Merge pull request #35 from snlab-ch/develop

v0.3.0

DESCRIPTION

@@ -1,8 +1,8 @@
 Package: manynet
-Title: Many Ways to Make, Manipulate, and Map Myriad Networks
-Version: 0.2.10
-Date: 2023-12-06
-Description: A set of tools for making, manipulating, and mapping many different types of networks.
+Title: Many Ways to Make, Modify, and Map Myriad Networks
+Version: 0.3.0
+Date: 2023-12-15
+Description: A set of tools for making, modifying, and mapping many different types of networks.
    All functions operate with matrices, edge lists, and 'igraph', 'network', and 'tidygraph' objects,
    and on one-mode, two-mode (bipartite), and sometimes three-mode networks.
    The package includes functions for importing and exporting, creating and generating networks,
@@ -20,31 +20,31 @@ Imports:
     dplyr (>= 1.1.0),
     ggplot2,
     ggraph,
-    igraph (>= 1.5.0.1),
+    igraph (>= 1.6.0),
     network,
     tidygraph
 Suggests: 
+    BiocManager,
+    concaveman,
     gganimate,
+    ggforce,
+    gifski,
+    graphlayouts,
+    grDevices,
+    knitr,
+    learnr,
     methods,
+    migraph,
+    minMSE,
+    multiplex,
+    patchwork,
+    png,
     readxl,
+    rmarkdown,
     roxygen2,
     RSiena,
     testthat,
-    xml2,
-    patchwork,
-    rmarkdown,
-    learnr,
-    grDevices,
-    BiocManager,
-    minMSE,
-    graphlayouts,
-    ggforce,
-    multiplex,
-    concaveman,
-    migraph,
-    knitr,
-    gifski,
-    png
+    xml2
 Enhances:
     Rgraphviz
 Authors@R: 

NAMESPACE

@@ -43,7 +43,9 @@ S3method(as_network,network.goldfish)
 S3method(as_network,siena)
 S3method(as_network,tbl_graph)
 S3method(as_siena,igraph)
+S3method(as_siena,tbl_graph)
 S3method(as_tidygraph,data.frame)
+S3method(as_tidygraph,diff_model)
 S3method(as_tidygraph,igraph)
 S3method(as_tidygraph,list)
 S3method(as_tidygraph,matrix)
@@ -248,7 +250,6 @@ export("%>%")
 export(.E)
 export(.G)
 export(.N)
-export(activate)
 export(add_node_attribute)
 export(add_nodes)
 export(add_tie_attribute)
@@ -292,13 +293,11 @@ export(ggplot)
 export(ggsave)
 export(ggtitle)
 export(guides)
-export(iheid_palette)
 export(is.igraph)
 export(is.network)
 export(is.tbl_graph)
 export(is_acyclic)
 export(is_aperiodic)
-export(is_bipartite)
 export(is_complex)
 export(is_connected)
 export(is_directed)
@@ -327,6 +326,7 @@ export(layout_tbl_graph_multilevel)
 export(layout_tbl_graph_quad)
 export(layout_tbl_graph_railway)
 export(layout_tbl_graph_triad)
+export(many_palettes)
 export(mutate)
 export(mutate_ties)
 export(na_to_mean)
@@ -350,17 +350,29 @@ export(rename)
 export(rename_ties)
 export(run_tute)
 export(scale_color_centres)
+export(scale_color_ethz)
 export(scale_color_iheid)
+export(scale_color_rug)
 export(scale_color_sdgs)
+export(scale_color_uzh)
 export(scale_colour_centres)
+export(scale_colour_ethz)
 export(scale_colour_iheid)
+export(scale_colour_rug)
 export(scale_colour_sdgs)
+export(scale_colour_uzh)
 export(scale_fill_centres)
+export(scale_fill_ethz)
 export(scale_fill_iheid)
+export(scale_fill_rug)
 export(scale_fill_sdgs)
+export(scale_fill_uzh)
 export(select_ties)
 export(summarise_ties)
+export(theme_ethz)
 export(theme_iheid)
+export(theme_rug)
+export(theme_uzh)
 export(tie_attribute)
 export(tie_signs)
 export(tie_weights)
@@ -446,10 +458,6 @@ importFrom(ggraph,geom_node_text)
 importFrom(ggraph,get_con)
 importFrom(ggraph,ggraph)
 importFrom(ggraph,scale_edge_width_continuous)
-importFrom(graphics,image)
-importFrom(graphics,par)
-importFrom(graphics,rect)
-importFrom(graphics,text)
 importFrom(igraph,E)
 importFrom(igraph,V)
 importFrom(igraph,add_edges)
@@ -458,8 +466,8 @@ importFrom(igraph,any_multiple)
 importFrom(igraph,as.directed)
 importFrom(igraph,as.undirected)
 importFrom(igraph,as_adjacency_matrix)
+importFrom(igraph,as_biadjacency_matrix)
 importFrom(igraph,as_data_frame)
-importFrom(igraph,as_incidence_matrix)
 importFrom(igraph,bipartite.projection)
 importFrom(igraph,complementer)
 importFrom(igraph,decompose)
@@ -474,8 +482,8 @@ importFrom(igraph,eulerian_path)
 importFrom(igraph,get.edgelist)
 importFrom(igraph,get.vertex.attribute)
 importFrom(igraph,graph_from_adjacency_matrix)
+importFrom(igraph,graph_from_biadjacency_matrix)
 importFrom(igraph,graph_from_data_frame)
-importFrom(igraph,graph_from_incidence_matrix)
 importFrom(igraph,gsize)
 importFrom(igraph,induced_subgraph)
 importFrom(igraph,is.connected)

NEWS.md

@@ -1,3 +1,42 @@
+# manynet 0.3.0
+
+2023-12-15
+
+## Package
+
+* Overhaul of the README to summarise many of the unique aspects of the package
+
+## Making
+
+* Added `as_tidygraph()` method for diff_model objects
+* Added `as_siena()` method for tidygraph objects
+
+## Modifying
+
+* Manipulating functions now called Modifying
+* `to_waves()` now works on diff_model objects, add attributes and names
+* `is_multiplex()` now recognises a tie/edge 'type' attribute as evidence of multiplexity
+* Deleted unnecessary reexports from other packages
+  - `igraph::is_bipartite()` is superseded by `is_twomode()`
+  - `tidygraph::activate()` is superseded by `mutate_ties()` and similar functions
+* Fixed bug by replacing older `igraph::as_incidence_matrix()` and `igraph::graph_from_incidence_matrix()`
+with `igraph::as_biadjacency_matrix()` and `igraph::graph_from_biadjacency_matrix()`
+
+## Mapping
+
+* `autographr()` now plots diff_model objects, showing the diffusion as a heatmap on the vertices
+* `autographs()` and `autographd()` now utilise network information in diff_model objects to provide better layouts 
+* Fixed bug with specifying `node_size` in `autographd()`
+* `many_palettes` replaces `iheid_palette`
+* Added new palettes, themes and scales for graphs
+  - `theme_ethz()`, `scale_color_ethz()`/`scale_colour_ethz()`, and `scale_fill_ethz()` for ETH Zürich
+  - `theme_uzh()`, `scale_color_uzh()`/`scale_colour_uzh()`, and `scale_fill_uzh()` for Uni Zürich
+  - `theme_rug()`, `scale_color_rug()`/`scale_colour_rug()`, and `scale_fill_rug()` for Uni Gröningen
+
+## Data
+
+* Added `ison_physicians` data that includes four, multiplex networks with adoption data
+
 # manynet 0.2.10
 
 2023-12-06

R/data_ison.R

@@ -344,3 +344,56 @@
 #'   ison_friends
 #'   ```
 "ison_friends"
+
+
+# Physicians ####
+
+#' Four multiplex one-mode physician diffusion data (Coleman, Katz, and Menzel, 1966)
+#'
+#' @description
+#'   Ron Burt prepared this data from 
+#'   Coleman, Katz and Menzel's 1966 study on medical innovation. 
+#'   They had collected data from physicians in four towns in Illinois: 
+#'   Peoria, Bloomington, Quincy and Galesburg.
+#'   These four networks are held as separate networks in a list.
+#'   
+#'   Coleman, Katz and Menzel were concerned with the impact of network ties 
+#'   on the physicians' adoption of a new drug, tetracycline. 
+#'   Data on three types of ties were collected in response to three questions:
+#'   
+#'   - advice: "When you need information or advice about questions of therapy 
+#'   where do you usually turn?" 
+#'   - discussion: "And who are the three or four physicians with whom you most often find yourself 
+#'   discussing cases or therapy in the course of an ordinary week – last week for instance?" 
+#'   - friendship: "Would you tell me the first names of your three friends 
+#'   whom you see most often socially?"
+#'   
+#'   Additional questions and records of prescriptions provided additional information: 
+#'   - recorded date of tetracycline `adoption` date
+#'   - years in `practice` 
+#'   (note that these are `{messydates}`-compatible dates)
+#'   - `conferences` attended 
+#'   (those that attended "Specialty" conferences presumably also attended "General" conferences)
+#'   - regular subscriptions to medical `journals`
+#'   - `free_time` spent associating with doctors
+#'   - `discussions` on medical matters when with other doctors sociallyy
+#'   - memberships in `clubs` with other doctores
+#'   - number of top 3 `friends` that are doctors
+#'   - time practicing in current `community`
+#'   - `patients` load (ordinal)
+#'   - physical `proximity` to other physicians (in building/sharing office)
+#'   - medical `specialty` (GP/Internist/Pediatrician/Other)
+#' @docType data
+#' @keywords datasets
+#' @name ison_physicians
+#' @usage data(ison_physicians)
+#' @references
+#'   Coleman, James, Elihu Katz, and Herbert Menzel. 1966.
+#'   \emph{Medical innovation: A diffusion study}.
+#'   Indianapolis: The Bobbs-Merrill Company.
+#' @source `{networkdata}`
+#' @format
+#'   ```{r, echo = FALSE}
+#'   ison_physicians
+#'   ```
+"ison_physicians"

R/make_as.R

@@ -147,7 +147,7 @@ as_edgelist.siena <- function(.data,
 
 #' @rdname as
 #' @importFrom dplyr arrange
-#' @importFrom igraph edge_attr_names as_adjacency_matrix as_incidence_matrix
+#' @importFrom igraph edge_attr_names as_adjacency_matrix as_biadjacency_matrix
 #' @importFrom network is.bipartite list.edge.attributes as.matrix.network
 #' @export
 as_matrix <- function(.data,
@@ -202,10 +202,10 @@ as_matrix.igraph <- function(.data,
                              twomode = NULL) {
   if ((!is.null(twomode) && twomode) | (is.null(twomode) & is_twomode(.data))) {
     if (is_weighted(.data) | is_signed(.data)) {
-      mat <- igraph::as_incidence_matrix(.data, sparse = FALSE,
+      mat <- igraph::as_biadjacency_matrix(.data, sparse = FALSE,
                                          attr = igraph::edge_attr_names(.data)[[1]])
     } else {
-      mat <- igraph::as_incidence_matrix(.data, sparse = FALSE,
+      mat <- igraph::as_biadjacency_matrix(.data, sparse = FALSE,
                                          attr = NULL)
     }
   } else {
@@ -293,7 +293,7 @@ as_matrix.siena <- function(.data,
 # igraph ####
 
 #' @rdname as
-#' @importFrom igraph graph_from_data_frame graph_from_incidence_matrix
+#' @importFrom igraph graph_from_data_frame graph_from_biadjacency_matrix
 #'  graph_from_adjacency_matrix delete_vertex_attr V vertex_attr
 #'  edge_attr delete_edge_attr set_edge_attr
 #' @importFrom network list.edge.attributes as.sociomatrix
@@ -329,11 +329,11 @@ as_igraph.matrix <- function(.data,
                              twomode = FALSE) {
   if (nrow(.data) != ncol(.data) | twomode) {
     if (!(all(.data %in% c(0, 1)))) {
-      graph <- igraph::graph_from_incidence_matrix(.data,
+      graph <- igraph::graph_from_biadjacency_matrix(.data,
                                                    weighted = TRUE,
                                                    directed = FALSE)
     } else {
-      graph <- igraph::graph_from_incidence_matrix(.data,
+      graph <- igraph::graph_from_biadjacency_matrix(.data,
                                                    directed = FALSE)
     }
   } else {
@@ -374,10 +374,10 @@ as_igraph.network <- function(.data,
   if (network::is.bipartite(.data)) {
     if ("weight" %in% network::list.edge.attributes(.data)) {
       graph <- network::as.sociomatrix(.data, attrname = "weight")
-      graph <- igraph::graph_from_incidence_matrix(graph, weighted = TRUE)
+      graph <- igraph::graph_from_biadjacency_matrix(graph, weighted = TRUE)
     } else {
       graph <- network::as.sociomatrix(.data)
-      graph <- igraph::graph_from_incidence_matrix(graph)
+      graph <- igraph::graph_from_biadjacency_matrix(graph)
     }
   } else {
     if ("weight" %in% network::list.edge.attributes(.data)) {
@@ -656,6 +656,17 @@ as_tidygraph.siena <- function(.data, twomode = FALSE) {
   as_tidygraph(as_igraph.siena(.data, twomode = FALSE))
 }
 
+#' @export
+as_tidygraph.diff_model <- function(.data, twomode = FALSE) {
+  out <- as_tidygraph(attr(.data, "network"))
+  attr(out, "diff_model") <- .data
+  if (!"name" %in% names(node_attribute(out))) {
+    out <- add_node_attribute(out, "name",
+                              as.character(seq_len(igraph::vcount(out))))
+  }
+  out
+}
+
 # Network ####
 
 #' @rdname as
@@ -775,6 +786,11 @@ as_siena.igraph <- function(.data, twomode = FALSE) {
   RSiena::sienaDataCreate(list("depnet" = depnet))
 }
 
+#' @export
+as_siena.tbl_graph <- function(.data, twomode = FALSE) {
+  as_siena.igraph(.data, twomode = twomode)
+}
+
 # graphAM ####
 
 #' @rdname as

R/make_create.R

@@ -44,7 +44,7 @@
 #'   using `as_edgelist()`, `as_matrix()`,
 #'   `as_tidygraph()`, or `as_network()`.
 #' @importFrom tidygraph as_tbl_graph
-#' @importFrom igraph graph_from_incidence_matrix
+#' @importFrom igraph graph_from_biadjacency_matrix
 NULL
 
 #' @describeIn create Creates an empty graph of the given dimensions.
@@ -135,7 +135,7 @@ create_ring <- function(n, directed = FALSE, width = 1, ...) {
 
 #' @describeIn create Creates a graph of the given dimensions
 #'   that has a maximally central node.
-#' @importFrom igraph graph_from_adjacency_matrix graph_from_incidence_matrix
+#' @importFrom igraph graph_from_adjacency_matrix graph_from_biadjacency_matrix
 #'   make_star
 #' @examples
 #' create_star(12)
@@ -464,7 +464,7 @@ create_explicit <- function(...){
 # #' Will construct an affiliation matrix,
 # #' with decreasing fill across n2.
 # #' @importFrom tidygraph as_tbl_graph
-# #' @importFrom igraph graph_from_incidence_matrix
+# #' @importFrom igraph graph_from_biadjacency_matrix
 # #' @examples
 # #' create_nest(10, 12)
 # #' @export
@@ -474,7 +474,7 @@ create_explicit <- function(...){
 #   out <- matrix(0, n1, n2)
 #   out[(row(out) - col(out)) >= 0] <- 1
 #   if(as == "tidygraph") out <- tidygraph::as_tbl_graph(out)
-#   if(as == "igraph") out <- igraph::graph_from_incidence_matrix(out)
+#   if(as == "igraph") out <- igraph::graph_from_biadjacency_matrix(out)
 #   out
 # }
 # 

R/manip_from.R

@@ -42,7 +42,6 @@ from_subgraphs <- function(.data) {
 #' @importFrom dplyr distinct
 #' @examples
 #' ison_adolescents %>%
-#'   activate(edges) %>%
 #'   to_egos() %>%
 #'   from_egos()
 #' @export