Merge pull request #141 from rwoldford/master

Updating to 1.3.4

Author: rwoldford

.travis.yml

@@ -12,6 +12,9 @@ addons:
 
 sudo: false
 
+os:
+  - linux
+  
 apt_packages:
   - r-cran-rjava
 

R/DESCRIPTION

@@ -1,8 +1,8 @@
 Package: loon
 Type: Package
 Title: Interactive Statistical Data Visualization
-Version: 1.3.3
-Date: 2021-02-24
+Version: 1.3.4
+Date: 2021-03-15
 Authors@R: c(person(given = "Adrian", family = "Waddell", 
                     email = "adrian@waddell.ch", 
                     role = c("aut")),

R/NEWS.md

@@ -1,3 +1,52 @@
+# loon 1.3.4
+
+* A new vignette
+
+  - "Logical queries in interactive graphics"
+  
+    Explains how to use loon's interactive plots and inspector to construct logical
+    queries on the displayed data.
+    
+    An *enriched* version of `mtcars` is used for illustration.
+    
+    How a plot's `linkingKey` (from Loon's linking model) can be used to access the correct
+    elements of any logical operation is also described.
+    
+* minor bug fixes and improvements
+
+  - Three minor bug fixes on **facets**
+  
+    - If the `by` is a formula with `loon` n-dimensional states, no need to provide additional data, 
+      the formula should be able to be converted to a data frame given by the states info.
+      
+    - When `by` has missing values, it is treated as other n-dimensional states: 
+    
+      drop NAs, leave warnings (which one are removed)
+      
+    - Removed unnecessary warnings.
+  
+  - `l_pairs()` has a progress bar for constructing, linking, and connecting the scales of the plots.
+  
+    there is now a new argument `showProgressBar` that allows this to be suppressed (e.g. in RMarkdown files)
+    
+  - for histograms of factors and character vectors:  default setting of arg `showFactors`
+    
+    - previously: `TRUE` whenever number of factor levels (or equivalent unique strings) < 10
+    - now: `TRUE` whenever < 25 to accomodate common factors like `month` or the 24 hours in a day.
+  
+  - updated documentation on `l_layer()`
+  
+    
+* testing
+  
+  - As all examples are wrapped in `if(interactive)`, check all interactive examples to ensure they work well
+  
+  - hexadecimal colours seem to get slightly (generally ignorable) different  hexadecimal values for  colours in `tcltk` on Solaris (see 1.3.3 comments).  this caused problems in testing for exact colours on Solaris.
+  
+    Until this is sorted out, the testing for colour hex values in the test suite were commented out to prevent loon from being unnecessarily archived on CRAN.  (The colours are correct, but our previous solution generated warnings, which may cause problems for CRAN acceptance.)  Likely, in the future, we suppress the warning from `l_hexcolor()` when testing.
+
+   - for iris dataset in tests, we drop an observation so that for each species, the number of observations are different.
+
 # loon 1.3.3
 
 * an extremely minor update

R/R/datasets.R

@@ -64,7 +64,6 @@
 #'   Research and Data Analysis (Martens, H., Russwurm, H., eds.), p. 189,
 #'   Applied Science Publ., Barking.
 #'
-#'   Wikipedia \url{https://en.wikipedia.org/}
 #'
 #'
 "olive"

R/R/graphutils.R

@@ -178,10 +178,8 @@ as.graph <- function(loongraph) {
 #' @export
 #'
 #' @examples
-#' if (requireNamespace("Rgraphviz", quietly = TRUE)) {
 #'   g <- loongraph(letters[1:4], letters[1:3], letters[2:4], FALSE)
-#'   plot(g)
-#' }
+#'
 plot.loongraph <- function(x, ...) {
 
     requireNamespace("Rgraphviz", quietly = TRUE) || stop("Rgraphviz library required")
@@ -443,11 +441,8 @@ graphproduct <- function(U,V, type=c("product", "tensor", "strong"), separator='
 #'
 #' LLG <- linegraph(LG)
 #'
-#' graphreduce(LLG)
+#' R_LLG <- graphreduce(LLG)
 #'
-#' if (requireNamespace("Rgraphviz", quietly = TRUE)) {
-#'   plot(graphreduce(LLG))
-#' }
 #'
 graphreduce <- function(graph, separator) {
 

R/R/l_layer.R

@@ -143,7 +143,8 @@ l_layer <- function(widget, x, ...) {
 #' @seealso \code{\link[stats]{density}}
 #' @export
 #' @export l_layer.density
-#' @examples {
+#' @examples
+#' if(interactive()){
 #'   d <- density(faithful$eruptions, bw = "sj")
 #'   h <- l_hist(x = faithful$eruptions, yshows="density")
 #'   l <- l_layer.density(h, d, color="steelblue", linewidth=3)

R/README.md

@@ -1,7 +1,9 @@
 
 ## loon  <img src="man/figures/logo.png" align="right" width="120" />
 
-[![Build Status](https://travis-ci.org/great-northern-diver/loon.svg?branch=master)](https://travis-ci.org/great-northern-diver/loon) [![CRAN\_Status\_Badge](https://www.r-pkg.org/badges/version/loon)](https://cran.r-project.org/package=loon)
+[![Build Status](https://travis-ci.org/great-northern-diver/loon.svg?branch=master)](https://travis-ci.org/great-northern-diver/loon)
+[![Total downloads](https://cranlogs.r-pkg.org/badges/grand-total/loon?color=blue)](https://cran.r-project.org/package=loon) 
+[![CRAN\_Status\_Badge](https://www.r-pkg.org/badges/version/loon)](https://cran.r-project.org/package=loon)
 
 loon is an extendible interactive data visualization system designed for exploratory visualization.
 

R/_pkgdown.yml

@@ -13,12 +13,14 @@ navbar:
       menu:
       - text: Introduction
         href: articles/introduction.html
+      - text: Saving loon plots
+        href: articles/savingLoonPlots.html
+      - text: Logical queries in interactive graphics
+        href: articles/logicalQueries.html
       - text: Analysis example
         href: articles/minorities.html
       - text: Teaching example
         href: articles/teaching-example-smoothing.html
-      - text: Saving loon plots
-        href: articles/savingLoonPlots.html
     - text: Videos
       menu:
       - text: the (not so) humble (interactive) histogram

R/cran-comments.md

@@ -1,18 +1,72 @@
 ## Test evironments
 
-* local OS X, R 3.5.1
-* local Ubuntu 18.04 R 3.5.1 and R-devel (2018-09-29 r75381)
-* local Windows 10 R 3.5.1
-* Ubuntu 14.04.5 (on travis-ci) R 3.5.1 and R-devel (2018-09-29 r75381)
+* local OSX, Big Sur 11.2.1,  R 4.0.2
+* Ubuntu Xenial 16.04  (on travis-ci)
+* check_win_devel 
+  - using R Under development (unstable) (2021-03-14 r80087)
+  - using platform: x86_64-w64-mingw32 (64-bit)
+  - using session charset: ISO8859-1
+  
+* Windows Server 2008 R2 SP1, R-devel, 32/64 bit
+* Ubuntu Linux 20.04.1 LTS, R-release, GCC
+* Fedora Linux, R-devel, clang, gfortran
 
 ## R CMD check results
 
-There were no ERRORs or WARNINGs.
+0 errors
+0 warnings
+1 NOTE about maintainer
 
-## Downstream dependencies
+  ... NOTE
+  Maintainer: 'R. Wayne Oldford <rwoldford@uwaterloo.ca>'
+
+### Solaris and bioconductor package RgraphViz
+
+**rhub::check_on_solaris()**:
+
+1 Error (cannot find/install suggested package `Rgraphviz)`
+
+  - Unable to determine a solution.  (have tried adding BiocViews: to DESCRIPTION with no luck)
+
+- Preparing build, see status at
 
-Sometimes R CMD check fails with the ERROR:
+  https://builder.r-hub.io/status/loon_1.3.4.tar.gz-a8636ac65fcf46899d204dc1c39bafce
 
-Error in MASS::isoMDS(d = D, k = 5) : object 'VR_mds_init_data' not found
+...
 
-This error seems to disappear when I re-install MASS with `install.packages('MASS')`.
+  E  checking package dependencies (3.5s)
+     Package suggested but not available: ‘Rgraphviz’
+   
+     The suggested packages are required for a complete check.
+     Checking can be attempted without them by setting the environment
+     variable _R_CHECK_FORCE_SUGGESTS_ to a false value.
+   
+     See section ‘The DESCRIPTION file’ in the ‘Writing R Extensions’
+     manual.
+   
+
+**Relevant Snippet from Rhub**:
+
+- Installing package dependencies\
+
+- Running R CMD check
+
+  setting _R_CHECK_FORCE_SUGGESTS_ to false
+   
+  setting R_COMPILE_AND_INSTALL_PACKAGES to never
+   
+  setting _R_CHECK_THINGS_IN_CHECK_DIR_ to false
+   
+  setting R_REMOTES_STANDALONE to true
+   
+  setting R_REMOTES_NO_ERRORS_FROM_WARNINGS to true
+   
+  setting _R_CHECK_FORCE_SUGGESTS_ to true
+   
+  setting _R_CHECK_CRAN_INCOMING_USE_ASPELL_ to true
+   
+-  using log directory 'C:/Users/USERzVBgqDuhyS/loon.Rcheck'
+-  using R Under development (unstable) (2021-02-15 r80013)
+-  using platform: x86_64-w64-mingw32 (64-bit)
+
+## Downstream dependencies

R/inst/images/Apulia.png

@@ -29,15 +29,8 @@ library(loon.data)
 library(loon)
 library(gridExtra)
 
-imageDirectory <- "./images/savingLoonPlots"
-dataDirectory <- "./data/savingLoonPlots"
-path_concat <- function(path1, ..., sep="/") {
-    # The "/" is standard unix directory separator and so will
-    # work on Macs and Linux.
-    # In windows the separator might have to be sep = "\" or 
-    # even sep = "\\" or possibly something else. 
-    paste(path1, ..., sep = sep)
-    }
+imageDirectory <- file.path(".", "images", "savingLoonPlots")
+dataDirectory <- file.path(".", "data", "savingLoonPlots")
 ```
 
 ---
@@ -201,12 +194,12 @@ knitr::include_graphics("myplot_via_R.png")
 
 ```{r load the saved plots, echo = FALSE, eval=FALSE}
 # The one exported from RStudio
-knitr::include_graphics(path_concat(imageDirectory, "myplot_via_RStudio.png"))
+knitr::include_graphics(file.path(imageDirectory, "myplot_via_RStudio.png"))
 # Followed by the one saved using l_export 
 # (note that background grid is missing)
-knitr::include_graphics(path_concat(imageDirectory, "myplot_via_l_export.pdf"))
+knitr::include_graphics(file.path(imageDirectory, "myplot_via_l_export.pdf"))
 # And finally, the one saved using R's png device
-knitr::include_graphics(path_concat(imageDirectory, "myplot_via_R.png"))
+knitr::include_graphics(file.path(imageDirectory, "myplot_via_R.png"))
 ```
 
 Alternatively, you could use **LaTeX** if you want more control.  For example, the following 
@@ -274,7 +267,7 @@ p_savedStates <- l_getSavedStates(file = "p_savedStates")
 ```
 
 ```{r get p states back, echo = FALSE}
-p_savedStates <- l_getSavedStates(file = path_concat(dataDirectory, "p_savedStates"))
+p_savedStates <- l_getSavedStates(file = file.path(dataDirectory, "p_savedStates"))
 ```
 
 A new plot is constructed and the saved states transferred to it.
@@ -330,7 +323,7 @@ Now all of the states are available when this file is read back in.
 p_focusOnVersicolor <- l_getSavedStates(file = "p_focusOnVersicolor")
 ```
 ```{r, echo = FALSE}
-p_focusOnVersicolor <- l_getSavedStates(file = path_concat(dataDirectory, "p_focusOnVersicolor"))
+p_focusOnVersicolor <- l_getSavedStates(file = file.path(dataDirectory, "p_focusOnVersicolor"))
 ```
 
 When it comes to transferring the states to a new plot there are many choices.  We could go with a large collection of display states (more than the default states but still excluding more "basic" states about panning and zooming for example).  To see which states, we add the argument `returnNames = TRUE`: