The stochastic self-consistent harmonic approximation (SSCHA) is a full computational Python package that simulates thermodynamic and phononic properties of materials, accounting for anharmonicity at a nonperturbative level, fully including quantum and thermal fluctuations.
See more info on the webpage:
The SSCHA code is available as a Python library, with computationally intensive parts accelerated using C, Fortran, and Julia.
A quick way to install all the requirements to compile the code in a separate environment is to use Anaconda.
Alternatively, when anaconda is too slow, we recommend using mamba or micromamba. Just replace coda with mamba or micromamba, respectively.
conda create -n sscha -c conda-forge python=3.12 gfortran libblas lapack openmpi julia openmpi-mpicc pip numpy scipy spglib=2.2
conda activate sscha
pip install ase juliacall mpi4py
pip install cellconstructor python-sscha tdscha
This is the safest and best way to install the SSCHA. The first line creates a new pristine Python environment with all the required libraries to compile the source code. The second line activates the newly installed environment. Then, the third command installs the additional dependencies, and the last line compiles and installs the SSCHA code.
Note, the first time you start up a sscha calculation, the code will download (through juliacall) Julia and the extra packages needed by the python-julia interface. This process may fail if you do not have an internet connection available. Note that Julia is not mandatory, as the code will fall back to the old Fortran implementation (prior to version 1.4) and continue to run.
The full recordings, both of theoretical lectures, tutorials and Hands-on sessions can be found in our youtube channel SSCHAcode
To use the SSCHA, you must activate the python environment with (replace conda with mamba or micromamba if you use those environment managers):
conda activate sscha
This installation method should also work on clusters and with computers with custom configurations. You must remember to activate the sscha environment even in your submission scripts on clusters.
To check that Julia is correctly set up (and download it the first time), run the following line:
python -c 'import sscha.JuliaExt as J; J.get_main()'
If you do not have Anaconda to handle your dependencies, you need to compile the code manually.
Most of the codes require a Fortran or C compiler and an MPI configured. Here we install all the requirements to set up the SSCHA code correctly. To properly compile and install the SSCHA code, you need a Fortran compiler and LAPACK/BLAS available.
On a Debian-based Linux distribution, all the software required is installed with (Tested on Quantum Mobile and Ubuntu 20.04):
sudo apt update
sudo apt install libblas-dev liblapack-dev liblapacke-dev gfortran openmpi-bin
Note that some of the names of the libraries may change slightly in different Linux versions or on macOS.
Up to version 1.4 of SSCHA, it supports only Python <= 3.10 and the old setuptools<=64 (we require the deprecated distutils). Starting from version 1.5, we dropped distutils and now support more recent version of python. If you are using the default Python in the system, make sure to have installed the development header files. On Ubuntu, they can be installed with:
sudo apt install python-dev
If you use anaconda (or mamba/micromamba), they are automatically installed.
The SSCHA code comprises three Python packages: CellConstructor, python-sscha, and tdscha.
- CellConstructor: utility to manage phonon dispersions, atomic structures and crystal symmetries
- sscha : This repository, relax the structure with anharmonicity and computes static linear response properties.
- tdscha : Compute the dynamical linear response (Raman and IR, spectral functions)
More details about installations are on the official website www.sscha.eu
The easiest way to install the code is through anaconda/mamba.
The following commands are sufficient to install the full sscha suite and its dependencies.
Replace conda with mamba or micromamba if that is the package manager you are using.
conda create -n sscha -c conda-forge python=3.12 gfortran libblas lapack openmpi julia openmpi-mpicc pip numpy scipy spglib=2.2
conda activate sscha
pip install ase juliacall mpi4py
pip install cellconstructor python-sscha tdscha
If you happen to get an error when using Julia, please try to install Julia from the official website and see the passages reported in the Manual installation.
To activate the environment and execute the SSCHA, run
conda activate sscha
The SSCHA benefits from Julia being installed in the system. If present, it will be automatically used to speedup the calculation.
The python-julia interface is provided by juliacall (PyJulia is no longer required). Install it with
pip install juliacall
There is no need to install Julia manually: the first time it is needed, juliacall downloads Julia and the required Julia packages automatically. You can trigger (and check) this step with
python -c 'import sscha.JuliaExt as J; J.get_main()'
If you prefer to use a Julia already installed in the system (e.g. from julialang.org/downloads/ or JuliaUp), point juliacall to the Julia executable (not the JuliaUp launcher) and to a Julia environment:
export PYTHON_JULIACALL_EXE=/path/to/julia/bin/julia
export PYTHON_JULIACALL_PROJECT=/path/to/a/julia/environment
The tdscha extension to compute Raman and IR (from version 1.6.2) uses the same juliacall interface, and the required Julia packages are installed automatically: no further setup is needed. It is not required to install Julia before TDSCHA; it can also be done at a later time.
Once the prerequisites have been installed, python-sscha can be downloaded and installed with
pip install cellconstructor python-sscha
Alternatively, it is possible to use the most recent version from the SSCHA GitHub repository, under CellConstructor and python-sscha repositories. The installation is performed in this case with
pip install .
If you have multiple compilers installed, and want to force pip to employ a specific fortran compiler, you can specify its path in the FC environment variable. Remember that the compiler employed to compile the code should match with the linker, indicated in the LDSHARED variable.
For example
FC=gfortran LDSHARED=gfortran pip install cellconstructor python-sscha
For the development version of the code.
To compile and install SSCHA with Meson, follow these typical steps:
First, you can open a terminal and then navigate to the root directory of the project source code. This is where the meson.build file is located.
cd /path/to/source/root/python-sschaCreate and configure a build directory by running:
meson setup builddiror if you are in a conda env (the best option for a local installation):
meson setup builddir --prefix=$CONDA_PREFIXif you want to use Intel MKL:
setup builddir -Duse_mkl=trueThis command sets up a separate build directory (builddir) where all compiled files and build artifacts will be placed, keeping the source directory clean. After this, change into the build directory:
cd builddirOnce inside the build directory, compile the project using:
meson compileThis will compile the source code according to the configuration from the previous step.
The project includes tests, you need to install pytest to work. You can run them with:
meson testThis step helps verify that the build works correctly.
To install the compiled binaries, libraries, and other files system-wide (or to a custom location), run:
meson installor
sudo meson installYou may need superuser privileges (hence sudo) to install to system directories.
Following these steps will help you successfully compile, test, and install SSCHA with Meson as their build system.