Merge pull request #322 from SchlossLab/release-1.5.0

Release 1.5.0
SchlossLab · Jan 16, 2023 · 4df6fe7 · 4df6fe7
2 parents 00c4bbb + 1a827e8
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,7 +1,7 @@
 Package: mikropml
 Title: User-Friendly R Package for Supervised Machine Learning Pipelines
-Version: 1.4.0.9000
-Date: 2022-10-15
+Version: 1.5.0
+Date: 2023-01-15
 Authors@R: 
     c(person(given = "Begüm",
              family = "Topçuoğlu",

diff --git a/NEWS.md b/NEWS.md
@@ -1,4 +1,4 @@
-# mikropml development version
+# mikropml 1.5.0
 
 - New example showing how to plot feature importances in the `parallel` vignette (#310, @kelly-sovacool).
 - You can now use `parRF`, a parallel implementation of the `rf` method, with

diff --git a/R/checks.R b/R/checks.R
@@ -1,4 +1,3 @@
-
 #' Check all params that don't return a value
 #'
 #' @inheritParams run_ml

diff --git a/R/performance.R b/R/performance.R
@@ -332,6 +332,7 @@ calc_mean_prc <- function(sensspec_dat) {
 #' @author Kelly Sovacool, \email{sovacool@@umich.edu}
 #'
 #' @examples
+#' \dontrun{
 #' library(dplyr)
 #' # get cumulative performance for a single model
 #' sensspec_1 <- calc_model_sensspec(
@@ -367,7 +368,7 @@ calc_mean_prc <- function(sensspec_dat) {
 #' baseline_prec <- calc_baseline_precision(otu_mini_bin, "dx", "cancer")
 #' prc_dat %>%
 #'   plot_mean_prc(baseline_precision = baseline_prec)
-#'
+#' }
 NULL
 
 #' Calculate the fraction of positives, i.e. baseline precision for a PRC curve

diff --git a/R/plot.R b/R/plot.R
@@ -305,7 +305,7 @@ plot_mean_prc <- function(dat, baseline_precision = NULL,
 #' @author Kelly Sovacool \email{sovacool@@umich.edu}
 #'
 #' @examples
-#'
+#' \dontrun{
 #' library(dplyr)
 #' # get performance for multiple models
 #' get_sensspec_seed <- function(seed) {
@@ -328,5 +328,5 @@ plot_mean_prc <- function(dat, baseline_precision = NULL,
 #' sensspec_dat %>%
 #'   calc_mean_prc() %>%
 #'   plot_mean_prc(baseline_precision = baseline_prec)
-#'
+#' }
 NULL
diff --git a/R/preprocess.R b/R/preprocess.R
@@ -1,4 +1,3 @@
-
 #' Preprocess data prior to running machine learning
 #'
 #' Function to preprocess your data for input into [run_ml()].

diff --git a/R/reexports.R b/R/reexports.R
@@ -1,4 +1,3 @@
-
 #' caret contr.ltfr
 #' @importFrom caret contr.ltfr
 #' @export

diff --git a/R/utils.R b/R/utils.R
@@ -1,4 +1,3 @@
-
 #' Randomize feature order to eliminate any position-dependent effects
 #'
 #'

diff --git a/cran-comments.md b/cran-comments.md
@@ -1,7 +1,9 @@
+This is a resubmission.
+I reduced the package tarball size, it should now be 2.2 MB.
 
 ## Test environments
 
-* local macOS install: R 4.2.1
+* local macOS install: R 4.2.2
 * GitHub Actions (ubuntu-16.04): devel, release, oldrel
 * GitHub Actions (windows): release
 * GitHub Actions (macOS): release
@@ -19,16 +21,6 @@ Found the following (possibly) invalid URLs:
           README.md
     Status: 400
     Message: Bad Request
-  URL: https://doi.org/10.1128/mBio.00434-20
-    From: inst/doc/introduction.html
-          inst/doc/paper.html
-          README.md
-    Status: 503
-    Message: Service Unavailable
-  URL: https://doi.org/10.1128/mBio.01680-20
-    From: inst/doc/paper.html
-    Status: 503
-    Message: Service Unavailable
   URL: https://doi.org/doi:10.1128/mBio.00434-20
     From: README.md
     Status: 503
@@ -37,12 +29,6 @@ Found the following (possibly) invalid URLs:
     From: man/otu_small.Rd
     Status: 503
     Message: Service Unavailable
-
-Found the following (possibly) invalid DOIs:
-  DOI: 10.1128/mBio.00434-20
-    From: DESCRIPTION
-    Status: Service Unavailable
-    Message: 503
 ```
 
 This is a spurious note as these URLs work in my local browser, and the DOIs are

diff --git a/docs/404.html b/docs/404.html
diff --git a/docs/CODE_OF_CONDUCT.html b/docs/CODE_OF_CONDUCT.html