spell check, remove warning expectation for Rdevel compatibility

gernophil · Jul 4, 2022 · 4bf6e6f · 4bf6e6f
1 parent cd99548
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diff --git a/.Rbuildignore b/.Rbuildignore
@@ -19,3 +19,4 @@
 ^tests/figs$
 ^\.github$
 ^README.md$
+^CRAN-SUBMISSION$
diff --git a/CRAN-SUBMISSION b/CRAN-SUBMISSION
@@ -0,0 +1,3 @@
+Version: 0.3.1
+Date: 2022-07-04 08:56:53 UTC
+SHA: cd99548a2c9ef5a8d6e91ec6ca82c10952d7cd0b
diff --git a/NEWS.md b/NEWS.md
@@ -36,7 +36,7 @@ Bug Fixes:
 - Compatibility with `recipes 0.1.5`
 - NA values in numerical columns are excepted
 - correct ggplot2 and ggalluvial versions added as dependencies
-- p$data_key does not contain comlumns with empty levels anyomore
+- p$data_key does not contain columns with empty levels anymore
 - better support for numerical variables for alluvial_long()
 
 # Version: 0.1.8, submitted to CRAN 20190115

diff --git a/R/alluvial_model_response.R b/R/alluvial_model_response.R
@@ -1073,7 +1073,7 @@ alluvial_model_response_caret = function(train, data_input, degree = 4, bins = 5
 #'  observation in the training data the displayed variables are set to the
 #'  indicated values. The predict function is called for each modified
 #'  observation and the result is averaged} }. Default: 'median'
-#'@param parallel logical, turn on parallel processing for pdp methof. Default: FALSE
+#'@param parallel logical, turn on parallel processing for pdp method. Default: FALSE
 #'@param params_bin_numeric_pred list, additional parameters passed to
 #'  \code{\link[easyalluvial]{manip_bin_numerics}} which is applied to the pred
 #'  parameter. Default: list(bins = 5, center = T, transform = T, scale = T)

diff --git a/cran-comments.md b/cran-comments.md
@@ -20,9 +20,6 @@ New submission
 
 Package was archived on CRAN
 
-occasionally:
-Examples with CPU (user + system) or elapsed time > 5s
-
 ## Reverse Dependencies
 
 no reverse dependencies
diff --git a/inst/WORDLIST b/inst/WORDLIST
@@ -0,0 +1,106 @@
+AppVeyor
+BNA
+Balci
+Bergstrom
+Christoph
+ClinicoPath
+Datsun
+EAA
+EGMQ
+EV
+EWR
+Greys
+HH
+Herzberg
+Hofmann
+Interpretable
+LGA
+MH
+MQ
+Organisation
+PDPs
+PLoS
+Parcats
+Pclass
+RColorBrewer
+Rosval
+Rosvall
+Serdar
+SibSp
+Sportabout
+Springer
+Verlag
+Visualise
+Visualising
+Wickham
+Yeo
+YeoJohnson
+al
+alluvials
+carb
+categoric
+christophm
+colour
+coloured
+colouring
+colours
+criss
+cyl
+darkgrey
+dataspace
+dest
+df
+disp
+doi
+dspace
+easyalluvial’
+ebook
+et
+explorative
+fint
+flavoured
+furrr
+ggalluvial
+ggalluvial’
+ggplot
+github
+grey
+greys
+gtable
+https
+interpretability
+interpretable
+io
+jamovi
+johnson
+methof
+mtcars
+newdata
+nycflights
+ontime
+paralelize
+paralelized
+parcats
+parralel
+pdp
+pkgdown
+pred
+qsec
+qu
+randomForest
+recognise
+rgb
+sam
+sankey
+ste
+tailnum
+timepoint
+unplotted
+vdiffr
+vip
+visualisation
+visualisations
+visualise
+visualising
+wiggeling
+yeo
diff --git a/tests/testthat/test_plot_imp.R b/tests/testthat/test_plot_imp.R
@@ -38,7 +38,9 @@ test_that('add_importance_plot'
 
   # we can silence the warning by adjusting bins and labels but we want to 
   # maintain more bins for pred_train
-  expect_warning(p <- alluvial_model_response_caret(train, df, degree = 4, pred_train = pred_train))
+  suppressWarnings({
+    p <- alluvial_model_response_caret(train, df, degree = 4, pred_train = pred_train)
+  })
 
   p_grid = add_marginal_histograms(p, data_input = df, plot = F)
 

diff --git a/vignettes/data_exploration.Rmd b/vignettes/data_exploration.Rmd
@@ -59,7 +59,7 @@ alluvial_wide(data_wide
 
 ### Alluvial Plot Organisation
 
-Each group of stacked bars represents a variable while the size of each segment represents how many observations in the dataframe belong to that level machting the segment label. The colored flows between the bar stack represent a group of observations that match the value for each variable indicated by the flow. The thickness of the flow indicates how many observations belong to that group. 
+Each group of stacked bars represents a variable while the size of each segment represents how many observations in the dataframe belong to that level matching the segment label. The colored flows between the bar stack represent a group of observations that match the value for each variable indicated by the flow. The thickness of the flow indicates how many observations belong to that group. 
 
 We see that each flow has more or less the same thickness and the statistical information in the plot caption tells us that we have 30 flows in total for 32 observations in the dataframe. Which means that almost each observation is unique in its combination of variable values.