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py-opencv
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public |
Computer vision and machine learning software library.
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2025-09-30 |
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r-geomap
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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.
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2025-09-30 |
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r-rstac
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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>).
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2025-09-30 |
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r-gridpattern
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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.
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2025-09-30 |
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r-gdalutilities
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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.
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2025-09-30 |
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r-protolite
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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.
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2025-09-30 |
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r-metr
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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.
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2025-09-30 |
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r-mbess
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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.
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2025-09-30 |
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r-tigris
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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.
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2025-09-30 |
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argocd-cli
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public |
Declarative Continuous Deployment for Kubernetes
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2025-09-30 |
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r-sftime
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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'.
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2025-09-30 |
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r-backbone
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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.
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2025-09-30 |
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r-stars
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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'.
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2025-09-30 |
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pesummary
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public |
Python package to produce summary pages for Parameter estimation codes
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2025-09-30 |
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r-zigg
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public |
The 'Ziggurat' pseudo-random number generator (or PRNG), introduced by Marsaglia and Tsang (2000, <doi:10.18637/jss.v005.i08>) and further improved by Leong et al (2005, <doi:10.18637/jss.v012.i07>), offers a lightweight and very fast PRNG for the normal, exponential, and uniform distributions. It is provided here in a small zero-dependency package. It can be used from R as well as from 'C/C++' code in other packages as is demonstrated by four included sample packages using four distinct methods to use the PRNG presented here in client package. The implementation is influenced by our package 'RcppZiggurat' which offers a comparison among multiple alternative implementations but presented here in a lighter-weight implementation that is easier to use by other packages. The PRNGs provided are generally faster than the ones in base R: on our machine, the relative gains for normal, exponential and uniform are on the order of 7.4, 5.2 and 4.7 times faster than base R. However, these generators are of potentially lesser quality and shorter period so if in doubt use of the base R functions remains the general recommendation.
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2025-09-30 |
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r-rxode2ll
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Provides the log-likelihoods with gradients from 'stan' (Carpenter et al (2015), <arXiv:1509.07164>) needed for generalized log-likelihood estimation in 'nlmixr2' (Fidler et al (2019) <doi:10.1002/psp4.12445>). This is split of to reduce computational burden of recompiling 'rxode2' (Wang, Hallow and James (2016) <doi:10.1002/psp4.12052>) which runs the 'nlmixr2' models during estimation.
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2025-09-30 |
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sphinx_parser
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public |
Parser for the DFT program SPHInX
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2025-09-30 |
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r-ggmulti
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public |
It provides materials (i.e. 'serial axes' objects, Andrew's plot, various glyphs for scatter plot) to visualize high dimensional data.
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2025-09-30 |
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compiler-rt
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public |
compiler-rt runtime libraries
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2025-09-30 |
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compiler-rt_osx-64
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public |
compiler-rt runtime libraries
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2025-09-30 |
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girder-client
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public |
Python client for interacting with Girder servers
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2025-09-30 |
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r-openmx
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Facilitates treatment of statistical model specifications as things that can be generated and manipulated programmatically. Structural equation models may be specified with reticular action model matrices or paths, linear structural relations matrices or paths, or directly in matrix algebra. Fit functions include full information maximum likelihood, maximum likelihood, and weighted least squares. Example models include confirmatory factor, multiple group, mixture distribution, categorical threshold, modern test theory, differential equations, state space, and many others. MacOS users can download the most up-to-date package binaries from <http://openmx.ssri.psu.edu>. See Neale, Hunter, Pritikin, Zahery, Brick, Kirkpatrick, Estabrook, Bates, Maes, & Boker (2016) <doi:10.1007/s11336-014-9435-8>.
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2025-09-30 |
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compiler-rt_osx-arm64
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public |
compiler-rt runtime libraries
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2025-09-30 |
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compiler-rt_win-64
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public |
compiler-rt runtime libraries
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2025-09-30 |
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r-gdalcubes
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public |
Processing collections of Earth observation images as on-demand multispectral, multitemporal raster data cubes. Users define cubes by spatiotemporal extent, resolution, and spatial reference system and let 'gdalcubes' automatically apply cropping, reprojection, and resampling using the 'Geospatial Data Abstraction Library' ('GDAL'). Implemented functions on data cubes include reduction over space and time, applying arithmetic expressions on pixel band values, moving window aggregates over time, filtering by space, time, bands, and predicates on pixel values, exporting data cubes as 'netCDF' or 'GeoTIFF' files, and plotting. The package implements lazy evaluation and multithreading. All computational parts are implemented in C++, linking to the 'GDAL', 'netCDF', 'CURL', and 'SQLite' libraries. See Appel and Pebesma (2019) <doi:10.3390/data4030092> for further details.
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2025-09-30 |
