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Package Name Access Summary Updated
dython public A set of data tools in Python 2025-09-30
kineticstoolkit_extensions public Additional modules and development of new features for Kinetics Toolkit. 2025-09-30
openinference-instrumentation-haystack public OpenInference Haystack Instrumentation 2025-09-30
r-semplot public Path diagrams and visual analysis of various SEM packages' output. 2025-09-30
r-emstreer public Fast and easily computes an Euclidean Minimum Spanning Tree (EMST) from data, relying on the R API for 'mlpack' - the C++ Machine Learning Library (Curtin et. al., 2013). 'emstreeR' uses the Dual-Tree Boruvka (March, Ram, Gray, 2010, <doi:10.1145/1835804.1835882>), which is theoretically and empirically the fastest algorithm for computing an EMST. This package also provides functions and an S3 method for readily plotting Minimum Spanning Trees (MST) using either the style of the 'base', 'scatterplot3d', or 'ggplot2' libraries. 2025-09-30
r-mxmmod public Provides a convenient interface in 'OpenMx' for building Estabrook's (2015) <doi:10.1037/a0034523> Measurement Model of Derivatives (MMOD). 2025-09-30
fancylog public Fancier logging in Python 2025-09-30
r-leafpop public Creates 'HTML' strings to embed tables, images or graphs in pop-ups of interactive maps created with packages like 'leaflet' or 'mapview'. Handles local images located on the file system or via remote URL. Handles graphs created with 'lattice' or 'ggplot2' as well as interactive plots created with 'htmlwidgets'. 2025-09-30
r-fmesher public Generate planar and spherical triangle meshes, compute finite element calculations for 1- and 2-dimensional flat and curved manifolds with associated basis function spaces, methods for lines and polygons, and transparent handling of coordinate reference systems and coordinate transformation, including 'sf' and 'sp' geometries. The core 'fmesher' library code was originally part of the 'INLA' package, and implements parts of "Triangulations and Applications" by Hjelle and Daehlen (2006) <doi:10.1007/3-540-33261-8>. 2025-09-30
r-ggspatial public Spatial data plus the power of the ggplot2 framework means easier mapping when input data are already in the form of spatial objects. 2025-09-30
opencv public Computer vision and machine learning software library. 2025-09-30
libopencv public Computer vision and machine learning software library. 2025-09-30
py-opencv public Computer vision and machine learning software library. 2025-09-30
r-geomap public Set of routines for making Map Projections (forward and inverse), Topographic Maps, Perspective plots, Geological Maps, geological map symbols, geological databases, interactive plotting and selection of focus regions. 2025-09-30
r-rstac public Provides functions to access, search and download spacetime earth observation data via SpatioTemporal Asset Catalog (STAC). This package supports the version 0.8.1 or higher of the STAC specification (<http://stacspec.org>). 2025-09-30
r-gridpattern public Provides 'grid' grobs that fill in a user-defined area with various patterns. Includes enhanced versions of the geometric and image-based patterns originally contained in the 'ggpattern' package as well as original 'pch', 'polygon_tiling', 'regular_polygon', 'rose', 'text', 'wave', and 'weave' patterns plus support for custom user-defined patterns. 2025-09-30
r-gdalutilities public R's 'sf' package ships with self-contained 'GDAL' executables, including a bare bones interface to several 'GDAL'-related utility programs collectively known as the 'GDAL utilities'. For each of those utilities, this package provides an R wrapper whose formal arguments closely mirror those of the 'GDAL' command line interface. The utilities operate on data stored in files and typically write their output to other files. Therefore, to process data stored in any of R's more common spatial formats (i.e. those supported by the 'sp', 'sf', and 'raster' packages), first write them to disk, then process them with the package's wrapper functions before reading the outputted results back into R. GDAL function arguments introduced in GDAL version 3.2.1 or earlier are supported. 2025-09-30
r-protolite public Optimized C++ implementations for reading and writing protocol-buffers. Currently supports 'rexp.proto' for serializing R objects and 'geobuf.proto' for geojson data. This lightweight package is complementary to the much larger 'RProtoBuf' package which provides a full featured toolkit for working with protocol-buffers in R. 2025-09-30
r-metr public Many useful functions and extensions for dealing with meteorological data in the tidy data framework. Extends 'ggplot2' for better plotting of scalar and vector fields and provides commonly used analysis methods in the atmospheric sciences. 2025-09-30
r-mbess public Implements methods that useful in designing research studies and analyzing data, with particular emphasis on methods that are developed for or used within the behavioral, educational, and social sciences (broadly defined). That being said, many of the methods implemented within MBESS are applicable to a wide variety of disciplines. MBESS has a suite of functions for a variety of related topics, such as effect sizes, confidence intervals for effect sizes (including standardized effect sizes and noncentral effect sizes), sample size planning (from the accuracy in parameter estimation [AIPE], power analytic, equivalence, and minimum-risk point estimation perspectives), mediation analysis, various properties of distributions, and a variety of utility functions. MBESS (pronounced 'em-bes') was originally an acronym for 'Methods for the Behavioral, Educational, and Social Sciences,' but at this point MBESS contains methods applicable and used in a wide variety of fields and is an orphan acronym, in the sense that what was an acronym is now literally its name. MBESS has greatly benefited from others, see <http://nd.edu/~kkelley/site/MBESS.html> for a detailed list of those that have contributed and other details. 2025-09-30
r-tigris public Download TIGER/Line shapefiles from the United States Census Bureau (<https://www.census.gov/geo/maps-data/data/tiger-line.html>) and load into R as 'sf' objects. 2025-09-30
argocd-cli public Declarative Continuous Deployment for Kubernetes 2025-09-30
r-sftime public Classes and methods for spatial objects that have a registered time column, in particular for irregular spatiotemporal data. The time column can be of any type, but needs to be ordinal. Regularly laid out spatiotemporal data (vector or raster data cubes) are handled by package 'stars'. 2025-09-30
r-backbone public Provides methods for extracting from a weighted graph a binary or signed backbone that retains only the significant edges. The user may input a weighted graph, or a bipartite graph from which a weighted graph is first constructed via projection. Backbone extraction methods include the stochastic degree sequence model (SDSM; Neal, Z. P. (2014). <doi:10.1016/j.socnet.2014.06.001>), the fixed degree sequence model (FDSM; Zweig, K. A., and Kaufmann, M. (2011). <doi:10.1007/s13278-011-0021-0>), the fixed row model (FRM; Neal, Z. P. (2013). <doi:10.1007/s13278-013-0107-y>), the fixed column model (FCM; Neal, Domagalski, and Sagan (2021). <arXiv:2105.13396>), the fixed fill model (FFM; Neal, Domagalski, and Sagan (2021). <arXiv:2105.13396>), and a universal threshold method. 2025-09-30
r-stars public Reading, manipulating, writing and plotting spatiotemporal arrays (raster and vector data cubes) in 'R', using 'GDAL' bindings provided by 'sf', and 'NetCDF' bindings by 'ncmeta' and 'RNetCDF'. 2025-09-30

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