index c26ee45c3..78ec5661e 100644 --- a/man/plus-.dist_spec.Rd +++ b/man/plus-.dist_spec.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/dist.R +% Please edit documentation in R/dist_spec.R \name{+.dist_spec} \alias{+.dist_spec} \title{Creates a delay distribution as the sum of two other delay distributions.} @@ -15,7 +15,6 @@ combine.} } \value{ A delay distribution representing the sum of the two delays -(with class \code{\link[=dist_spec]{dist_spec()}}) } \description{ Creates a delay distribution as the sum of two other delay distributions. diff --git a/man/print.dist_spec.Rd b/man/print.dist_spec.Rd index 0b3a346a2..0bca4f824 100644 --- a/man/print.dist_spec.Rd +++ b/man/print.dist_spec.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/dist.R +% Please edit documentation in R/dist_spec.R \name{print.dist_spec} \alias{print.dist_spec} \title{Prints the parameters of one or more delay distributions} diff --git a/man/sample_approx_dist.Rd b/man/sample_approx_dist.Rd index 817fbca38..d21926e1d 100644 --- a/man/sample_approx_dist.Rd +++ b/man/sample_approx_dist.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/dist.R +% Please edit documentation in R/adjust.R \name{sample_approx_dist} \alias{sample_approx_dist} \title{Approximate Sampling a Distribution using Counts} diff --git a/man/sd_dist.Rd b/man/sd_dist.Rd index 0751b31d0..ec580a8f4 100644 --- a/man/sd_dist.Rd +++ b/man/sd_dist.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/dist.R +% Please edit documentation in R/dist_spec.R \name{sd_dist} \alias{sd_dist} \title{Returns the standard deviation of one or more delay distribution} diff --git a/man/trunc_opts.Rd b/man/trunc_opts.Rd index 736c7e3ea..619829e10 100644 --- a/man/trunc_opts.Rd +++ b/man/trunc_opts.Rd @@ -28,7 +28,7 @@ estimate these distributions. trunc_opts() # truncation dist -trunc_opts(dist = dist_spec(mean = 3, sd = 2, max = 10)) +trunc_opts(dist = LogNormal(mean = 3, sd = 2, max = 10)) } \seealso{ \code{\link[=convert_to_logmean]{convert_to_logmean()}} \code{\link[=convert_to_logsd]{convert_to_logsd()}} diff --git a/man/tune_inv_gamma.Rd b/man/tune_inv_gamma.Rd index c1c907d99..d97498f3e 100644 --- a/man/tune_inv_gamma.Rd +++ b/man/tune_inv_gamma.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/dist.R +% Please edit documentation in R/deprecated.R \name{tune_inv_gamma} \alias{tune_inv_gamma} \title{Tune an Inverse Gamma to Achieve the Target Truncation} From 3a5f45a81f6ddc6d699a0650141e6f0ecf9a44bb Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Mon, 26 Feb 2024 17:18:03 +0100 Subject: [PATCH 108/129] initial design sketch --- inst/dev/design_dist.md | 33 +++++++++++++++++++++++++++++++++ 1 file changed, 33 insertions(+) create mode 100644 inst/dev/design_dist.md diff --git a/inst/dev/design_dist.md b/inst/dev/design_dist.md new file mode 100644 index 000000000..ebb920c89 --- /dev/null +++ b/inst/dev/design_dist.md @@ -0,0 +1,33 @@ +# Design considerations of the distribution interface + +We are aiming for an interface with the following properties + * it should be clear to users which probability distribution is being used + * it can represent discrete and continuous parameters + * distribution parameters are labelled according to their meaning (e.g. mean vs. meanlog) + +We need to be able to represent + * (especially left-)truncated and untruncated distributions + * nested distributions (parameters of one distribution can be distributed according to another distribution) + +Ideally we'd also be able to represent + * parametric and nonparametric distributions + * distributions that are convolutions of two specified distributions + +This interface could be of potential use to other packages (e.g. `epinowcast`, `epidist`, `epiparameter`). It should therefore stand on its own. Any `EpiNow2` specific functionality (especially relating to conversion to stan code) should not interfere with core functionality of the distribution interface. + +## Proposed interface + +We are an proposing an dinterface similar to what is used in `{rstanarm}` and `{distributions3}`, where probability distributions are called according to their capitalised names. This avoids masking `base::gamma()` (although we still mask `stats::Gamma`). There is potential for integration especially with `{distributionS3}`. Parameters are nested according to the same syntax. + +Examples: +```{r} +Gamma(mean = 3, sd = 1) +Gamma(mean = 3, sd = 1, max = 14) +Gamma(mean = Normal(mean = 3, sd = 1), sd = 4, max = 14) +Gamma(shape = Normal(mean = 3, sd = 1), rate = Normal(mean = 2, sd = 0.5), max = 14) +Gamma(shape = 2, rate = 1, max = 14) +LogNormal(meanlog = 1.5, sdlog = 1) +LogNormal(mean = Normal(1.5, 0.1), sd = Normal(1, 0.1)) +pmf(c(0.2, 0.4, 0.4)) +pmf(c(0.2, 0.4, 0.2, 0.05)) +``` From ca56d2cc5e81e4d324dfb449e0aed7ef5c5c3f92 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 28 Feb 2024 08:44:26 +0100 Subject: [PATCH 109/129] make parameter conversion more flexible --- R/dist_spec.R | 37 +++++++++++++++++++++++++------------ 1 file changed, 25 insertions(+), 12 deletions(-) diff --git a/R/dist_spec.R b/R/dist_spec.R index 62dd4aa69..bd8f3df3b 100644 --- a/R/dist_spec.R +++ b/R/dist_spec.R @@ -1034,12 +1034,6 @@ new_dist_spec <- function(params, distribution) { ## convert any unnatural parameters unnatural_params <- setdiff(names(params), natural_params(distribution)) if (length(unnatural_params) > 0) { - if (length(unnatural_params) < length(params)) { - stop( - "Incompatible combination of parameters of a ", distribution, - " distribution specified." - ) - } ## sample parameters if they are uncertain if (any(vapply(params, sd_dist, numeric(1)) > 0)) { warning( @@ -1098,17 +1092,36 @@ convert_to_natural <- function(params, distribution) { ## store natural parameters x <- list() if (distribution == "gamma") { + ## given as mean and sd if ("mean" %in% names(ux) && "sd" %in% names(ux)) { x$shape <- ux$mean**2 / ux$sd**2 x$rate <- x$shape / ux$mean - } else if (!("rate" %in% names(ux)) && ("scale" %in% names(ux))) { + } else { + ## convert scale => rate + if ("scale" %in% names(ux)) { + x$rate <- 1 / ux$scale + } else { + x$rate <- ux$rate + } x$shape <- ux$shape - x$rate <- 1 / ux$scale } - } else if (distribution == "lognormal" && - "mean" %in% names(params) && "sd" %in% names(params)) { - x$meanlog <- log(ux$mean^2 / sqrt(ux$sd^2 + ux$mean^2)) - x$sdlog <- convert_to_logsd(ux$mean, ux$sd) + } else if (distribution == "lognormal") { + if ("mean" %in% names(params) && "sd" %in% names(params)) { + x$meanlog <- log(ux$mean^2 / sqrt(ux$sd^2 + ux$mean^2)) + x$sdlog <- convert_to_logsd(ux$mean, ux$sd) + } else { + x$meanlog <- ux$meanlog + x$sdlog <- ux$sdlog + } + } + ## sort + x <- x[natural_params(distribution)] + if (anyNA(names(x))) { + stop( + "Incompatible combination of parameters of a ", distribution, + " distribution specified:\n ", paste(names(params), collapse = ", "), + "." + ) } if (rel_unc > 0) { params <- lapply(names(x), function(param_name) { From c6884e3e658930e99f7952271026e991863f3c35 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 28 Feb 2024 08:44:44 +0100 Subject: [PATCH 110/129] add test for alternative gama params --- tests/testthat/test-dist_spec.R | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/tests/testthat/test-dist_spec.R b/tests/testthat/test-dist_spec.R index 1c02badee..e5f729f78 100644 --- a/tests/testthat/test-dist_spec.R +++ b/tests/testthat/test-dist_spec.R @@ -24,6 +24,14 @@ test_that("dist_spec returns correct output for uncertain gamma distribution", { expect_equal(result[[1]]$max, 19) }) +test_that("dist_spec returns correct output for gamma distribution parameterised with scale", { + result <- Gamma(shape = 3, scale = 2) + expect_equal(result[[1]]$parameters$shape, 3) + expect_equal(result[[1]]$parameters$rate, 0.5) + expect_equal(result[[1]]$distribution, "gamma") + expect_true(is.infinite(result[[1]]$max)) +}) + test_that("dist_spec returns correct output for fixed distribution", { result <- discretise( fix_dist(LogNormal(meanlog = Normal(5, 3), sdlog = 1, max = 19)) From bb861dc5206b5f52f3589a42b74543dfd4c0e586 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 28 Feb 2024 08:55:20 +0100 Subject: [PATCH 111/129] update syntax in simulate_infections --- inst/stan/simulate_infections.stan | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/inst/stan/simulate_infections.stan b/inst/stan/simulate_infections.stan index 52b0c3c16..d6ff12128 100644 --- a/inst/stan/simulate_infections.stan +++ b/inst/stan/simulate_infections.stan @@ -79,7 +79,7 @@ generated quantities { vector[delay_type_max[trunc_id] + 1] trunc_rev_cmf = get_delay_rev_pmf( trunc_id, delay_type_max[trunc_id] + 1, delay_types_p, delay_types_id, delay_types_groups, delay_max, delay_np_pmf, - delay_np_pmf_groups, delay_mean[i], delay_sd[i], delay_dist, + delay_np_pmf_groups, delay_params[i], delay_params_groups, delay_dist, 0, 1, 1 ); reports[i] = to_row_vector(truncate( From 52855bb08ca6eac8c1cfb6c6b4962a06f6fa22d3 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 28 Feb 2024 08:58:32 +0100 Subject: [PATCH 112/129] add missing tag --- R/dist_spec.R | 1 + man/convert_to_natural.Rd | 22 ++++++++-------------- 2 files changed, 9 insertions(+), 14 deletions(-) diff --git a/R/dist_spec.R b/R/dist_spec.R index bd8f3df3b..4ac59b7c0 100644 --- a/R/dist_spec.R +++ b/R/dist_spec.R @@ -1078,6 +1078,7 @@ new_dist_spec <- function(params, distribution) { #' mean and sd of natural parameters. #' @author Sebastian Funk #' @keywords internal +#' @examples #' \dontrun{ #' convert_to_natural( #' params = list(mean = 2, sd = 1, max = Inf), diff --git a/man/convert_to_natural.Rd b/man/convert_to_natural.Rd index b324d9682..0d23affd3 100644 --- a/man/convert_to_natural.Rd +++ b/man/convert_to_natural.Rd @@ -19,21 +19,15 @@ mean and sd of natural parameters. This is used for preprocessing before generating a \code{dist_spec} object from a given set of parameters and distribution } +\examples{ +\dontrun{ +convert_to_natural( + params = list(mean = 2, sd = 1, max = Inf), + distribution = "gamma" +) +} +} \author{ Sebastian Funk } -\keyword{"gamma"} -\keyword{)} -\keyword{1,} -\keyword{2,} -\keyword{=} -\keyword{Inf),} -\keyword{\dontrun{} -\keyword{convert_to_natural(} -\keyword{distribution} \keyword{internal} -\keyword{list(mean} -\keyword{max} -\keyword{params} -\keyword{sd} -\keyword{}} From 29db428014b4663e170515138d996811ac2702fc Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 28 Feb 2024 08:58:56 +0100 Subject: [PATCH 113/129] update man pages --- man/estimate_truncation.Rd | 3 ++- man/secondary_opts.Rd | 2 +- 2 files changed, 3 insertions(+), 2 deletions(-) diff --git a/man/estimate_truncation.Rd b/man/estimate_truncation.Rd index e229ed035..eaa7ff1d1 100644 --- a/man/estimate_truncation.Rd +++ b/man/estimate_truncation.Rd @@ -9,7 +9,8 @@ estimate_truncation( max_truncation, trunc_max = 10, trunc_dist = "lognormal", - truncation = trunc_opts(LogNormal(meanlog = Normal(0, 1), sdlog = Normal(1, 1), max = 10)), + truncation = trunc_opts(LogNormal(meanlog = Normal(0, 1), sdlog = Normal(1, 1), max = + 10)), model = NULL, stan = stan_opts(), CrIs = c(0.2, 0.5, 0.9), diff --git a/man/secondary_opts.Rd b/man/secondary_opts.Rd index 46442bb32..6d41ea516 100644 --- a/man/secondary_opts.Rd +++ b/man/secondary_opts.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/estimate_secondary.R +% Please edit documentation in R/opts.R \name{secondary_opts} \alias{secondary_opts} \title{Secondary Reports Options} From 14a2c172899fed26115ad91177c296bb435130c3 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 28 Feb 2024 09:03:45 +0100 Subject: [PATCH 114/129] update estimate_secondary tests --- tests/testthat/test-estimate_secondary.R | 15 ++++----------- 1 file changed, 4 insertions(+), 11 deletions(-) diff --git a/tests/testthat/test-estimate_secondary.R b/tests/testthat/test-estimate_secondary.R index c3ad21880..e1d161d43 100644 --- a/tests/testthat/test-estimate_secondary.R +++ b/tests/testthat/test-estimate_secondary.R @@ -82,10 +82,7 @@ test_that("estimate_secondary successfully returns estimates when passed NA valu cases_na[sample(1:60, 5), secondary := NA] inc_na <- estimate_secondary(cases_na[1:60], delays = delay_opts( - dist_spec( - mean = 1.8, mean_sd = 0, - sd = 0.5, sd_sd = 0, max = 30 - ) + LogNormal(meanlog = 1.8, sdlog = 0.5, max = 30) ), obs = obs_opts(scale = list(mean = 0.2, sd = 0.2), week_effect = FALSE), verbose = FALSE @@ -95,10 +92,7 @@ test_that("estimate_secondary successfully returns estimates when passed NA valu prev_na <- estimate_secondary(prev_cases_na[1:60], secondary = secondary_opts(type = "prevalence"), delays = delay_opts( - dist_spec( - mean = 1.8, mean_sd = 0, - sd = 0.5, sd_sd = 0, max = 30 - ) + LogNormal(mean = 1.8, sd = 0.5, max = 30) ), obs = obs_opts(scale = list(mean = 0.2, sd = 0.2), week_effect = FALSE), verbose = FALSE @@ -117,9 +111,8 @@ test_that("estimate_secondary successfully returns estimates when accumulating t ) inc_weekly <- estimate_secondary(cases_weekly, delays = delay_opts( - dist_spec( - mean = 1.8, mean_sd = 0, - sd = 0.5, sd_sd = 0, max = 30 + LogNormal( + mean = 1.8, sd = 0.5, max = 30 ) ), obs = obs_opts( From df2253aa3f0c9dbdf01a2202a0fb903be196a897 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 28 Feb 2024 09:04:11 +0100 Subject: [PATCH 115/129] update simulate_infections for new interface --- R/simulate_infections.R | 13 ++++--------- 1 file changed, 4 insertions(+), 9 deletions(-) diff --git a/R/simulate_infections.R b/R/simulate_infections.R index 623004975..e3919451e 100644 --- a/R/simulate_infections.R +++ b/R/simulate_infections.R @@ -119,22 +119,17 @@ simulate_infections <- function(estimates, R, initial_infections, trunc = truncation )) - if ((length(data$delay_mean_sd) > 0 && any(data$delay_mean_sd > 0)) || - (length(data$delay_sd_sd) > 0 && any(data$delay_sd_sd > 0))) { + if (length(data$delay_params_sd) > 0 && any(data$delay_params_sd > 0)) { stop( "Cannot simulate from uncertain parameters. Use the [fix_dist()] ", "function to set the parameters of uncertain distributions either the ", "mean or a randomly sampled value" ) } - data$delay_mean <- array( - data$delay_mean_mean, dim = c(1, length(data$delay_mean_mean)) + data$delay_params <- array( + data$delay_params_mean, dim = c(1, length(data$delay_params_mean)) ) - data$delay_sd <- array( - data$delay_sd_mean, dim = c(1, length(data$delay_sd_mean)) - ) - data$delay_mean_sd <- NULL - data$delay_sd_sd <- NULL + data$delay_params_sd <- NULL data <- c(data, create_obs_model( obs, dates = R$date From a16c23733cf0eea0955a7b046b9f39ed695334ca Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 28 Feb 2024 09:18:33 +0100 Subject: [PATCH 116/129] udpate snapshots --- tests/testthat/_snaps/simulate-infections.md | 84 ++++++++++---------- 1 file changed, 42 insertions(+), 42 deletions(-) diff --git a/tests/testthat/_snaps/simulate-infections.md b/tests/testthat/_snaps/simulate-infections.md index 5f0ba10c8..27fa990f6 100644 --- a/tests/testthat/_snaps/simulate-infections.md +++ b/tests/testthat/_snaps/simulate-infections.md @@ -16,53 +16,53 @@ 12: infections 2023-01-12 117.41367 13: infections 2023-01-13 93.93093 14: infections 2023-01-14 75.14475 - 15: reported_cases 2023-01-01 128.00000 - 16: reported_cases 2023-01-02 151.00000 - 17: reported_cases 2023-01-03 145.00000 - 18: reported_cases 2023-01-04 188.00000 - 19: reported_cases 2023-01-05 252.00000 - 20: reported_cases 2023-01-06 276.00000 - 21: reported_cases 2023-01-07 371.00000 - 22: reported_cases 2023-01-08 273.00000 - 23: reported_cases 2023-01-09 234.00000 - 24: reported_cases 2023-01-10 192.00000 - 25: reported_cases 2023-01-11 157.00000 - 26: reported_cases 2023-01-12 120.00000 - 27: reported_cases 2023-01-13 78.00000 - 28: reported_cases 2023-01-14 63.00000 + 15: reported_cases 2023-01-01 138.00000 + 16: reported_cases 2023-01-02 134.00000 + 17: reported_cases 2023-01-03 184.00000 + 18: reported_cases 2023-01-04 214.00000 + 19: reported_cases 2023-01-05 242.00000 + 20: reported_cases 2023-01-06 298.00000 + 21: reported_cases 2023-01-07 372.00000 + 22: reported_cases 2023-01-08 299.00000 + 23: reported_cases 2023-01-09 244.00000 + 24: reported_cases 2023-01-10 203.00000 + 25: reported_cases 2023-01-11 152.00000 + 26: reported_cases 2023-01-12 111.00000 + 27: reported_cases 2023-01-13 94.00000 + 28: reported_cases 2023-01-14 67.00000 variable date value # simulate_infections works as expected with additional parameters variable date value - 1: infections 2023-01-01 240.6049 - 2: infections 2023-01-02 253.8951 - 3: infections 2023-01-03 267.7099 - 4: infections 2023-01-04 282.1928 - 5: infections 2023-01-05 297.4201 - 6: infections 2023-01-06 313.4477 - 7: infections 2023-01-07 330.3258 - 8: infections 2023-01-08 232.0685 - 9: infections 2023-01-09 222.6294 - 10: infections 2023-01-10 212.0540 - 11: infections 2023-01-11 201.3581 - 12: infections 2023-01-12 190.8991 - 13: infections 2023-01-13 180.8132 - 14: infections 2023-01-14 171.1484 - 15: reported_cases 2023-01-01 425.0000 - 16: reported_cases 2023-01-02 335.0000 - 17: reported_cases 2023-01-03 376.0000 - 18: reported_cases 2023-01-04 250.0000 - 19: reported_cases 2023-01-05 301.0000 - 20: reported_cases 2023-01-06 275.0000 - 21: reported_cases 2023-01-07 844.0000 - 22: reported_cases 2023-01-08 235.0000 - 23: reported_cases 2023-01-09 205.0000 - 24: reported_cases 2023-01-10 251.0000 - 25: reported_cases 2023-01-11 239.0000 - 26: reported_cases 2023-01-12 80.0000 - 27: reported_cases 2023-01-13 128.0000 - 28: reported_cases 2023-01-14 276.0000 + 1: infections 2023-01-01 214.1121 + 2: infections 2023-01-02 225.6793 + 3: infections 2023-01-03 237.8341 + 4: infections 2023-01-04 250.6285 + 5: infections 2023-01-05 264.1041 + 6: infections 2023-01-06 278.3004 + 7: infections 2023-01-07 293.2573 + 8: infections 2023-01-08 206.0109 + 9: infections 2023-01-09 197.6193 + 10: infections 2023-01-10 188.2225 + 11: infections 2023-01-11 178.7223 + 12: infections 2023-01-12 169.4362 + 13: infections 2023-01-13 160.4852 + 14: infections 2023-01-14 151.9122 + 15: reported_cases 2023-01-01 133.0000 + 16: reported_cases 2023-01-02 175.0000 + 17: reported_cases 2023-01-03 105.0000 + 18: reported_cases 2023-01-04 148.0000 + 19: reported_cases 2023-01-05 109.0000 + 20: reported_cases 2023-01-06 601.0000 + 21: reported_cases 2023-01-07 209.0000 + 22: reported_cases 2023-01-08 74.0000 + 23: reported_cases 2023-01-09 192.0000 + 24: reported_cases 2023-01-10 398.0000 + 25: reported_cases 2023-01-11 118.0000 + 26: reported_cases 2023-01-12 442.0000 + 27: reported_cases 2023-01-13 232.0000 + 28: reported_cases 2023-01-14 107.0000 variable date value From 19eb1ebfe0aede045cf13360ac5ed0f6c821bb38 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 28 Feb 2024 09:24:57 +0100 Subject: [PATCH 117/129] get_dist deprecation test with natural params --- tests/testthat/test-get_dist.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/testthat/test-get_dist.R b/tests/testthat/test-get_dist.R index 463c3c964..97cafd400 100644 --- a/tests/testthat/test-get_dist.R +++ b/tests/testthat/test-get_dist.R @@ -1,5 +1,5 @@ test_that("get_dist is deprecated", { - data <- data.table::data.table(mean = 1, mean_sd = 1, sd = 1, sd_sd = 1, source = "test", disease = "test", dist = "gamma") + data <- data.table::data.table(mean = 1, mean_sd = 1, sd = 1, sd_sd = 1, source = "test", disease = "test", dist = "lognormal") expect_deprecated( get_dist(data, disease = "test", source = "test") ) From 12460c275e56d0b5129d7d16fa55ef51ab4eeb62 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 28 Feb 2024 09:25:10 +0100 Subject: [PATCH 118/129] update phi syntax --- tests/testthat/test-simulate-infections.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/testthat/test-simulate-infections.R b/tests/testthat/test-simulate-infections.R index 758c93fde..7f4f902cd 100644 --- a/tests/testthat/test-simulate-infections.R +++ b/tests/testthat/test-simulate-infections.R @@ -25,7 +25,7 @@ test_that("simulate_infections works as expected with additional parameters", { sim <- test_simulate_infections( generation_time = generation_time_opts(fix_dist(example_generation_time)), delays = delay_opts(fix_dist(example_reporting_delay)), - obs = obs_opts(family = "negbin", phi = c(0.5, 0)) + obs = obs_opts(family = "negbin", phi = list(mean = 0.5, sd = 0)) ) expect_equal(nrow(sim), 2 * nrow(R)) expect_snapshot_output(sim) From 5b57b56d5846f4b5ba07dbc6fa0c6bf20d480f9c Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 28 Feb 2024 09:40:01 +0100 Subject: [PATCH 119/129] hide internal example --- R/dist_spec.R | 6 ++++-- man/extract_single_dist.Rd | 6 ++++-- 2 files changed, 8 insertions(+), 4 deletions(-) diff --git a/R/dist_spec.R b/R/dist_spec.R index 4ac59b7c0..13381172e 100644 --- a/R/dist_spec.R +++ b/R/dist_spec.R @@ -732,8 +732,10 @@ plot.dist_spec <- function(x, ...) { #' ) #' #' # Multiple distributions -#' dist <- dist1 + dist2 -#' extract_single_dist(dist, 2) +#' \dontrun{ +#' dist <- dist1 + dist2 +#' extract_single_dist(dist, 2) +#' } extract_single_dist <- function(x, i) { if (i > length(x)) { stop("i can't be greater than the number of distributions.") diff --git a/man/extract_single_dist.Rd b/man/extract_single_dist.Rd index 05f94e402..f6a15f8a4 100644 --- a/man/extract_single_dist.Rd +++ b/man/extract_single_dist.Rd @@ -26,8 +26,10 @@ dist2 <- Gamma( ) # Multiple distributions -dist <- dist1 + dist2 -extract_single_dist(dist, 2) +\dontrun{ + dist <- dist1 + dist2 + extract_single_dist(dist, 2) +} } \author{ Sebastian Funk From 68b0463c2d5f3fdfcc7c75c80e690532f5c77a59 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 28 Feb 2024 10:20:49 +0100 Subject: [PATCH 120/129] update deprecations --- R/adjust.R | 2 +- R/deprecated.R | 16 ++++++++-------- R/estimate_truncation.R | 5 +++-- R/simulate_infections.R | 6 +++--- man/simulate_infections.Rd | 2 +- 5 files changed, 16 insertions(+), 15 deletions(-) diff --git a/R/adjust.R b/R/adjust.R index 7335f487c..378690e25 100644 --- a/R/adjust.R +++ b/R/adjust.R @@ -146,7 +146,7 @@ adjust_infection_to_report <- function(infections, delay_defs, } } else { deprecate_warn( - "2.0.0", + "1.5.0", "adjust_infection_to_report(delay_defs = 'should be a dist_spec')", details = "Specifying this as a list of data tables is deprecated." ) diff --git a/R/deprecated.R b/R/deprecated.R index ab28bed15..0a01218eb 100644 --- a/R/deprecated.R +++ b/R/deprecated.R @@ -43,8 +43,8 @@ gamma_dist_def <- function(shape, shape_sd, sd, sd_sd, max_value, samples) { lifecycle::deprecate_warn( - "2.0.0", "gamma_dist_def()", "Gamma()", - "The function will be removed completely in version 2.1.0." + "1.5.0", "gamma_dist_def()", "Gamma()", + "The function will be removed completely in version 2.0.0." ) if (missing(shape) && missing(scale) && !missing(mean) && !missing(sd)) { @@ -132,8 +132,8 @@ lognorm_dist_def <- function(mean, mean_sd, max_value, samples, to_log = FALSE) { lifecycle::deprecate_warn( - "2.0.0", "lognorm_dist_def()", "LogNormal()", - "The function will be removed completely in version 2.1.0." + "1.5.0", "lognorm_dist_def()", "LogNormal()", + "The function will be removed completely in version 2.0.0." ) transform_mean <- function(mu, sig) { @@ -262,20 +262,20 @@ dist_spec <- function(distribution = c( max = Inf, pmf = numeric(0), fixed = FALSE) { lifecycle::deprecate_warn( - "2.0.0", + "1.5.0", "dist_spec()", details = c( paste0( "Please use distribution functions such as `Gamma()` or `Lognormal()` ", "instead." ), - "The function will become internal only in version 2.1.0." + "The function will become internal only in version 2.0.0." ) ) ## check for deprecated parameters if (!missing(fixed)) { lifecycle::deprecate_warn( - "2.0.0", + "1.5.0", "dist_spec(fixed)", "fix_dist()" ) @@ -291,7 +291,7 @@ dist_spec <- function(distribution = c( ## check if distribution is given as empty and warn about deprecation if so if (distribution == "empty") { deprecate_warn( - "2.0.0", + "1.5.0", "dist_spec(distribution = 'must not be \"empty\"')", details = "Please use `Fixed(0)` instead." ) diff --git a/R/estimate_truncation.R b/R/estimate_truncation.R index bc751bb08..efcc19e3d 100644 --- a/R/estimate_truncation.R +++ b/R/estimate_truncation.R @@ -148,7 +148,8 @@ estimate_truncation <- function(obs, max_truncation, trunc_max = 10, trunc_dist = "lognormal", truncation = trunc_opts( LogNormal( - meanlog = Normal(0, 1), sdlog = Normal(1, 1), + meanlog = Normal(0, 1), + sdlog = Normal(1, 1), max = 10 ) ), @@ -161,7 +162,7 @@ estimate_truncation <- function(obs, max_truncation, trunc_max = 10, if (!is.null(model)) { lifecycle::deprecate_stop( - "2.0.0", + "1.5.0", "estimate_truncation(model)", "estimate_truncation(stan)" ) diff --git a/R/simulate_infections.R b/R/simulate_infections.R index e6a7d078c..88ab6d4b0 100644 --- a/R/simulate_infections.R +++ b/R/simulate_infections.R @@ -11,7 +11,7 @@ #' A previous function called [simulate_infections()] that simulates from a #' given model fit has been renamed [forecast_infections()]. Using #' [simulate_infections()] with existing estimates is now deprecated. This -#' option will be removed in version 2.1.0. +#' option will be removed in version 2.0.0. #' @param R a data frame of reproduction numbers (column `R`) by date (column #' `date`). Column `R` must be numeric and `date` must be in date format. If #' not all days between the first and last day in the `date` are present, @@ -67,8 +67,8 @@ simulate_infections <- function(estimates, R, initial_infections, "simulate_infections(estimates)", "forecast_infections()", details = paste0( - "This `estimates` option will be removed from [simulate_infections()] ", - "in version 2.1.0." + "The `estimates` option will be removed from [simulate_infections()] ", + "in version 2.0.0." ) ) return(forecast_infections(estimates = estimates, ...)) diff --git a/man/simulate_infections.Rd b/man/simulate_infections.Rd index 0f6b6ab12..398a5a375 100644 --- a/man/simulate_infections.Rd +++ b/man/simulate_infections.Rd @@ -79,7 +79,7 @@ Uncertain parameters are not allowed. A previous function called \code{\link[=simulate_infections]{simulate_infections()}} that simulates from a given model fit has been renamed \code{\link[=forecast_infections]{forecast_infections()}}. Using \code{\link[=simulate_infections]{simulate_infections()}} with existing estimates is now deprecated. This -option will be removed in version 2.1.0. +option will be removed in version 2.0.0. } \examples{ \donttest{ From 9f8d86a1e34fdac9b5568c34d86aafea2a7903e1 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 28 Feb 2024 10:22:47 +0100 Subject: [PATCH 121/129] use toString --- R/dist_spec.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/dist_spec.R b/R/dist_spec.R index 13381172e..f6434a318 100644 --- a/R/dist_spec.R +++ b/R/dist_spec.R @@ -1122,7 +1122,7 @@ convert_to_natural <- function(params, distribution) { if (anyNA(names(x))) { stop( "Incompatible combination of parameters of a ", distribution, - " distribution specified:\n ", paste(names(params), collapse = ", "), + " distribution specified:\n ", toString(names(params)), "." ) } From 3ced45378d7721ab7c2a8fbeabd23d492c2c50f9 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 28 Feb 2024 16:19:38 +0100 Subject: [PATCH 122/129] pmf -> NonParametric --- NAMESPACE | 2 +- R/dist_spec.R | 10 +++++----- inst/dev/design_dist.md | 4 ++-- man/Distributions.Rd | 10 +++++----- tests/testthat/test-dist_spec.R | 11 +++++++---- 5 files changed, 20 insertions(+), 17 deletions(-) diff --git a/NAMESPACE b/NAMESPACE index 644379f3f..11ed0c17f 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -15,6 +15,7 @@ S3method(summary,estimate_infections) export(Fixed) export(Gamma) export(LogNormal) +export(NonParametric) export(Normal) export(R_to_growth) export(add_day_of_week) @@ -79,7 +80,6 @@ export(opts_list) export(package_model) export(plot_estimates) export(plot_summary) -export(pmf) export(regional_epinow) export(regional_runtimes) export(regional_summary) diff --git a/R/dist_spec.R b/R/dist_spec.R index f6434a318..9e2680dc7 100644 --- a/R/dist_spec.R +++ b/R/dist_spec.R @@ -890,7 +890,7 @@ Fixed <- function(value, max = Inf) { #' Generates a nonparametric distribution. #' -#' @param mass Probability mass of the given distribution; this is +#' @param pmf Probability mass of the given distribution; this is #' passed as a zero-indexed numeric vector (i.e. the fist entry represents #' the probability mass of zero). If not summing to one it will be normalised #' to sum to one internally. @@ -899,10 +899,10 @@ Fixed <- function(value, max = Inf) { #' @order 5 #' @export #' @examples -#' pmf(c(0.1, 0.3, 0.2, 0.4)) -#' pmf(c(0.1, 0.3, 0.2, 0.1, 0.1)) -pmf <- function(mass) { - params <- list(pmf = mass / sum(mass)) +#' NonParametric(c(0.1, 0.3, 0.2, 0.4)) +#' NonParametric(c(0.1, 0.3, 0.2, 0.1, 0.1)) +NonParametric <- function(pmf) { + params <- list(pmf = pmf / sum(pmf)) return(new_dist_spec(params, "nonparametric")) } diff --git a/inst/dev/design_dist.md b/inst/dev/design_dist.md index ebb920c89..d172b2b9e 100644 --- a/inst/dev/design_dist.md +++ b/inst/dev/design_dist.md @@ -28,6 +28,6 @@ Gamma(shape = Normal(mean = 3, sd = 1), rate = Normal(mean = 2, sd = 0.5), max = Gamma(shape = 2, rate = 1, max = 14) LogNormal(meanlog = 1.5, sdlog = 1) LogNormal(mean = Normal(1.5, 0.1), sd = Normal(1, 0.1)) -pmf(c(0.2, 0.4, 0.4)) -pmf(c(0.2, 0.4, 0.2, 0.05)) +NonParametric(c(0.2, 0.4, 0.4)) +NonParametric(c(0.2, 0.4, 0.2, 0.05)) ``` diff --git a/man/Distributions.Rd b/man/Distributions.Rd index 4510f4721..6a78cee7e 100644 --- a/man/Distributions.Rd +++ b/man/Distributions.Rd @@ -6,7 +6,7 @@ \alias{Gamma} \alias{Normal} \alias{Fixed} -\alias{pmf} +\alias{NonParametric} \title{Probability distributions} \usage{ LogNormal(meanlog, sdlog, mean, sd, max = Inf) @@ -17,7 +17,7 @@ Normal(mean, sd, max = Inf) Fixed(value, max = Inf) -pmf(mass) +NonParametric(pmf) } \arguments{ \item{meanlog, sdlog}{mean and standard deviation of the distribution @@ -35,7 +35,7 @@ be truncated at this value. Default: \code{Inf}, i.e. no maximum.} \item{value}{Value of the fixed (delta) distribution} -\item{mass}{Probability mass of the given distribution; this is +\item{pmf}{Probability mass of the given distribution; this is passed as a zero-indexed numeric vector (i.e. the fist entry represents the probability mass of zero). If not summing to one it will be normalised to sum to one internally.} @@ -86,8 +86,8 @@ Normal(mean = 4, sd = 1) Normal(mean = 4, sd = 1, max = 10) Fixed(value = 3) Fixed(value = 3.5) -pmf(c(0.1, 0.3, 0.2, 0.4)) -pmf(c(0.1, 0.3, 0.2, 0.1, 0.1)) +NonParametric(c(0.1, 0.3, 0.2, 0.4)) +NonParametric(c(0.1, 0.3, 0.2, 0.1, 0.1)) } \author{ Sebastian Funk diff --git a/tests/testthat/test-dist_spec.R b/tests/testthat/test-dist_spec.R index e5f729f78..73547cc03 100644 --- a/tests/testthat/test-dist_spec.R +++ b/tests/testthat/test-dist_spec.R @@ -73,8 +73,8 @@ test_that("c.dist_spec returns correct output for sum of two distributions", { }) test_that("collapse returns correct output for sum of two nonparametric distributions", { - dist1 <- pmf(c(0.1, 0.2, 0.3, 0.4)) - dist2 <- pmf(c(0.1, 0.2, 0.3, 0.4)) + dist1 <- NonParametric(c(0.1, 0.2, 0.3, 0.4)) + dist2 <- NonParametric(c(0.1, 0.2, 0.3, 0.4)) result <- collapse(c(dist1, dist2)) expect_null(result[[1]]$parameters) expect_equal(result[[1]]$distribution, "nonparametric") @@ -263,9 +263,12 @@ test_that("delay distributions can be specified in different ways", { ) expect_equal(discretise(Fixed(value = 3))[[1]]$pmf, c(0, 0, 0, 1)) expect_equal(Fixed(value = 3.5)[[1]]$parameters$value, 3.5) - expect_equal(pmf(c(0.1, 0.3, 0.2, 0.4))[[1]]$pmf, c(0.1, 0.3, 0.2, 0.4)) expect_equal( - round(pmf(c(0.1, 0.3, 0.2, 0.1, 0.1))[[1]]$pmf, 2), + NonParametric(c(0.1, 0.3, 0.2, 0.4))[[1]]$pmf, + c(0.1, 0.3, 0.2, 0.4) + ) + expect_equal( + round(NonParametric(c(0.1, 0.3, 0.2, 0.1, 0.1))[[1]]$pmf, 2), c(0.12, 0.37, 0.25, 0.12, 0.12) ) }) From a630d69834c7eff50b4f7459ae81156926147276 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Thu, 29 Feb 2024 12:38:18 +0000 Subject: [PATCH 123/129] add american spelling --- NAMESPACE | 1 + R/dist_spec.R | 3 +++ man/discretise.Rd | 3 +++ 3 files changed, 7 insertions(+) diff --git a/NAMESPACE b/NAMESPACE index 11ed0c17f..07549e7b6 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -44,6 +44,7 @@ export(create_stan_args) export(create_stan_data) export(delay_opts) export(discretise) +export(discretize) export(dist_fit) export(dist_skel) export(dist_spec) diff --git a/R/dist_spec.R b/R/dist_spec.R index 9e2680dc7..6ca9b998a 100644 --- a/R/dist_spec.R +++ b/R/dist_spec.R @@ -483,6 +483,9 @@ discretise <- function(x, silent = TRUE) { attr(ret, "class") <- c("dist_spec", "list") return(ret) } +#' @rdname discretise +#' @export +discretize <- discretise #' Collapse nonparametric distributions in a #' diff --git a/man/discretise.Rd b/man/discretise.Rd index d8ee31d16..2119da8e6 100644 --- a/man/discretise.Rd +++ b/man/discretise.Rd @@ -2,9 +2,12 @@ % Please edit documentation in R/dist_spec.R \name{discretise} \alias{discretise} +\alias{discretize} \title{Discretise a } \usage{ discretise(x, silent = TRUE) + +discretize(x, silent = TRUE) } \arguments{ \item{x}{A \verb{}} From b4c04cae359b38f7c40208d953fd59892dc10d7b Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Mon, 4 Mar 2024 09:37:04 +0000 Subject: [PATCH 124/129] fix gamma deprecation --- R/deprecated.R | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/R/deprecated.R b/R/deprecated.R index 0a01218eb..c50d0a3a7 100644 --- a/R/deprecated.R +++ b/R/deprecated.R @@ -310,8 +310,8 @@ dist_spec <- function(distribution = c( mean = Normal(mean, mean_sd), sd = Normal(sd, sd_sd) ) - params_mean <- temp_dist$params_mean - params_sd <- temp_dist$params_sd + params_mean <- vapply(temp_dist[[1]]$parameters, mean, numeric(1)) + params_sd <- vapply(temp_dist[[1]]$parameters, sd_dist, numeric(1)) } else if (distribution == "normal") { params_mean <- c(mean = mean, sd = sd) params_sd <- c(mean = mean_sd, sd = sd_sd) From c39b28e13552314f4ad205f15d2ab936f116fcf7 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 6 Mar 2024 08:44:19 +0000 Subject: [PATCH 125/129] add new functions to pkgdown --- _pkgdown.yml | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/_pkgdown.yml b/_pkgdown.yml index b7740bb64..75c7313b6 100644 --- a/_pkgdown.yml +++ b/_pkgdown.yml @@ -122,6 +122,10 @@ reference: - title: Define, Fit and Parameterise Distributions desc: Functions to define, fit and parameterise distributions contents: + - Distributions + - apply_tolerance + - collapse + - discretise - contains("dist") - title: Simulate desc: Functions to help with simulating data or mapping to reported cases From d1c3cf7236af5c9dd4b0d5f2aebf19cf8224db2c Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 6 Mar 2024 09:58:54 +0000 Subject: [PATCH 126/129] update vignette --- vignettes/EpiNow2.Rmd.orig | 19 ++++++------------- 1 file changed, 6 insertions(+), 13 deletions(-) diff --git a/vignettes/EpiNow2.Rmd.orig b/vignettes/EpiNow2.Rmd.orig index 26a8ff8c1..e92080dea 100644 --- a/vignettes/EpiNow2.Rmd.orig +++ b/vignettes/EpiNow2.Rmd.orig @@ -24,9 +24,9 @@ library(EpiNow2) ### Reporting delays, incubation period and generation time -Distributions can be supplied in two ways. First, by supplying delay data to `estimate_delay()`, where a subsampled bootstrapped lognormal will be fit to account for uncertainty in the observed data without being biased by changes in incidence (see `?EpiNow2::estimate_delay()`). +Distributions can be supplied in two ways. First, one can supplying delay data to `estimate_delay()`, where a subsampled bootstrapped lognormal will be fit to account for uncertainty in the observed data without being biased by changes in incidence (see `?EpiNow2::estimate_delay()`). -Second, by specifying predetermined delays with uncertainty using `dist_spec()`. An arbitrary number of delay distributions are supported in `dist_spec()` with the most common use case likely to be an incubation period followed by a reporting delay (see `?EpiNow2::dist_spec()`). +Second, one can specify predetermined delays with uncertainty using the distribution functions such as `Gamma` or `Lognormal`. An arbitrary number of delay distributions are supported in `dist_spec()` with a common use case being an incubation period followed by a reporting delay. For more information on specifying distributions see (see `?EpiNow2::Distributions`). For example if data on the delay between onset and infection was available we could fit a distribution to it, using `estimate_delay()`, with appropriate uncertainty as follows (note this is a synthetic example), ```{r, eval = FALSE} @@ -36,18 +36,11 @@ reporting_delay <- estimate_delay( ) ``` -If data was not available we could instead specify an informed estimate of the likely delay -using `dist_spec()`. To demonstrate, we choose a lognormal distribution with mean 2, standard deviation 1 (both with some uncertainty) and a maximum of 10. *This is just an example and unlikely to apply in any particular use case*. +If data was not available we could instead specify an informed estimate of the likely delay using the distribution functions `Gamma` or `LogNormal`. +To demonstrate, we choose a lognormal distribution with mean 2, standard deviation 1 and a maximum of 10. *This is just an example and unlikely to apply in any particular use case*. ```{r} -reporting_delay <- dist_spec( - mean = convert_to_logmean(2, 1), - mean_sd = 0.1, - sd = convert_to_logsd(2, 1), - sd_sd = 0.1, - max = 10, - distribution = "lognormal" -) +reporting_delay <- LogNormal(mean = 2, sd = 1, max = 10) reporting_delay ``` @@ -150,4 +143,4 @@ A range of plots are again returned (with the single summary plot shown below). ```{r, dpi = 330, fig.width = 12, fig.height = 12, message = FALSE, warning = FALSE} estimates$summary$summary_plot -``` \ No newline at end of file +``` From 4ffd5330d3eb678749618d21939cd796a03529aa Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 6 Mar 2024 11:10:13 +0000 Subject: [PATCH 127/129] recompile vignettes --- vignettes/EpiNow2.Rmd | 177 +++++----- vignettes/epinow.Rmd | 102 +++--- vignettes/estimate_infections_options.Rmd | 304 +++++++++++------- vignettes/estimate_infections_workflow.Rmd | 50 ++- vignettes/figure/bp-1.png | Bin 44096 -> 66069 bytes vignettes/figure/data-1.png | Bin 3808 -> 11336 bytes vignettes/figure/default-1.png | Bin 49065 -> 76529 bytes vignettes/figure/fixed-1.png | Bin 37436 -> 62004 bytes vignettes/figure/gp_projection-1.png | Bin 48673 -> 75922 bytes vignettes/figure/lower_accuracy-1.png | Bin 48630 -> 75818 bytes vignettes/figure/no_delays-1.png | Bin 45803 -> 71297 bytes vignettes/figure/nonparametric-1.png | Bin 47295 -> 70105 bytes vignettes/figure/regional_epinow-1.png | Bin 33728 -> 58371 bytes .../figure/regional_epinow_multiple-1.png | Bin 32539 -> 52374 bytes vignettes/figure/results-1.png | Bin 57921 -> 85776 bytes vignettes/figure/susceptible_depletion-1.png | Bin 48500 -> 76524 bytes vignettes/figure/truncation-1.png | Bin 4747 -> 76466 bytes vignettes/figure/unnamed-chunk-10-1.png | Bin 970122 -> 974063 bytes vignettes/figure/unnamed-chunk-14-1.png | Bin 387122 -> 387195 bytes vignettes/figure/weekly_rw-1.png | Bin 47636 -> 75060 bytes 20 files changed, 380 insertions(+), 253 deletions(-) diff --git a/vignettes/EpiNow2.Rmd b/vignettes/EpiNow2.Rmd index fbf69082e..399ab5273 100644 --- a/vignettes/EpiNow2.Rmd +++ b/vignettes/EpiNow2.Rmd @@ -25,9 +25,9 @@ library(EpiNow2) ### Reporting delays, incubation period and generation time -Distributions can be supplied in two ways. First, by supplying delay data to `estimate_delay()`, where a subsampled bootstrapped lognormal will be fit to account for uncertainty in the observed data without being biased by changes in incidence (see `?EpiNow2::estimate_delay()`). +Distributions can be supplied in two ways. First, one can supplying delay data to `estimate_delay()`, where a subsampled bootstrapped lognormal will be fit to account for uncertainty in the observed data without being biased by changes in incidence (see `?EpiNow2::estimate_delay()`). -Second, by specifying predetermined delays with uncertainty using `dist_spec()`. An arbitrary number of delay distributions are supported in `dist_spec()` with the most common use case likely to be an incubation period followed by a reporting delay (see `?EpiNow2::dist_spec()`). +Second, one can specify predetermined delays with uncertainty using the distribution functions such as `Gamma` or `Lognormal`. An arbitrary number of delay distributions are supported in `dist_spec()` with a common use case being an incubation period followed by a reporting delay. For more information on specifying distributions see (see `?EpiNow2::Distributions`). For example if data on the delay between onset and infection was available we could fit a distribution to it, using `estimate_delay()`, with appropriate uncertainty as follows (note this is a synthetic example), @@ -38,33 +38,21 @@ reporting_delay <- estimate_delay( ) ``` -If data was not available we could instead specify an informed estimate of the likely delay -using `dist_spec()`. To demonstrate, we choose a lognormal distribution with mean 2, standard deviation 1 (both with some uncertainty) and a maximum of 10. *This is just an example and unlikely to apply in any particular use case*. +If data was not available we could instead specify an informed estimate of the likely delay using the distribution functions `Gamma` or `LogNormal`. +To demonstrate, we choose a lognormal distribution with mean 2, standard deviation 1 and a maximum of 10. *This is just an example and unlikely to apply in any particular use case*. ```r -reporting_delay <- dist_spec( - mean = convert_to_logmean(2, 1), - mean_sd = 0.1, - sd = convert_to_logsd(2, 1), - sd_sd = 0.1, - max = 10, - distribution = "lognormal" -) -``` - -``` -## Warning: The meaning of the 'max' argument has changed compared to previous versions. It now indicates the maximum of a distribution rather than the length of the probability mass function (including 0) that it represented previously. To replicate previous behaviour reduce max by 1. -## This warning is displayed once every 8 hours. -``` - -```r +reporting_delay <- LogNormal(mean = 2, sd = 1, max = 10) reporting_delay ``` ``` -## -## Uncertain lognormal distribution with (untruncated) logmean 0.58 (SD 0.1) and logSD 0.47 (SD 0.1) +## - lognormal distribution (max: 10): +## meanlog: +## 0.58 +## sdlog: +## 0.47 ``` For the rest of this vignette, we will use inbuilt example literature estimates for the incubation period and generation time of Covid-19 (see [here](https://github.com/epiforecasts/EpiNow2/tree/main/data-raw) for the code that generates these estimates). *These distributions are unlikely to be applicable for your use case. We strongly recommend investigating what might be the best distributions to use in any given use case.* @@ -75,8 +63,19 @@ example_generation_time ``` ``` -## -## Uncertain gamma distribution with (untruncated) mean 3.6 (SD 0.71) and SD 3.1 (SD 0.77) +## - gamma distribution (max: 14): +## shape: +## - normal distribution: +## mean: +## 1.4 +## sd: +## 0.48 +## rate: +## - normal distribution: +## mean: +## 0.38 +## sd: +## 0.25 ``` ```r @@ -84,8 +83,19 @@ example_incubation_period ``` ``` -## -## Uncertain lognormal distribution with (untruncated) logmean 1.6 (SD 0.064) and logSD 0.42 (SD 0.069) +## - lognormal distribution (max: 14): +## meanlog: +## - normal distribution: +## mean: +## 1.6 +## sd: +## 0.064 +## sdlog: +## - normal distribution: +## mean: +## 0.42 +## sd: +## 0.069 ``` Now, to the functions. @@ -104,6 +114,7 @@ head(reported_cases) ``` ## date confirm +## ## 1: 2020-02-22 14 ## 2: 2020-02-23 62 ## 3: 2020-02-24 53 @@ -127,7 +138,7 @@ estimates <- epinow( ``` ``` -## DEBUG [2023-11-24 16:30:24] epinow: Running in exact mode for 2000 samples (across 4 chains each with a warm up of 250 iterations each) and 79 time steps of which 7 are a forecast +## DEBUG [2024-03-06 10:56:48] epinow: Running in exact mode for 2000 samples (across 4 chains each with a warm up of 250 iterations each) and 81 time steps of which 7 are a forecast ``` ```r @@ -135,8 +146,9 @@ names(estimates) ``` ``` -## [1] "estimates" "estimated_reported_cases" "summary" -## [4] "plots" "timing" +## [1] "estimates" "estimated_reported_cases" +## [3] "summary" "plots" +## [5] "timing" ``` Both summary measures and posterior samples are returned for all parameters in an easily explored format which can be accessed using `summary`. The default is to return a summary table of estimates for key parameters at the latest date partially supported by data. @@ -150,11 +162,11 @@ knitr::kable(summary(estimates)) |measure |estimate | |:-------------------------------------|:----------------------| -|New confirmed cases by infection date |2274 (1099 -- 4314) | +|New confirmed cases by infection date |2275 (1119 -- 4289) | |Expected change in daily cases |Likely decreasing | -|Effective reproduction no. |0.88 (0.6 -- 1.2) | -|Rate of growth |-0.027 (-0.1 -- 0.037) | -|Doubling/halving time (days) |-25 (19 -- -6.8) | +|Effective reproduction no. |0.88 (0.59 -- 1.2) | +|Rate of growth |-0.026 (-0.1 -- 0.034) | +|Doubling/halving time (days) |-26 (20 -- -6.8) | Summarised parameter estimates can also easily be returned, either filtered for a single parameter or for all parameters. @@ -164,20 +176,22 @@ head(summary(estimates, type = "parameters", params = "R")) ``` ``` -## date variable strat type median mean sd lower_90 lower_50 lower_20 -## 1: 2020-02-22 R estimate 2.221079 2.224645 0.14975914 1.982998 2.120541 2.184087 -## 2: 2020-02-23 R estimate 2.188992 2.189990 0.12321715 1.987626 2.105233 2.156689 -## 3: 2020-02-24 R estimate 2.154198 2.153534 0.10184039 1.984744 2.083930 2.129261 -## 4: 2020-02-25 R estimate 2.115460 2.115351 0.08536356 1.976180 2.057553 2.093551 -## 5: 2020-02-26 R estimate 2.076472 2.075590 0.07338724 1.955627 2.025919 2.055536 -## 6: 2020-02-27 R estimate 2.033228 2.034460 0.06529358 1.925234 1.990964 2.017267 -## upper_20 upper_50 upper_90 -## 1: 2.256138 2.321166 2.481580 -## 2: 2.219594 2.269469 2.400337 -## 3: 2.179742 2.222020 2.331207 -## 4: 2.139824 2.173188 2.256432 -## 5: 2.095006 2.125832 2.198023 -## 6: 2.051111 2.079405 2.142454 +## date variable strat type median mean sd lower_90 +## +## 1: 2020-02-22 R estimate 2.235313 2.242778 0.15785751 1.994122 +## 2: 2020-02-23 R estimate 2.204258 2.206780 0.13441775 1.994963 +## 3: 2020-02-24 R estimate 2.165179 2.168790 0.11730902 1.983866 +## 4: 2020-02-25 R estimate 2.123195 2.128927 0.10599589 1.958182 +## 5: 2020-02-26 R estimate 2.081865 2.087395 0.09931082 1.931449 +## 6: 2020-02-27 R estimate 2.038602 2.044461 0.09574420 1.896977 +## lower_50 lower_20 upper_20 upper_50 upper_90 +## +## 1: 2.133553 2.196041 2.273706 2.343048 2.510622 +## 2: 2.117524 2.168279 2.232611 2.295411 2.431460 +## 3: 2.092001 2.134802 2.192621 2.247227 2.364333 +## 4: 2.057449 2.099115 2.151714 2.200477 2.308683 +## 5: 2.018154 2.055255 2.107715 2.153086 2.256241 +## 6: 1.978879 2.014504 2.063162 2.107575 2.208615 ``` Reported cases are returned in a separate data frame in order to streamline the reporting of forecasts and for model evaluation. @@ -188,13 +202,22 @@ head(summary(estimates, output = "estimated_reported_cases")) ``` ``` -## date type median mean sd lower_90 lower_50 lower_20 upper_20 upper_50 upper_90 -## 1: 2020-02-22 gp_rt 67 68.2710 18.40907 41.95 55 62 71 79 101 -## 2: 2020-02-23 gp_rt 77 79.2985 21.72877 47.00 64 73 83 92 117 -## 3: 2020-02-24 gp_rt 77 78.9005 20.98294 49.00 64 72 82 91 116 -## 4: 2020-02-25 gp_rt 74 75.0540 21.44484 43.00 60 68 78 87 114 -## 5: 2020-02-26 gp_rt 78 80.1645 21.46518 48.00 65 73 84 93 118 -## 6: 2020-02-27 gp_rt 110 113.6910 30.39336 68.00 92 104 118 134 168 +## date type median mean sd lower_90 lower_50 lower_20 +## +## 1: 2020-02-22 gp_rt 69 70.3425 18.36240 43.95 58 64.0 +## 2: 2020-02-23 gp_rt 77 79.1820 20.80436 48.00 64 73.0 +## 3: 2020-02-24 gp_rt 76 77.5690 20.52722 48.00 63 71.0 +## 4: 2020-02-25 gp_rt 73 74.9525 19.90978 46.95 61 68.0 +## 5: 2020-02-26 gp_rt 77 79.1355 20.81427 50.00 64 72.0 +## 6: 2020-02-27 gp_rt 111 112.9385 28.65963 70.00 93 103.6 +## upper_20 upper_50 upper_90 +## +## 1: 73 81 102.00 +## 2: 83 92 116.00 +## 3: 81 90 113.05 +## 4: 78 87 110.00 +## 5: 82 92 116.00 +## 6: 118 130 165.00 ``` A range of plots are returned (with the single summary plot shown below). These plots can also be generated using the following `plot` method. @@ -225,6 +248,7 @@ head(reported_cases) ``` ## date confirm region +## ## 1: 2020-02-22 14 testland ## 2: 2020-02-23 62 testland ## 3: 2020-02-24 53 testland @@ -248,27 +272,30 @@ estimates <- regional_epinow( ``` ``` -## INFO [2023-11-24 16:31:54] Producing following optional outputs: regions, summary, samples, plots, latest -## INFO [2023-11-24 16:31:54] Reporting estimates using data up to: 2020-04-21 -## INFO [2023-11-24 16:31:54] No target directory specified so returning output -## INFO [2023-11-24 16:31:54] Producing estimates for: testland, realland -## INFO [2023-11-24 16:31:54] Regions excluded: none -## DEBUG [2023-11-24 16:31:54] testland: Running in exact mode for 1000 samples (across 4 chains each with a warm up of 250 iterations each) and 79 time steps of which 7 are a forecast -## WARN [2023-11-24 16:32:07] testland (chain: 1): Bulk Effective Samples Size (ESS) is too low, indicating posterior means and medians may be unreliable. +## INFO [2024-03-06 10:57:48] Producing following optional outputs: regions, summary, samples, plots, latest +## INFO [2024-03-06 10:57:48] Reporting estimates using data up to: 2020-04-21 +## INFO [2024-03-06 10:57:48] No target directory specified so returning output +## INFO [2024-03-06 10:57:48] Producing estimates for: testland, realland +## INFO [2024-03-06 10:57:48] Regions excluded: none +## DEBUG [2024-03-06 10:57:48] testland: Running in exact mode for 1000 samples (across 4 chains each with a warm up of 250 iterations each) and 81 time steps of which 7 are a forecast +## WARN [2024-03-06 10:57:59] testland (chain: 1): Bulk Effective Samples Size (ESS) is too low, indicating posterior means and medians may be unreliable. ## Running the chains for more iterations may help. See ## https://mc-stan.org/misc/warnings.html#bulk-ess - -## INFO [2023-11-24 16:32:08] Completed estimates for: testland -## DEBUG [2023-11-24 16:32:08] realland: Running in exact mode for 1000 samples (across 4 chains each with a warm up of 250 iterations each) and 79 time steps of which 7 are a forecast -## WARN [2023-11-24 16:32:21] realland (chain: 1): Bulk Effective Samples Size (ESS) is too low, indicating posterior means and medians may be unreliable. +## WARN [2024-03-06 10:58:00] testland (chain: 1): Tail Effective Samples Size (ESS) is too low, indicating posterior variances and tail quantiles may be unreliable. +## Running the chains for more iterations may help. See +## https://mc-stan.org/misc/warnings.html#tail-ess - +## INFO [2024-03-06 10:58:00] Completed estimates for: testland +## DEBUG [2024-03-06 10:58:00] realland: Running in exact mode for 1000 samples (across 4 chains each with a warm up of 250 iterations each) and 81 time steps of which 7 are a forecast +## WARN [2024-03-06 10:58:10] realland (chain: 1): Bulk Effective Samples Size (ESS) is too low, indicating posterior means and medians may be unreliable. ## Running the chains for more iterations may help. See ## https://mc-stan.org/misc/warnings.html#bulk-ess - -## INFO [2023-11-24 16:32:21] Completed estimates for: realland -## INFO [2023-11-24 16:32:21] Completed regional estimates -## INFO [2023-11-24 16:32:21] Regions with estimates: 2 -## INFO [2023-11-24 16:32:21] Regions with runtime errors: 0 -## INFO [2023-11-24 16:32:21] Producing summary -## INFO [2023-11-24 16:32:21] No summary directory specified so returning summary output -## INFO [2023-11-24 16:32:22] No target directory specified so returning timings +## INFO [2024-03-06 10:58:11] Completed estimates for: realland +## INFO [2024-03-06 10:58:11] Completed regional estimates +## INFO [2024-03-06 10:58:11] Regions with estimates: 2 +## INFO [2024-03-06 10:58:11] Regions with runtime errors: 0 +## INFO [2024-03-06 10:58:11] Producing summary +## INFO [2024-03-06 10:58:11] No summary directory specified so returning summary output +## INFO [2024-03-06 10:58:11] No target directory specified so returning timings ``` Results from each region are stored in a `regional` list with across region summary measures and plots stored in a `summary` list. All results can be set to be internally saved by setting the `target_folder` and `summary_dir` arguments. Each region can be estimated in parallel using the `{future}` package (when in most scenarios `cores` should be set to 1). For routine use each MCMC chain can also be run in parallel (with `future` = TRUE) with a time out (`max_execution_time`) allowing for partial results to be returned if a subset of chains is running longer than expected. See the documentation for the `{future}` package for details on nested futures. @@ -282,10 +309,10 @@ knitr::kable(estimates$summary$summarised_results$table) -|Region |New confirmed cases by infection date |Expected change in daily cases |Effective reproduction no. |Rate of growth |Doubling/halving time (days) | -|:--------|:-------------------------------------|:------------------------------|:--------------------------|:----------------------|:----------------------------| -|realland |2137 (1071 -- 4099) |Likely decreasing |0.85 (0.6 -- 1.2) |-0.034 (-0.1 -- 0.034) |-20 (20 -- -6.9) | -|testland |2219 (1155 -- 4015) |Likely decreasing |0.87 (0.63 -- 1.1) |-0.03 (-0.093 -- 0.03) |-23 (23 -- -7.4) | +|Region |New confirmed cases by infection date |Expected change in daily cases |Effective reproduction no. |Rate of growth |Doubling/halving time (days) | +|:--------|:-------------------------------------|:------------------------------|:--------------------------|:------------------------|:----------------------------| +|realland |2160 (1134 -- 4105) |Likely decreasing |0.86 (0.62 -- 1.1) |-0.032 (-0.093 -- 0.03) |-22 (23 -- -7.5) | +|testland |2137 (1110 -- 4238) |Likely decreasing |0.86 (0.62 -- 1.2) |-0.032 (-0.097 -- 0.032) |-22 (22 -- -7.2) | A range of plots are again returned (with the single summary plot shown below). diff --git a/vignettes/epinow.Rmd b/vignettes/epinow.Rmd index ee6bb0524..31a3e3c04 100644 --- a/vignettes/epinow.Rmd +++ b/vignettes/epinow.Rmd @@ -46,13 +46,13 @@ res <- epinow(reported_cases, target_folder = "results" ) #> Logging threshold set at INFO for the EpiNow2 logger -#> Writing EpiNow2 logs to the console and: /tmp/RtmpBdeheM/regional-epinow/2020-04-21.log +#> Writing EpiNow2 logs to the console and: /var/folders/n9/h_419gjj2mg3d208nplgvbg40000gp/T//RtmpCLEtE0/regional-epinow/2020-04-21.log #> Logging threshold set at INFO for the EpiNow2.epinow logger -#> Writing EpiNow2.epinow logs to the console and: /tmp/RtmpBdeheM/epinow/2020-04-21.log -#> WARN [2023-11-30 15:22:43] epinow: There were 10 divergent transitions after warmup. See +#> Writing EpiNow2.epinow logs to the console and: /var/folders/n9/h_419gjj2mg3d208nplgvbg40000gp/T//RtmpCLEtE0/epinow/2020-04-21.log +#> WARN [2024-03-06 10:52:09] epinow: There were 9 divergent transitions after warmup. See #> https://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup #> to find out why this is a problem and how to eliminate them. - -#> WARN [2023-11-30 15:22:43] epinow: Examine the pairs() plot to diagnose sampling problems +#> WARN [2024-03-06 10:52:09] epinow: Examine the pairs() plot to diagnose sampling problems #> - res$plots$R #> NULL @@ -86,34 +86,37 @@ region_rt <- regional_epinow( delays = delay_opts(delay), rt = rt_opts(prior = rt_prior), ) -#> INFO [2023-11-30 15:22:50] Producing following optional outputs: regions, summary, samples, plots, latest +#> INFO [2024-03-06 10:52:13] Producing following optional outputs: regions, summary, samples, plots, latest #> Logging threshold set at INFO for the EpiNow2 logger -#> Writing EpiNow2 logs to the console and: /tmp/RtmpBdeheM/regional-epinow/2020-04-21.log +#> Writing EpiNow2 logs to the console and: /var/folders/n9/h_419gjj2mg3d208nplgvbg40000gp/T//RtmpCLEtE0/regional-epinow/2020-04-21.log #> Logging threshold set at INFO for the EpiNow2.epinow logger -#> Writing EpiNow2.epinow logs to: /tmp/RtmpBdeheM/epinow/2020-04-21.log -#> INFO [2023-11-30 15:22:50] Reporting estimates using data up to: 2020-04-21 -#> INFO [2023-11-30 15:22:50] No target directory specified so returning output -#> INFO [2023-11-30 15:22:50] Producing estimates for: testland, realland -#> INFO [2023-11-30 15:22:50] Regions excluded: none -#> INFO [2023-11-30 15:56:46] Completed estimates for: testland -#> INFO [2023-11-30 16:03:20] Completed estimates for: realland -#> INFO [2023-11-30 16:03:20] Completed regional estimates -#> INFO [2023-11-30 16:03:20] Regions with estimates: 2 -#> INFO [2023-11-30 16:03:20] Regions with runtime errors: 0 -#> INFO [2023-11-30 16:03:20] Producing summary -#> INFO [2023-11-30 16:03:20] No summary directory specified so returning summary output -#> INFO [2023-11-30 16:03:20] No target directory specified so returning timings +#> Writing EpiNow2.epinow logs to: /var/folders/n9/h_419gjj2mg3d208nplgvbg40000gp/T//RtmpCLEtE0/epinow/2020-04-21.log +#> INFO [2024-03-06 10:52:13] Reporting estimates using data up to: 2020-04-21 +#> INFO [2024-03-06 10:52:13] No target directory specified so returning output +#> INFO [2024-03-06 10:52:13] Producing estimates for: testland, realland +#> INFO [2024-03-06 10:52:13] Regions excluded: none +#> INFO [2024-03-06 10:52:48] Completed estimates for: testland +#> INFO [2024-03-06 10:53:17] Completed estimates for: realland +#> INFO [2024-03-06 10:53:17] Completed regional estimates +#> INFO [2024-03-06 10:53:17] Regions with estimates: 2 +#> INFO [2024-03-06 10:53:17] Regions with runtime errors: 0 +#> INFO [2024-03-06 10:53:17] Producing summary +#> INFO [2024-03-06 10:53:17] No summary directory specified so returning summary output +#> INFO [2024-03-06 10:53:17] No target directory specified so returning timings ## summary region_rt$summary$summarised_results$table #> Region New confirmed cases by infection date -#> 1: realland 2075 (865 -- 4051) -#> 2: testland 2481 (935 -- 7971) +#> +#> 1: realland 2254 (1153 -- 4243) +#> 2: testland 2261 (1059 -- 4347) #> Expected change in daily cases Effective reproduction no. -#> 1: Likely decreasing 0.88 (0.6 -- 1.1) -#> 2: Stable 0.94 (0.62 -- 1.3) -#> Rate of growth Doubling/halving time (days) -#> 1: -0.036 (-0.14 -- 0.036) -19 (19 -- -5) -#> 2: -0.016 (-0.13 -- 0.045) -44 (15 -- -5.3) +#> +#> 1: Likely decreasing 0.87 (0.6 -- 1.2) +#> 2: Likely decreasing 0.88 (0.6 -- 1.2) +#> Rate of growth Doubling/halving time (days) +#> +#> 1: -0.028 (-0.1 -- 0.034) -24 (20 -- -6.9) +#> 2: -0.027 (-0.1 -- 0.037) -25 (19 -- -6.8) ## plot region_rt$summary$plots$R ``` @@ -133,34 +136,37 @@ region_separate_rt <- regional_epinow( delays = delay_opts(delay), rt = rt, gp = gp, ) -#> INFO [2023-11-30 16:03:21] Producing following optional outputs: regions, summary, samples, plots, latest +#> INFO [2024-03-06 10:53:17] Producing following optional outputs: regions, summary, samples, plots, latest #> Logging threshold set at INFO for the EpiNow2 logger -#> Writing EpiNow2 logs to the console and: /tmp/RtmpBdeheM/regional-epinow/2020-04-21.log +#> Writing EpiNow2 logs to the console and: /var/folders/n9/h_419gjj2mg3d208nplgvbg40000gp/T//RtmpCLEtE0/regional-epinow/2020-04-21.log #> Logging threshold set at INFO for the EpiNow2.epinow logger -#> Writing EpiNow2.epinow logs to: /tmp/RtmpBdeheM/epinow/2020-04-21.log -#> INFO [2023-11-30 16:03:21] Reporting estimates using data up to: 2020-04-21 -#> INFO [2023-11-30 16:03:21] No target directory specified so returning output -#> INFO [2023-11-30 16:03:21] Producing estimates for: testland, realland -#> INFO [2023-11-30 16:03:21] Regions excluded: none -#> INFO [2023-11-30 16:05:12] Completed estimates for: testland -#> INFO [2023-11-30 16:05:44] Completed estimates for: realland -#> INFO [2023-11-30 16:05:44] Completed regional estimates -#> INFO [2023-11-30 16:05:44] Regions with estimates: 2 -#> INFO [2023-11-30 16:05:44] Regions with runtime errors: 0 -#> INFO [2023-11-30 16:05:44] Producing summary -#> INFO [2023-11-30 16:05:44] No summary directory specified so returning summary output -#> INFO [2023-11-30 16:05:44] No target directory specified so returning timings +#> Writing EpiNow2.epinow logs to: /var/folders/n9/h_419gjj2mg3d208nplgvbg40000gp/T//RtmpCLEtE0/epinow/2020-04-21.log +#> INFO [2024-03-06 10:53:17] Reporting estimates using data up to: 2020-04-21 +#> INFO [2024-03-06 10:53:17] No target directory specified so returning output +#> INFO [2024-03-06 10:53:17] Producing estimates for: testland, realland +#> INFO [2024-03-06 10:53:17] Regions excluded: none +#> INFO [2024-03-06 10:53:50] Completed estimates for: testland +#> INFO [2024-03-06 10:53:59] Completed estimates for: realland +#> INFO [2024-03-06 10:53:59] Completed regional estimates +#> INFO [2024-03-06 10:53:59] Regions with estimates: 2 +#> INFO [2024-03-06 10:53:59] Regions with runtime errors: 0 +#> INFO [2024-03-06 10:53:59] Producing summary +#> INFO [2024-03-06 10:53:59] No summary directory specified so returning summary output +#> INFO [2024-03-06 10:54:00] No target directory specified so returning timings ## summary region_separate_rt$summary$summarised_results$table #> Region New confirmed cases by infection date -#> 1: realland 2001 (956 -- 4028) -#> 2: testland 2048 (901 -- 4080) +#> +#> 1: realland 2122 (1144 -- 3976) +#> 2: testland 2177 (992 -- 4216) #> Expected change in daily cases Effective reproduction no. -#> 1: Likely decreasing 0.88 (0.66 -- 1.2) -#> 2: Likely decreasing 0.88 (0.61 -- 1.2) -#> Rate of growth Doubling/halving time (days) -#> 1: -0.035 (-0.12 -- 0.042) -20 (16 -- -6) -#> 2: -0.036 (-0.13 -- 0.04) -19 (17 -- -5.2) +#> +#> 1: Likely decreasing 0.85 (0.61 -- 1.2) +#> 2: Likely decreasing 0.86 (0.54 -- 1.2) +#> Rate of growth Doubling/halving time (days) +#> +#> 1: -0.033 (-0.094 -- 0.031) -21 (22 -- -7.3) +#> 2: -0.031 (-0.11 -- 0.034) -22 (20 -- -6.1) ## plot region_separate_rt$summary$plots$R ``` diff --git a/vignettes/estimate_infections_options.Rmd b/vignettes/estimate_infections_options.Rmd index fe39d08ba..5a76749ac 100644 --- a/vignettes/estimate_infections_options.Rmd +++ b/vignettes/estimate_infections_options.Rmd @@ -28,13 +28,13 @@ We first load the _EpiNow2_ package and also the _rstan_ package that we will us library("EpiNow2") #> #> Attaching package: 'EpiNow2' -#> The following object is masked from 'package:base': +#> The following object is masked from 'package:stats': #> -#> gamma +#> Gamma library("rstan") #> Loading required package: StanHeaders #> -#> rstan version 2.32.3 (Stan version 2.26.1) +#> rstan version 2.32.6 (Stan version 2.32.2) #> For execution on a local, multicore CPU with excess RAM we recommend calling #> options(mc.cores = parallel::detectCores()). #> To avoid recompilation of unchanged Stan programs, we recommend calling @@ -79,8 +79,19 @@ Delays reflect the time that passes between infection and reporting, if these ex ```r example_incubation_period -#> -#> lognormal distribution (max: 14) with uncertain meanlog (mean = 1.6, sd = 0.064) and uncertain sdlog (mean = 0.42, sd = 0.069). +#> - lognormal distribution (max: 14): +#> meanlog: +#> - normal distribution: +#> mean: +#> 1.6 +#> sd: +#> 0.064 +#> sdlog: +#> - normal distribution: +#> mean: +#> 0.42 +#> sd: +#> 0.069 ``` For the reporting delay, we use a lognormal distribution with mean of 2 days and standard deviation of 1 day. @@ -89,11 +100,12 @@ Note that the mean and standard deviation must be converted to the log scale, wh ```r reporting_delay <- LogNormal(mean = 2, sd = 1, max = 10) -#> Warning: The meaning of the 'max' argument has changed compared to previous versions. It now indicates the maximum of a distribution rather than the length of the probability mass function (including 0) that it represented previously. To replicate previous behaviour reduce max by 1. -#> This warning is displayed once every 8 hours. reporting_delay -#> -#> distribution with PMF [0.11 0.48 0.27 0.093 0.029 0.0096 0.0033 0.0012 0.00045 0.00018 7.4e-05]. +#> - lognormal distribution (max: 10): +#> meanlog: +#> 0.58 +#> sdlog: +#> 0.47 ``` _EpiNow2_ provides a feature that allows us to combine these delays into one by summing them up @@ -102,10 +114,25 @@ _EpiNow2_ provides a feature that allows us to combine these delays into one by ```r delay <- example_incubation_period + reporting_delay delay -#> -#> Composite delay distribution: -#> lognormal distribution (max: 14) with uncertain meanlog (mean = 1.6, sd = 0.064) and uncertain sdlog (mean = 0.42, sd = 0.069). -#> distribution with PMF [0.11 0.48 0.27 0.093 0.029 0.0096 0.0033 0.0012 0.00045 0.00018 7.4e-05]. +#> Composite distribution: +#> - lognormal distribution (max: 14): +#> meanlog: +#> - normal distribution: +#> mean: +#> 1.6 +#> sd: +#> 0.064 +#> sdlog: +#> - normal distribution: +#> mean: +#> 0.42 +#> sd: +#> 0.069 +#> - lognormal distribution (max: 10): +#> meanlog: +#> 0.58 +#> sdlog: +#> 0.47 ``` ## Generation time @@ -115,8 +142,19 @@ If we want to estimate the reproduction number we need to provide a distribution ```r example_generation_time -#> -#> gamma distribution (max: 14) with uncertain shape (mean = 1.9, sd = 2.2) and uncertain rate (mean = 0.51, sd = 0.54). +#> - gamma distribution (max: 14): +#> shape: +#> - normal distribution: +#> mean: +#> 1.4 +#> sd: +#> 0.48 +#> rate: +#> - normal distribution: +#> mean: +#> 0.38 +#> sd: +#> 0.25 ``` ## Initial reproduction number @@ -144,25 +182,26 @@ def <- estimate_infections(reported_cases, delays = delay_opts(delay), rt = rt_opts(prior = rt_prior) ) -#> Warning: There were 2 divergent transitions after warmup. See +#> Warning: There were 4 divergent transitions after warmup. See #> https://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup #> to find out why this is a problem and how to eliminate them. #> Warning: Examine the pairs() plot to diagnose sampling problems # summarise results summary(def) #> measure estimate -#> 1: New confirmed cases by infection date 2272 (1082 -- 4222) +#> +#> 1: New confirmed cases by infection date 2271 (1111 -- 4285) #> 2: Expected change in daily cases Likely decreasing -#> 3: Effective reproduction no. 0.89 (0.61 -- 1.2) +#> 3: Effective reproduction no. 0.88 (0.6 -- 1.2) #> 4: Rate of growth -0.027 (-0.1 -- 0.037) -#> 5: Doubling/halving time (days) -26 (19 -- -6.7) +#> 5: Doubling/halving time (days) -25 (19 -- -6.9) # elapsed time (in seconds) get_elapsed_time(def$fit) #> warmup sample -#> chain:1 39.631 49.732 -#> chain:2 32.870 44.510 -#> chain:3 37.056 45.843 -#> chain:4 41.190 41.020 +#> chain:1 11.075 14.604 +#> chain:2 13.366 9.757 +#> chain:3 13.132 13.092 +#> chain:4 13.467 17.969 # summary plot plot(def) ``` @@ -181,25 +220,26 @@ agp <- estimate_infections(reported_cases, rt = rt_opts(prior = rt_prior), gp = gp_opts(basis_prop = 0.1) ) -#> Warning: There were 10 divergent transitions after warmup. See +#> Warning: There were 4 divergent transitions after warmup. See #> https://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup #> to find out why this is a problem and how to eliminate them. #> Warning: Examine the pairs() plot to diagnose sampling problems # summarise results summary(agp) #> measure estimate -#> 1: New confirmed cases by infection date 2318 (1221 -- 4292) +#> +#> 1: New confirmed cases by infection date 2306 (1175 -- 4321) #> 2: Expected change in daily cases Likely decreasing -#> 3: Effective reproduction no. 0.9 (0.66 -- 1.2) -#> 4: Rate of growth -0.024 (-0.092 -- 0.036) -#> 5: Doubling/halving time (days) -29 (19 -- -7.5) +#> 3: Effective reproduction no. 0.88 (0.63 -- 1.2) +#> 4: Rate of growth -0.026 (-0.093 -- 0.034) +#> 5: Doubling/halving time (days) -26 (20 -- -7.5) # elapsed time (in seconds) get_elapsed_time(agp$fit) #> warmup sample -#> chain:1 21.668 45.690 -#> chain:2 20.766 22.758 -#> chain:3 19.043 35.899 -#> chain:4 18.513 45.408 +#> chain:1 7.821 9.160 +#> chain:2 8.874 11.466 +#> chain:3 10.379 14.372 +#> chain:4 6.943 12.677 # summary plot plot(agp) ``` @@ -222,25 +262,26 @@ dep <- estimate_infections(reported_cases, pop = 1000000, future = "latest" ) ) -#> Warning: There were 24 divergent transitions after warmup. See +#> Warning: There were 12 divergent transitions after warmup. See #> https://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup #> to find out why this is a problem and how to eliminate them. #> Warning: Examine the pairs() plot to diagnose sampling problems # summarise results summary(dep) -#> measure estimate -#> 1: New confirmed cases by infection date 2259 (1106 -- 4245) -#> 2: Expected change in daily cases Likely decreasing -#> 3: Effective reproduction no. 0.88 (0.61 -- 1.2) -#> 4: Rate of growth -0.027 (-0.11 -- 0.035) -#> 5: Doubling/halving time (days) -25 (20 -- -6.5) +#> measure estimate +#> +#> 1: New confirmed cases by infection date 2329 (1146 -- 4415) +#> 2: Expected change in daily cases Likely decreasing +#> 3: Effective reproduction no. 0.89 (0.62 -- 1.2) +#> 4: Rate of growth -0.026 (-0.094 -- 0.037) +#> 5: Doubling/halving time (days) -27 (19 -- -7.4) # elapsed time (in seconds) get_elapsed_time(dep$fit) #> warmup sample -#> chain:1 26.983 25.015 -#> chain:2 32.689 25.745 -#> chain:3 34.598 24.593 -#> chain:4 33.245 25.095 +#> chain:1 13.161 9.823 +#> chain:2 12.282 14.130 +#> chain:3 14.255 18.819 +#> chain:4 10.584 9.753 # summary plot plot(dep) ``` @@ -255,21 +296,29 @@ Here, instead of doing so we assume that we know about truncation with mean of 1 ```r trunc_dist <- LogNormal( - mean = normal(0.5, 0.1), - sd = normal(0.5, 0.1), + mean = Normal(0.5, 0.1), + sd = Normal(0.5, 0.1), max = 3 ) -#> Warning in generate_dist_spec(params, "lognormal"): Uncertain lognormal -#> distribution specified in terms of parameters that are not the "natural" -#> parameters of the distribution (meanlog, sdlog). Converting using a crude and -#> very approximate method that is likely to produce biased results. If possible, -#> it is preferable to specify the distribution direclty in terms of the natural -#> parameters. -#> Warning in sqrt(natural_means * rel_unc): NaNs produced +#> Warning in new_dist_spec(params, "lognormal"): Uncertain lognormal distribution +#> specified in terms of parameters that are not the "natural" parameters of the +#> distribution (meanlog, sdlog). Converting using a crude and very approximate +#> method that is likely to produce biased results. If possible, it is preferable +#> to specify the distribution directly in terms of the natural parameters. trunc_dist -#> -#> lognormal distribution (max: 3) with -#> Error in if (x$params_sd[pos] > 0) {: missing value where TRUE/FALSE needed +#> - lognormal distribution (max: 3): +#> meanlog: +#> - normal distribution: +#> mean: +#> -1 +#> sd: +#> 0.14 +#> sdlog: +#> - normal distribution: +#> mean: +#> 0.83 +#> sd: +#> 0.13 ``` We can then use this in the `esimtate_infections()` function using the `truncation` option. @@ -282,17 +331,26 @@ trunc <- estimate_infections(reported_cases, truncation = trunc_opts(trunc_dist), rt = rt_opts(prior = rt_prior) ) -#> Error in FUN(X[[i]], ...) : -#> Stan does not support NA (in delay_params_sd) in data -#> failed to preprocess the data; sampling not done -#> Error in `fit_model_with_nuts()`: -#> ! model fitting was timed out or failed +#> Warning: There were 11 divergent transitions after warmup. See +#> https://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup +#> to find out why this is a problem and how to eliminate them. +#> Warning: Examine the pairs() plot to diagnose sampling problems # summarise results summary(trunc) -#> Error in object[[i]]: object of type 'builtin' is not subsettable +#> measure estimate +#> +#> 1: New confirmed cases by infection date 2485 (1252 -- 4790) +#> 2: Expected change in daily cases Likely decreasing +#> 3: Effective reproduction no. 0.91 (0.65 -- 1.2) +#> 4: Rate of growth -0.019 (-0.087 -- 0.045) +#> 5: Doubling/halving time (days) -36 (15 -- -7.9) # elapsed time (in seconds) get_elapsed_time(trunc$fit) -#> Error in (function (cond) : error in evaluating the argument 'object' in selecting a method for function 'get_elapsed_time': object of type 'builtin' is not subsettable +#> warmup sample +#> chain:1 11.657 9.733 +#> chain:2 16.154 9.816 +#> chain:3 16.801 13.905 +#> chain:4 12.173 10.649 # summary plot plot(trunc) ``` @@ -313,25 +371,26 @@ project_rt <- estimate_infections(reported_cases, prior = rt_prior, future = "project" ) ) -#> Warning: There were 20 divergent transitions after warmup. See +#> Warning: There were 19 divergent transitions after warmup. See #> https://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup #> to find out why this is a problem and how to eliminate them. #> Warning: Examine the pairs() plot to diagnose sampling problems # summarise results summary(project_rt) -#> measure estimate -#> 1: New confirmed cases by infection date 2245 (1119 -- 4319) -#> 2: Expected change in daily cases Likely decreasing -#> 3: Effective reproduction no. 0.89 (0.61 -- 1.2) -#> 4: Rate of growth -0.026 (-0.1 -- 0.039) -#> 5: Doubling/halving time (days) -26 (18 -- -6.7) +#> measure estimate +#> +#> 1: New confirmed cases by infection date 2285 (1145 -- 4321) +#> 2: Expected change in daily cases Likely decreasing +#> 3: Effective reproduction no. 0.89 (0.61 -- 1.2) +#> 4: Rate of growth -0.025 (-0.099 -- 0.039) +#> 5: Doubling/halving time (days) -28 (18 -- -7) # elapsed time (in seconds) get_elapsed_time(project_rt$fit) #> warmup sample -#> chain:1 35.447 34.177 -#> chain:2 33.563 30.859 -#> chain:3 31.365 24.099 -#> chain:4 34.837 45.162 +#> chain:1 14.177 17.887 +#> chain:2 13.982 9.758 +#> chain:3 11.849 9.622 +#> chain:4 16.444 13.904 # summary plot plot(project_rt) ``` @@ -351,19 +410,20 @@ fixed <- estimate_infections(reported_cases, ) # summarise results summary(fixed) -#> measure estimate -#> 1: New confirmed cases by infection date 15440 (8847 -- 27843) -#> 2: Expected change in daily cases Increasing -#> 3: Effective reproduction no. 1.2 (1.1 -- 1.3) -#> 4: Rate of growth 0.037 (0.026 -- 0.05) -#> 5: Doubling/halving time (days) 19 (14 -- 27) +#> measure estimate +#> +#> 1: New confirmed cases by infection date 15887 (9181 -- 28140) +#> 2: Expected change in daily cases Increasing +#> 3: Effective reproduction no. 1.2 (1.1 -- 1.3) +#> 4: Rate of growth 0.038 (0.027 -- 0.049) +#> 5: Doubling/halving time (days) 18 (14 -- 26) # elapsed time (in seconds) get_elapsed_time(fixed$fit) #> warmup sample -#> chain:1 1.129 1.270 -#> chain:2 1.443 1.295 -#> chain:3 1.569 1.252 -#> chain:4 1.571 1.244 +#> chain:1 0.666 0.524 +#> chain:2 0.671 0.398 +#> chain:3 0.706 0.425 +#> chain:4 0.551 0.514 # summary plot plot(fixed) ``` @@ -396,19 +456,20 @@ bkp <- estimate_infections(bp_cases, ) # summarise results summary(bkp) -#> measure estimate -#> 1: New confirmed cases by infection date 2577 (2146 -- 3130) -#> 2: Expected change in daily cases Decreasing -#> 3: Effective reproduction no. 0.9 (0.88 -- 0.93) -#> 4: Rate of growth -0.019 (-0.025 -- -0.013) -#> 5: Doubling/halving time (days) -36 (-52 -- -28) +#> measure estimate +#> +#> 1: New confirmed cases by infection date 2537 (2117 -- 3067) +#> 2: Expected change in daily cases Decreasing +#> 3: Effective reproduction no. 0.91 (0.88 -- 0.93) +#> 4: Rate of growth -0.02 (-0.025 -- -0.014) +#> 5: Doubling/halving time (days) -35 (-50 -- -28) # elapsed time (in seconds) get_elapsed_time(bkp$fit) #> warmup sample -#> chain:1 2.585 3.471 -#> chain:2 3.000 5.255 -#> chain:3 7.665 4.073 -#> chain:4 3.232 5.177 +#> chain:1 1.301 1.325 +#> chain:2 1.147 1.201 +#> chain:3 1.710 1.384 +#> chain:4 0.961 1.147 # summary plot plot(bkp) ``` @@ -431,18 +492,19 @@ rw <- estimate_infections(reported_cases, # summarise results summary(rw) #> measure estimate -#> 1: New confirmed cases by infection date 2105 (1075 -- 3960) +#> +#> 1: New confirmed cases by infection date 2182 (1103 -- 4267) #> 2: Expected change in daily cases Likely decreasing -#> 3: Effective reproduction no. 0.86 (0.64 -- 1.1) -#> 4: Rate of growth -0.034 (-0.099 -- 0.032) -#> 5: Doubling/halving time (days) -20 (22 -- -7) +#> 3: Effective reproduction no. 0.87 (0.62 -- 1.2) +#> 4: Rate of growth -0.031 (-0.097 -- 0.032) +#> 5: Doubling/halving time (days) -22 (21 -- -7.1) # elapsed time (in seconds) get_elapsed_time(rw$fit) #> warmup sample -#> chain:1 7.975 10.738 -#> chain:2 8.867 10.287 -#> chain:3 7.698 10.673 -#> chain:4 9.396 11.083 +#> chain:1 2.500 3.987 +#> chain:2 2.341 4.075 +#> chain:3 2.303 3.118 +#> chain:4 2.235 3.873 # summary plot plot(rw) ``` @@ -459,25 +521,26 @@ no_delay <- estimate_infections( reported_cases, generation_time = generation_time_opts(example_generation_time) ) -#> Warning: There were 3 divergent transitions after warmup. See +#> Warning: There were 5 divergent transitions after warmup. See #> https://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup #> to find out why this is a problem and how to eliminate them. #> Warning: Examine the pairs() plot to diagnose sampling problems # summarise results summary(no_delay) #> measure estimate -#> 1: New confirmed cases by infection date 2773 (2338 -- 3307) +#> +#> 1: New confirmed cases by infection date 2776 (2336 -- 3311) #> 2: Expected change in daily cases Decreasing -#> 3: Effective reproduction no. 0.89 (0.78 -- 0.99) -#> 4: Rate of growth -0.026 (-0.056 -- -0.0025) -#> 5: Doubling/halving time (days) -26 (-280 -- -12) +#> 3: Effective reproduction no. 0.88 (0.77 -- 0.99) +#> 4: Rate of growth -0.028 (-0.055 -- -0.0034) +#> 5: Doubling/halving time (days) -25 (-200 -- -13) # elapsed time (in seconds) get_elapsed_time(no_delay$fit) #> warmup sample -#> chain:1 42.074 39.484 -#> chain:2 35.120 44.165 -#> chain:3 36.850 70.171 -#> chain:4 39.259 44.068 +#> chain:1 17.540 15.429 +#> chain:2 20.581 19.910 +#> chain:3 16.588 28.510 +#> chain:4 15.363 17.303 # summary plot plot(no_delay) ``` @@ -502,19 +565,20 @@ non_parametric <- estimate_infections(reported_cases, ) # summarise results summary(non_parametric) -#> measure estimate -#> 1: New confirmed cases by infection date 2366 (1813 -- 3047) -#> 2: Expected change in daily cases Decreasing -#> 3: Effective reproduction no. 0.9 (0.68 -- 0.99) -#> 4: Rate of growth -0.022 (-0.044 -- -0.0026) -#> 5: Doubling/halving time (days) -32 (-270 -- -16) +#> measure estimate +#> +#> 1: New confirmed cases by infection date 2306 (1696 -- 3051) +#> 2: Expected change in daily cases Decreasing +#> 3: Effective reproduction no. 0.89 (0.72 -- 0.99) +#> 4: Rate of growth -0.024 (-0.05 -- -0.0025) +#> 5: Doubling/halving time (days) -29 (-280 -- -14) # elapsed time (in seconds) get_elapsed_time(non_parametric$fit) #> warmup sample -#> chain:1 2.770 0.883 -#> chain:2 3.029 0.813 -#> chain:3 3.299 0.865 -#> chain:4 3.036 0.644 +#> chain:1 0.950 0.325 +#> chain:2 1.007 0.331 +#> chain:3 0.996 0.332 +#> chain:4 0.958 0.332 # summary plot plot(non_parametric) ``` diff --git a/vignettes/estimate_infections_workflow.Rmd b/vignettes/estimate_infections_workflow.Rmd index 7e1b9b88f..875cded97 100644 --- a/vignettes/estimate_infections_workflow.Rmd +++ b/vignettes/estimate_infections_workflow.Rmd @@ -30,6 +30,7 @@ An example data set called `example_confirm` is included in the package: ```r head(example_confirmed) #> date confirm +#> #> 1: 2020-02-22 14 #> 2: 2020-02-23 62 #> 3: 2020-02-24 53 @@ -83,8 +84,11 @@ For example, to define a fixed gamma distribution with mean 3, standard deviatio ```r Gamma(mean = 3, sd = 1, max = 10) -#> -#> distribution with PMF [0.0038 0.15 0.39 0.3 0.12 0.03 0.006 0.00096 0.00013 1.6e-05 1.8e-06]. +#> - gamma distribution (max: 10): +#> shape: +#> 9 +#> rate: +#> 3 ``` If distributions are variable, the values with uncertainty are treated as [prior probability densities](https://en.wikipedia.org/wiki/Prior_probability) in the Bayesian inference framework used by _EpiNow2_, i.e. they are estimated as part of the inference. @@ -93,13 +97,24 @@ For example, to define a variable gamma distribution where uncertainty in the me ```r Gamma(mean = Normal(3, 2), sd = Normal(1, 0.1), max = 10) -#> Warning in generate_dist_spec(params, "gamma"): Uncertain gamma distribution +#> Warning in new_dist_spec(params, "gamma"): Uncertain gamma distribution #> specified in terms of parameters that are not the "natural" parameters of the #> distribution (shape, rate). Converting using a crude and very approximate #> method that is likely to produce biased results. If possible, it is preferable -#> to specify the distribution direclty in terms of the natural parameters. -#> -#> gamma distribution (max: 10) with uncertain shape (mean = 9, sd = 2.5) and uncertain rate (mean = 3, sd = 1.4). +#> to specify the distribution directly in terms of the natural parameters. +#> - gamma distribution (max: 10): +#> shape: +#> - normal distribution: +#> mean: +#> 9 +#> sd: +#> 2.5 +#> rate: +#> - normal distribution: +#> mean: +#> 3 +#> sd: +#> 1.4 ``` Note the warning about parameters. @@ -144,10 +159,25 @@ incubation_period <- LogNormal( ) reporting_delay <- LogNormal(meanlog = 0.5, sdlog = 0.5, max = 10) incubation_period + reporting_delay -#> -#> Composite delay distribution: -#> lognormal distribution (max: 14) with uncertain meanlog (mean = 1.6, sd = 0.05) and uncertain sdlog (mean = 0.5, sd = 0.05). -#> distribution with PMF [0.16 0.49 0.23 0.077 0.025 0.0084 0.003 0.0011 0.00045 0.00019 8.2e-05]. +#> Composite distribution: +#> - lognormal distribution (max: 14): +#> meanlog: +#> - normal distribution: +#> mean: +#> 1.6 +#> sd: +#> 0.05 +#> sdlog: +#> - normal distribution: +#> mean: +#> 0.5 +#> sd: +#> 0.05 +#> - lognormal distribution (max: 10): +#> meanlog: +#> 0.5 +#> sdlog: +#> 0.5 ``` In _EpiNow2_, the reporting delay distribution is defined by a call to `delay_opts()`, a function that takes a single argument defined as a `dist_spec` object (returned by `LogNormal()`, `Gamma()` etc.). diff --git a/vignettes/figure/bp-1.png b/vignettes/figure/bp-1.png index f40a85c25d5e78036582379de299741eea2dc75a..f1beee16e52ae2e6c0ccc9e143bc02ae8f36d3e8 100644 GIT binary patch literal 66069 zcmcF~Wm_CUw=DsJyF<{x;7)K01a}5^cXxLSPH=Y!?(XjHGPt|DU2^U@@40{Ae(2|^ zsp+n++PkWHueDc&%E^c#!r{Szfq@~4iwOb2z`o4=yI`O`YXT^iEy2Jbk<5PmlC$_F z`pd@B#$Lfz&%j93$lA!>%m64V2nNOx8L6aYim!yhm)2ZMLpBjGS6CQ}^v)VzX9=7R zTseFu(Q*<;@3DgPXU%u`1bgrCT5D%;`-Zwscn4DC|iGKOL7PM5xG4g%e2<#oRzedX! zQs89>c2WNkwvXE~op>9qw;oIdClmRyW-{du^KTttTFR1$_rBHN&X6V5m#a}c 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