Merge pull request #83 from ModelOriented/cran_subm

CRAN candidate

CRAN-SUBMISSION

@@ -1,3 +1,3 @@
-Version: 0.3.4
-Date: 2023-02-25 08:41:03 UTC
-SHA: 01441b6edb0721229d98242fabe7795eaeb1af39
+Version: 0.3.5
+Date: 2023-03-31 11:06:08 UTC
+SHA: 63c092a7f51eb9eed7d88e02e38431a2bf04d0ae

DESCRIPTION

@@ -3,7 +3,9 @@ Title: Kernel SHAP
 Version: 0.3.5
 Authors@R: c(
     person("Michael", "Mayer", , "[email protected]", role = c("aut", "cre")),
-    person("David", "Watson", , "[email protected]", role = "ctb")
+    person("David", "Watson", , "[email protected]", role = "aut"),
+    person("Przemyslaw", "Biecek", , "[email protected]", role = "ctb",
+           comment = c(ORCID = "0000-0001-8423-1823"))
   )
 Description: Efficient implementation of Kernel SHAP, see Lundberg and Lee
     (2017) <https://dl.acm.org/doi/10.5555/3295222.3295230>, and Covert

NEWS.md

@@ -1,19 +1,18 @@
 # kernelshap 0.3.5
 
-## Github repository
+## Maintenance
 
+- New contributor: Przemyslaw Biecek - welcome on board!
 - My new cozy home: https://github.com/ModelOriented/kernelshap
-- Webpage created with "pgkdown": https://modeloriented.github.io/kernelshap
+- Webpage created with "pkgdown"
+- Introduced Github workflows
+- More unit tests
 
-## User visible changes
+## Small visible changes
 
 - Removed the `ks_extract()` function. It was designed to extract objects like the matrix `S` of SHAP values from the resulting "kernelshap" object `x`. We feel that the standard extraction options (`x$S`, `x[["S"]]`, or `getElement(x, "S")`) are sufficient.
 - Adding $(n \times K)$ matrix of predictions to the output, where $n$ is the number of rows in the explainer data `X`, and $K$ is the dimension of a single prediction (usually 1).
-
-## Other changes
-
-- More unit tests
-
+- Setting `verbose = FALSE` now does not suppress the warning on too large background data anymore. Use `suppressWarnings()` instead.
 
 # kernelshap 0.3.4
 

R/kernelshap.R

@@ -238,10 +238,10 @@ kernelshap.default <- function(object, X, bg_X, pred_fun = stats::predict,
   if (verbose) {
     message(txt)
   }
-  if (verbose && max(m, m_exact) * bg_n > 2e5) {
+  if (max(m, m_exact) * bg_n > 2e5) {
     warning("\nPredictions on large data sets with ", max(m, m_exact), "x", bg_n,
-            " observations are being done. Consider reducing the computational burden ",
-            "(e.g. exact = FALSE, low hybrid_degree, smaller background data, smaller m)")
+            " observations are being done.\n",
+            "Consider reducing the computational burden (e.g. use smaller X_bg)")
   }
 
   # Apply Kernel SHAP to each row of X

cran-comments.md

@@ -1,26 +1,22 @@
-Dear CRAN team
+Hello CRAN
 
-This is mainly a documentation update (new logo, better DESCRIPTION, better README, adding a relevant link to the description file).
+This is mainly a documentation update (new contributor, new Github repo),
+with only some small code changes (removing unnecessary function).
 
 ## Checks
 
-### `check(manual = TRUE, cran = TRUE)`
+### Revdep
 
-── R CMD check results ──────────── kernelshap 0.3.4 ────
-Duration: 30.9s
+survex: OK
 
-unable to verify current time
+### `check(manual = TRUE, cran = TRUE)`
 
-0 errors ✔ | 0 warnings ✔ | 1 note ✖
+Note: unable to verify current time
 
 ### `check_win_devel()`
 
-1 NOTE
-R Under development (unstable) (2023-02-23 r83894 ucrt)
-
+OK
 
 ### `check_rhub()`
 
-Status: OK
-
-
+OK

packaging.R

@@ -23,8 +23,11 @@ use_description(
     Otherwise, an almost exact hybrid algorithm involving iterative sampling is used.
     The package plays well together with meta-learning packages like 'tidymodels', 'caret' or 'mlr3'.
     Visualizations can be done using the R package 'shapviz'.",
-    `Authors@R` = "c(person('Michael', family = 'Mayer', role = c('aut', 'cre'), email = '[email protected]'),
-       person('David', family = 'Watson', role = 'ctb', email = '[email protected]'))",
+    `Authors@R` = 
+    "c(person('Michael', family='Mayer', role=c('aut', 'cre'), email='[email protected]'),
+       person('David', family='Watson', role='aut', email='[email protected]'),
+       person('Przemyslaw', family='Biecek', email='[email protected]', role='ctb', comment=c(ORCID='0000-0001-8423-1823'))
+      )",
     Depends = "R (>= 3.2.0)",
     LazyData = NULL
   ),
@@ -41,7 +44,7 @@ use_gpl_license(2)
 
 # Your files that do not belong to the package itself (others are added by "use_* function")
 use_build_ignore(c("^packaging.R$", "[.]Rproj$", "^compare_with_python.R$",
-                   "^cran-comments.md$", "^logo.png$", "^Z_exact.R$"), escape = FALSE)
+                   "^cran-comments.md$", "^logo.png$"), escape = FALSE)
 
 # If your code uses the pipe operator %>%
 # use_pipe()

revdep/README.md

@@ -0,0 +1,26 @@
+# Platform
+
+|field    |value                                                |
+|:--------|:----------------------------------------------------|
+|version  |R version 4.2.2 (2022-10-31 ucrt)                    |
+|os       |Windows 10 x64 (build 22621)                         |
+|system   |x86_64, mingw32                                      |
+|ui       |RStudio                                              |
+|language |(EN)                                                 |
+|collate  |German_Switzerland.utf8                              |
+|ctype    |German_Switzerland.utf8                              |
+|tz       |Europe/Berlin                                        |
+|date     |2023-03-31                                           |
+|rstudio  |2022.12.0+353 Elsbeth Geranium (desktop)             |
+|pandoc   |2.12 @ C:\Users\Michael\anaconda3\Scripts\pandoc.exe |
+
+# Dependencies
+
+|package    |old    |new    |Δ  |
+|:----------|:------|:------|:--|
+|kernelshap |0.3.4  |0.3.5  |*  |
+|foreach    |1.5.2  |1.5.2  |   |
+|iterators  |1.0.14 |1.0.14 |   |
+
+# Revdeps
+

revdep/cran.md

@@ -0,0 +1,7 @@
+## revdepcheck results
+
+We checked 1 reverse dependencies, comparing R CMD check results across CRAN and dev versions of this package.
+
+ * We saw 0 new problems
+ * We failed to check 0 packages
+

revdep/failures.md

@@ -0,0 +1 @@
+*Wow, no problems at all. :)*

revdep/problems.md

@@ -0,0 +1 @@
+*Wow, no problems at all. :)*

tests/testthat/test-kernelshap.R

@@ -53,10 +53,8 @@ test_that("verbose is chatty", {
 
 test_that("large background data cause warning", {
   large_bg <- iris[rep(1:150, 230), ]
-  suppressMessages(
-    expect_warning(
-      kernelshap(fit, iris[1L, x], bg_X = large_bg, verbose = TRUE)
-    )
+  expect_warning(
+    kernelshap(fit, iris[1L, x], bg_X = large_bg, verbose = FALSE)
   )
 })