Package: gasper 1.1.6

Fabien Navarro

gasper: Graph Signal Processing

Provides the standard operations for signal processing on graphs: graph Fourier transform, spectral graph wavelet transform, visualization tools. It also implements a data driven method for graph signal denoising/regression, for details see De Loynes, Navarro, Olivier (2019) <arxiv:1906.01882>. The package also provides an interface to the SuiteSparse Matrix Collection, <https://sparse.tamu.edu/>, a large and widely used set of sparse matrix benchmarks collected from a wide range of applications.

Authors:Basile de Loynes [aut], Fabien Navarro [aut, cre], Baptiste Olivier [aut]

gasper_1.1.6.tar.gz
gasper_1.1.6.tar.gz(r-4.5-noble)gasper_1.1.6.tar.gz(r-4.4-noble)
gasper_1.1.6.tgz(r-4.4-emscripten)gasper_1.1.6.tgz(r-4.3-emscripten)
gasper.pdf |gasper.html✨
gasper/json (API)
NEWS

# Install 'gasper' in R:
install.packages('gasper', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/fabnavarro/gasper/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:

2.64 score 22 scripts 284 downloads 33 exports 39 dependencies

Last updated 8 months agofrom:bde52b6c84. Checks:ERROR: 1 OK: 1. Indexed: no.

TargetResultDate
Doc / VignettesFAILOct 26 2024
R-4.5-linux-x86_64OKOct 26 2024

Exports:adjacency_matanalysisbetathreshdownload_grapheigendeceigensortforward_gftforward_sgwtfullfullupget_graph_infoGVNHPFVNinverse_gftinverse_sgwtlaplacian_matLD_SUREthreshlocalize_gftlocalize_sgwtplot_filterplot_graphplot_signalPSNRrandsignalsmoothmodulusSNRspectral_coordsSURE_MSEthreshSUREthreshswissrollsynthesistight_framezetav

Dependencies:askpassclicolorspacecurlfansifarverggplot2gluegtablehttrisobandjsonlitelabelinglatticelifecyclemagrittrMASSMatrixmgcvmimemunsellnlmeopensslpillarpkgconfigR6RColorBrewerRcppRcppArmadilloRcppEigenrlangRSpectrascalessystibbleutf8vctrsviridisLitewithr

Gasper: GrAph Signal ProcEssing in R

Basile de Loynes, Fabien Navarro, Baptiste Olivier

Rendered fromgasper_vignette.rmdusingknitr::rmarkdownon Oct 26 2024.

Last update: 2024-02-29
Started: 2020-08-03

Readme and manuals

Help Manual

Help pageTopics
Compute the Adjacency Matrix of a Gaussian Weighted Graphadjacency_mat
Compute the Analysis Operator for a Graph Signalanalysis
Apply Beta Threshold to Databetathresh
Download Sparse Matrix form the SuiteSparse Matrix Collectiondownload_graph
Spectral decomposition of a symetric matrixeigendec
Spectral Decomposition of a Symmetric Matrixeigensort
Compute Forward Graph Fourier Transformforward_gft
Compute Forward Spectral Graph Wavelet Transformforward_sgwt
Conversion of Symmetric Sparse Matrix to Full Matrixfull
Convert Symmetric Sparse Matrix to Full Matrixfullup
Retrieve Information Tables about a Specific Graph from the SuiteSparse Matrix Collectionget_graph_info
Grid1 Graph from AG-Monien Graph Collectiongrid1
Graph Von Neumann Variance EstimatorGVN
High Pass Filter Von Neumann EstimatorHPFVN
Compute Inverse Graph Fourier Transforminverse_gft
Compute Inverse Spectral Graph Wavelet Transforminverse_sgwt
Compute the Graph Laplacian Matrixlaplacian_mat
Level Dependent Stein's Unbiased Risk Estimate ThresholdingLD_SUREthresh
Localize Kernel at a Graph Vertex Using GFTlocalize_gft
Localize a Kernel at a Specific Vertex using SGWTlocalize_sgwt
Minnesota Road Networkminnesota
NYC Taxi Network DatasetNYCdata
Pittsburgh Census Tracts Network.pittsburgh
Plot Tight-Frame Filtersplot_filter
Plot Graphplot_graph
Plot a Signal on Top of a Given Graphplot_signal
Compute the Peak Signal to Noise RatioPSNR
Generate Random Signal with Varying Regularityrandsignal
R logo graph.rlogo
Modulus of Smoothness for Graph Signalsmoothmodulus
Compute the Signal to Noise RatioSNR
Spectral Coordinates for Graph Drawingspectral_coords
Matrix Data from SuiteSparse Matrix CollectionSuiteSparseData
Stein's Unbiased Risk Estimate with MSESURE_MSEthresh
Stein's Unbiased Risk EstimateSUREthresh
Swiss Roll Graph Generationswissroll
Compute the Synthesis Operator for Transform Coefficientssynthesis
Tight-Frame Computationtight_frame
Evaluate Localized Tight-Frame Filter Functionszetav