Package index • dgraphs

Graph construction and parameter sequences

create.ian.graph(): Construct an Iterated Adaptive Neighborhood Graph
build.ian.backend(): Build the Optional IAN Backend
create.mknn.graph(): Compute a Mutual k-Nearest Neighbor Graph with Weights
create.mknn.graphs(): Create Multiple Mutual kNN Graphs with Geometric Pruning
create.sknn.graph(): Compute a Symmetric k-Nearest Neighbor Graph
create.sknn.graphs(): Compute a Series of Symmetric k-Nearest Neighbor Graphs
create.rknn.graph(): Compute a Radius-kNN Graph
create.rknn.graphs(): Compute Adaptive Radius-kNN Graphs Across k Values
create.cknn.graph(): Compute a Continuous-kNN Graph
create.single.iknn.graph(): Create a Single Intersection-weighted k-Nearest Neighbors Graph
create.iknn.graphs(): Create intersection k-nearest neighbor graphs with dual pruning
create.geodesic.iknn.graph(): Create a graph-geodesic iKNN graph
create.iterated.iknn.graphs(): Create iterated graph-geodesic iKNN graphs
build.iknn.graphs.and.selectk(): Build iKNN Graphs and Select a Neighborhood Size
create.cmst.graph(): Construct a Minimal Spanning Tree (MST) Completion Graph
create.threshold.distance.graph(): Create a Threshold Distance Graph
nerve.graph(): Construct the Nerve Graph of a Cover

Basic graphs and representation

create.graph(): Create a Standard Graph
dgraph() graph.adjacency() graph.lengths() graph.order() graph.stages() graph.edge.attribute() graph.edges(): Construct and Inspect an Undirected Metric Graph
as_igraph(): Convert a dgraph to igraph
convert.adjacency.list.to.adjacency.matrix(): Convert an Adjacency List to an Adjacency Matrix
convert.weighted.adjacency.matrix.to.adjacency.list(): Convert a Weighted Adjacency Matrix to Lists
convert.adjacency.to.edge.matrix(): Convert an Adjacency List to an Edge Matrix
count.edges(): Count Edges in an Undirected Adjacency List
compare.adj.lists(): Compare Two Adjacency Lists
edge.diff(): Compute Edge Difference Between Two Graphs
identical.vertex.set.weighted.graph.similarity(): Weighted Graph Distance Between Graphs with Identical Vertex Sets

Connectivity and graph editing

graph.connected.components(): Assign Vertices to Connected Components
convert.to.undirected(): Convert a Directed Adjacency List to an Undirected Adjacency List
rm.self.loops(): Remove Self-Loops from an Adjacency List
join.graphs(): Join Two Adjacency-List Graphs
create.subgraph(): Extract an Induced Subgraph
create.grid.graph(): Create a Refined Graph with Approximately Uniform Edge Spacing

Paths and distances

graph.geodesic.distances(): Compute Graph Geodesic Distances
fermat.distances(): Compute Complete or Graph-Restricted Sample Fermat Distances
fermat.knn() create.fermat.sknn.graph(): Find Exact Sample Fermat Nearest Neighbors
compute.graph.distance(): Compute a Weighted Shortest-Path Distance
compute.graph.diameter(): Compute a Weighted Graph Diameter
get.shortest.path(): Get Shortest Path Between Two Vertices
geodesic.disk(): Geodesic Disk in a Weighted Graph
geodesic.knn(): Find Geodesic Neighbors Within a Point Cloud
geodesic.knnx(): Find Geodesic Neighbors from Grid Queries to Observations
create.path.graph(): Construct Path Graphs Across Hop Limits
create.plm.graph(): Create a Path Length Matrix Graph Structure
compare.paths(): Compare Paths Across Hop Limits
minh.limit(): Find the Minimum Hop Limit for Path Existence
path.length(): Compute Euclidean Path Length
path.dist(): Normalized Cumulative Distance Along a Vertex Path
subdivide.path(): Subdivide a Path into Arc-Length Spaced Points

Edge lengths and pruning

extract.trajectory.edge.lengths(): Extract Edge Lengths Along a Graph Path
wgraph.prune.long.edges(): Prune Long Edges in a Weighted Graph

Diagnostics, endpoints and packing

compute.graph.summary.pmf(): Compute a graph summary as a probability mass function
graph.summary.divergence(): Compute divergence between two graphs using a selected graph summary
jensen.shannon.divergence(): Jensen-Shannon Divergence
compute.graph.summary.stability(): Compute graph-summary stability across a graph sequence
compute.stability.metrics(): Compute Stability Metrics Across a Sequence of IkNN Graphs
compute.geodesic.stats(): Compute Geodesic Statistics for Grid Vertices
compute.vertex.geodesic.stats(): Compute Geodesic Statistics for a Single Grid Vertex
compute.graph.endpoint.scores(): Compute Graph Endpoint Scores from a 3D Embedding
detect.graph.endpoints(): Detect Graph Endpoints from a 3D Embedding
geodesic.core.endpoints(): Select Graph Endpoints by Core-Eccentricity Geometry
detect.local.extrema(): Detect Local Extrema in a Graph
vertices(): Extract Vertices from a Graph Result
remove.knn.outliers(): Remove Outliers from a State Space Using k-Nearest Neighbors
create.maximal.packing(): Create a Maximal Packing of Vertices in a Graph
validate.maximal.packing(): Validate a Maximal Packing
verify.maximal.packing(): Verify Maximal Packing Created by create.maximal.packing
isometry.scale(): Compute the Optimal Isometry Calibration Scale
isometry.rel.rms.error(): Compute Relative RMS Isometry Error
isometry.rel.abs.error(): Compute Relative Absolute Isometry Errors
isometry.distortion.quantiles(): Compute Multiplicative Distortion Quantiles
isometry.distance.correlations(): Compute Distance Preservation Correlations
isometry.geodesic.diagnostics(): Compute Geodesic-Isometry Diagnostics
summarize.isometry.deviation(): Summarize Deviation from Isometry

Spectral methods and graph display

graph.spectrum(): Compute the Positive Spectrum of an Unweighted Graph Laplacian
graph.spectral.embedding(): Embed a Connected Graph Using its Positive Laplacian Spectrum
graph.embedding(): Embed Graph in 2D or 3D Space

Synthetic geometry and embedding

synthetic.quadform(): Specify a quadform geometry
synthetic.circle(): Specify a circle geometry
synthetic.helix(): Specify a helix geometry
synthetic.trefoil(): Specify a trefoil-knot geometry
synthetic.sphere.cap(): Specify a sphere-cap geometry
synthetic.torus.patch(): Specify a torus-patch geometry
synthetic.simplex(): Specify a simplex geometry
synthetic.stratum.point(): Specify a point stratum
synthetic.stratum.segment(): Specify a line-segment stratum
synthetic.stratum.rectangle(): Specify a rectangle stratum
synthetic.stratified(): Assemble a stratified geometry
synthetic.point.line.junction(): Specify a point-line junction
embed.synthetic.geometry(): Embed latent coordinates through a synthetic geometry
embed.quadform.surface(): Lift coordinates onto a quadratic surface using Geometry Lab arithmetic
quadform.gradient(): Evaluate gradients of all quadforms
quadform.metric(): Evaluate the induced metric of a quadform geometry
edge.lengths.synthetic.geometry(): Exact latent-segment lengths under a synthetic geometry
validate.synthetic.geometry(): Validate a geometry specification or its latent coordinates

Point sampling

sample.synthetic.geometry(): Realize points on a synthetic geometry with explicit random-state control
synthetic.sampling.uniform.interval(): Uniform-interval sampling specification
synthetic.sampling.grid.interval(): Deterministic interval-grid sampling specification
synthetic.sampling.uniform.box(): Uniform-box sampling specification
synthetic.sampling.uniform.rectangle(): Uniform-rectangle sampling specification
synthetic.sampling.uniform.disk(): Uniform-disk sampling specification
synthetic.sampling.truncated.normal(): Truncated-normal sampling specification
synthetic.sampling.gapped.uniform(): Gapped-uniform sampling specification
synthetic.sampling.clustered(): Clustered sampling specification
synthetic.sampling.dirichlet.zeros(): Dirichlet sampling with structural zeros
synthetic.sampling.quadform.lab(): Versioned quadratic-surface sampling used by Geometry Lab
validate.synthetic.sampling(): Validate a point-sampling specification and geometric support

Interactive graph reconstruction explorer

explore.graphs(): Open the Graph Reconstruction Explorer
read.graph.benchmark(): Read a Saved Graph Reconstruction Benchmark
register.graph.project(): Remember a Graph Explorer Project

Object methods and supporting reference

dgraphs dgraphs-package: dgraphs: Data-Derived Graph Construction Utilities
print(<path.graph>) summary(<path.graph>): Inspect a Path Graph
summary(<path.graph.series>) print(<path.graph.series>): Inspect a Collection of Hop-Constrained Path Graphs
print(<synthetic_geometry_sample>) summary(<synthetic_geometry_sample>) print(<summary.synthetic_geometry_sample>): Inspect a Synthetic Geometry Sample
overlap.distribution.plot(): Plot the distribution of overlap values
plot(<IkNNgraphs>): Plot Diagnostics for Intersection k-NN Graph Analysis
plot(<build_iknn_graphs_and_selectk>): Plot method for build_iknn_graphs_and_selectk
plot(<cst_graph_mixing_stats>): Plot method for cst_graph_mixing_stats
plot(<dgraph>): Plot a dgraph with Reusable Coordinates
plot(<geodesic_stats>): Plot Geodesic Statistics
plot(<iknn_stability_metrics>): Plot Method for IkNN Stability Metrics
plot(<vertex_geodesic_stats>): Plot method for vertex_geodesic_stats objects
print(<build_iknn_graphs_and_selectk>): Print method for build_iknn_graphs_and_selectk
print(<dgraph>): Print an Undirected Graph
print(<geodesic_stats>): Print method for geodesic_stats objects
print(<radius_graph>) print(<cknn_graph>) print(<rknn_graphs>) print(<adaptive_radius_graph>) print(<sknn_graphs>) print(<sknn_graph>): Print Graph Constructor Results
print(<knn.outliers>): Print Method for knn.outliers Objects
print(<maximal_packing>): Print Method for Maximal Packing Results
print(<mknn_graph>): Print Method for mknn_graph Objects
print(<mknn_graphs>): Print Method for mknn_graphs Objects
print(<mst_completion_graph>): Print Method for MST Completion Graph Objects
print(<packing_validation>): Print Method for Packing Validation Results
print(<path.graph.plm>): Print a Path-Length-Metric Graph
print(<summary.knn.outliers>): Print Method for summary.knn.outliers Objects
print(<summary.mst_completion_graph>): Print Summary of MST Completion Graph
summary(<IkNN>): Summarize IkNN Graph Object
summary(<geodesic_stats>): Summary method for geodesic_stats objects
summary(<iknn_graphs>): Summarize an iknn_graphs Object
summary(<iterated_iknn_graphs>): Summarize Iterated Intersection k-NN Graphs
summary(<knn.outliers>): Summary Method for knn.outliers Objects
summary(<local_extrema>) print(<summary.local_extrema>): Summarize Local Extrema
summary(<mknn_graphs>): Summary Method for mknn_graphs Objects
summary(<mst_completion_graph>): Summary Method for MST Completion Graph Objects
summary(<rknn_graphs>): Summarize an rknn_graphs Object
summary(<vertex_geodesic_stats>): Summary method for vertex_geodesic_stats objects
vertices(<local_extrema>): Extract a Local-Extremum Neighborhood