First steps in Yambopy: Difference between revisions
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The yambopy project aims to develop python tools to: | |||
* | * Read and edit yambo and quantum espresso input files | ||
* | * Easily perform pre- and post-processing of the simulation data for these two codes - including hard-to-get, database-encoded data beyond standard outputs | ||
* Provide easy visualization and plotting options | |||
* Set up simple automatization workflows (e.g., convergence tests) | |||
* | |||
* | |||
=== Setup === | |||
First of all, make sure that you have a suitable python environment (crated for example with [https://docs.anaconda.com/miniconda/install/ conda] or [https://docs.python.org/3/library/venv.html venv]) with python >=3.8. | |||
If you are not used with python environments, here two simple commands that you can use | |||
python -m venv MYPATH/yamboenv/ | |||
(you can replace `MYPATH` with any path you prefer, e.g. `~/`) | |||
source MYPATH/yamboenv/bin/activate | |||
(for bash users, you can add to your .bashrt the line `. MYPATH/yamboenv/bin/activate`) | |||
Then, you may install yambopy in one of the following ways. | |||
==== Quick installation from PyPI repository ==== | |||
* | * In order to quickly install the officially released version type: | ||
pip install yambopy | |||
==== Installation from tarball ==== | |||
* | * In case you don't want to download from the pip repository and prefer to install a version of yambopy locally, you may download the appropriate tarball from the [https://github.com/yambo-code/yambopy/releases| yambopy github page]. Extract the tarball, enter the yambopy folder and type <code>pip install .</code> | ||
==== Installation of latest patch ==== | |||
* In case you want the latest version of the code including new updates and patches that might not be present in the official version, then you can clone the yambopy git repository (a basic knowledge of git may be helpful): | |||
git clone https://github.com/yambo-code/yambopy.git | |||
cd yambopy | cd yambopy | ||
pip install . | |||
==== Dependencies ==== | |||
< | * In principle, <code>pip</code> should take care of the required python dependencies. They are <code>numpy</code>, <code>scipy</code>, <code>matplotlib</code>, <code>netCDF4</code>, <code>lxml</code>, <code>PyYAML</code> and <code>monty</code>. In case some dependency-related problem arises, you can install each of them separately beforehand with: | ||
</ | |||
pip install <code>dependency-name</code> | |||
=== Tutorials === | |||
Now yambopy is ready to use! Just go to the tutorials folder and follow the docs! | |||
cd tutorial/ | |||
On this wiki, we provide steps for the following tutorials: | |||
1. Data postprocessing: | |||
* [[Yambopy tutorial: band structures | Database and plotting tutorial for quantum espresso: qepy]] (Get the databases: [https://media.yambo-code.eu/educational/tutorials/files/databases_qepy.tar.gz databases_qepy], 46.5MB) | |||
* Yambopy | * [[Yambopy tutorial: Yambo databases | Database and plotting tutorial for yambo: yambopy ]] (Get the databases: [https://media.yambo-code.eu/educational/tutorials/files/databases_yambopy.tar.gz databases_yambopy], 129MB) | ||
2. Manage QE and Yambo runs: | |||
* [[GW tutorial. Convergence and approximations (BN)]] | |||
* [[Bethe-Salpeter equation tutorial. Optical absorption (BN)]] | |||
3. Advanced topics: | |||
* [[Phonon-assisted luminescence by finite atomic displacements]] | |||
* | |||
Latest revision as of 13:49, 22 November 2024
The yambopy project aims to develop python tools to:
- Read and edit yambo and quantum espresso input files
- Easily perform pre- and post-processing of the simulation data for these two codes - including hard-to-get, database-encoded data beyond standard outputs
- Provide easy visualization and plotting options
- Set up simple automatization workflows (e.g., convergence tests)
Setup
First of all, make sure that you have a suitable python environment (crated for example with conda or venv) with python >=3.8.
If you are not used with python environments, here two simple commands that you can use
python -m venv MYPATH/yamboenv/
(you can replace `MYPATH` with any path you prefer, e.g. `~/`)
source MYPATH/yamboenv/bin/activate
(for bash users, you can add to your .bashrt the line `. MYPATH/yamboenv/bin/activate`)
Then, you may install yambopy in one of the following ways.
Quick installation from PyPI repository
- In order to quickly install the officially released version type:
pip install yambopy
Installation from tarball
- In case you don't want to download from the pip repository and prefer to install a version of yambopy locally, you may download the appropriate tarball from the yambopy github page. Extract the tarball, enter the yambopy folder and type
pip install .
Installation of latest patch
- In case you want the latest version of the code including new updates and patches that might not be present in the official version, then you can clone the yambopy git repository (a basic knowledge of git may be helpful):
git clone https://github.com/yambo-code/yambopy.git cd yambopy pip install .
Dependencies
- In principle,
pip
should take care of the required python dependencies. They arenumpy
,scipy
,matplotlib
,netCDF4
,lxml
,PyYAML
andmonty
. In case some dependency-related problem arises, you can install each of them separately beforehand with:
pip install dependency-name
Tutorials
Now yambopy is ready to use! Just go to the tutorials folder and follow the docs!
cd tutorial/
On this wiki, we provide steps for the following tutorials:
1. Data postprocessing:
- Database and plotting tutorial for quantum espresso: qepy (Get the databases: databases_qepy, 46.5MB)
- Database and plotting tutorial for yambo: yambopy (Get the databases: databases_yambopy, 129MB)
2. Manage QE and Yambo runs:
- GW tutorial. Convergence and approximations (BN)
- Bethe-Salpeter equation tutorial. Optical absorption (BN)
3. Advanced topics: