Merge pull request #230 from snlab-ch/develop

v0.10.2

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: migraph
 Title: Multimodal and Multilevel Network Analysis
-Version: 0.10.1
-Date: 2022-06-17
+Version: 0.10.2
+Date: 2022-06-20
 Description: A set of tools that extend common social network analysis packages
    for analysing multimodal and multilevel networks.
    It includes functions for one- and two-mode (and sometimes three-mode) 

NEWS.md

@@ -1,3 +1,9 @@
+# migraph 0.10.2
+
+## Memberships
+
+- Further shortened equivalence examples
+
 # migraph 0.10.1
 
 ## Measures
@@ -7,7 +13,7 @@
 
 ## Memberships
 
-- Trimmed equivalence examples
+- Shortened equivalence examples
 
 # migraph 0.10.0
 

R/member_equivalence.R

@@ -82,9 +82,8 @@ node_equivalence <- function(object, census,
 #' @describeIn equivalence Returns nodes' membership in 
 #'   structurally equivalent classes
 #' @examples
-#' (nse_conc <- node_structural_equivalence(ison_southern_women, 
-#'                   cluster = "concor"))
-#' plot(nse_conc)
+#' (nse <- node_structural_equivalence(mpn_elite_usa_advice))
+#' plot(nse)
 #' @export
 node_structural_equivalence <- function(object,
                                         k = c("silhouette", "elbow", "strict"),
@@ -102,9 +101,6 @@ node_structural_equivalence <- function(object,
 
 #' @describeIn equivalence Returns nodes' membership in 
 #'   regularly equivalent classes
-#' @examples
-#' (nre <- node_regular_equivalence(ison_algebra, "elbow"))
-#' plot(nre)
 #' @export
 node_regular_equivalence <- function(object, 
                                      k = c("silhouette", "elbow", "strict"),
@@ -124,9 +120,6 @@ node_regular_equivalence <- function(object,
 
 #' @describeIn equivalence Returns nodes' membership in 
 #'   automorphically equivalent classes
-#' @examples 
-#' (nae <- node_automorphic_equivalence(mpn_elite_usa_advice))
-#' plot(nae)
 #' @export
 node_automorphic_equivalence <- function(object,
                                          k = c("silhouette", "elbow", "strict"),

tests/testthat/test-model_regression.R

@@ -34,3 +34,9 @@ test_that("glance works correctly for network_reg",{
   expect_s3_class(glances, "tbl_df")
   expect_equal(round(glances$r.squared, 4), 0.0575)
 })
+
+plots <- plot(test)
+test_that("plot works correctly for network_reg",{
+  expect_s3_class(plots, "gg")
+  expect_equal(plots$labels$x, "Statistic")
+})