Merge pull request #75 from stocnet/develop

v1.0.2

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: manynet
-Title: Many Ways to Make, Modify, Mark, and Map Myriad Networks
-Version: 1.0.1
-Date: 2024-07-08
+Title: Many Ways to Make, Modify, Map, Mark, and Measure Myriad Networks
+Version: 1.0.2
+Date: 2024-07-20
 Description: Many tools for making, modifying, mapping, marking, measuring, 
    and motifs and memberships of many different types of networks.
    All functions operate with matrices, edge lists, and 'igraph', 'network', and 'tidygraph' objects,
@@ -16,7 +16,7 @@ License: MIT + file LICENSE
 Language: en-GB
 Encoding: UTF-8
 LazyData: true
-RoxygenNote: 7.3.1
+RoxygenNote: 7.3.2
 Imports:
     dplyr (>= 1.1.0),
     ggplot2,

NEWS.md

@@ -1,3 +1,36 @@
+# manynet 1.0.2
+
+## Package
+
+- Added alttext to images in the README, tutorials, and website
+- Added CRAN link to homepage
+- Updated favicons
+- Added more structure to the function overview
+
+## Making
+
+- Updated intro tutorial with images, exercises, questions, and more explanation and structure
+- Updated data tutorial with images, new function names, questions, and more explanation and structure
+- Updated data tutorial with more details on adding and deleting nodes, ties, and attributes
+- Updated topology tutorial with new function names and more structure
+
+## Mapping
+
+- Updated viz tutorial with examples of `graphs()` and `grapht()`
+- Updated viz tutorial with more details and examples on colors and theming
+- Updated viz tutorial with overview, examples, and details on layouts,
+including force-directed, layered, circular, spectral, and grid layouts
+
+## Measures
+
+- Updated centrality tutorial with images, new function names, and more structure
+- Updated centrality tutorial with more interpretation of centrality measures
+- Updated position tutorial with new function names and more structure
+
+## Memberships
+
+- Updated community tutorial with new function names and more structure
+
 # manynet 1.0.1
 
 ## Package
@@ -13,6 +46,7 @@
 - Renamed all functions starting with the `network_*` prefix to `net_*` for conciseness
 - Migrated network measures, membership, motifs, and models' functions from `{migraph}`
 - Migrated community, position, topology, and diffusion tutorials from `{migraph}`
+- Added descriptions to tutorials
 
 ## Making
 
@@ -46,13 +80,16 @@ and `node_is_infected()` (closes #71)
 
 ## Modifying
 
-- Fixed bug in `as_diff_model()` where events were out of order and named
-- Added `to_correlation()` that implements pairwise correlation on network
-- Added `arrange_ties()` for `{dplyr}`-like reordering of ties based on some attribute
 - `to_named()` now randomly generates and adds an alphabetic sequence of names,
   where previously this was just a random sample,
   which may assist pedagogical use
   - baby_names (internal) now includes a few extra "Q" and "U" names
+- Added `to_correlation()` that implements pairwise correlation on network
+- Added `arrange_ties()` for `{dplyr}`-like reordering of ties based on some attribute
+- Added `to_correlation()` for calculating the Pearson correlation
+  - This takes a method argument for "all", "diag", "recip", or "complex"
+  - These are similar to functions implemented by Ron Breiger and shared by him in correspondence
+- Fixed bug in `as_diff_model()` where events were out of order and named
 
 ## Marking
 
@@ -101,35 +138,56 @@ and `node_is_infected()` (closes #71)
     - Updated `node_attribute()` and `tie_attribute()` to return measures
     when the output is numeric
 - Updated `node_exposure()` to work with two-mode and signed networks
+- Fixed `node_constraint()` to work with weighted two-mode networks, thanks to Toshitaka Izumi for spotting this
+- All measure functions can now be used in e.g. `mutate()` without specifying `.data`
+- Added `net_independence()` for calculating the number of nodes in the largest independent set
+- `node_coreness()` now returns 'node_measure' output
+- `node_exposure()` now sums tie weights where passed a weighted network
 
 ## Members
 
 - Migrated members from `{migraph}`
-  - Cliques memberships includes `node_in_roulette()`
-  - Community and hierarchical memberships includes `node_in_optimal()`, `node_in_partition()`,
+  - Cliques memberships `node_in_roulette()` (previously `node_roulette()`)
+  - Community and hierarchical memberships includes `node_in_optimal()`, 
+  `node_in_partition()` (previously `node_kernaghinlin()`),
   `node_in_infomap()`, `node_in_spinglass()`, `node_in_fluid()`, 
   `node_in_louvain()`, `node_in_leiden()`, `node_in_betweenness()`,
   `node_in_greedy()`, `node_in_eigen()`, and `node_in_walktrap()`
   - Components' memberships include `node_in_component()`, `node_in_weak()`, and
-  `node_in_strong()`
+  `node_in_strong()` (NB: `node_in_component()` is no longer phrased in the plural)
   - Core-periphery memberships include `node_is_core()` and `node_coreness()`
   - Diffusion memberships include `node_in_adopter()`
   - Equivalence memberships include `node_in_equivalence()`, `node_in_structural()`,
   `node_in_regular()`, and `node_in_automorphic()`
   - Note that these functions were previously named `node_*()`, but including the preposition `_in_` is more consistent.
+- `node_member` class is now categorical
+  - `make_node_member()` now converts numeric results to LETTER character results
+  - `print.node_member()` now works with categorical membership vectors
+  - `print.node_member()` now declares how many groups before reporting the vectors
+- All membership functions can now be used in e.g. `mutate()` without specifying `.data`
+- Hierarchical clustering algorithms now return dendrograms
 
 ## Motifs
 
 - Migrated motifs to take census of network, node positions, and brokerage from `{migraph}`,
 these include `node_by_tie()`, `node_by_triad()`, `node_by_quad()`, `node_by_path()`, 
 `net_by_dyad()`, `net_by_triad()`, `net_by_mixed()`, `node_by_brokerage()`, `net_by_brokerage()`
   - Note that these functions were previously named `*_*_census()`, but the preposition `_by_` is more consistent.
+- `node_tie_census()` now works on longitudinal network data
+- Fixed bug where `print.node_motif()` wasn't printing the requested number of lines
 
 ## Methods
 
 - Migrated methods from `{migraph}`
   - Methods for equivalence clustering include `cluster_hierarchical()` and `cluster_concor()`
   - Methods for selecting clusters include `k_strict()`, `k_elbow()`, and `k_silhouette()`
+- Several improvements to `cluster_concor()`
+  - `cluster_concor()` now uses `to_correlation()` for initial correlation
+  - It still uses `stats::cor()` for subsequent iterations
+  - Fixed how `cluster_concor()` handles unlabelled networks
+  - Fixed how `cluster_concor()` handles two-mode networks
+  - Fixed bug where `cluster_concor()` cutoff resulted in unsplit groups
+- `cluster_hierarchical()` now also uses `to_correlation()`
 
 ## Data
 

R/reexports_classes.R

@@ -42,7 +42,7 @@ expect_nodes <- function() {
 
 expect_edges <- function() {
   if (!tidygraph::.graph_context$free() && tidygraph::.graph_context$active() != "edges") {
-    stop("This call requires edges to be active", call. = FALSE)
+    stop("This call requires ties to be active", call. = FALSE)
   }
 }