Home: https://github.com/romerogroup/pyprocar
Package license: GPL-3.0-only
Feedstock license: BSD-3-Clause
Summary: A Python library for electronic structure pre/post-processing.
Development: https://github.com/romerogroup/pyprocar
Documentation: https://romerogroup.github.io/pyprocar/
PyProcar is a robust, open-source Python library used for pre- and post-processing of the electronic structure data coming from DFT calculations. PyProcar provides a set of functions that manage data obtained from the PROCAR format. Basically, the PROCAR format is a projection of the Kohn-Sham states over atomic orbitals. That projection is performed to every k-point in the considered mesh, every energy band and every atom. PyProcar is capable of performing a multitude of tasks including plotting plain and spin/atom/orbital projected band structures and Fermi surfaces- both in 2D and 3D, Fermi velocity plots, unfolding bands of a super cell, comparing band structures from multiple DFT calculations, plotting partial density of states and generating a k-path for a given crystal structure.
All platforms: |
Name | Downloads | Version | Platforms |
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Installing pyprocar
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, pyprocar
can be installed with:
conda install pyprocar
It is possible to list all of the versions of pyprocar
available on your platform with:
conda search pyprocar --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 CircleCI, AppVeyor and TravisCI it is possible to build and upload installable packages to the conda-forge Anaconda-Cloud 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.
conda-smithy - the tool which helps orchestrate the feedstock.
Its primary use is in the construction of the CI .yml
files
and simplify the management of many feedstocks.
conda-forge - the place where the feedstock and smithy live and work to produce the finished article (built conda distributions)
If you would like to improve the pyprocar 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/pyprocar-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/number
back to 0.