v1.5.0

.github/workflows/pushrelease.yml

@@ -134,7 +134,7 @@ jobs:
 
       - uses: r-lib/actions/setup-r@v2
 
-      - uses: r-lib/actions/setup-pandoc@v1
+      - uses: r-lib/actions/setup-pandoc@v2
 
       - uses: r-lib/actions/setup-r-dependencies@v2
         with:

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: manynet
 Title: Many Ways to Make, Modify, Map, Mark, and Measure Myriad Networks
-Version: 1.4.1
-Date: 2025-04-09
+Version: 1.5.0
+Date: 2025-06-22
 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,

NAMESPACE

@@ -140,18 +140,7 @@ S3method(net_dims,igraph)
 S3method(net_dims,matrix)
 S3method(net_dims,network)
 S3method(pillar_shaft,logi)
-S3method(plot,diff_model)
-S3method(plot,diffs_model)
-S3method(plot,learn_model)
-S3method(plot,matrix)
-S3method(plot,network_measures)
-S3method(plot,network_motif)
-S3method(plot,node_measure)
-S3method(plot,node_member)
-S3method(plot,node_motif)
-S3method(plot,tie_measure)
 S3method(print,diff_model)
-S3method(print,diffs_model)
 S3method(print,learn_model)
 S3method(print,mnet)
 S3method(print,network_measure)
@@ -165,7 +154,6 @@ S3method(print,tie_measure)
 S3method(select_nodes,igraph)
 S3method(select_nodes,tbl_graph)
 S3method(summary,diff_model)
-S3method(summary,diffs_model)
 S3method(summary,learn_model)
 S3method(summary,network_measure)
 S3method(summary,network_motif)
@@ -242,6 +230,7 @@ S3method(to_no_isolates,list)
 S3method(to_no_isolates,matrix)
 S3method(to_no_isolates,network)
 S3method(to_no_isolates,tbl_graph)
+S3method(to_no_missing,tbl_graph)
 S3method(to_onemode,igraph)
 S3method(to_onemode,matrix)
 S3method(to_onemode,tbl_graph)
@@ -792,6 +781,7 @@ export(to_mode2)
 export(to_multilevel)
 export(to_named)
 export(to_no_isolates)
+export(to_no_missing)
 export(to_onemode)
 export(to_permuted)
 export(to_reciprocated)
@@ -844,15 +834,9 @@ importFrom(dplyr,tibble)
 importFrom(dplyr,ungroup)
 importFrom(ggplot2,aes)
 importFrom(ggplot2,arrow)
-importFrom(ggplot2,element_blank)
-importFrom(ggplot2,element_text)
-importFrom(ggplot2,geom_histogram)
-importFrom(ggplot2,geom_hline)
 importFrom(ggplot2,geom_point)
 importFrom(ggplot2,geom_segment)
 importFrom(ggplot2,geom_text)
-importFrom(ggplot2,geom_tile)
-importFrom(ggplot2,geom_vline)
 importFrom(ggplot2,ggplot)
 importFrom(ggplot2,ggsave)
 importFrom(ggplot2,ggtitle)
@@ -861,12 +845,7 @@ importFrom(ggplot2,labs)
 importFrom(ggplot2,scale_alpha_manual)
 importFrom(ggplot2,scale_color_brewer)
 importFrom(ggplot2,scale_fill_brewer)
-importFrom(ggplot2,scale_fill_gradient)
 importFrom(ggplot2,scale_size)
-importFrom(ggplot2,scale_x_discrete)
-importFrom(ggplot2,scale_y_discrete)
-importFrom(ggplot2,theme)
-importFrom(ggplot2,theme_grey)
 importFrom(ggplot2,theme_void)
 importFrom(ggplot2,unit)
 importFrom(ggplot2,xlab)

NEWS.md

@@ -1,3 +1,34 @@
+# manynet 1.5.0
+
+## Package
+
+- Updated pandoc setup in pushrelease workflow
+
+## Making
+
+- Dropped print and summary methods for diffs_model (moved to `{migraph}`)
+
+## Modifying
+
+- Added `to_no_missing()` for removing nodes with missing data
+- Fixed `as_diffusion.mnet()` so that it includes "diff_model" class
+
+## Measuring
+
+- Dropped plotting methods (moved to `{autograph}`)
+- Added Page 2010 citation to `node_richness()` documentation
+
+## Memberships
+
+- Fixed `node_in_leiden()` to use resolution parameter in call to igraph
+
+## Data
+
+- Improved `table_data()` so that it lists components, longitudinal, dynamic, 
+and changing data
+- Added more description for `fict_lotr`
+- Added `irps_revere` data
+
 # manynet 1.4.1
 
 ## Making

R/class_measures.R

@@ -28,16 +28,6 @@ make_network_measure <- function(out, .data, call) {
   out
 }
 
-make_network_measures <- function(out, .data) {
-  time <- value <- NULL
-  out <- dplyr::as_tibble(out) %>% 
-    dplyr::mutate(time = as.numeric(names(out))) %>% 
-    dplyr::select(time, value)
-  class(out) <- c("network_measures", class(out))
-  attr(out, "mode") <- net_dims(.data)
-  out
-}
-
 # Printing ####
 #' @importFrom cli spark_bar
 #' @export
@@ -135,70 +125,3 @@ summary.network_measure <- function(object, ...,
                 ", p = ", cli::style_italic(round(p,3)),
                 ")")
 }
-
-# Plotting ####
-#' @export
-plot.node_measure <- function(x, type = c("h", "d"), ...) {
-  #type <- match.arg(type)
-  density <- NULL
-  if (is.null(attr(x, "mode"))) attr(x, "mode") <- rep(FALSE, length(x))
-  data <- data.frame(Score = x, Mode = attr(x, "mode"))
-  if (length(type) == 2) {
-    p <- ggplot2::ggplot(data = data, ggplot2::aes(x = .data$Score)) +
-      ggplot2::geom_histogram(ggplot2::aes(y = ggplot2::after_stat(density)),
-                              binwidth = ifelse(max(data$Score) > 1, 1,
-                                                ifelse(max(data$Score) > 
-                                                         .1, .1, .01))) +
-      ggplot2::geom_density(col = 2) +
-      ggplot2::scale_y_continuous("Frequency", sec.axis = 
-                                    ggplot2::sec_axis(~ ., breaks = c(0,1),
-                                                      name = "Density"))
-  } else if (length(type) == 1 & type == "h") {
-    p <- ggplot2::ggplot(data = data, ggplot2::aes(x = .data$Score)) +
-      ggplot2::geom_histogram(ggplot2::aes(y = ggplot2::after_stat(density)),
-                              binwidth = ifelse(max(data$Score) > 1, 1,
-                                                ifelse(max(data$Score) >
-                                                         .1, .1, .01))) +
-      ggplot2::labs(x = "Density", y = "Frequency")
-  } else if (length(type) == 1 & type == "d") {
-    p <- ggplot2::ggplot(data = data, ggplot2::aes(x = .data$Score)) +
-      ggplot2::geom_density(col = 2) +
-      ggplot2::ylab("Density")
-  }
-  p +
-    ggplot2::theme_classic() +
-    ggplot2::theme(panel.grid.major = ggplot2::element_line(colour = "grey90"))
-}
-
-#' @export
-plot.tie_measure <- function(x, type = c("h", "d"), ...) {
-  type <- match.arg(type)
-  data <- data.frame(Score = x)
-  if (type == "h") {
-    p <- ggplot2::ggplot(data = data) +
-      ggplot2::geom_histogram(ggplot2::aes(x = .data$Score),
-                              binwidth = ifelse(max(data$Score) > 1, 1,
-                                                ifelse(max(data$Score) > .1,
-                                                       .1,
-                                                       .01))) +
-      ggplot2::ylab("Frequency")
-  } else {
-    p <- ggplot2::ggplot(data = data) +
-      ggplot2::geom_density(ggplot2::aes(x = .data$Score)) +
-      ggplot2::ylab("Density")
-  }
-  p + ggplot2::theme_classic() +
-    ggplot2::theme(panel.grid.major = ggplot2::element_line(colour = "grey90"))
-}
-
-#' @export
-plot.network_measures <- function(x, ...) {
-  ggplot2::ggplot(data = x, ggplot2::aes(x = .data$time, y = .data$value)) +
-    ggplot2::geom_line() +
-    ggplot2::theme_minimal() +
-    ggplot2::xlab("Time") +
-    ggplot2::ylab("Value")
-}
-
-# defining global variables more centrally
-utils::globalVariables(c(".data"))

R/class_members.R

@@ -58,144 +58,4 @@ summary.node_member <- function(object, ...,
   }
 }
 
-#' @importFrom stats cutree
-#' @export
-plot.node_member <- function(x, ...) {
-  thisRequires("ggdendro")
-    hc <- attr(x, "hc")
-    k <- attr(x, "k")
-    memb <- x[hc$order]
-    clust <- memb[!duplicated(memb)]
-    colors <- ifelse(match(memb, clust) %% 2,
-                     "#000000", "#E20020")
-    ggdendro::ggdendrogram(hc, rotate = TRUE) +
-      ggplot2::geom_hline(yintercept = hc$height[length(hc$order) - k],
-                          linetype = 2,
-                          color = "#E20020") +
-      ggplot2::theme(axis.text.x = ggplot2::element_text(colour = "#5c666f"),
-                     axis.text.y = suppressWarnings(
-                       ggplot2::element_text(colour = colors)))
-}
-
-# plot(as_matrix(ison_adolescents),
-#   membership = node_regular_equivalence(ison_adolescents, "e"))
-# plot(as_matrix(ison_southern_women),
-#   membership = node_regular_equivalence(ison_southern_women, "e"))
-#' @importFrom ggplot2 ggplot geom_tile aes scale_fill_gradient theme_grey labs theme scale_x_discrete scale_y_discrete geom_vline geom_hline element_blank element_text
-#' @export
-plot.matrix <- function(x, ..., membership = NULL) {
-
-  thisRequires("tidyr")
-  if (!is_twomode(x)) {
-    blocked_data <- as_matrix(x)
-    if (!is.null(membership)) blocked_data <- blocked_data[order(membership),
-                                                          order(membership)]
-  } else if (is_twomode(x) &&
-     length(intersect(membership[!node_is_mode(x)], 
-                      membership[!node_is_mode(x)])) > 0) {
-    blocked_data <- as_matrix(to_multilevel(x))
-    if (!is.null(membership)) blocked_data <- blocked_data[order(membership),
-                                                          order(membership)]
-  } else {
-    blocked_data <- manynet::as_matrix(x)
-  }
-
-  from <- to <- weight <- NULL
-
-  plot_data <- as_edgelist(blocked_data)
-  if(!is_labelled(x)){
-    indices <- c(plot_data$from,plot_data$to)
-    plot_data$from <- paste0("N", gsub("\\s", "0", 
-                                       format(plot_data$from, 
-                                              width=max(nchar(indices)))))
-    plot_data$to <- paste0("N", gsub("\\s", "0", 
-                                     format(plot_data$to, 
-                                            width=max(nchar(indices)))))
-  }
-  all_nodes <- expand.grid(node_names(blocked_data), 
-                            node_names(blocked_data))
-  all_nodes <- data.frame(from = all_nodes$Var1, to = all_nodes$Var2,
-                          weight = 0)
-  plot_data <- rbind(plot_data, all_nodes) %>% dplyr::distinct(from, to, .keep_all = TRUE)
-  g <- ggplot2::ggplot(plot_data, ggplot2::aes(to, from)) +
-    ggplot2::theme_grey(base_size = 9) +
-    ggplot2::labs(x = "", y = "") +
-    ggplot2::theme(
-      legend.position = "none",
-      axis.ticks = ggplot2::element_blank(),
-      axis.text.y = ggplot2::element_text(
-        size = 9 * 0.8,
-        colour = "grey50"
-      ),
-      axis.text.x = ggplot2::element_text(
-        size = 9 * 0.8,
-        angle = 30, hjust = 0,
-        colour = "grey50"
-      )
-    ) +
-    # ggplot2::geom_tile(ggplot2::aes(fill = .data[["value"]]),
-    ggplot2::geom_tile(ggplot2::aes(fill = weight),
-                       colour = "white"
-    )
-
-  # Color for signed networks
-  if (is_signed(x)) {
-    g <- g +
-      ggplot2::scale_fill_gradient2(high = "#003049",
-        mid = "white",
-        low = "#d62828")
-  } else {
-    g <- g +
-      ggplot2::scale_fill_gradient(
-        low = "white",
-        high = "black"
-      )
-  }
-
-  # Structure for multimodal networks
-  if (!is_twomode(x)) {
-    g <- g +
-      ggplot2::scale_x_discrete(expand = c(0, 0), position = "top",
-                                limits = colnames(blocked_data)
-      ) +
-      ggplot2::scale_y_discrete(expand = c(0, 0),
-                                limits = rev(rownames(blocked_data))
-      )
-    if (!is.null(membership))
-      if(!is.numeric(membership)) membership <- as.numeric(as.factor(membership))
-      g <- g + ggplot2::geom_vline(
-        xintercept = c(1 + which(diff(membership[order(membership)]) != 0))
-        - .5,
-        colour = "red"
-      ) +
-      ggplot2::geom_hline(
-        yintercept = nrow(blocked_data) -
-          c(1 + which(diff(membership[order(membership)]) != 0)) +
-          1.5,
-        colour = "red"
-      )
-  } else {
-    g <- g +
-      ggplot2::scale_y_discrete(expand = c(0, 0),
-                                limits = rev(rownames(x[["blocked.data"]])[x[["order.vector"]][["nodes1"]]])
-      ) +
-      ggplot2::scale_x_discrete(expand = c(0, 0), position = "top",
-                                limits = colnames(x[["blocked.data"]])[x[["order.vector"]][["nodes2"]]]
-      ) +
-      ggplot2::geom_vline(
-        xintercept =
-          c(1 + which(diff(x[["block.membership"]][["nodes2"]]) != 0))
-        - .5,
-        colour = "blue"
-      ) +
-      ggplot2::geom_hline(
-        yintercept = nrow(x[["blocked.data"]])
-        - c(1 + which(diff(x[["block.membership"]][["nodes1"]]) != 0))
-        + 1.5,
-        colour = "red"
-      )
-  }
-  g
-}
-
 elementwise.all.equal <- Vectorize(function(x, y) {isTRUE(all.equal(x, y))})