First steps in Yambopy

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)

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.

pip install yambopy

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 .

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 .

In principle, pip should take care of the required python dependencies. They are numpy, scipy, matplotlib, netCDF4, lxml, PyYAML and monty. In case some dependency-related problem arises, you can install each of them separately beforehand with:

pip install dependency-name

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:

2. Manage QE and Yambo runs:

3. Advanced topics:

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