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r-spam
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public |
No Summary
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2023-06-16 |
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r-rsaga
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public |
No Summary
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2023-06-16 |
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r-spacetime
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public |
No Summary
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2023-06-16 |
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r-proxy
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public |
No Summary
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2023-06-16 |
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r-fnn
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public |
No Summary
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2023-06-16 |
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r-matching
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public |
No Summary
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2023-06-16 |
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r-geosphere
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public |
No Summary
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2023-06-16 |
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r-rstoolbox
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public |
No Summary
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2023-06-16 |
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r-rgdal
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public |
No Summary
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2023-06-16 |
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r-colorramps
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public |
No Summary
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2023-06-16 |
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gmaps
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public |
Google maps plugin for Jupyter notebooks
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2023-06-16 |
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r-rgeos
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public |
No Summary
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2023-06-16 |
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r-rcpparmadillo
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public |
'Armadillo' is a templated C++ linear algebra library (by Conrad Sanderson) that aims towards a good balance between speed and ease of use. Integer, floating point and complex numbers are supported, as well as a subset of trigonometric and statistics functions. Various matrix decompositions are provided through optional integration with LAPACK and ATLAS libraries. The 'RcppArmadillo' package includes the header files from the templated 'Armadillo' library. Thus users do not need to install 'Armadillo' itself in order to use 'RcppArmadillo'. 'Armadillo' is licensed under the MPL 2.0, while 'RcppArmadillo' (the 'Rcpp' bindings/bridge to Armadillo) is licensed under the GNU GPL version 2 or later, as is the rest of 'Rcpp'. Note that Armadillo requires a fairly recent compiler; for the g++ family at least version 4.6.* is required.
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2023-06-16 |
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r-bbmle
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public |
No Summary
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2023-06-16 |
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r-ncdf4
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public |
Provides a high-level R interface to data files written using Unidata's netCDF library (version 4 or earlier), which are binary data files that are portable across platforms and include metadata information in addition to the data sets. Using this package, netCDF files (either version 4 or "classic" version 3) can be opened and data sets read in easily. It is also easy to create new netCDF dimensions, variables, and files, in either version 3 or 4 format, and manipulate existing netCDF files. This package replaces the former ncdf package, which only worked with netcdf version 3 files. For various reasons the names of the functions have had to be changed from the names in the ncdf package. The old ncdf package is still available at the URL given below, if you need to have backward compatibility. It should be possible to have both the ncdf and ncdf4 packages installed simultaneously without a problem. However, the ncdf package does not provide an interface for netcdf version 4 files.
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2023-06-16 |
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usgs
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public |
Access the USGS inventory service
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2023-06-16 |
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termcolor
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public |
ANSII Color formatting for output in terminal.
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2023-06-16 |
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humanize
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public |
python humanize utilities
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2023-06-16 |
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homura
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public |
Python downloader with progress
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2023-06-16 |
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requests-futures
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public |
Asynchronous Python HTTP for Humans.
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2023-06-16 |
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python-dateutil
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public |
Extensions to the standard Python datetime module
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2023-06-16 |
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r-rhdfs
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public |
This package provides basic connectivity to the Hadoop Distributed File System. R programmers can browse, read, write, and modify files stored in HDFS from within R. Install this package only on the node that will run the R client.
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2023-06-16 |
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oct2py
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public |
Python to GNU Octave bridge --> run m-files from python
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2023-06-16 |
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flake8
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public |
the modular source code checker: pep8, pyflakes and co
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2023-06-16 |
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landsat-util
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public |
A utility to search, download and process Landsat 8 satellite imagery
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2023-06-16 |
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pdoc
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public |
A simple program and library to auto generate API documentation for Python modules.
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2023-06-16 |
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polyline
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public |
A Python implementation of Google's Encoded Polyline Algorithm Format.
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2023-06-16 |
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rasterio
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public |
Fast and direct raster I/O for use with Numpy and SciPy
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2023-06-16 |
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geocoder
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public |
Geocoder is a simple and consistent geocoding library.
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2023-06-16 |
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click-plugins
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public |
An extension module for click to enable registering CLI commands via setuptools entry-points.
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2023-06-16 |
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ratelim
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public |
Makes it easy to respect rate limits.
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2023-06-16 |
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r-bit
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public |
bitmapped vectors of booleans (no NAs), coercion from and to logicals, integers and integer subscripts; fast boolean operators and fast summary statistics. With 'bit' vectors you can store true binary booleans {FALSE,TRUE} at the expense of 1 bit only, on a 32 bit architecture this means factor 32 less RAM and ~ factor 32 more speed on boolean operations. Due to overhead of R calls, actual speed gain depends on the size of the vector: expect gains for vectors of size > 10000 elements. Even for one-time boolean operations it can pay-off to convert to bit, the pay-off is obvious, when such components are used more than once. Reading from and writing to bit is approximately as fast as accessing standard logicals - mostly due to R's time for memory allocation. The package allows to work with pre-allocated memory for return values by calling .Call() directly: when evaluating the speed of C-access with pre-allocated vector memory, coping from bit to logical requires only 70% of the time for copying from logical to logical; and copying from logical to bit comes at a performance penalty of 150%. the package now contains further classes for representing logical selections: 'bitwhich' for very skewed selections and 'ri' for selecting ranges of values for chunked processing. All three index classes can be used for subsetting 'ff' objects (ff-2.1-0 and higher).
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2023-06-16 |
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r-rastervis
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public |
Methods for enhanced visualization and interaction with raster data. It implements visualization methods for quantitative data and categorical data, both for univariate and multivariate rasters. It also provides methods to display spatiotemporal rasters, and vector fields. See the website for examples.
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2023-06-16 |
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r-ff
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public |
The ff package provides data structures that are stored on disk but behave (almost) as if they were in RAM by transparently mapping only a section (pagesize) in main memory - the effective virtual memory consumption per ff object. ff supports R's standard atomic data types 'double', 'logical', 'raw' and 'integer' and non-standard atomic types boolean (1 bit), quad (2 bit unsigned), nibble (4 bit unsigned), byte (1 byte signed with NAs), ubyte (1 byte unsigned), short (2 byte signed with NAs), ushort (2 byte unsigned), single (4 byte float with NAs). For example 'quad' allows efficient storage of genomic data as an 'A','T','G','C' factor. The unsigned types support 'circular' arithmetic. There is also support for close-to-atomic types 'factor', 'ordered', 'POSIXct', 'Date' and custom close-to-atomic types. ff not only has native C-support for vectors, matrices and arrays with flexible dimorder (major column-order, major row-order and generalizations for arrays). There is also a ffdf class not unlike data.frames and import/export filters for csv files. ff objects store raw data in binary flat files in native encoding, and complement this with metadata stored in R as physical and virtual attributes. ff objects have well-defined hybrid copying semantics, which gives rise to certain performance improvements through virtualization. ff objects can be stored and reopened across R sessions. ff files can be shared by multiple ff R objects (using different data en/de-coding schemes) in the same process or from multiple R processes to exploit parallelism. A wide choice of finalizer options allows to work with 'permanent' files as well as creating/removing 'temporary' ff files completely transparent to the user. On certain OS/Filesystem combinations, creating the ff files works without notable delay thanks to using sparse file allocation. Several access optimization techniques such as Hybrid Index Preprocessing and Virtualization are implemented to achieve good performance even with large datasets, for example virtual matrix transpose without touching a single byte on disk. Further, to reduce disk I/O, 'logicals' and non-standard data types get stored native and compact on binary flat files i.e. logicals take up exactly 2 bits to represent TRUE, FALSE and NA. Beyond basic access functions, the ff package also provides compatibility functions that facilitate writing code for ff and ram objects and support for batch processing on ff objects (e.g. as.ram, as.ff, ffapply). ff interfaces closely with functionality from package 'bit': chunked looping, fast bit operations and coercions between different objects that can store subscript information ('bit', 'bitwhich', ff 'boolean', ri range index, hi hybrid index). This allows to work interactively with selections of large datasets and quickly modify selection criteria. Further high-performance enhancements can be made available upon request.
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2023-06-16 |
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seawater
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public |
Seawater Library for Python
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2023-06-16 |
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gdal
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public |
No Summary
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2023-06-16 |
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python-redmine
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public |
Library for communicating with a Redmine project management application
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2023-06-16 |
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sen2cor
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public |
Sentinel 2 Level-2A Processor
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2023-06-16 |
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r-viridislite
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public |
Port of the new 'matplotlib' color maps ('viridis' - the default -, 'magma', 'plasma' and 'inferno') to 'R'. 'matplotlib' <http://matplotlib.org/ > is a popular plotting library for 'python'. These color maps are designed in such a way that they will analytically be perfectly perceptually-uniform, both in regular form and also when converted to black-and-white. They are also designed to be perceived by readers with the most common form of color blindness. This is the 'lite' version of the more complete 'viridis' package that can be found at <https://cran.r-project.org/package=viridis>.
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2023-06-16 |
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cioppy
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None |
ciop python bindings
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2023-06-16 |
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ecmwfapi
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None |
ECMWF API is a set of services developed by ECMWF http://www.ecmwf.int to allow users from the outside to access some internal features and data of the centre.
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2023-06-16 |
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proj4
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None |
PROJ.4 Cartographic Projections library
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2023-06-16 |
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beampy
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None |
beampy is a module that implements the link from Python to the BEAM Java API. The beampy module depends on a bi-directional Java-Python bridge jpy.
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2023-06-16 |
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jpy
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None |
jpy is a bi-directional Python-Java bridge which you can use to embed Java code in Python programs or the other way round
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2023-06-16 |
