Corrections and updates

Author: RonaldVisser

R/clique_community_names_par.R

@@ -17,7 +17,7 @@
 #' @references
 #' Palla, G., Derényi, I., Farkas, I., & Vicsek, T. (2005). Uncovering the overlapping community structure of complex networks in nature and society. Nature, 435(7043), 814-818.
 #'
-#' Code adapted from source: # uit: https://github.com/angelosalatino/CliquePercolationMethod-R/blob/master/clique.community.opt.par.R
+#' Code adapted from source: https://github.com/angelosalatino/CliquePercolationMethod-R/blob/master/clique.community.opt.par.R
 #'
 #' @author Angelo Salatino
 #' @author Ronald Visser

R/cor_mat_overlap.R

@@ -10,6 +10,8 @@
 #'
 #' @returns a list with two matrices: one with the correlation values and one with the number of overlapping tree rings for each correlation value. The matrices have row names and column names of the compared tree-ring curves
 #' @examples
+#' rwl_object1 <- hol_rom
+#' rwl_object2 <- hol_rom
 #' cor_mat_overlap(rwl_object1, rwl_object2, 50)
 #' cor_mat_overlap(rwl_object1, rwl_object1, 50)
 #'

R/wuchswerte.R

@@ -7,7 +7,8 @@
 #' @param x tree-ring series
 #' @returns tree-ring series normalized according to Hollstein (1980, 14-15)
 #' @examples
-#' wuchswerte(trs)
+#' data(hol_rom)
+#' wuchswerte(hol_rom)
 #' # to convert a rwl object into wuchwerte use:
 #' dplR::as.rwl(apply(anos1, 2, wuchswerte))
 #' @export wuchswerte

README.Rmd

@@ -29,7 +29,7 @@ The package aims to make the creation of dendrochronological (provenance) networ
 
 The first steps are visualized in the flowchart below, including community detection using either (or both) the Girvan-Newman algorithm [@girvan2002] and Clique Percolation Method [@palla2005] for all clique sizes.
 
-```{r flowchart of workflow, echo=FALSE, fig.width=15}
+```{r flowchart_workflow, echo=FALSE, fig.width=15}
 DiagrammeR::grViz("
 digraph {
   # graph attributes
@@ -55,7 +55,7 @@ digraph {
 ")
 ```
 
-```{r building a network with Hollstein (1980 data)}
+```{r network_hollstein_1980}
 library(dendroNetwork)
 data(hol_rom) # 1
 sim_table_hol <- sim_table(hol_rom) # 2

README.md

@@ -40,7 +40,7 @@ community detection using either (or both) the Girvan-Newman algorithm
 (Girvan and Newman 2002) and Clique Percolation Method (Palla et al.
 2005) for all clique sizes.
 
-![](README_files/figure-gfm/flowchart%20of%20workflow-1.png)<!-- -->
+![](README_files/figure-gfm/flowchart_workflow-1.png)<!-- -->
 
 ``` r
 library(dendroNetwork)
@@ -53,14 +53,14 @@ hol_com_cpm_all <- find_all_cpm_com(g_hol) # 5
 plot(g_hol)  # plotting the graph in R
 ```
 
-![](README_files/figure-gfm/building%20a%20network%20with%20Hollstein%20(1980%20data)-1.png)<!-- -->
+![](README_files/figure-gfm/network_hollstein_1980-1.png)<!-- -->
 
 ``` r
 plot(g_hol, vertex.color="deepskyblue", vertex.size=15, vertex.frame.color="gray",
      vertex.label.color="darkslategrey", vertex.label.cex=0.8, vertex.label.dist=2) # better readable version
 ```
 
-![](README_files/figure-gfm/building%20a%20network%20with%20Hollstein%20(1980%20data)-2.png)<!-- -->
+![](README_files/figure-gfm/network_hollstein_1980-2.png)<!-- -->
 
 ### Visualization in Cytoscape