A package for post-processing SEM data.
Documentation is available here.
To install in your pip enviroment, clone this repository and execute:
pip install --editable .
The --editable flag is optional, and will allow changes in the code of the package to be used
directly without reinstalling.
You can install dependencies as follow:
pip install numpy
pip install scipy
pip install pymech
pip install tdqm
mpi4py is needed even when running in serial, as the library is built with communication in mind. It can typically be installed with:
pip install mpi4py
In some instances, such as in supercomputers, it is typically necesary that the mpi of the system is used. If mpi4py is not available as a module, we have found (so far) that installing it as follows works:
export MPICC=$(which CC)
pip install mpi4py --no-cache-dir
where CC should be replaced by the correct C wrappers of the system (In a workstation you would probably need mpicc or so). It is always a good idea to contact support or check the specific documentation if things do not work.
Some functionalities such as data streaming require the use of adios2. You can check how the installation is performed here
Specifically for the interpolator routines, a pytorch module is available in case you have GPUs and want to use them in the process. We note that we only use pytorch in this one instance as an option. There are versions that work exclusively with numpy on CPUs so pytorch can be avoided.
To install pytorch, you can check here. A simple installation for CUDA v12.1 on linux would look like this (following the instructions from the link):
pip3 install torch torchvision torchaudio
The process of installing pytorch in supercomputers is more intricate. In this case it is best to use the documentation of the specific cluster or contact support.
To get an idea on how the codes are used, feel free to check the examples we have provided. Please note that most of the routines included here work in prallalel. In fact, python scripts are encouraged rather than notebooks to take advantage of this capability.
You can use the provided tests to check if your installation is complete (Not all functionallities are currently tested but more to come).
The tests rely on pytest. To install it in your pip enviroment simply execute pip install pytest. To run the tests, execute the pytest tests/ command from the root directory of the repository.