v1.6.6

DESCRIPTION

@@ -1,10 +1,9 @@
 Package: migraph
 Title: Inferential Methods for Multimodal and Other Networks 
-Version: 1.6.5
+Version: 1.6.6
 Description: A set of tools for testing networks.
-   It includes functions for univariate and multivariate 
-   conditional uniform graph and quadratic assignment procedure testing,
-   and network regression.
+   It includes functions for univariate and multivariate conditional uniform graph 
+   and quadratic assignment procedure testing, and network regression.
    The package is a complement to 
    'Multimodal Political Networks' (2021, ISBN:9781108985000),
    and includes various datasets used in the book.
@@ -20,7 +19,7 @@ LazyData: true
 Depends:
     R (>= 4.1.0),
     manynet (>= 2.1.2),
-    autograph (>= 0.4.0),
+    autograph (>= 1.0.0),
     netrics (>= 0.3.1)
 Imports: 
     dplyr (>= 1.1.0),

NEWS.md

@@ -1,3 +1,12 @@
+# migraph 1.6.6
+
+2026-06-23
+
+## Package
+
+- Improved goodpractices
+- Dropped netrics tutorial testing
+
 # migraph 1.6.5
 
 2026-06-22

R/class_makes.R

@@ -24,6 +24,7 @@ print.diffs_model <- function(x, ...){
   x <- x[,colSums(x, na.rm=TRUE) != 0]
   x$I_new <- NULL
   print(dplyr::tibble(x, ...))
+  invisible(x)
 }
 
 ## Over ####
@@ -37,6 +38,7 @@ make_over_memb <- function(out, categ) {
 #' @export
 print.over_memb <- function(x, ...){
   print(round(unclass(x),3), ...)
+  invisible(x)
 }
 
 

R/class_models.R

@@ -266,6 +266,7 @@ print.netlm <- function(x, ...){
   print(tidy(x))
   cat("\n# Model summary statistics\n")
   print(glance(x))
+  invisible(x)
 }
 
 #' @export
@@ -274,6 +275,7 @@ print.netlogit <- function(x, ...){
   print(tidy(x))
   cat("\n# Model summary statistics\n")
   print(glance(x))
+  invisible(x)
 }
 
 # Unused because infinite recursion through summary.ergm() in tidy.ergm()

R/model_tests.R

@@ -172,5 +172,6 @@ print.network_test <- function(x, ...,
   cat("Observed Value:", x$testval, "\n")
   cat("Pr(X>=Obs):", x$pgteobs, "\n")
   cat("Pr(X<=Obs):", x$plteobs, "\n\n")
+  invisible(x)
 }
 

cran-comments.md

@@ -11,3 +11,7 @@
 
 - Updated manynet dependency to 1.2.1 to fix reverse dependency issue
 - Updated netrics dependency to 0.3.1 to fix reverse dependency issue
+- Checked with CRAN versions of dependencies
+  - Only issue was CRAN versions of manynet and netrics built under R v4.6.1,
+  whereas this package was built locally under R v4.6.0, 
+  though this should not be a problem for CRAN submission.

inst/tutorials/tutorial0/tutorial0.Rmd

@@ -105,7 +105,7 @@
 Remove the hash symbol at the start of this line to run it:
 
 ```{r comments, exercise = TRUE}
 # 1/5 # this will still be commented...
 ```
 
 In an R script you can toggle commenting for one or more lines using Cmd-Shift-C/Ctrl-Shift-C.
@@ -148,9 +148,9 @@
 In R, we can write such logical statements as:
 
 ```{r equivalence, exercise = TRUE}
 "James"=="james" # Try also "James"!="james"
 # Other logical statements include: ">", ">=", "<=", "<".
 # 1 < 5 # Try also "1 <= 5"
 ```
 
 Logical values are always either `TRUE` or `FALSE`,
@@ -168,10 +168,11 @@
 
 ```{r assignment, exercise = TRUE}
 surname <- "Hollway"
 y.chromosome <- T # or TRUE
 siblings <- 1
 age <- NA # This is used for missing information
-# Note that these objects then appear in RStudio's environment pane (by default the top right)
+# Note that these objects then appear in RStudio's environment pane 
+# (by default the top right)
 ```
 
 You can then recover this information by simply calling these objects:
@@ -186,7 +187,7 @@
 And even operate on them:
 
 ```{r mult, exercise = TRUE, exercise.setup = "assignment"}
 siblings*3
 # Try multiplying the other objects by 3
 ```
 
@@ -211,10 +212,11 @@
 ```{r series, exercise = TRUE}
 teenageyrs <- 13:19
 teenageqrtrs <- seq(13, 19.99, by = 0.25)
 # We can recall every third value from this object using a repeating vector 
 teenageqrtrs
 teenageqrtrs[c(FALSE, FALSE, TRUE)]
-# teenageqrtrs[c(F, F, T)] # Also works but it is best practice to write out the logic.
+# teenageqrtrs[c(F, F, T)] 
+# Also works but it is best practice to write out the logic.
 ```
 
 So R can help us store and recall values and even vectors of values,
@@ -327,7 +329,8 @@
 You can also add lists to a list:
 
 ```{r list-nest, exercise = TRUE, exercise.setup="list-names"}
-mylist$Lived <- list(c("New Zealand", "UK", "New Zealand", "Germany", "UK", "Switzerland"), NA)
+mylist$Lived <- list(c("New Zealand", "UK", "New Zealand", 
+                       "Germany", "UK", "Switzerland"), NA)
 ```
 
 Note that we've been using parentheses, `()`, here and not brackets, `[]`,

inst/tutorials/tutorial8/diversity.Rmd

@@ -49,7 +49,7 @@ learnr::random_phrases_add(language = "en",
                                       "Beau travail!",
                                       "Bravo!",
                                       "Super!"),
-                           encouragement = c("Bon effort"))
+                           encouragement = "Bon effort")
 marvel_friends <- to_unsigned(to_uniplex(fict_marvel, "relationship"), keep = "positive")
 marvel_friends <- to_giant(marvel_friends)
 marvel_friends <- marvel_friends %>% to_subgraph(Appearances >= mean(Appearances))

inst/tutorials/tutorial9/ergm.Rmd

@@ -54,7 +54,7 @@ learnr::random_phrases_add(language = "en",
                                       "Beau travail!",
                                       "Bravo!",
                                       "Super!"),
-                           encouragement = c("Bon effort"))
+                           encouragement = "Bon effort")
 ```
 
 ## This tutorial
@@ -282,10 +282,10 @@ how much change there is depends critically on “where you are on the curve”.
 ```{r predprobplot, echo = F, fig.height=3, fig.width=8, purl = FALSE}
   ggplot(data.frame(x = c(-4, 4)), aes(x = x)) +
     ggplot2::stat_function(fun = plogis, colour = "blue") +
-    ggplot2::geom_line(aes(x = 0, y=c(.5,.73), colour = "+1 unit change @0")) +
-    ggplot2::geom_line(aes(x = c(0,1), y=.73, colour = "+1 unit change @0")) +
-    ggplot2::geom_line(aes(x = 1, y=c(.73,.88), colour = "+1 unit change @1")) +
-    ggplot2::geom_line(aes(x = c(1,2), y=.88, colour = "+1 unit change @1")) +
+    ggplot2::geom_line(aes(x = 0, y=c(0.5,.73), colour = "+1 unit change @0")) +
+    ggplot2::geom_line(aes(x = c(0,1), y=0.73, colour = "+1 unit change @0")) +
+    ggplot2::geom_line(aes(x = 1, y=c(0.73,0.88), colour = "+1 unit change @1")) +
+    ggplot2::geom_line(aes(x = c(1,2), y=0.88, colour = "+1 unit change @1")) +
     ggplot2::theme_minimal()
 ```
 

tests/testthat/test-model_tests.R

@@ -17,7 +17,7 @@ test_that("test_random works", {
   # Set the cugtest up
   # Test stuff cug1
   expect_equal(as.numeric(cugtest$testval), -0.85714, tolerance = 0.001)
-  expect_equal(length(cugtest$testdist), 200) # NB: Stochastic
+  expect_length(cugtest$testdist, 200) # NB: Stochastic
   expect_false(cugtest$mode)
   expect_false(cugtest$diag)
   expect_equal(cugtest$cmode, "edges")
@@ -28,7 +28,7 @@ test_that("test_random works", {
   # Test stuff cug2
   expect_equal(as.numeric(cugtest2$testval), 0.2375, tolerance = 0.001)
   # expect_equal(mean(cugtest3$testdist), 0.3600, tolerance = 0.02)
-  expect_equal(length(cugtest2$testdist), 200) # NB: Stochastic
+  expect_length(cugtest2$testdist, 200) # NB: Stochastic
   expect_false(cugtest2$mode)
   expect_false(cugtest2$diag)
   expect_equal(cugtest2$cmode, "edges")
@@ -46,9 +46,9 @@ qaptest <- test_permutation(marvel_friends,
 
 test_that("test_permutation works", {
   expect_equal(as.numeric(qaptest$testval), -0.85714, tolerance = 0.001)
-  expect_equal(length(qaptest$testdist), 200) # NB: Stochastic
   expect_equal(class(qaptest$plteobs), "numeric") # NB: Stochastic
   expect_equal(class(qaptest$pgteobs), "numeric") # NB: Stochastic
+  expect_length(qaptest$testdist, 200) # NB: Stochastic
   expect_equal(qaptest$reps, 200)
   expect_s3_class(qaptest, "network_test")
 })
@@ -62,9 +62,9 @@ test_that("test_configuration works", {
                                    times = 200)
   expect_s3_class(configtest, "network_test")
   expect_equal(as.numeric(configtest$testval), -0.85714, tolerance = 0.001)
-  expect_equal(length(configtest$testdist), 200) # NB: Stochastic
   expect_equal(class(configtest$plteobs), "numeric") # NB: Stochastic
   expect_equal(class(configtest$pgteobs), "numeric") # NB: Stochastic
+  expect_length(configtest$testdist, 200) # NB: Stochastic
 })