Feedstock license: BSD-3-Clause
Home: https://github.com/jwood000/RcppAlgos, https://gmplib.org/, https://github.com/kimwalisch/primesieve, http://libdivide.com, https://github.com/kimwalisch/primecount, http://ridiculousfish.com/, http://sweet.ua.pt/tos/software/prime_sieve.html
Package license: GPL-2.0-or-later
Summary: Provides optimized functions and flexible combinatorial iterators implemented in C++ with 'Rcpp' for solving problems in combinatorics and computational mathematics. Utilizes parallel programming via 'RcppThread' for maximal performance. Also makes use of the RMatrix class from the 'RcppParallel' library. There are combination/permutation functions with constraint parameters that allow for generation of all results of a vector meeting specific criteria (e.g. generating integer partitions/compositions or finding all combinations such that the sum is between two bounds). Capable of generating specific combinations/permutations (e.g. retrieve only the nth lexicographical result) which sets up nicely for parallelization as well as random sampling. Gmp support permits exploration where the total number of results is large (e.g. comboSample(10000, 500, n = 4)). Additionally, there are several high performance number theoretic functions that are useful for problems common in computational mathematics. Some of these functions make use of the fast integer division library 'libdivide'. The primeSieve function is based on the segmented sieve of Eratosthenes implementation by Kim Walisch. It is also efficient for large numbers by using the cache friendly improvements originally developed by Tomás Oliveira. Finally, there is a prime counting function that implements Legendre's formula based on the work of Kim Walisch.
Home: https://github.com/jwood000/RcppAlgos, https://gmplib.org/, https://github.com/kimwalisch/primesieve, http://libdivide.com, https://github.com/kimwalisch/primecount, http://ridiculousfish.com/, http://sweet.ua.pt/tos/software/prime_sieve.html
Package license: GPL-2.0-or-later
Summary: Provides optimized functions and flexible combinatorial iterators implemented in C++ with 'Rcpp' for solving problems in combinatorics and computational mathematics. Utilizes parallel programming via 'RcppThread' for maximal performance. Also makes use of the RMatrix class from the 'RcppParallel' library. There are combination/permutation functions with constraint parameters that allow for generation of all results of a vector meeting specific criteria (e.g. generating integer partitions/compositions or finding all combinations such that the sum is between two bounds). Capable of generating specific combinations/permutations (e.g. retrieve only the nth lexicographical result) which sets up nicely for parallelization as well as random sampling. Gmp support permits exploration where the total number of results is large (e.g. comboSample(10000, 500, n = 4)). Additionally, there are several high performance number theoretic functions that are useful for problems common in computational mathematics. Some of these functions make use of the fast integer division library 'libdivide'. The primeSieve function is based on the segmented sieve of Eratosthenes implementation by Kim Walisch. It is also efficient for large numbers by using the cache friendly improvements originally developed by Tomás Oliveira. Finally, there is a prime counting function that implements Legendre's formula based on the work of Kim Walisch.
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Installing r-rcppalgos from the conda-forge channel can be achieved by adding conda-forge to your channels with:
conda config --add channels conda-forge
conda config --set channel_priority strict
Once the conda-forge channel has been enabled, r-rcppalgos can be installed with conda:
conda install r-rcppalgos
or with mamba:
mamba install r-rcppalgos
It is possible to list all of the versions of r-rcppalgos available on your platform with conda:
conda search r-rcppalgos --channel conda-forge
or with mamba:
mamba search r-rcppalgos --channel conda-forge
Alternatively, mamba repoquery may provide more information:
# Search all versions available on your platform:
mamba repoquery search r-rcppalgos --channel conda-forge
# List packages depending on `r-rcppalgos`:
mamba repoquery whoneeds r-rcppalgos --channel conda-forge
# List dependencies of `r-rcppalgos`:
mamba repoquery depends r-rcppalgos --channel conda-forge
conda-forge is a community-led conda channel of installable packages. In order to provide high-quality builds, the process has been automated into the conda-forge GitHub organization. The conda-forge organization contains one repository for each of the installable packages. Such a repository is known as a feedstock.
A feedstock is made up of a conda recipe (the instructions on what and how to build the package) and the necessary configurations for automatic building using freely available continuous integration services. Thanks to the awesome service provided by Azure, GitHub, CircleCI, AppVeyor, Drone, and TravisCI it is possible to build and upload installable packages to the conda-forge anaconda.org channel for Linux, Windows and OSX respectively.
To manage the continuous integration and simplify feedstock maintenance
conda-smithy has been developed.
Using the conda-forge.yml within this repository, it is possible to re-render all of
this feedstock's supporting files (e.g. the CI configuration files) with conda smithy rerender.
For more information please check the conda-forge documentation.
feedstock - the conda recipe (raw material), supporting scripts and CI configuration.
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Its primary use is in the construction of the CI .yml files
and simplify the management of many feedstocks.
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If you would like to improve the r-rcppalgos recipe or build a new
package version, please fork this repository and submit a PR. Upon submission,
your changes will be run on the appropriate platforms to give the reviewer an
opportunity to confirm that the changes result in a successful build. Once
merged, the recipe will be re-built and uploaded automatically to the
conda-forge channel, whereupon the built conda packages will be available for
everybody to install and use from the conda-forge channel.
Note that all branches in the conda-forge/r-rcppalgos-feedstock are
immediately built and any created packages are uploaded, so PRs should be based
on branches in forks and branches in the main repository should only be used to
build distinct package versions.
In order to produce a uniquely identifiable distribution:
- If the version of a package is not being increased, please add or increase
the
build/number. - If the version of a package is being increased, please remember to return
the
build/numberback to 0.