diff --git a/dev/pkgdown.yml b/dev/pkgdown.yml index f53753dab..e06cf743c 100644 --- a/dev/pkgdown.yml +++ b/dev/pkgdown.yml @@ -10,7 +10,7 @@ articles: estimate_secondary: estimate_secondary.html estimate_truncation: estimate_truncation.html gaussian_process_implementation_details: gaussian_process_implementation_details.html -last_built: 2023-11-16T22:51Z +last_built: 2023-11-17T10:51Z urls: reference: epiforecasts.io/EpiNow2/reference article: epiforecasts.io/EpiNow2/articles diff --git a/dev/reference/adjust_infection_to_report.html b/dev/reference/adjust_infection_to_report.html index d61b2c54a..48c717760 100644 --- a/dev/reference/adjust_infection_to_report.html +++ b/dev/reference/adjust_infection_to_report.html @@ -166,17 +166,17 @@

Examples) print(report) #> date cases -#> 1: 2020-02-27 6 -#> 2: 2020-02-28 13 -#> 3: 2020-02-29 17 -#> 4: 2020-03-01 25 -#> 5: 2020-03-02 39 +#> 1: 2020-02-25 1 +#> 2: 2020-02-26 2 +#> 3: 2020-02-27 6 +#> 4: 2020-02-28 8 +#> 5: 2020-02-29 23 #> --- -#> 121: 2020-06-26 253 -#> 122: 2020-06-27 267 -#> 123: 2020-06-28 225 -#> 124: 2020-06-29 243 -#> 125: 2020-06-30 278 +#> 123: 2020-06-26 292 +#> 124: 2020-06-27 278 +#> 125: 2020-06-28 232 +#> 126: 2020-06-29 268 +#> 127: 2020-06-30 270 # mapping with a weekly reporting effect report_weekly <- adjust_infection_to_report( @@ -187,16 +187,16 @@

Examplesprint(report_weekly) #> date cases #> 1: 2020-02-26 1 -#> 2: 2020-02-27 3 -#> 3: 2020-02-28 7 -#> 4: 2020-02-29 16 -#> 5: 2020-03-01 28 +#> 2: 2020-02-27 4 +#> 3: 2020-02-28 10 +#> 4: 2020-02-29 15 +#> 5: 2020-03-01 22 #> --- -#> 122: 2020-06-26 275 -#> 123: 2020-06-27 248 -#> 124: 2020-06-28 257 -#> 125: 2020-06-29 246 -#> 126: 2020-06-30 265 +#> 122: 2020-06-26 273 +#> 123: 2020-06-27 226 +#> 124: 2020-06-28 214 +#> 125: 2020-06-29 262 +#> 126: 2020-06-30 228 # map using a deterministic median shift for both delays report_median <- adjust_infection_to_report(cases, @@ -229,17 +229,17 @@

Examples) print(report_stochastic) #> date cases -#> 1: 2020-02-27 7 -#> 2: 2020-02-28 8 -#> 3: 2020-02-29 15 -#> 4: 2020-03-01 21 -#> 5: 2020-03-02 29 +#> 1: 2020-02-26 1 +#> 2: 2020-02-27 13 +#> 3: 2020-02-28 5 +#> 4: 2020-02-29 26 +#> 5: 2020-03-01 41 #> --- -#> 121: 2020-06-26 285 -#> 122: 2020-06-27 232 -#> 123: 2020-06-28 216 -#> 124: 2020-06-29 270 -#> 125: 2020-06-30 241 +#> 122: 2020-06-26 249 +#> 123: 2020-06-27 256 +#> 124: 2020-06-28 263 +#> 125: 2020-06-29 267 +#> 126: 2020-06-30 237 # } diff --git a/dev/reference/bootstrapped_dist_fit.html b/dev/reference/bootstrapped_dist_fit.html index 018711278..b6fb736db 100644 --- a/dev/reference/bootstrapped_dist_fit.html +++ b/dev/reference/bootstrapped_dist_fit.html @@ -177,7 +177,7 @@

Examples#> This warning is displayed once every 8 hours. out #> -#> Uncertain lognormal distribution with (untruncated) logmean 1.4 (SD 0.11) and logSD 1.2 (SD 0.085) +#> Uncertain lognormal distribution with (untruncated) logmean 1.5 (SD 0.099) and logSD 1.1 (SD 0.071) #> # } diff --git a/dev/reference/create_stan_args.html b/dev/reference/create_stan_args.html index bbd94997c..917d9a904 100644 --- a/dev/reference/create_stan_args.html +++ b/dev/reference/create_stan_args.html @@ -971,7 +971,7 @@

Examples#> [1] FALSE #> #> $seed -#> [1] 43571636 +#> [1] 64493168 #> #> $future #> [1] FALSE @@ -1833,7 +1833,7 @@

Examples#> [1] FALSE #> #> $seed -#> [1] 35759370 +#> [1] 17128374 #> #> $future #> [1] FALSE diff --git a/dev/reference/dist_fit.html b/dev/reference/dist_fit.html index 8251907dc..93292cb76 100644 --- a/dev/reference/dist_fit.html +++ b/dev/reference/dist_fit.html @@ -144,8 +144,8 @@

Examples#> #> SAMPLING FOR MODEL 'dist_fit' NOW (CHAIN 1). #> Chain 1: -#> Chain 1: Gradient evaluation took 4.1e-05 seconds -#> Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.41 seconds. +#> Chain 1: Gradient evaluation took 4.2e-05 seconds +#> Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.42 seconds. #> Chain 1: Adjust your expectations accordingly! #> Chain 1: #> Chain 1: @@ -192,21 +192,15 @@

Examples#> Chain 1: Iteration: 1950 / 2000 [ 97%] (Sampling) #> Chain 1: Iteration: 2000 / 2000 [100%] (Sampling) #> Chain 1: -#> Chain 1: Elapsed Time: 0.148 seconds (Warm-up) -#> Chain 1: 0.158 seconds (Sampling) -#> Chain 1: 0.306 seconds (Total) +#> Chain 1: Elapsed Time: 0.144 seconds (Warm-up) +#> Chain 1: 0.155 seconds (Sampling) +#> Chain 1: 0.299 seconds (Total) #> Chain 1: #> #> SAMPLING FOR MODEL 'dist_fit' NOW (CHAIN 2). -#> Chain 2: Rejecting initial value: -#> Chain 2: Log probability evaluates to log(0), i.e. negative infinity. -#> Chain 2: Stan can't start sampling from this initial value. -#> Chain 2: Rejecting initial value: -#> Chain 2: Log probability evaluates to log(0), i.e. negative infinity. -#> Chain 2: Stan can't start sampling from this initial value. #> Chain 2: -#> Chain 2: Gradient evaluation took 3.9e-05 seconds -#> Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 0.39 seconds. +#> Chain 2: Gradient evaluation took 3.8e-05 seconds +#> Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 0.38 seconds. #> Chain 2: Adjust your expectations accordingly! #> Chain 2: #> Chain 2: @@ -254,18 +248,18 @@

Examples#> Chain 2: Iteration: 2000 / 2000 [100%] (Sampling) #> Chain 2: #> Chain 2: Elapsed Time: 0.142 seconds (Warm-up) -#> Chain 2: 0.151 seconds (Sampling) -#> Chain 2: 0.293 seconds (Total) +#> Chain 2: 0.161 seconds (Sampling) +#> Chain 2: 0.303 seconds (Total) #> Chain 2: #> Inference for Stan model: dist_fit. #> 2 chains, each with iter=2000; warmup=1000; thin=1; #> post-warmup draws per chain=1000, total post-warmup draws=2000. #> -#> mean se_mean sd 2.5% 25% 50% 75% 97.5% n_eff Rhat -#> lambda[1] 2.39 0.01 0.35 1.8 2.14 2.36 2.61 3.17 744 1 -#> lp__ -20.05 0.02 0.67 -22.0 -20.21 -19.80 -19.62 -19.57 737 1 +#> mean se_mean sd 2.5% 25% 50% 75% 97.5% n_eff Rhat +#> lambda[1] 2.15 0.01 0.29 1.63 1.94 2.13 2.34 2.75 663 1 +#> lp__ -25.11 0.03 0.64 -26.87 -25.30 -24.86 -24.68 -24.63 566 1 #> -#> Samples were drawn using NUTS(diag_e) at Thu Nov 16 22:52:41 2023. +#> Samples were drawn using NUTS(diag_e) at Fri Nov 17 10:52:48 2023. #> For each parameter, n_eff is a crude measure of effective sample size, #> and Rhat is the potential scale reduction factor on split chains (at #> convergence, Rhat=1). @@ -279,8 +273,8 @@

Examples#> #> SAMPLING FOR MODEL 'dist_fit' NOW (CHAIN 1). #> Chain 1: -#> Chain 1: Gradient evaluation took 0.00022 seconds -#> Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.2 seconds. +#> Chain 1: Gradient evaluation took 0.000231 seconds +#> Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.31 seconds. #> Chain 1: Adjust your expectations accordingly! #> Chain 1: #> Chain 1: @@ -327,15 +321,15 @@

Examples#> Chain 1: Iteration: 1950 / 2000 [ 97%] (Sampling) #> Chain 1: Iteration: 2000 / 2000 [100%] (Sampling) #> Chain 1: -#> Chain 1: Elapsed Time: 1.902 seconds (Warm-up) -#> Chain 1: 2.41 seconds (Sampling) -#> Chain 1: 4.312 seconds (Total) +#> Chain 1: Elapsed Time: 1.99 seconds (Warm-up) +#> Chain 1: 1.663 seconds (Sampling) +#> Chain 1: 3.653 seconds (Total) #> Chain 1: #> #> SAMPLING FOR MODEL 'dist_fit' NOW (CHAIN 2). #> Chain 2: -#> Chain 2: Gradient evaluation took 0.000244 seconds -#> Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 2.44 seconds. +#> Chain 2: Gradient evaluation took 0.00023 seconds +#> Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 2.3 seconds. #> Chain 2: Adjust your expectations accordingly! #> Chain 2: #> Chain 2: @@ -382,22 +376,22 @@

Examples#> Chain 2: Iteration: 1950 / 2000 [ 97%] (Sampling) #> Chain 2: Iteration: 2000 / 2000 [100%] (Sampling) #> Chain 2: -#> Chain 2: Elapsed Time: 1.985 seconds (Warm-up) -#> Chain 2: 1.929 seconds (Sampling) -#> Chain 2: 3.914 seconds (Total) +#> Chain 2: Elapsed Time: 1.983 seconds (Warm-up) +#> Chain 2: 2.058 seconds (Sampling) +#> Chain 2: 4.041 seconds (Total) #> Chain 2: #> Inference for Stan model: dist_fit. #> 2 chains, each with iter=2000; warmup=1000; thin=1; #> post-warmup draws per chain=1000, total post-warmup draws=2000. #> #> mean se_mean sd 2.5% 25% 50% 75% 97.5% n_eff Rhat -#> alpha_raw[1] 0.88 0.03 0.54 0.05 0.46 0.84 1.23 2.05 396 1 -#> beta_raw[1] 0.95 0.03 0.52 0.11 0.56 0.90 1.27 2.09 355 1 -#> alpha[1] 5.56 0.03 0.54 4.73 5.14 5.52 5.91 6.73 396 1 -#> beta[1] 5.62 0.03 0.52 4.78 5.24 5.58 5.95 6.77 355 1 -#> lp__ -16.68 0.10 1.59 -20.47 -17.35 -16.21 -15.55 -15.14 244 1 +#> alpha_raw[1] 0.92 0.03 0.58 0.06 0.48 0.85 1.28 2.20 307 1 +#> beta_raw[1] 0.98 0.03 0.55 0.12 0.56 0.93 1.34 2.18 357 1 +#> alpha[1] 6.47 0.03 0.58 5.61 6.03 6.40 6.83 7.75 307 1 +#> beta[1] 6.23 0.03 0.55 5.38 5.81 6.18 6.60 7.44 357 1 +#> lp__ -15.04 0.09 1.47 -18.76 -15.71 -14.57 -13.93 -13.55 262 1 #> -#> Samples were drawn using NUTS(diag_e) at Thu Nov 16 22:52:50 2023. +#> Samples were drawn using NUTS(diag_e) at Fri Nov 17 10:52:56 2023. #> For each parameter, n_eff is a crude measure of effective sample size, #> and Rhat is the potential scale reduction factor on split chains (at #> convergence, Rhat=1). @@ -410,8 +404,8 @@

Examples#> #> SAMPLING FOR MODEL 'dist_fit' NOW (CHAIN 1). #> Chain 1: -#> Chain 1: Gradient evaluation took 5.5e-05 seconds -#> Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.55 seconds. +#> Chain 1: Gradient evaluation took 5.4e-05 seconds +#> Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.54 seconds. #> Chain 1: Adjust your expectations accordingly! #> Chain 1: #> Chain 1: @@ -458,15 +452,15 @@

Examples#> Chain 1: Iteration: 1950 / 2000 [ 97%] (Sampling) #> Chain 1: Iteration: 2000 / 2000 [100%] (Sampling) #> Chain 1: -#> Chain 1: Elapsed Time: 0.3 seconds (Warm-up) -#> Chain 1: 0.291 seconds (Sampling) -#> Chain 1: 0.591 seconds (Total) +#> Chain 1: Elapsed Time: 0.31 seconds (Warm-up) +#> Chain 1: 0.326 seconds (Sampling) +#> Chain 1: 0.636 seconds (Total) #> Chain 1: #> #> SAMPLING FOR MODEL 'dist_fit' NOW (CHAIN 2). #> Chain 2: -#> Chain 2: Gradient evaluation took 5.2e-05 seconds -#> Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 0.52 seconds. +#> Chain 2: Gradient evaluation took 5.5e-05 seconds +#> Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 0.55 seconds. #> Chain 2: Adjust your expectations accordingly! #> Chain 2: #> Chain 2: @@ -513,20 +507,20 @@

Examples#> Chain 2: Iteration: 1950 / 2000 [ 97%] (Sampling) #> Chain 2: Iteration: 2000 / 2000 [100%] (Sampling) #> Chain 2: -#> Chain 2: Elapsed Time: 0.305 seconds (Warm-up) -#> Chain 2: 0.283 seconds (Sampling) -#> Chain 2: 0.588 seconds (Total) +#> Chain 2: Elapsed Time: 0.307 seconds (Warm-up) +#> Chain 2: 0.277 seconds (Sampling) +#> Chain 2: 0.584 seconds (Total) #> Chain 2: #> Inference for Stan model: dist_fit. #> 2 chains, each with iter=2000; warmup=1000; thin=1; #> post-warmup draws per chain=1000, total post-warmup draws=2000. #> #> mean se_mean sd 2.5% 25% 50% 75% 97.5% n_eff Rhat -#> mu[1] 1.65 0.00 0.02 1.60 1.63 1.65 1.66 1.69 1144 1 -#> sigma[1] 0.18 0.00 0.02 0.15 0.17 0.18 0.19 0.22 1085 1 -#> lp__ -82.87 0.03 0.96 -85.33 -83.27 -82.59 -82.19 -81.94 946 1 +#> mu[1] 1.60 0.00 0.02 1.56 1.59 1.60 1.62 1.64 1466 1 +#> sigma[1] 0.17 0.00 0.02 0.14 0.15 0.16 0.18 0.20 1330 1 +#> lp__ -74.74 0.04 1.02 -77.55 -75.15 -74.41 -74.02 -73.75 848 1 #> -#> Samples were drawn using NUTS(diag_e) at Thu Nov 16 22:52:51 2023. +#> Samples were drawn using NUTS(diag_e) at Fri Nov 17 10:52:57 2023. #> For each parameter, n_eff is a crude measure of effective sample size, #> and Rhat is the potential scale reduction factor on split chains (at #> convergence, Rhat=1). diff --git a/dev/reference/dist_skel.html b/dev/reference/dist_skel.html index b94e3f922..51cde5168 100644 --- a/dev/reference/dist_skel.html +++ b/dev/reference/dist_skel.html @@ -155,7 +155,7 @@

Examples## Exponential model # sample dist_skel(10, model = "exp", params = list(rate = 1)) -#> [1] 1 0 2 0 1 0 1 1 0 0 +#> [1] 0 0 0 0 0 0 0 3 2 0 # cumulative prob density dist_skel(1:10, model = "exp", dist = TRUE, params = list(rate = 1)) @@ -173,7 +173,7 @@

Examples## Gamma model # sample dist_skel(10, model = "gamma", params = list(shape = 1, scale = 2)) -#> [1] 0 0 0 0 1 0 0 1 1 0 +#> [1] 0 0 0 0 0 0 1 0 0 0 # cumulative prob density dist_skel(0:10, @@ -195,7 +195,7 @@

Examples## Log normal model # sample dist_skel(10, model = "lognormal", params = list(mean = log(5), sd = log(2))) -#> [1] 8 4 6 1 5 1 10 4 6 5 +#> [1] 5 1 4 4 6 7 2 9 7 2 # cumulative prob density dist_skel(0:10, diff --git a/dev/reference/epinow-1.png b/dev/reference/epinow-1.png index f41527fe3..340703f5c 100644 Binary files a/dev/reference/epinow-1.png and b/dev/reference/epinow-1.png differ diff --git a/dev/reference/epinow.html b/dev/reference/epinow.html index a79718940..25f40e0ef 100644 --- a/dev/reference/epinow.html +++ b/dev/reference/epinow.html @@ -305,22 +305,22 @@

Examples delays = delay_opts(incubation_period + reporting_delay) ) #> Logging threshold set at INFO for the EpiNow2 logger -#> Writing EpiNow2 logs to the console and: /tmp/RtmpNmGfWk/regional-epinow/2020-04-01.log +#> Writing EpiNow2 logs to the console and: /tmp/Rtmp1L2HWE/regional-epinow/2020-04-01.log #> Logging threshold set at INFO for the EpiNow2.epinow logger -#> Writing EpiNow2.epinow logs to the console and: /tmp/RtmpNmGfWk/epinow/2020-04-01.log -#> WARN [2023-11-16 22:53:45] epinow: There were 15 divergent transitions after warmup. See +#> Writing EpiNow2.epinow logs to the console and: /tmp/Rtmp1L2HWE/epinow/2020-04-01.log +#> WARN [2023-11-17 10:53:44] 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 [2023-11-16 22:53:45] epinow: Examine the pairs() plot to diagnose sampling problems +#> WARN [2023-11-17 10:53:44] epinow: Examine the pairs() plot to diagnose sampling problems #> - # summary of the latest estimates summary(out) #> measure estimate -#> 1: New confirmed cases by infection date 3410 (1588 -- 7754) +#> 1: New confirmed cases by infection date 3415 (1540 -- 7632) #> 2: Expected change in daily cases Likely decreasing -#> 3: Effective reproduction no. 0.74 (0.45 -- 1.2) -#> 4: Rate of growth -0.044 (-0.11 -- 0.028) -#> 5: Doubling/halving time (days) -16 (25 -- -6.3) +#> 3: Effective reproduction no. 0.75 (0.44 -- 1.2) +#> 4: Rate of growth -0.044 (-0.11 -- 0.026) +#> 5: Doubling/halving time (days) -16 (27 -- -6.2) # plot estimates plot(out) @@ -328,151 +328,151 @@

Examples# summary of R estimates summary(out, type = "parameters", params = "R") #> date variable strat type median -#> 1: 2020-02-22 R <NA> estimate 2.0978020 -#> 2: 2020-02-23 R <NA> estimate 2.1528208 -#> 3: 2020-02-24 R <NA> estimate 2.1976443 -#> 4: 2020-02-25 R <NA> estimate 2.2388574 -#> 5: 2020-02-26 R <NA> estimate 2.2733348 -#> 6: 2020-02-27 R <NA> estimate 2.3001316 -#> 7: 2020-02-28 R <NA> estimate 2.3178621 -#> 8: 2020-02-29 R <NA> estimate 2.3236165 -#> 9: 2020-03-01 R <NA> estimate 2.3167491 -#> 10: 2020-03-02 R <NA> estimate 2.2959241 -#> 11: 2020-03-03 R <NA> estimate 2.2666524 -#> 12: 2020-03-04 R <NA> estimate 2.2281395 -#> 13: 2020-03-05 R <NA> estimate 2.1825266 -#> 14: 2020-03-06 R <NA> estimate 2.1288752 -#> 15: 2020-03-07 R <NA> estimate 2.0667364 -#> 16: 2020-03-08 R <NA> estimate 2.0007968 -#> 17: 2020-03-09 R <NA> estimate 1.9323482 -#> 18: 2020-03-10 R <NA> estimate 1.8616270 -#> 19: 2020-03-11 R <NA> estimate 1.7906728 -#> 20: 2020-03-12 R <NA> estimate 1.7178514 -#> 21: 2020-03-13 R <NA> estimate 1.6422517 -#> 22: 2020-03-14 R <NA> estimate 1.5699316 -#> 23: 2020-03-15 R <NA> estimate 1.4982534 -#> 24: 2020-03-16 R <NA> estimate 1.4261070 -#> 25: 2020-03-17 R <NA> estimate 1.3584162 -#> 26: 2020-03-18 R <NA> estimate 1.2945392 -#> 27: 2020-03-19 R <NA> estimate 1.2302324 -#> 28: 2020-03-20 R <NA> estimate 1.1695420 -#> 29: 2020-03-21 R <NA> estimate 1.1118390 -#> 30: 2020-03-22 R <NA> estimate based on partial data 1.0603888 -#> 31: 2020-03-23 R <NA> estimate based on partial data 1.0117496 -#> 32: 2020-03-24 R <NA> estimate based on partial data 0.9676433 -#> 33: 2020-03-25 R <NA> estimate based on partial data 0.9281484 -#> 34: 2020-03-26 R <NA> estimate based on partial data 0.8930065 -#> 35: 2020-03-27 R <NA> estimate based on partial data 0.8614169 -#> 36: 2020-03-28 R <NA> estimate based on partial data 0.8321716 -#> 37: 2020-03-29 R <NA> estimate based on partial data 0.8061551 -#> 38: 2020-03-30 R <NA> estimate based on partial data 0.7831689 -#> 39: 2020-03-31 R <NA> estimate based on partial data 0.7613739 -#> 40: 2020-04-01 R <NA> estimate based on partial data 0.7436352 -#> 41: 2020-04-02 R <NA> forecast 0.7436352 -#> 42: 2020-04-03 R <NA> forecast 0.7436352 -#> 43: 2020-04-04 R <NA> forecast 0.7436352 -#> 44: 2020-04-05 R <NA> forecast 0.7436352 -#> 45: 2020-04-06 R <NA> forecast 0.7436352 -#> 46: 2020-04-07 R <NA> forecast 0.7436352 -#> 47: 2020-04-08 R <NA> forecast 0.7436352 +#> 1: 2020-02-22 R <NA> estimate 2.1011150 +#> 2: 2020-02-23 R <NA> estimate 2.1498008 +#> 3: 2020-02-24 R <NA> estimate 2.1982362 +#> 4: 2020-02-25 R <NA> estimate 2.2361427 +#> 5: 2020-02-26 R <NA> estimate 2.2676263 +#> 6: 2020-02-27 R <NA> estimate 2.2931229 +#> 7: 2020-02-28 R <NA> estimate 2.3081905 +#> 8: 2020-02-29 R <NA> estimate 2.3124999 +#> 9: 2020-03-01 R <NA> estimate 2.3072306 +#> 10: 2020-03-02 R <NA> estimate 2.2901652 +#> 11: 2020-03-03 R <NA> estimate 2.2610566 +#> 12: 2020-03-04 R <NA> estimate 2.2244901 +#> 13: 2020-03-05 R <NA> estimate 2.1774082 +#> 14: 2020-03-06 R <NA> estimate 2.1241053 +#> 15: 2020-03-07 R <NA> estimate 2.0646939 +#> 16: 2020-03-08 R <NA> estimate 2.0015989 +#> 17: 2020-03-09 R <NA> estimate 1.9312019 +#> 18: 2020-03-10 R <NA> estimate 1.8616381 +#> 19: 2020-03-11 R <NA> estimate 1.7902493 +#> 20: 2020-03-12 R <NA> estimate 1.7181118 +#> 21: 2020-03-13 R <NA> estimate 1.6443540 +#> 22: 2020-03-14 R <NA> estimate 1.5699748 +#> 23: 2020-03-15 R <NA> estimate 1.4974495 +#> 24: 2020-03-16 R <NA> estimate 1.4272065 +#> 25: 2020-03-17 R <NA> estimate 1.3585566 +#> 26: 2020-03-18 R <NA> estimate 1.2926163 +#> 27: 2020-03-19 R <NA> estimate 1.2304763 +#> 28: 2020-03-20 R <NA> estimate 1.1728283 +#> 29: 2020-03-21 R <NA> estimate 1.1159573 +#> 30: 2020-03-22 R <NA> estimate based on partial data 1.0618867 +#> 31: 2020-03-23 R <NA> estimate based on partial data 1.0141568 +#> 32: 2020-03-24 R <NA> estimate based on partial data 0.9706584 +#> 33: 2020-03-25 R <NA> estimate based on partial data 0.9318087 +#> 34: 2020-03-26 R <NA> estimate based on partial data 0.8967106 +#> 35: 2020-03-27 R <NA> estimate based on partial data 0.8648103 +#> 36: 2020-03-28 R <NA> estimate based on partial data 0.8324546 +#> 37: 2020-03-29 R <NA> estimate based on partial data 0.8049301 +#> 38: 2020-03-30 R <NA> estimate based on partial data 0.7821883 +#> 39: 2020-03-31 R <NA> estimate based on partial data 0.7624889 +#> 40: 2020-04-01 R <NA> estimate based on partial data 0.7471743 +#> 41: 2020-04-02 R <NA> forecast 0.7471743 +#> 42: 2020-04-03 R <NA> forecast 0.7471743 +#> 43: 2020-04-04 R <NA> forecast 0.7471743 +#> 44: 2020-04-05 R <NA> forecast 0.7471743 +#> 45: 2020-04-06 R <NA> forecast 0.7471743 +#> 46: 2020-04-07 R <NA> forecast 0.7471743 +#> 47: 2020-04-08 R <NA> forecast 0.7471743 #> date variable strat type median #> mean sd lower_90 lower_50 lower_20 upper_20 upper_50 -#> 1: 2.0996851 0.09867560 1.9413314 2.0321494 2.0737098 2.1221886 2.1641801 -#> 2: 2.1528652 0.09036630 2.0098217 2.0904923 2.1303902 2.1717695 2.2104121 -#> 3: 2.2028669 0.09320540 2.0553091 2.1400039 2.1757277 2.2229093 2.2640516 -#> 4: 2.2472447 0.10185672 2.0930743 2.1794863 2.2166614 2.2660661 2.3078964 -#> 5: 2.2837231 0.11058858 2.1186108 2.2092732 2.2505211 2.2998092 2.3486963 -#> 6: 2.3103967 0.11597805 2.1372194 2.2315279 2.2748501 2.3301980 2.3811081 -#> 7: 2.3258938 0.11684415 2.1490106 2.2463346 2.2886372 2.3465482 2.3948437 -#> 8: 2.3294707 0.11365162 2.1584970 2.2498401 2.2938953 2.3523972 2.3991071 -#> 9: 2.3210162 0.10791760 2.1554582 2.2456912 2.2891156 2.3449369 2.3910237 -#> 10: 2.3009774 0.10155895 2.1403650 2.2306915 2.2723363 2.3263511 2.3654613 -#> 11: 2.2702336 0.09619467 2.1169598 2.2037041 2.2431213 2.2935683 2.3342155 -#> 12: 2.2299543 0.09259853 2.0822277 2.1683326 2.2053737 2.2530983 2.2900334 -#> 13: 2.1814648 0.09059933 2.0375269 2.1224772 2.1605698 2.2027482 2.2394203 -#> 14: 2.1261345 0.08948248 1.9783101 2.0691505 2.1064848 2.1479191 2.1832133 -#> 15: 2.0652900 0.08853606 1.9181468 2.0112609 2.0477926 2.0881209 2.1230232 -#> 16: 2.0001541 0.08736688 1.8524560 1.9462542 1.9828223 2.0209024 2.0562349 -#> 17: 1.9318093 0.08591635 1.7879144 1.8785691 1.9148227 1.9524284 1.9869207 -#> 18: 1.8611864 0.08430119 1.7208307 1.8062255 1.8436835 1.8826745 1.9163830 -#> 19: 1.7890756 0.08262924 1.6558864 1.7366296 1.7706889 1.8089398 1.8422453 -#> 20: 1.7161554 0.08090352 1.5828201 1.6644216 1.6955860 1.7353209 1.7682110 -#> 21: 1.6430295 0.07904664 1.5130657 1.5917730 1.6233648 1.6615388 1.6936271 -#> 22: 1.5702615 0.07698388 1.4454620 1.5199337 1.5516073 1.5881633 1.6208497 -#> 23: 1.4983982 0.07470394 1.3781473 1.4484661 1.4794860 1.5159536 1.5460358 -#> 24: 1.4279797 0.07228948 1.3096567 1.3786861 1.4102515 1.4447163 1.4743038 -#> 25: 1.3595372 0.06996080 1.2467408 1.3110452 1.3425656 1.3771211 1.4035593 -#> 26: 1.2935823 0.06813381 1.1811277 1.2460882 1.2760529 1.3114150 1.3363291 -#> 27: 1.2305924 0.06742307 1.1201310 1.1856774 1.2127654 1.2464578 1.2726107 -#> 28: 1.1709931 0.06851964 1.0622920 1.1245841 1.1521682 1.1871938 1.2143020 -#> 29: 1.1151419 0.07196736 1.0029458 1.0666761 1.0960090 1.1313222 1.1609569 -#> 30: 1.0633155 0.07798331 0.9430349 1.0114085 1.0426965 1.0796845 1.1114799 -#> 31: 1.0157047 0.08645859 0.8816187 0.9574368 0.9915810 1.0333413 1.0708685 -#> 32: 0.9724161 0.09710367 0.8249947 0.9053732 0.9464178 0.9931067 1.0325237 -#> 33: 0.9334800 0.10959982 0.7648704 0.8583994 0.9015821 0.9583143 1.0003842 -#> 34: 0.8988629 0.12368111 0.7093997 0.8142082 0.8623778 0.9241606 0.9755091 -#> 35: 0.8684795 0.13915560 0.6579153 0.7710912 0.8265051 0.8959636 0.9561412 -#> 36: 0.8422037 0.15589716 0.6071385 0.7329861 0.7915321 0.8709487 0.9400864 -#> 37: 0.8198765 0.17382822 0.5600266 0.6972271 0.7608280 0.8496131 0.9271865 -#> 38: 0.8013105 0.19290091 0.5212724 0.6660586 0.7365653 0.8277345 0.9211358 -#> 39: 0.7862923 0.21307692 0.4844711 0.6371059 0.7131715 0.8113475 0.9121523 -#> 40: 0.7745814 0.23430482 0.4469029 0.6111109 0.6936058 0.7943674 0.9057101 -#> 41: 0.7745814 0.23430482 0.4469029 0.6111109 0.6936058 0.7943674 0.9057101 -#> 42: 0.7745814 0.23430482 0.4469029 0.6111109 0.6936058 0.7943674 0.9057101 -#> 43: 0.7745814 0.23430482 0.4469029 0.6111109 0.6936058 0.7943674 0.9057101 -#> 44: 0.7745814 0.23430482 0.4469029 0.6111109 0.6936058 0.7943674 0.9057101 -#> 45: 0.7745814 0.23430482 0.4469029 0.6111109 0.6936058 0.7943674 0.9057101 -#> 46: 0.7745814 0.23430482 0.4469029 0.6111109 0.6936058 0.7943674 0.9057101 -#> 47: 0.7745814 0.23430482 0.4469029 0.6111109 0.6936058 0.7943674 0.9057101 +#> 1: 2.1002645 0.10111712 1.9357037 2.0284965 2.0735992 2.1265761 2.1692135 +#> 2: 2.1510236 0.09112286 2.0009489 2.0884798 2.1273012 2.1739446 2.2126442 +#> 3: 2.1988051 0.09387295 2.0506808 2.1353657 2.1748081 2.2187703 2.2588833 +#> 4: 2.2412512 0.10300553 2.0860517 2.1754081 2.2144490 2.2580310 2.3014094 +#> 5: 2.2761828 0.11188142 2.1109266 2.2049728 2.2456008 2.2923953 2.3369565 +#> 6: 2.3017892 0.11685922 2.1351776 2.2247662 2.2683422 2.3184139 2.3656319 +#> 7: 2.3167698 0.11691487 2.1469100 2.2388625 2.2804537 2.3333748 2.3854114 +#> 8: 2.3204040 0.11279595 2.1557160 2.2447848 2.2852690 2.3378536 2.3874876 +#> 9: 2.3125409 0.10631720 2.1508477 2.2381504 2.2795680 2.3321943 2.3776833 +#> 10: 2.2935232 0.09962828 2.1395088 2.2262837 2.2624712 2.3135651 2.3560996 +#> 11: 2.2640768 0.09441432 2.1142946 2.1991280 2.2364024 2.2855543 2.3236871 +#> 12: 2.2251932 0.09128086 2.0798170 2.1654512 2.1994334 2.2478658 2.2830384 +#> 13: 2.1780252 0.08973462 2.0371230 2.1192430 2.1557665 2.1996576 2.2323327 +#> 14: 2.1238023 0.08878185 1.9824949 2.0664039 2.1033452 2.1457345 2.1811870 +#> 15: 2.0637632 0.08761408 1.9253812 2.0112552 2.0433495 2.0856838 2.1196151 +#> 16: 1.9991037 0.08593848 1.8610905 1.9462026 1.9797096 2.0207740 2.0539413 +#> 17: 1.9309377 0.08393461 1.7923785 1.8795624 1.9116199 1.9556452 1.9863241 +#> 18: 1.8602737 0.08200599 1.7252574 1.8088932 1.8418595 1.8828587 1.9143801 +#> 19: 1.7880062 0.08048712 1.6536413 1.7381609 1.7697838 1.8087508 1.8396311 +#> 20: 1.7149229 0.07944169 1.5810315 1.6629652 1.6973190 1.7346370 1.7661410 +#> 21: 1.6417208 0.07864356 1.5126265 1.5913130 1.6252427 1.6620156 1.6918939 +#> 22: 1.5690281 0.07772565 1.4432379 1.5177486 1.5532652 1.5880014 1.6177069 +#> 23: 1.4974219 0.07638401 1.3739738 1.4476111 1.4797695 1.5152975 1.5454070 +#> 24: 1.4274398 0.07453085 1.3107957 1.3792417 1.4090409 1.4438491 1.4735978 +#> 25: 1.3595816 0.07236392 1.2484430 1.3131065 1.3395430 1.3758328 1.4039653 +#> 26: 1.2943053 0.07036726 1.1889478 1.2482456 1.2745541 1.3097384 1.3358085 +#> 27: 1.2320178 0.06925072 1.1262330 1.1864873 1.2142397 1.2468854 1.2734918 +#> 28: 1.1730662 0.06980901 1.0666029 1.1261258 1.1545857 1.1876533 1.2165489 +#> 29: 1.1177310 0.07269962 1.0071158 1.0675519 1.0989570 1.1344023 1.1634492 +#> 30: 1.0662241 0.07823410 0.9422242 1.0141613 1.0444142 1.0832761 1.1169260 +#> 31: 1.0186919 0.08633108 0.8816833 0.9601792 0.9946941 1.0364581 1.0753395 +#> 32: 0.9752222 0.09665458 0.8203275 0.9101682 0.9480752 0.9953844 1.0400945 +#> 33: 0.9358539 0.10880868 0.7655895 0.8630955 0.9044813 0.9594036 1.0076215 +#> 34: 0.9005865 0.12247057 0.7079034 0.8181656 0.8646616 0.9263163 0.9806362 +#> 35: 0.8693864 0.13743484 0.6565125 0.7753177 0.8300802 0.8979387 0.9580303 +#> 36: 0.8421887 0.15359530 0.6069230 0.7365397 0.7958116 0.8755375 0.9397031 +#> 37: 0.8188950 0.17090193 0.5586615 0.6988255 0.7657957 0.8545638 0.9252721 +#> 38: 0.7993691 0.18932134 0.5153123 0.6659731 0.7371208 0.8346088 0.9180492 +#> 39: 0.7834340 0.20881072 0.4782377 0.6344911 0.7127805 0.8173930 0.9075752 +#> 40: 0.7708697 0.22929972 0.4428590 0.6091187 0.6923416 0.8036643 0.9003281 +#> 41: 0.7708697 0.22929972 0.4428590 0.6091187 0.6923416 0.8036643 0.9003281 +#> 42: 0.7708697 0.22929972 0.4428590 0.6091187 0.6923416 0.8036643 0.9003281 +#> 43: 0.7708697 0.22929972 0.4428590 0.6091187 0.6923416 0.8036643 0.9003281 +#> 44: 0.7708697 0.22929972 0.4428590 0.6091187 0.6923416 0.8036643 0.9003281 +#> 45: 0.7708697 0.22929972 0.4428590 0.6091187 0.6923416 0.8036643 0.9003281 +#> 46: 0.7708697 0.22929972 0.4428590 0.6091187 0.6923416 0.8036643 0.9003281 +#> 47: 0.7708697 0.22929972 0.4428590 0.6091187 0.6923416 0.8036643 0.9003281 #> mean sd lower_90 lower_50 lower_20 upper_20 upper_50 #> upper_90 -#> 1: 2.264206 -#> 2: 2.308642 -#> 3: 2.359812 -#> 4: 2.421268 -#> 5: 2.476442 -#> 6: 2.520242 -#> 7: 2.536325 -#> 8: 2.524971 -#> 9: 2.501525 -#> 10: 2.467550 -#> 11: 2.430582 -#> 12: 2.385577 -#> 13: 2.333305 -#> 14: 2.269430 -#> 15: 2.207854 -#> 16: 2.137651 -#> 17: 2.064896 -#> 18: 1.997889 -#> 19: 1.925619 -#> 20: 1.849006 -#> 21: 1.771605 -#> 22: 1.694840 -#> 23: 1.621942 -#> 24: 1.547761 -#> 25: 1.475005 -#> 26: 1.402950 -#> 27: 1.341270 -#> 28: 1.283577 -#> 29: 1.233336 -#> 30: 1.194546 -#> 31: 1.163442 -#> 32: 1.140752 -#> 33: 1.118705 -#> 34: 1.107934 -#> 35: 1.109148 -#> 36: 1.113518 -#> 37: 1.123222 -#> 38: 1.129463 -#> 39: 1.149138 -#> 40: 1.187983 -#> 41: 1.187983 -#> 42: 1.187983 -#> 43: 1.187983 -#> 44: 1.187983 -#> 45: 1.187983 -#> 46: 1.187983 -#> 47: 1.187983 +#> 1: 2.263574 +#> 2: 2.301238 +#> 3: 2.354674 +#> 4: 2.420333 +#> 5: 2.469412 +#> 6: 2.507129 +#> 7: 2.523730 +#> 8: 2.519812 +#> 9: 2.497725 +#> 10: 2.466869 +#> 11: 2.420979 +#> 12: 2.380824 +#> 13: 2.324347 +#> 14: 2.265558 +#> 15: 2.201724 +#> 16: 2.134428 +#> 17: 2.061760 +#> 18: 1.988834 +#> 19: 1.918167 +#> 20: 1.842050 +#> 21: 1.765292 +#> 22: 1.693842 +#> 23: 1.616954 +#> 24: 1.545359 +#> 25: 1.476438 +#> 26: 1.407635 +#> 27: 1.344414 +#> 28: 1.288102 +#> 29: 1.239676 +#> 30: 1.195504 +#> 31: 1.161009 +#> 32: 1.138174 +#> 33: 1.120989 +#> 34: 1.110238 +#> 35: 1.106652 +#> 36: 1.110793 +#> 37: 1.112478 +#> 38: 1.128244 +#> 39: 1.150121 +#> 40: 1.171524 +#> 41: 1.171524 +#> 42: 1.171524 +#> 43: 1.171524 +#> 44: 1.171524 +#> 45: 1.171524 +#> 46: 1.171524 +#> 47: 1.171524 #> upper_90 options(old_opts) diff --git a/dev/reference/estimate_delay.html b/dev/reference/estimate_delay.html index 78a8bc9ff..8a4f44d29 100644 --- a/dev/reference/estimate_delay.html +++ b/dev/reference/estimate_delay.html @@ -124,7 +124,7 @@

Examples#> Warning: `samples` must be at least 1000. Now setting it to 1000 internally. #> Warning: `samples` must be at least 1000. Now setting it to 1000 internally. #> -#> Uncertain lognormal distribution with (untruncated) logmean 1.4 (SD 0.1) and logSD 1.1 (SD 0.076) +#> Uncertain lognormal distribution with (untruncated) logmean 1.5 (SD 0.1) and logSD 1.1 (SD 0.094) #> # } diff --git a/dev/reference/estimate_infections-1.png b/dev/reference/estimate_infections-1.png index 28de677fc..99cabeafe 100644 Binary files a/dev/reference/estimate_infections-1.png and b/dev/reference/estimate_infections-1.png differ diff --git a/dev/reference/estimate_infections.html b/dev/reference/estimate_infections.html index 95ef19410..af6056a67 100644 --- a/dev/reference/estimate_infections.html +++ b/dev/reference/estimate_infections.html @@ -296,18 +296,18 @@

Examples rt = rt_opts(prior = list(mean = 2, sd = 0.1)), stan = stan_opts(control = list(adapt_delta = 0.95)) ) -#> Warning: There were 11 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 # real time estimates summary(def) -#> measure estimate -#> 1: New confirmed cases by infection date 2170 (1106 -- 4227) -#> 2: Expected change in daily cases Likely decreasing -#> 3: Effective reproduction no. 0.8 (0.5 -- 1.2) -#> 4: Rate of growth -0.033 (-0.095 -- 0.032) -#> 5: Doubling/halving time (days) -21 (22 -- -7.3) +#> measure estimate +#> 1: New confirmed cases by infection date 2246 (1145 -- 4294) +#> 2: Expected change in daily cases Likely decreasing +#> 3: Effective reproduction no. 0.82 (0.52 -- 1.2) +#> 4: Rate of growth -0.03 (-0.092 -- 0.031) +#> 5: Doubling/halving time (days) -23 (23 -- -7.5) # summary plot plot(def) diff --git a/dev/reference/estimate_secondary-1.png b/dev/reference/estimate_secondary-1.png index a3bae2625..55cca660a 100644 Binary files a/dev/reference/estimate_secondary-1.png and b/dev/reference/estimate_secondary-1.png differ diff --git a/dev/reference/estimate_secondary-2.png b/dev/reference/estimate_secondary-2.png index 945c8d52c..4658d090a 100644 Binary files a/dev/reference/estimate_secondary-2.png and b/dev/reference/estimate_secondary-2.png differ diff --git a/dev/reference/estimate_secondary-3.png b/dev/reference/estimate_secondary-3.png index b4f4b96eb..059304b68 100644 Binary files a/dev/reference/estimate_secondary-3.png and b/dev/reference/estimate_secondary-3.png differ diff --git a/dev/reference/estimate_secondary-4.png b/dev/reference/estimate_secondary-4.png index b24d6a9e6..fccbff233 100644 Binary files a/dev/reference/estimate_secondary-4.png and b/dev/reference/estimate_secondary-4.png differ diff --git a/dev/reference/regional_epinow.html b/dev/reference/regional_epinow.html index aff2dbde6..cf9b5f054 100644 --- a/dev/reference/regional_epinow.html +++ b/dev/reference/regional_epinow.html @@ -304,23 +304,23 @@

Examples ), verbose = interactive() ) -#> INFO [2023-11-16 22:58:23] Producing following optional outputs: regions, summary, samples, plots, latest +#> INFO [2023-11-17 10:57:06] 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/RtmpNmGfWk/regional-epinow/2020-04-21.log +#> Writing EpiNow2 logs to the console and: /tmp/Rtmp1L2HWE/regional-epinow/2020-04-21.log #> Logging threshold set at INFO for the EpiNow2.epinow logger -#> Writing EpiNow2.epinow logs to: /tmp/RtmpNmGfWk/epinow/2020-04-21.log -#> INFO [2023-11-16 22:58:23] Reporting estimates using data up to: 2020-04-21 -#> INFO [2023-11-16 22:58:23] No target directory specified so returning output -#> INFO [2023-11-16 22:58:23] Producing estimates for: testland, realland -#> INFO [2023-11-16 22:58:23] Regions excluded: none -#> INFO [2023-11-16 23:00:24] Completed estimates for: testland -#> INFO [2023-11-16 23:02:01] Completed estimates for: realland -#> INFO [2023-11-16 23:02:01] Completed regional estimates -#> INFO [2023-11-16 23:02:01] Regions with estimates: 2 -#> INFO [2023-11-16 23:02:01] Regions with runtime errors: 0 -#> INFO [2023-11-16 23:02:01] Producing summary -#> INFO [2023-11-16 23:02:01] No summary directory specified so returning summary output -#> INFO [2023-11-16 23:02:01] No target directory specified so returning timings +#> Writing EpiNow2.epinow logs to: /tmp/Rtmp1L2HWE/epinow/2020-04-21.log +#> INFO [2023-11-17 10:57:06] Reporting estimates using data up to: 2020-04-21 +#> INFO [2023-11-17 10:57:06] No target directory specified so returning output +#> INFO [2023-11-17 10:57:06] Producing estimates for: testland, realland +#> INFO [2023-11-17 10:57:06] Regions excluded: none +#> INFO [2023-11-17 10:59:06] Completed estimates for: testland +#> INFO [2023-11-17 11:00:43] Completed estimates for: realland +#> INFO [2023-11-17 11:00:43] Completed regional estimates +#> INFO [2023-11-17 11:00:43] Regions with estimates: 2 +#> INFO [2023-11-17 11:00:43] Regions with runtime errors: 0 +#> INFO [2023-11-17 11:00:43] Producing summary +#> INFO [2023-11-17 11:00:43] No summary directory specified so returning summary output +#> INFO [2023-11-17 11:00:43] No target directory specified so returning timings options(old_opts) # } diff --git a/dev/reference/regional_runtimes.html b/dev/reference/regional_runtimes.html index 74592fbef..e0ad1ef65 100644 --- a/dev/reference/regional_runtimes.html +++ b/dev/reference/regional_runtimes.html @@ -125,7 +125,7 @@

Examples package = "EpiNow2", "extdata", "example_regional_epinow.rds" )) regional_runtimes(regional_output = regional_out$regional) -#> INFO [2023-11-16 23:02:03] No target directory specified so returning timings +#> INFO [2023-11-17 11:00:44] No target directory specified so returning timings #> region time #> 1: testland 44.5 #> 2: realland 29.7 diff --git a/dev/reference/regional_summary.html b/dev/reference/regional_summary.html index a23b810a5..5ed42d1f8 100644 --- a/dev/reference/regional_summary.html +++ b/dev/reference/regional_summary.html @@ -175,7 +175,7 @@

Examples regional_output = regional_out$regional, reported_cases = regional_out$summary$reported_cases ) -#> INFO [2023-11-16 23:02:04] No summary directory specified so returning summary output +#> INFO [2023-11-17 11:00:46] No summary directory specified so returning summary output #> $latest_date #> [1] "2020-04-21" #> diff --git a/dev/reference/setup_default_logging.html b/dev/reference/setup_default_logging.html index 771d5adb1..294b1b5a0 100644 --- a/dev/reference/setup_default_logging.html +++ b/dev/reference/setup_default_logging.html @@ -118,9 +118,9 @@

Value

Examples

setup_default_logging()
 #> Logging threshold set at INFO for the EpiNow2 logger
-#> Writing EpiNow2 logs to the console and: /tmp/RtmpNmGfWk/regional-epinow/latest.log
+#> Writing EpiNow2 logs to the console and: /tmp/Rtmp1L2HWE/regional-epinow/latest.log
 #> Logging threshold set at INFO for the EpiNow2.epinow logger
-#> Writing EpiNow2.epinow logs to: /tmp/RtmpNmGfWk/epinow/latest.log
+#> Writing EpiNow2.epinow logs to: /tmp/Rtmp1L2HWE/epinow/latest.log