v1.6.0

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: migraph
 Title: Inferential Methods for Multimodal and Other Networks 
-Version: 1.5.7
-Date: 2026-02-18
+Version: 1.6.0
+Date: 2026-04-04
 Description: A set of tools for testing networks.
    It includes functions for univariate and multivariate 
    conditional uniform graph and quadratic assignment procedure testing,
@@ -22,17 +22,22 @@ RoxygenNote: 7.3.3
 Depends:
     R (>= 3.6.0),
     manynet (>= 1.0.5),
-    autograph (>= 0.4.0)
+    autograph (>= 0.4.0),
+    netrics
 Imports: 
     dplyr (>= 1.1.0),
     ergm,
     future,
     furrr,
     generics,
+    knitr,
+    learnr,
     purrr
 Suggests: 
     covr,
+    rmarkdown,
     roxygen2,
+    shiny,
     testthat (>= 3.0.0)
 Authors@R: 
     c(person(given = "James",
@@ -58,4 +63,4 @@ Authors@R:
 Roxygen: list(markdown = TRUE, roclets = c("namespace", "rd"))
 Config/testthat/parallel: true
 Config/testthat/edition: 3
-Config/testthat/start-first: helper-functions 
+Config/testthat/start-first: tutorials_manynet

NAMESPACE

@@ -12,31 +12,37 @@ S3method(print,netlogit)
 S3method(print,network_test)
 S3method(print,over_memb)
 S3method(summary,diffs_model)
-S3method(summary,ergm)
 S3method(summary,sienaFit)
 S3method(tidy,ergm)
 S3method(tidy,netlm)
 S3method(tidy,netlogit)
 S3method(tidy,sienaFit)
 export("%>%")
+export(extract_tute)
 export(glance)
 export(net_regression)
 export(network_reg)
 export(over_membership)
 export(over_time)
 export(over_waves)
 export(play_diffusions)
+export(run_tute)
 export(test_configuration)
 export(test_distribution)
 export(test_fit)
 export(test_gof)
 export(test_permutation)
 export(test_random)
+export(test_tutorials)
 export(tidy)
 importFrom(autograph,ag_base)
+importFrom(dplyr,"%>%")
 importFrom(dplyr,`%>%`)
+importFrom(dplyr,as_tibble)
 importFrom(dplyr,bind_cols)
 importFrom(dplyr,left_join)
+importFrom(dplyr,select)
+importFrom(dplyr,tibble)
 importFrom(ergm,as.rlebdm)
 importFrom(furrr,furrr_options)
 importFrom(furrr,future_map_dfr)
@@ -50,6 +56,7 @@ importFrom(manynet,is_complex)
 importFrom(manynet,is_directed)
 importFrom(manynet,play_diffusion)
 importFrom(manynet,to_subgraph)
+importFrom(netrics,net_by_heterophily)
 importFrom(purrr,flatten)
 importFrom(stats,as.formula)
 importFrom(stats,binomial)

NEWS.md

@@ -1,10 +1,33 @@
-# migraph 1.5.7
+# migraph 1.6.0
+
+2026-04-04
+
+## Package
+
+- Updated logo
+- Now Depends on `{netrics}`
+- Fixed generic arguments and rely on `dplyr::tibble()` instead of `tibble::tibble()` internally
+
+## Testing
+
+- Fixed `test_permutation()` to use `netrics::net_by_density()`
+- Fixed `net_regression()` to use `manynet::to_permuted()`
+
+## Tutorials
+
+- Moved `run_tute()` and `extract_tute()` from `{manynet}` to here
+- Fixed `fict_marvel` example
+- Fixed diversity tutorial to work with `fict_marvel`
+- Fixed ergm tutorial to work with `{netrics}`
+- Moved tutorial0/data from `{manynet}`
+- Added tutorial testing, with a quiet option
+- Tutorials are highlighted in the README
 
-2026-02-18
+# migraph 1.5.7
 
-- Using fict_marvel in tests
-- Added tidy(), glance(), and summary() methods for sienaFit class objects
-- Added summary.ergm()
+- Using `fict_marvel` in tests
+- Added `tidy()`, `glance()`, and `summary()` methods for sienaFit class objects
+- Added `summary.ergm()`
 
 # migraph 1.5.6
 

R/class_models.R

@@ -98,14 +98,15 @@ tidy.ergm <- function(
 }
 
 #' @method tidy sienaFit
+#' @importFrom dplyr tibble
 #' @export
-tidy.sienaFit <- function(ans){
-  tibble::tibble(
-    dv = ans$effects$name,
-    term = ans$effects$effectName,
-    estimate = ans$theta,
-    se = ans$se,
-    tstat = ans$theta/ans$se
+tidy.sienaFit <- function(x, ...){
+  dplyr::tibble(
+    dv = x$effects$name,
+    term = x$effects$effectName,
+    estimate = x$theta,
+    std.error = x$se,
+    statistic = x$theta/x$se
   )
 }
 
@@ -252,10 +253,10 @@ glance.ergm <- function(x, deviance = FALSE, mcmc = FALSE, ...) {
 
 #' @method glance sienaFit
 #' @export
-glance.sienaFit <- function(ans){
-  tibble::tibble(
-    tmax = ans$tmax,
-    tconv.max = ans$tconv.max[,1]
+glance.sienaFit <- function(x, ...){
+  dplyr::tibble(
+    tmax = x$tmax,
+    tconv.max = x$tconv.max[,1]
   )
 }
 
@@ -275,20 +276,21 @@ print.netlogit <- function(x, ...){
   print(glance(x))
 }
 
-#' @export
-summary.ergm <- function(x, ...){
-  cat("# Fitted model results\n")
-  print(tidy(x))
-  cat("\n# Model summary statistics\n")
-  print(glance(x))
-}
+# Unused because infinite recursion through summary.ergm() in tidy.ergm()
+# #' @export
+# summary.ergm <- function(x, ...){
+#   cat("# Fitted model results\n")
+#   print(tidy(x))
+#   cat("\n# Model summary statistics\n")
+#   print(glance(x))
+# }
 
 #' @export
-summary.sienaFit <- function(x, ...){
+summary.sienaFit <- function(object, ...){
   cat("# Fitted model results\n")
-  print(tidy(x))
+  print(tidy(object))
   cat("\n# Model summary statistics\n")
-  print(glance(x))
+  print(glance(object))
 }
 
 

R/migraph-package.R

@@ -20,15 +20,18 @@ thisRequires <- function(pkgname){
 }
 
 # defining global variables more centrally
-utils::globalVariables(c(".data", "obs", "fin","n","sim","time","value","conf.low","conf.high"))
+utils::globalVariables(c(".data", "obs", "fin","n","sim","time","value","conf.low","conf.high",
+                         "name"))
 
 # Suppress R CMD check note
 # Namespace in Imports field not imported from: PKG
 #   All declared Imports should be used.
 #' @importFrom autograph ag_base
+#' @importFrom netrics net_by_heterophily
 ignore_unused_imports <- function() {
   # This function exists only to reference autograph::ag_base and suppress R CMD check notes about unused imports.
   autograph::ag_base
+  netrics::net_by_heterophily
   NULL
 }
 

R/model_regression.R

@@ -171,14 +171,14 @@ net_regression <- function(formula, .data,
   on.exit(future::plan(oplan), add = TRUE)
     if(valued){
       repdist <- furrr::future_map_dfr(1:times, function(j){
-        nlmfit(c(list(manynet::generate_permutation(g[[1]], with_attr = FALSE)),
+        nlmfit(c(list(manynet::to_permuted(g[[1]], with_attr = FALSE)),
                  g[2:(nx+1)]),
                directed = directed, diag = diag,
                rety = FALSE)
       }, .progress = verbose, .options = furrr::furrr_options(seed = T))
     } else {
       repdist <- furrr::future_map_dfr(1:times, function(j){
-        repfit <- nlgfit(c(list(manynet::generate_permutation(g[[1]], with_attr = FALSE)),
+        repfit <- nlgfit(c(list(manynet::to_permuted(g[[1]], with_attr = FALSE)),
                            g[2:(nx+1)]),
                          directed = directed, diag = diag)
         repfit$coef/sqrt(diag(chol2inv(repfit$qr$qr)))
@@ -207,14 +207,14 @@ net_regression <- function(formula, .data,
       if(valued){
         repdist[,i] <- furrr::future_map_dbl(1:times, function(j){
           nlmfit(c(g[-(1 + i)],
-                   list(manynet::generate_permutation(xres, with_attr = FALSE))),
+                   list(manynet::to_permuted(xres, with_attr = FALSE))),
                  directed = directed, diag = diag,
                  rety = FALSE)[nx]
         }, .progress = verbose, .options = furrr::furrr_options(seed = T))
       } else {
         repdist[,i] <- furrr::future_map_dbl(1:times, function(j){
           repfit <- nlgfit(c(g[-(1 + i)],
-                             list(manynet::generate_permutation(xres, with_attr = FALSE))),
+                             list(manynet::to_permuted(xres, with_attr = FALSE))),
                            directed = directed, diag = diag)
           repfit$coef[nx]/sqrt(diag(chol2inv(repfit$qr$qr)))[nx]
         }, .progress = verbose, .options = furrr::furrr_options(seed = T))

R/model_tests.R

@@ -23,10 +23,10 @@ NULL
 #' @rdname tests 
 #' @importFrom manynet generate_random bind_node_attributes is_directed is_complex
 #' @examples 
-#' marvel_friends <- to_unsigned(ison_marvel_relationships)
-#' marvel_friends <- to_giant(marvel_friends) %>% 
+#' marvel_friends <- fict_marvel %>% to_uniplex("relationship") %>% 
+#'   to_unsigned() %>% to_giant() %>% 
 #'   to_subgraph(PowerOrigin == "Human")
-#' (cugtest <- test_random(marvel_friends, manynet::net_heterophily, attribute = "Attractive",
+#' (cugtest <- test_random(marvel_friends, net_by_heterophily, attribute = "Attractive",
 #'    times = 200))
 #' # plot(cugtest)
 #' @export
@@ -119,7 +119,7 @@ test_configuration <- function(.data, FUN, ...,
 #' @rdname tests 
 #' @examples 
 #' # (qaptest <- test_permutation(marvel_friends, 
-#' #                 manynet::net_heterophily, attribute = "Attractive",
+#' #                 net_by_heterophily, attribute = "Attractive",
 #' #                 times = 200))
 #' # plot(qaptest)
 #' @export
@@ -134,7 +134,7 @@ test_permutation <- function(.data, FUN, ...,
     obsd <- FUN(.data)
   }
   n <- manynet::net_dims(.data)
-  d <- manynet::net_density(.data)
+  d <- netrics::net_by_density(.data)
   oplan <- future::plan(strategy)
   on.exit(future::plan(oplan), add = TRUE)
   rands <- furrr::future_map(1:times, 

R/tutorial_run.R

@@ -0,0 +1,92 @@
+# Tutorials overview ####
+
+#' Open and extract code from tutorials
+#' 
+#' @description 
+#'   These functions make it easy to use the tutorials
+#'   in the `{manynet}` and `{migraph}` packages:
+#'   
+#'   - `run_tute()` runs a `{learnr}` tutorial from 
+#'   either the `{manynet}` or `{migraph}` packages,
+#'   wraps `learnr::run_tutorial()` with some convenience.
+#'   - `extract_tute()` extracts and opens just the solution code
+#'   from a `{manynet}` or `{migraph}` tutorial,
+#'   saving the .R script to the current working directory.
+#'   
+#' @param tute String, name of the tutorial (e.g. "tutorial2").
+#' @importFrom dplyr %>% as_tibble select tibble
+#' @name tutorials
+NULL
+
+stocnet <- c("manynet", "migraph", "autograph")
+
+#' @rdname tutorials 
+#' @export
+run_tute <- function(tute) {
+  thisRequires("learnr")
+  avail_pkgs <- stocnet[suppressWarnings(unlist(lapply(stocnet, 
+                                                       function(x) nzchar(system.file(package = x)))))]
+  if (missing(tute)) {
+    tutelist <- lapply(manynet::snet_progress_along(avail_pkgs, 
+                                               name = "Checking tutorials in stocnet packages"), 
+                       function(p){
+                         dplyr::as_tibble(learnr::available_tutorials(package = avail_pkgs[p]),
+                                          silent = TRUE) %>% dplyr::select(1:3)
+                       })
+    dplyr::bind_rows(tutelist) %>% dplyr::arrange(name) %>% print()
+    manynet::snet_info("You can run a tutorial by typing e.g `run_tute('tutorial1')` or `run_tute('Data')` into the console.")
+  } else {
+    try(learnr::run_tutorial(tute, "manynet"), silent = TRUE)
+    try(learnr::run_tutorial(tute, "migraph"), silent = TRUE)
+    try(learnr::run_tutorial(tute, "autograph"), silent = TRUE)
+    manynet::snet_info("Didn't find a direct match, so looking for close matches...")
+    tutelist <- lapply(manynet::snet_progress_along(avail_pkgs, 
+                                               name = "Checking tutorials in stocnet packages"), function(p){
+                                                 dplyr::as_tibble(learnr::available_tutorials(package = avail_pkgs[p]),
+                                                                  silent = TRUE) %>% dplyr::select(1:3)
+                                               })
+    avails <- dplyr::bind_rows(tutelist)
+    inftit <- grepl(tute, avails$title, ignore.case = TRUE)
+    if(!any(inftit) | sum(inftit)>1)
+      inftit <- which.min(utils::adist(tute, avails$title, ignore.case = TRUE,
+                                       costs = list(ins=0, del=1, sub=1)))
+    if(any(inftit) & sum(inftit)==1){
+      manynet::snet_success("And found one!")
+      try(learnr::run_tutorial(avails$name[inftit], avails$package[inftit]), silent = TRUE)
+    } else{
+      manynet::snet_warn("...and couldn't find which one you meant. Please specify one of these titles:\n")
+      print(avails)
+    }
+  }
+}
+
+#' @rdname tutorials 
+#' @export
+extract_tute <- function(tute) {
+  if (missing(tute)) {
+    thisRequires("learnr")
+    avail_pkgs <- stocnet[suppressWarnings(unlist(lapply(stocnet, function(x) nzchar(system.file(package = x)))))]
+    tutelist <- lapply(manynet::snet_progress_along(avail_pkgs, 
+                                               name = "Checking tutorials in stocnet packages"), function(p){
+                                                 dplyr::as_tibble(learnr::available_tutorials(package = avail_pkgs[p]),
+                                                                  silent = TRUE) %>% dplyr::select(1:3)
+                                               })
+    dplyr::bind_rows(tutelist) %>% dplyr::arrange(name) %>% print()
+    manynet::snet_info("You can extract the code from one of these tutorials by typing e.g `extract_tute('tutorial1')` into the console.")
+  } else {
+    thisRequires("knitr")
+    pth <- file.path(path.package("manynet"), "tutorials", tute)
+    if(!dir.exists(pth)) {
+      thisRequires("autograph")
+      pth <- gsub("manynet", "autograph", pth)
+    }
+    if(!dir.exists(pth)) {
+      thisRequires("migraph")
+      pth <- gsub("autograph", "migraph", pth)
+    }
+    knitr::purl(file.path(pth, list.files(pth, pattern = "*.Rmd")),
+                documentation = 1)
+    utils::file.edit(gsub(".Rmd", ".R", list.files(pth, pattern = "*.Rmd")))
+  }
+}
+