dgraphs 0.2.0

Breaking API changes

Removes the deprecated create.radius.graph() and create.adaptive.radius.graph() compatibility wrappers. Use create.rknn.graph() with type = "fixed" or type = "adaptive.radius", respectively.
Removes the temporary public backend entry point cpp.create.rknn.graphs(). Use create.rknn.graphs(backend = "cpp").
Internalizes the low-level dist.to.knn(), euclidean.distance(), and graph.adj.mat() helpers.
Removes the superseded adjlist.to.igraph() conversion function. as_igraph() now accepts bare adjacency lists and an optional aligned weight.list argument.
Removes the unused graph-edit workflow comprising graph.edit.distance(), load.graph.data(), calculate.edit.distances(), and create.distance.plot().

Fixes a C++ One Definition Rule violation reported by CRAN’s special link-time-optimization check. The minimum-spanning-tree implementation now uses a privately scoped edge type, and an unused conflicting intersection-kNN helper type has been removed. This does not change the R API or graph semantics.
Fixes an ANN fixed-radius boundary issue that could omit adaptive-radius edges lying exactly at a local-scale threshold. In particular, the adaptive maximum-radius rule with factor one now reproduces symmetric-kNN edges for exact, tie-free searches.
Clarifies that the historical rel_geodesic_stress diagnostic is a target-normalized graph-geodesic relative RMSE, not Kruskal’s Stress-1.
Adds a full workflow vignette covering graph construction, lifecycle diagnostics, connectivity repair, parameter sequences, conversion to igraph, and geodesic-isometry diagnostics.
Expands examples across the exported API in preparation for an R Journal package paper.
Extends as_igraph() to current dgraphs graph objects while preserving support for legacy basin graph objects.

First public release.
Provides mutual, shared-neighbor, intersection, geodesic nearest-neighbor, radius, adaptive-radius, and minimum-spanning-tree-completed graph constructors.
Provides graph conversion, weighting, pruning, diagnostics, spectral embedding, endpoint detection, and path utilities.
Includes native implementations for performance-sensitive graph construction and analysis.