update vignettes for build on CRAN

DESCRIPTION

@@ -1,8 +1,8 @@
 Package: leiden
 Type: Package
 Title: R Implementation of Leiden Clustering Algorithm
-Version: 0.3.4
-Date: 2020-10-30
+Version: 0.3.5
+Date: 2020-11-09
 Authors@R: c(person("S. Thomas", "Kelly", email = "tom.kelly@riken.jp", role = c("aut", "cre", "trl")),
            person("Vincent A.", "Traag", email = "v.a.traag@cwts.leidenuniv.nl", role = c("com")))
 Description: Implements the 'Python leidenalg' module to be called in R.

NAMESPACE

@@ -28,4 +28,5 @@ importFrom(methods,is)
 importFrom(reticulate,import)
 importFrom(reticulate,py_to_r)
 importFrom(reticulate,r_to_py)
+importFrom(utils,capture.output)
 importFrom(utils,install.packages)

NEWS.md

@@ -1,3 +1,7 @@
+# leiden 0.3.5
+
+* background changes to build vignettes on CRAN
+
 # leiden 0.3.4
 
 * add support for bipartite graphs (requires leidenalg 0.6.1 or later)

R/leiden.R

@@ -421,7 +421,7 @@ numpy <- NULL
 
                 if (all) {
                     suppressWarnings(suppressMessages(suppressPackageStartupMessages(
-                        utils::capture.output(expr, file = file)
+                        capture.output(expr, file = file)
                     )))
                 } else {
                     capture.output(expr, file = file)

README.md

@@ -1,6 +1,6 @@
 # Leiden Algorithm
 
-## leiden version 0.3.4
+## leiden version 0.3.5
 
 [![CRAN_Status_Badge](http://www.r-pkg.org/badges/version/leiden)](https://cran.r-project.org/package=leiden)
 [![Travis Build Status](https://travis-ci.org/TomKellyGenetics/leiden.svg?branch=master)](https://travis-ci.org/TomKellyGenetics/leiden)
@@ -275,15 +275,15 @@ Please cite this implementation R in if you use it:
 To cite the leiden package in publications use:
 
   S. Thomas Kelly (2020). leiden: R implementation of the Leiden algorithm. R
-  package version 0.3.4 https://github.com/TomKellyGenetics/leiden
+  package version 0.3.5 https://github.com/TomKellyGenetics/leiden
 
 A BibTeX entry for LaTeX users is
 
   @Manual{,
     title = {leiden: R implementation of the Leiden algorithm},
     author = {S. Thomas Kelly},
     year = {2020},
-    note = {R package version 0.3.4},
+    note = {R package version 0.3.5},
     url = {https://github.com/TomKellyGenetics/leiden},
   }
  ```

cran-comments.md

@@ -13,11 +13,7 @@
 
 ## Updates
 
-Minor update to implement functions in python version.
-
-Improvements to install of python libraries upon loading if python
-or conda environments are available (checks suppressed on systems
-where they are not).
+Minor update to disable warnings when building vignettes. No GitHub dependencies found if no internet connection.
 
 ## Python integration
 

inst/CITATION

@@ -4,11 +4,11 @@ citEntry(entry = "Manual",
          title        = "leiden: R implementation of the Leiden algorithm",
          author       = personList(as.person("S. Thomas Kelly")),
          year         = "2020",
-         note         = "R package version 0.3.4",
+         note         = "R package version 0.3.5",
          url          = "https://github.com/TomKellyGenetics/leiden",
 
          textVersion  =
-           paste("S. Thomas Kelly (2020). leiden: R implementation of the Leiden algorithm. R package version 0.3.4",
+           paste("S. Thomas Kelly (2020). leiden: R implementation of the Leiden algorithm. R package version 0.3.5",
                  "https://github.com/TomKellyGenetics/leiden")
 )
 

vignettes/benchmarking.Rmd

@@ -269,7 +269,7 @@ The R version can be installed with devtools or from CRAN:
 install.packages("leiden")
 ```
 
-```{r, eval=TRUE, include=FALSE}
+```{r, eval=FALSE, include=FALSE}
 install.packages("leiden",  quiet = TRUE, repos = 1)
 devtools::install_github("TomKellyGenetics/leiden", ref = "dev")
 ```

vignettes/run_bipartite.Rmd

@@ -108,9 +108,8 @@ Here we import a plotting function to display these 2 groups.
 
 ```{r, warning=FALSE, message=FALSE, fig.align='center', out.width="80%",fig.height = 6, fig.width = 6, fig.retina=1.5}
 library("graphsim")
-plot_directed(bipartite_graph,
-              fill.node = c("palevioletred", "lightblue")[as.integer(V(bipartite_graph)$type)+1],
-              cex.arrow = 0.75, col.arrow = "grey75")
+node.cols <- c("palevioletred", "lightblue")[as.integer(V(bipartite_graph)$type)+1]
+plot(bipartite_graph, vertex.color = node.cols, layout = layout.kamada.kawai)
 ```
 
 This data can also be represented by an adjacency matrix derived from a graph object.
@@ -160,7 +159,7 @@ Here we can see partitions in the plotted results. The nodes that are more inter
 ```{r, warning=FALSE, message=FALSE, fig.align='center', out.width="80%",fig.height = 6, fig.width = 6, fig.retina=1.5}
 library("RColorBrewer")
 node.cols <- brewer.pal(max(c(3, partition)),"Pastel1")[partition]
-plot(bipartite_graph, vertex.color = node.cols)
+plot(bipartite_graph, vertex.color = node.cols, layout = layout.kamada.kawai)
 ```
 
 
@@ -188,7 +187,7 @@ Here we can see partitions in the plotted results are different to as those comp
 ```{r, warning=FALSE, message=FALSE, fig.align='center', out.width="80%",fig.height = 6, fig.width = 6, fig.retina=1.5}
 library("RColorBrewer")
 node.cols <- brewer.pal(max(c(3, partition)),"Pastel1")[partition]
-plot(bipartite_graph, vertex.color = node.cols)
+plot(bipartite_graph, vertex.color = node.cols, layout = layout.kamada.kawai)
 ```
 
 #### Resolution Parameter
@@ -213,7 +212,7 @@ Here we can see partitions in the plotted results are the same as those computed
 ```{r, eval=module, warning=FALSE, message=FALSE, fig.align='center', out.width="80%",fig.height = 6, fig.width = 6, fig.retina=1.5}
 library("RColorBrewer")
 node.cols <- brewer.pal(max(c(3, partition)),"Pastel1")[partition]
-plot(bipartite_graph, vertex.color = node.cols)
+plot(bipartite_graph, vertex.color = node.cols, layout = layout.kamada.kawai)
 ```
 
 
@@ -240,5 +239,5 @@ Here we can see partitions in the plotted results are the same as those computed
 ```{r, eval=module, warning=FALSE, message=FALSE, fig.align='center', out.width="80%",fig.height = 6, fig.width = 6, fig.retina=1.5}
 library("RColorBrewer")
 node.cols <- brewer.pal(max(c(3, partition)),"Pastel1")[partition]
-plot(bipartite_graph, vertex.color = node.cols)
+plot(bipartite_graph, vertex.color = node.cols, layout = layout.kamada.kawai)
 ```

vignettes/run_igraph.Rmd

@@ -48,7 +48,7 @@ The current release on CRAN can be installed with:
 install.packages("leiden")
 ```
 
-```{r, eval=TRUE, include=FALSE}
+```{r, eval=FALSE, include=FALSE}
 install.packages("leiden",  quiet = TRUE, repos = 1)
 devtools::install_github("TomKellyGenetics/leiden", ref = "dev")
 ```

vignettes/run_leiden.Rmd

@@ -48,7 +48,7 @@ The current release on CRAN can be installed with:
 install.packages("leiden")
 ```
 
-```{r, eval=TRUE, include=FALSE}
+```{r, eval=FALSE, include=FALSE}
 install.packages("leiden",  quiet = TRUE, repos = 1)
 devtools::install_github("TomKellyGenetics/leiden", ref = "dev")
 ```