Installing Muscat

Conda

If you use conda, you can install Muscat CPU version from the conda-forge channel.

A good practice is to use a separate environment rather than modifying the base environment:

conda create -n my-env
conda activate my-env

The actual install command is:

conda install -c conda-forge muscat

The Conda-Forge packages of Muscat are split in 4 packages :

  • Muscat-core: Muscat package with the mandatory dependencies.

  • Muscat-extensions: a meta package with the extra dependencies to enable all functionalities of Muscat.

  • Muscat: this meta package install Muscat-core and Muscat-extensions to have a full installation in one shot.

  • Muscat-devenv: is a meta package with the dependencies necessarily for the development, debugging, compilation and documentation generation.

One may consider Muscat-devenv without Kokkos & ArborX packages that will be automatically fetched and configured auto-detecting your GPU hardware if an internet connection is available.

PIP

Pip installation is not available any more. The main reason is the increasing complexity of the building chain (kokkos and Cuda support).

Manual Installation (from Sources) for advanced Users and Developers

In the case you want the latest developer version, make changes to Muscat or contribute new features, an installation from sources is mandatory. The sources can be downloaded from https://gitlab.com/drti/muscat:

git clone https://gitlab.com/drti/muscat.git

Inside the repository folder, you must compile the C++ extensions to have the optimized algorithms available:

If your hardware architecture includes a Nvidia GPU, please refer to the developer section to build a Cuda-enabled Muscat version CMake.

For Kokkos::Cuda backend use, please refer to section Parallel Computations

Compilation

You will need cmake version greater than 3.28, and a compiler supporting C++17.

cmake ./superbuild -B build
make -j -C build

If you already tried to compile, you may already have a file CMakeCache.txt and folders build and CMakeFiles. You should remove them first.

Using it in Python

Add the MUSCAT_REPOSITORY/build/Muscat-build/src/:MUSCAT_REPOSITORY/src/ folders to the PYTHONPATH environment variables (more information on https://docs.python.org/3/using/cmdline.html#envvar-PYTHONPATH).

Warning

Make sure MUSCAT_REPOSITORY/build/Muscat-build/src/ is placed before MUSCAT_REPOSITORY/src/

The user can also install permanently using (Not recommended):

make -j -C install

Building the Documentation

The documentation for Muscat can be compiled using a python environment with the following packages:

  • sphinx

  • nbsphinx

  • jupyter

  • furo

  • doxygen

  • ninja

make -j -C build doc_html

Requirements

Python Dependencies

Python minimal version: 3.9. Some features may be unavailable when optional packages are not installed.

Module Name

Version

Used during (Optional #)

Conda packages name

Notes

Compile

Run

Debug

Doc

Muscat-core

Muscat-extensions

Muscat

Muscat-devenv

python

>=3.9

*

*

*

*

*

*

*

*

Supported distributions are: conda-forge

numpy

>=1.21

*

*

*

*

*

*

array manipulation and linear algebra

scipy

>=1.12

*

*

*

*

*

sparse (coo_matrix), spatial (KDTree, delaunay, ConvexHull)

sympy

*

*

*

*

*

*

matrices, Symbols, lambdify, Derivative, symplify

cython

*

*

*

*

*

Compilation of c++ extensions

vtk

*

*

*

*

*

stlReader, MeshFieldOperations, ImplicitGeometryObjects, vtkBridge

eigency

>=2

*

*

*

*

*

*

Compilation and run of c++ extensions

mkl

*

*

*

*

*

*

Can be deactivated at compilation using the env variable : MUSCAT_USE_MKL = 0

mkl-include

*

*

*

Can be deactivated at compilation using the env variable : MUSCAT_USE_MKL = 0

psutil

#

*

*

*

*

*

memory usage and cpu_count()

dill

#

#

#

*

*

*
for faster Muscat start up (cache finite

element shape function pointers)

scikit-sparse

#

Linear solver: Cholesky “cholesky”

pypardiso

#

Linear solver: mkl-Intel Pardiso

matplotlib

#

*

*

*

*

plot shape function for debugin

pyamg

#

*

*

*

linear solver: Algebraic Multigrid “AMG”

h5py

#

*

*

*

xdmf Reader/Writer

meshio

#

*

*

*

main usage in MeshIOBridge.py (derivated usage in Mesh File Converter)

sphinx

*

*

Documentation Generation

sphinx-rtd-theme

*

*

Documentation Generation

breathe

*

*

cmake documentation integration

setuptools-scm

*

Only during conda packaging

pyvista

#

*

*

*

pyvista bridge

networkx

>=3

*

*

*

*

*

only use in MeshGraphTools.py

mpi4py

#

only use in MPIInterface.py

pytest

*

To test Muscat in development face

pywin32

*

*

* (only Win)

* (only Win)

Correctly find exec on disk (only Win)

cvxpy

*

*

Only used in AnisotropicMetricComputation.py

C++ Dependencies

Name

Version

Used during

Conda packages name

Notes

Compile

Run

Debug

Doc

Muscat-devenv

eigen

>=3.4

*

*

For compilation of the C++ extensions

libboost-headers

>=1.8 2

*

*

For the compilation of the extension field transfer

kokkos

=v4.7.01

*

*

*

https://github.com/kokkos/kokkos

arborx

=v2.0.1

*

*

*

https://github.com/arborx/ArborX

mmg

>=5.8

*

*

*

https://www.mmgtools.org/

External Dependencies

Name

Version

Compile

Run

Debug

Doc

Notes

cmake

>=3.22

(*)

*

for the cpp documentation generation

abaqus

#

odb reader. This feature is deprecated (only available on python 2.7, BasicTools 1.7.2)