Merge pull request #296 from stocnet/develop

v1.4.1

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: migraph
-Title: Univariate and multivariate tests for multimodal and other networks 
-Version: 1.4.0
-Date: 2024-07-18
+Title: Univariate and Multivariate Tests for Multimodal and Other Networks 
+Version: 1.4.1
+Date: 2024-07-19
 Description: A set of tools for testing networks.
    It includes functions for univariate and multivariate 
    conditional uniform graph and quadratic assignment procedure testing,
@@ -24,25 +24,15 @@ Depends:
     manynet
 Imports: 
     dplyr (>= 1.1.0),
-    generics,
-    ggplot2,
-    igraph (>= 1.5.0),
-    network,
     future,
     furrr,
-    purrr,
-    tidygraph,
-    tidyr
+    generics,
+    ggplot2,
+    purrr
 Suggests: 
-    concaveman,
     covr,
-    ggdendro,
-    minMSE,
-    oaqc,
     roxygen2,
-    rsconnect,
-    testthat,
-    xml2
+    testthat
 Authors@R: 
     c(person(given = "James",
              family = "Hollway",

NAMESPACE

@@ -9,32 +9,22 @@ S3method(print,network_test)
 S3method(tidy,netlm)
 S3method(tidy,netlogit)
 export("%>%")
-export(.E)
-export(.G)
-export(.N)
 export(aes)
-export(as.network)
-export(bind_edges)
 export(ggplot)
 export(ggsave)
 export(ggtitle)
 export(glance)
 export(guides)
-export(is.network)
-export(is.tbl_graph)
-export(is_igraph)
 export(labs)
-export(mutate)
+export(net_regression)
 export(network_reg)
-export(rename)
 export(scale_y_discrete)
 export(test_distribution)
 export(test_fit)
 export(test_gof)
 export(test_permutation)
 export(test_random)
 export(tidy)
-export(with_graph)
 export(xlab)
 export(ylab)
 importFrom(dplyr,"%>%")
@@ -54,25 +44,14 @@ importFrom(ggplot2,labs)
 importFrom(ggplot2,scale_y_discrete)
 importFrom(ggplot2,xlab)
 importFrom(ggplot2,ylab)
-importFrom(igraph,is_igraph)
 importFrom(manynet,bind_node_attributes)
 importFrom(manynet,generate_random)
 importFrom(manynet,is_complex)
 importFrom(manynet,is_directed)
-importFrom(network,as.network)
-importFrom(network,is.network)
 importFrom(purrr,flatten)
 importFrom(stats,as.formula)
 importFrom(stats,binomial)
 importFrom(stats,df.residual)
 importFrom(stats,glm.fit)
 importFrom(stats,pchisq)
 importFrom(stats,quantile)
-importFrom(tidygraph,.E)
-importFrom(tidygraph,.G)
-importFrom(tidygraph,.N)
-importFrom(tidygraph,bind_edges)
-importFrom(tidygraph,is.tbl_graph)
-importFrom(tidygraph,mutate)
-importFrom(tidygraph,rename)
-importFrom(tidygraph,with_graph)

NEWS.md

@@ -1,3 +1,21 @@
+# migraph 1.4.1
+
+2024-07-19
+
+## Package
+
+- Made package title Title Case in DESCRIPTION
+- Added alttext to icons used in pkgdown site
+- Added CRAN link in pkgdown site
+- Removed unnecessary reexports
+- Dropped 6 Suggests dependencies
+- Dropped 4 Imports dependencies (including `{tidyr}`, see below)
+
+## Models
+
+- `network_reg()` renamed to `net_regression()` for consistency
+- Refactored several functions to avoid `{tidyr}` dependency for pivoting longer and wider
+
 # migraph 1.4.0
 
 2024-07-18

R/class_models.R

@@ -138,8 +138,15 @@ plot.netlm <- function(x, ...){
   distrib <- as.data.frame(distrib)
   names(distrib) <- x$names
   distrib$obs <- seq_len(nrow(distrib))
-  distrib <- tidyr::pivot_longer(distrib, 
-                                 cols = 1:(ncol(distrib)-1))
+  distrib <- stats::reshape(data = distrib, # tidyr::pivot_longer replacement
+                     direction = "long",
+                     varying = colnames(distrib)[-ncol(distrib)],
+                     v.names = "value",
+                     times = colnames(distrib)[-ncol(distrib)],
+                     timevar = "name")
+  rownames(distrib) <- NULL
+  distrib$id <- NULL
+  distrib <- dplyr::arrange(distrib, obs)
   distrib$coef <- rep(unname(x$coefficients), nrow(x$dist))
   distrib$tstat <- rep(unname(x$tstat), nrow(x$dist))
   distrib$name <- factor(distrib$name, x$names)
@@ -158,8 +165,15 @@ plot.netlogit <- function(x, ...){
   distrib <- as.data.frame(distrib)
   names(distrib) <- x$names
   distrib$obs <- seq_len(nrow(distrib))
-  distrib <- tidyr::pivot_longer(distrib, 
-                                 cols = 1:(ncol(distrib)-1))
+  distrib <- stats::reshape(data = distrib, # tidyr::pivot_longer replacement
+                     direction = "long",
+                     varying = colnames(distrib)[-ncol(distrib)],
+                     v.names = "value",
+                     times = colnames(distrib)[-ncol(distrib)],
+                     timevar = "name")
+  rownames(distrib) <- NULL
+  distrib$id <- NULL
+  distrib <- dplyr::arrange(distrib, obs)
   distrib$coef <- rep(unname(x$coefficients), nrow(x$dist))
   distrib$tstat <- rep(unname(x$tstat), nrow(x$dist))
   distrib$name <- factor(distrib$name, x$names)

R/migraph-defunct.R

@@ -18,3 +18,16 @@ test_gof <- function(diff_model, diff_models) {
               old = "test_gof")
   test_fit(diff_model, diff_models)
 }
+
+#' @describeIn defunct Deprecated on 2024-07-19.
+#' @export
+network_reg <- function(formula, .data,
+                        method = c("qap","qapy"),
+                        times = 1000,
+                        strategy = "sequential",
+                        verbose = FALSE) {
+  .Deprecated("net_regression", package = "migraph",
+              old = "network_reg")
+  net_regression(formula, .data, method, times,
+                 strategy, verbose)
+}

R/migraph-package.R

@@ -18,4 +18,4 @@ thisRequires <- function(pkgname){
 }
 
 # defining global variables more centrally
-utils::globalVariables(c(".data", ".graph_context"))
+utils::globalVariables(c(".data", "obs"))

R/model_regression.R

@@ -86,14 +86,14 @@
 #'   
 #' @examples
 #' networkers <- ison_networkers %>% to_subgraph(Discipline == "Sociology")
-#' model1 <- network_reg(weight ~ alter(Citations) + sim(Citations), 
+#' model1 <- net_regression(weight ~ ego(Citations) + alter(Citations) + sim(Citations), 
 #'                       networkers, times = 20)
 #' # Should be run many more `times` for publication-ready results
 #' tidy(model1)
 #' glance(model1)
 #' plot(model1)
 #' @export
-network_reg <- function(formula, .data,
+net_regression <- function(formula, .data,
                         method = c("qap","qapy"),
                         times = 1000,
                         strategy = "sequential",

R/model_tests.R

@@ -34,7 +34,6 @@ test_random <- function(.data, FUN, ...,
                         times = 1000, 
                         strategy = "sequential", 
                         verbose = FALSE){
-  if(missing(.data)) {expect_nodes(); .data <- .G()}
   args <- unlist(list(...))
   if (!is.null(args)) {
     obsd <- FUN(.data, args)
@@ -71,6 +70,7 @@ test_random <- function(.data, FUN, ...,
   class(out) <- "network_test"
   out
 }
+
 #' @rdname tests 
 #' @examples 
 #' # (qaptest <- test_permutation(marvel_friends, 
@@ -82,7 +82,6 @@ test_permutation <- function(.data, FUN, ...,
                              times = 1000, 
                              strategy = "sequential", 
                              verbose = FALSE){
-  if(missing(.data)) {expect_nodes(); .data <- .G()}
   args <- unlist(list(...))
   if (!is.null(args)) {
     obsd <- FUN(.data, args)
@@ -231,13 +230,13 @@ test_fit <- function(diff_model, diff_models){ # make into method?
   x <- diff_model
   y <- diff_models
   sim <- `0` <- NULL
-  sims <- y |> dplyr::select(sim, t, I) |> 
-    tidyr::pivot_wider(names_from = t, values_from = I) |> 
-    dplyr::select(-c(sim, `0`))
+  sims <- y |> dplyr::select(sim, t, I)
+  sims <- as.data.frame.matrix(stats::xtabs(I ~ sim + t, sims)) # tidyr::pivot_wider replacement
   sims <- sims[,colSums(stats::cov(sims))!=0]
   mah <- stats::mahalanobis(x$I[-1], colMeans(sims), stats::cov(sims))
   pval <- pchisq(mah, df=length(x$I[-1]), lower.tail=FALSE)
   dplyr::tibble(statistic = mah, p.value = pval, 
                 df = length(x$I[-1]), nobs = nrow(sims))
 }
 
+

R/reexports_classes.R

@@ -1,61 +1,5 @@
-#' @importFrom igraph is_igraph
-#' @export
-igraph::is_igraph
-
-#' @importFrom network is.network
-#' @export
-network::is.network
-
-#' @importFrom network as.network
-#' @export
-network::as.network
-
 #' @importFrom dplyr %>%
 #' @export
 dplyr::`%>%`
 
-#' @importFrom tidygraph with_graph
-#' @export
-tidygraph::with_graph
-
-#' @importFrom tidygraph is.tbl_graph
-#' @export
-tidygraph::is.tbl_graph
-
-#' @importFrom tidygraph .G
-#' @export
-tidygraph::.G
-
-#' @importFrom tidygraph .N
-#' @export
-tidygraph::.N
-
-#' @importFrom tidygraph .E
-#' @export
-tidygraph::.E
-
-#' @importFrom tidygraph mutate
-#' @export
-tidygraph::mutate
-
-#' @importFrom tidygraph rename
-#' @export
-tidygraph::rename
-
-#' @importFrom tidygraph bind_edges
-#' @export
-tidygraph::bind_edges
-
-expect_nodes <- function() {
-  if (!.graph_context$free() && .graph_context$active() != "nodes") {
-    stop("This call requires nodes to be active", call. = FALSE)
-  }
-}
-
-expect_edges <- function() {
-  if (!.graph_context$free() && .graph_context$active() != "edges") {
-    stop("This call requires edges to be active", call. = FALSE)
-  }
-}
-
 # #' @importFrom rlang `%||%`

cran-comments.md

@@ -11,5 +11,7 @@
 
 * This release is expected to create errors with older versions of manynet,
 but should create no errors with the latest version
+* Currently binaries of manynet have been built for most flavors, with the exception of r-release-windows-x86_66
+* There is expected to be test errors for this flavor until a manynet binary for v1.0.1 has been built
 * Since manynet is a Depends for migraph, this should not pose a problem for users
 upgrading