NEWS.md

In cograph: Analysis and Visualization of Complex Networks

cograph 1.8.2

New Features

• plot_simplicial() now accepts tna, netobject, net_hon, and net_hypa objects directly — higher-order pathways are auto-built and visualized with proper state labels, no manual extraction needed. New parameters: method ("hon" / "hypa"), max_pathways, ncol. Dismantled mode uses gridExtra grid layout with scaled nodes
• print.cograph_network() now shows a structured summary: node/edge counts, density, reciprocity, weight range, and top-degree nodes — replacing the minimal R6 default output
• Added mcml S3 class with as_mcml() generic for type-safe handling of Markov Chain Multi-Level models — enables print(), plot(), and method dispatch on MCML objects
• Added local %||% operator for R 4.1 compatibility (no longer requires R 4.4+)

Breaking Changes

• MCML field names renamed for clarity: $between → $macro, $within → $clusters
• as_tna() on MCML objects now returns a flat group_tna list instead of a nested structure

Bug Fixes

• plot_mcml() now suppresses zero-weight edges instead of drawing invisible lines, and strips leading zeros from edge labels (.32 instead of 0.32)
• Self-loops in cluster_summary() are now preserved in the macro diagonal, reflecting intra-cluster retention rates
• Sequence data is properly propagated through the full tna → macro → cluster pipeline, so downstream models can use bootstrap and permutation tests

cograph 1.8.0

New Features

• Added overlay_communities() for drawing community blob overlays on any network plot — accepts method names, membership vectors, or pre-computed community objects
• Added plot_simplicial() for higher-order pathway visualization, rendering simplicial complexes as smooth blobs with flexible separators and a dismantled view option
• Added value_nudge parameter to plot_transitions() for controlling the distance between flow labels and nodes
• Added bundle legend label controls: bundle_legend_size, bundle_legend_color, bundle_legend_fontface, bundle_legend_position
• Added per-function label controls (label_size, label_color, label_fontface, label_hjust) to plot_transitions(), plot_trajectories(), and plot_alluvial()

Bug Fixes

• Fixed spiky text halo artifacts in transition and heatmap plots by increasing circular offset directions from 8 to 16 (22.5° spacing for smooth outlines)

cograph 1.7.0

New Features

Cluster Analysis

• Added cluster_summary() for aggregating network weights at the cluster level, producing between-cluster and within-cluster matrices from raw transition data
• Added build_mcml() for constructing Markov Chain Multi-Level models from edge lists or sequence data with automatic cluster detection
• Added cluster_quality() for modularity-based cluster quality metrics and cluster_significance() for permutation-based significance testing
• Added as_tna() to convert cluster summaries to TNA objects for bootstrapping, permutation testing, and plotting with splot()

Network Operations

• Added simplify() for pruning weak edges from networks, with configurable weight threshold and aggregation method
• Added disparity_filter() for backbone extraction (Serrano et al. 2009), with methods for matrices, tna, igraph, and cograph_network objects
• Added robustness() for network robustness analysis with targeted (betweenness, degree) and random attack strategies, plus ggplot_robustness() for faceted ggplot2 output
• Added temporal_edge_list() for converting sequence data to timestamped edge lists
• Added supra_adjacency(), supra_layer(), supra_interlayer() for multilayer supra-adjacency matrix construction
• Added layer_similarity(), layer_similarity_matrix(), and layer_degree_correlation() for comparing layers in multilayer networks
• Added aggregate_weights() and aggregate_layers() for weight aggregation across layers
• Added verify_with_igraph() for cross-validating cograph centrality and network metrics against igraph

Motif Analysis

• Added motifs() / subgraphs() as a unified API for triad census (node-exchangeable counts) and instance extraction (named node triples), with auto-detection of actor/session columns, rolling/tumbling window support, and exact configuration model significance testing

Visualization

• Added plot_mcml() for Markov Chain Multi-Level visualization showing between-cluster summary edges alongside within-cluster detail, with pie charts, self-loops, and 22 customization parameters
• Added plot_chord() for native chord diagrams with automatic weight-based arc sizing
• Added plot_time_line() for cluster membership timeline visualization
• Added plot_htna() orientations: "facing" (tip-to-tip columns) and "circular" (two semicircles), plus intra_curvature for drawing intra-group edges as dotted bezier arcs
• Added threshold parameter to all plot functions for filtering edges/cells below a minimum absolute weight
• Added value_fontface, value_fontfamily, and value_halo parameters to plot_heatmap() for text styling control
• Added directional shorthands for scale_nodes_by: indegree, outdegree, instrength, outstrength, incloseness, outcloseness, inharmonic, outharmonic, ineccentricity, outeccentricity
• Added scale_nodes_scale parameter to splot() for dampening (< 1) or exaggerating (> 1) centrality-based node sizing differences
• Added qgraph argument translation in splot(): when plotting tna objects, qgraph-style parameters (vsize, asize, edge.color, lty, shape) are automatically mapped to cograph equivalents

Transition Plot Enhancements

• Added intermediate labels with node_label_format (e.g., "{state} (n={count})") for showing counts on transition plot nodes
• Added line bundling via bundle_size for aggregating individual trajectories into weighted summary lines in large datasets
• Added flow value labels via show_values / value_position for displaying transition counts on flow lines
• Added label_position consistency across ALL columns (first, middle, last) in trajectory plots

Data & Infrastructure

• Added example datasets: gamer_data, group_engagement, srl_data
• Added set_node_groups() / get_node_groups() for managing cluster assignments on cograph_network objects
• Consolidated cograph_network metadata under $meta with getter/setter functions
• Added group_tna support to splot() for direct plotting of grouped TNA models
• Gave each centrality_* wrapper its own focused help page

Bug Fixes

• Fixed load and percolation centrality computation: the BFS assumed unit edge weights, causing infinite loops on weighted graphs; directed graphs now transpose correctly (matching sna convention); disconnected nodes no longer contribute spurious centrality
• Fixed self-loop and edge clipping in splot() viewport calculation
• Fixed argument forwarding in splot dispatch for bootstrap/permutation objects — named parameters (minimum, threshold, layout, title) were consumed by splot()'s signature and silently dropped when dispatching
• Fixed overlapping flow value labels in multi-step alluvial plots
• Fixed alluvial label halo rendering producing spike artifacts (8 → 16 offset directions)
• Fixed viridis palette direction in plot_heatmap() so high values get dark colors
• Fixed build_mcml() density method crash when weight vector had no names
• Fixed display label priority resolution (labels > label > identifier)
• Removed zero-value labels that appeared after rounding in transition plots

Improvements

• Simplified splot dispatch: extracted .collect_dispatch_args() helper to replace 6 copy-paste dispatch blocks, using match.call() + mget() for reliable argument capture

cograph 1.6.0

New Features

Centrality

• Added centrality() with 23 measures and individual wrappers: degree, strength, betweenness, closeness, eigenvector, pagerank, harmonic, authority, hub, alpha, power, kreach, diffusion, percolation, eccentricity, transitivity, constraint, coreness, load, subgraph, leverage, laplacian, current-flow betweenness, current-flow closeness, voterank
• Added edge_betweenness() for edge-level centrality
• Added automatic weight inversion for path-based measures when working with tna transition matrices (where higher weight = stronger connection, not shorter distance)

Community Detection

• Added detect_communities() with 11 algorithms: louvain, walktrap, fast_greedy, label_propagation, leading_eigenvector, infomap, spinglass, leiden, optimal, edge_betweenness, multilevel — plus com_* shorthand aliases
• Added consensus clustering and cluster_significance() for permutation-based validation

Network Metrics

• Added network_summary() and summarize_network() for computing comprehensive network-level statistics (density, reciprocity, transitivity, diameter, components, degree distribution)

Visualization

• Added plot_transitions() for alluvial/Sankey flow diagrams, with plot_alluvial() and plot_trajectories() wrappers
• Added plot_bootstrap() and plot_permutation() for significance-styled visualization of bootstrap and permutation test results — significant edges rendered solid on top, non-significant edges dashed behind
• Added plot_mixed_network() for overlaying symmetric (undirected, straight) and asymmetric (directed, curved) edges on the same network
• Added plot_heatmap() for adjacency matrix heatmaps with optional hierarchical clustering and plot_ml_heatmap() for multilayer 3D perspective heatmaps
• Added plot_compare() for difference network visualization showing edge-weight changes between two networks
• Added splot() S3 methods for tna_bootstrap and tna_permutation objects

Motif Analysis

• Added motif_census(), triad_census(), and extract_motifs() for triad motif analysis with pattern filtering, significance testing, and network diagram visualization

Network Utilities

• Added filter_edges(), subset_edges(), select_nodes(), select_edges() for flexible network subsetting
• Added set_groups() for storing cluster assignments on cograph_network objects with automatic dispatch to plot_htna() / plot_mtna()

Infrastructure

• All plot functions now accept cograph_network objects as input, in addition to matrices, igraph objects, and tna objects
• Layout computation is now lazy — coordinates are only calculated when first needed
• Improved layout_spring and layout_gephi_fr algorithms: vectorized attraction forces, edge aggregation for dense networks
• Renamed package from Sonnet to cograph

Bug Fixes

• Fixed par(pin) error on exit when plot device state was corrupted
• Fixed motif plot scaling and margins for different device sizes

cograph 1.5.2

Breaking Changes

• Standardized first parameter name to x across all plotting functions:
• plot_tna(): input → x
• plot_htna(): input → x (was model)
• plot_mtna(): input → x (was model)
• splot() already used x

Bug Fixes

• Fixed tplot() default margins causing tiny plots compared to splot()

Documentation

• Added qgraph to splot migration guide (vignettes/qgraph-to-splot.md)

cograph 1.5.1

Breaking Changes (with backwards compatibility)

The following parameters have been renamed for consistency. The old names still work but emit deprecation warnings:

| Old Name | New Name | Reason | |----------|----------|--------| | esize | edge_size | Add edge_ prefix, expand abbreviation | | cut | edge_cutoff | Add edge_ prefix, clarify meaning | | usePCH | use_pch | Fix camelCase to snake_case | | positive_color | edge_positive_color | Add edge_ prefix (matches theme storage) | | negative_color | edge_negative_color | Add edge_ prefix (matches theme storage) | | donut_border_lty | donut_line_type | Expand lty abbreviation |

Improvements

• edge_label_fontface now accepts string values ("plain", "bold", "italic", "bold.italic") in addition to numeric values

cograph 1.4.0

New Features

• Added mlna() for multilevel network visualization with 3D perspective
• Added mtna() for multi-cluster network visualization with shape-based cluster containers
• Added plot_htna() for hierarchical multi-group network layouts with polygon and circular arrangements
• Added tplot() as a qgraph drop-in replacement with automatic parameter translation
• Added arrow_angle parameter for customizable arrowhead geometry

Bug Fixes

• Fixed Rd cross-reference warning in splot documentation
• Fixed pie/donut segment divider lines rendering when border width is 0

cograph 1.3.1

New Features

• Added edge_start_dot_density parameter for TNA-style dotted edge starts indicating direction
• Added direct support for tna objects via from_tna() — no manual matrix extraction needed
• Added direct support for statnet network and qgraph objects as input
• Added auto-conversion of pie_values vector to donut_fill when all values are in [0,1]

Bug Fixes

• Fixed TNA visual defaults being silently overwritten in splot() when other parameters were specified
• Fixed self-loop edge labels overlapping the loop arc
• Fixed donut_shape validation rejecting custom SVG shapes
• Fixed title clipping when title text exceeded plot margins
• Fixed edge rendering crash on certain edge/node configurations
• Removed underscore prefix requirement for custom SVG shape names

cograph 1.2.7

Bug Fixes

• Fixed oversized nodes in from_qgraph() when a layout override was provided
• Fixed oval layout using independent axis scaling, which distorted aspect ratios — now uses uniform scaling via normalize_coords()
• Fixed edge label alignment in from_qgraph() by using a matrix intermediary for per-edge vector reordering
• Fixed nrow(el) crash: qgraph's Edgelist is a list, not a data.frame
• Fixed oval layout node distortion and donut fill values when converting from qgraph

cograph 1.2.6

New Features

• Added donut_empty parameter for rendering unfilled donut nodes
• Added from_qgraph() for converting qgraph objects to cograph format, reading resolved graphAttributes for accurate parameter extraction

Bug Fixes

• Fixed oval layout_info guard causing errors on certain device configurations
• Fixed curvature extraction passing vector values instead of scalars

cograph 1.2.0

New Features

• Added soplot() for grid/ggplot2-based network plotting — full feature parity with splot() using a different rendering backend
• Added layout_oval() for oval/elliptical node arrangements
• Added layout_scale parameter to expand or contract the network layout, with "auto" mode for node-count-based scaling
• Added Gephi-style Fruchterman-Reingold layout algorithm
• Added edge_start_style parameter for visually indicating edge direction via styled start segments (dashed, dotted)

Bug Fixes

• Fixed soplot() curve direction and edge defaults diverging from splot() behavior
• Fixed rescale_layout distorting oval aspect ratios by switching to uniform scaling
• Fixed edge scaling producing abnormally thick edges on small networks
• Fixed par(pin) restoration error on plot device exit

cograph 1.1.0

New Features

• Added splot() — a base R graphics engine for network visualization using polygon(), lines(), and xspline(), providing better performance than grid-based rendering for large networks
• Added polygon-shaped donut nodes, custom SVG node shapes, and AI-generated shape support
• Added shadow/halo labels and fine-grained text control (fontface, fontfamily, hjust, vjust, angle)
• Added double donut nodes with separate inner/outer border controls
• Added edge CI (confidence interval) underlays and template-based edge labels
• Added comprehensive legend support: groups, edge color scales, and node size scales
• Added high-resolution output via sn_save() with configurable DPI
• Added edge curve modes, bidirectional arrows, self-loop rotation, and per-edge curve control

Bug Fixes

• Fixed donut rendering producing artifacts and simplified the donut_color API to accept 1 color (fill), 2 colors (fill + background), or n colors (per-node)
• Fixed arrow positioning and curve direction for qgraph-style edges
• Fixed edge label positioning to avoid overlap with edge lines
• Fixed self-loop rendering to use qgraph-style circular arcs
• Fixed arrow placement on non-square viewports
• Fixed reciprocal edge auto-separation causing edge crossings

cograph 1.0.0

• Initial release of cograph network visualization package

cograph documentation built on April 1, 2026, 1:07 a.m.