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dgraphs - Data-Derived Graph Construction Utilities

Constructs data-derived graphs from numerical observations using mutual, shared-neighbor, intersection, geodesic, radius, adaptive-radius, minimum-spanning-tree completion, and optional iterated adaptive neighborhood methods. Provides graph conversion, pruning, diagnostics, spectral embedding, endpoint detection, and path utilities, with reproducible synthetic geometries and point sampling for graph and embedding experiments. The implemented graph constructions include methods described by Jarvis and Patrick (1973) <doi:10.1109/T-C.1973.223640>, Brito et al. (1997) <doi:10.1016/S0167-7152(96)00213-1>, Berry and Sauer (2019) <doi:10.3934/fods.2019001>, and Gower and Ross (1969) <doi:10.2307/2346439>.

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cpp

6.82 score 1 stars 1 dependents 49 scripts 375 downloads

linf - L-Infinity Normalization and Dominant Community State Types

Implements L-infinity normalization for compositional matrices, assigns samples to dominant features, constructs truncated and hierarchically refined dominant community state types, constructs unordered dominance sets with support-based sample filtering, and computes representative landmark profiles. The methods are described by Gajer and Ravel (2025) <doi:10.48550/arXiv.2503.21543>. Bundled vaginal and gut microbiome data support reproducible demonstrations of the package interface; phenotype fields in the stratified gut subset are illustrative and are not suitable for population-level inference.

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5.51 score 342 downloads

geosmooth - Geometric Methods for Nonparametric Regression and Density Estimation

Provides geometric methods for nonparametric regression and density estimation on data represented as coordinate matrices or weighted graphs. Methods include local polynomial smoothing, model-averaged local polynomial smoothing, local polynomial lifting trend filtering, synchronized local polynomial lifting trend filtering, graph low-pass filtering, and Hessian-energy regression. Methodological references include Gajer and Ravel (2025) "Adaptive Geometric Regression for High-Dimensional Structured Data" <doi:10.48550/arXiv.2511.03817>, Fan and Gijbels (1996, ISBN:9780412983214), Wang et al. (2016) "Trend Filtering on Graphs" <https://www.jmlr.org/papers/v17/15-147.html>, and Kim et al. (2009) "Semi-Supervised Regression Using Hessian Energy" <https://papers.nips.cc/paper/3741-semi-supervised-regression-using-hessian-energy-with-an-application-to-semi-supervised-dimensionality-reduction>.

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openblascpp

5.11 score 455 downloads

ivue - Interactive 3D Visualization of Data and Graphs

Creates interactive three-dimensional point clouds and embedded weighted graphs with numerical or categorical annotations. Provides reusable continuous and categorical color scales, matching legends, highlighting, and geometric edge, path, and label layers. Supports multiple weighted-graph formats and optional layouts through 'igraph', with explicit distance or strength weight semantics. Renders browser widgets using 'rgl' without requiring a native graphics window. Plays recorded coordinate frames with interactive controls and exports orthographic graph animations to GIF.

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4.88 score 174 downloads

grip - Graph Drawing with Intelligent Placement (GRIP)

Implements GRIP multiscale graph layout with a unified choice between hop-count and geometry-aware edge-length graph metrics in 2D and 3D. Provides layout scoring, candidate comparison, multiscale trace diagnostics, synthetic graph families, and advanced experimental geodesic-KK utilities for weighted-layout evaluation and polish. Based on Gajer and Kobourov (2002) <doi:10.7155/jgaa.00052> and Gajer, Goodrich and Kobourov (2004) <doi:10.1016/j.comgeo.2004.03.014>. Includes derived graph datasets from the SuiteSparse Matrix Collection, with source attribution and transformation metadata.

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cpp

3.95 score 420 downloads