If you wish to try a different DAE solver, PyBaMM currently offers a
direct interface to the sparse KLU solver within Sundials. This solver
comes as a C++ python extension module. Therefore, when installing
PyBaMM from source (e.g. from the GitHub repository), the KLU sparse
solver module must be compiled. Running pip install . or
python setup.py install in the PyBaMM directory will result in a
attempt to compile the KLU module.
Note that if CMake of pybind11 are not found (see below), the
installation of PyBaMM will carry on, however skipping the compilation
of the idaklu module. This allows developers that are not interested
in the KLU module to install PyBaMM from source without having to
install the required dependencies.
To build the KLU solver, the following dependencies are required:
g++)gfortran)The first four should be available through your favourite package manager. On Debian-based GNU/Linux distributions:
apt update
apt install python3-dev gcc gfortran cmake libopenblas-dev
The pybind11 source directory should be located in the PyBaMM project directory at the time of compilation. Simply clone the GitHub repository, for example:
# In the PyBaMM project dir (next to setup.py)
git clone https://github.com/pybind/pybind11.git
The PyBaMM repository contains a script
scripts/setup_KLU_module_build.py that automatically downloads,
extracts, compiles and installs the two libraries.
First install the Python wget module
pip install wget
Then execute the script
# In the PyBaMM project dir (next to setup.py)
python scripts/setup_KLU_module_build.py
The above will install the required component of SuiteSparse and
Sundials in your home directory under ~/.local/. Note that you can
provide the option --install-dir=<install/path> to install both
libraries to an alternative location. If <install/path> is not
absolute, it will be interpreted as relative to the PyBaMM project
directory.
Finally, reactivate your virtual environment by running
source $(VIRTUAL_ENV)/bin/activate
Alternatively, you update the LD_LIBRARY_PATH environment variable
as follows
export LD_LIBRARY_PATH=$(HOME)/.local:$LD_LIBRARY_PATH
The above export statement will be ran automatically the next time you activate you python virtual environment.
If did not run the convenience script inside a python virtual environment, execute you bash config file
source ~/.bashrc
(or start a new shell).
Build files are located inside the PyBaMM project directory under
KLU_module_deps/. Feel free to remove this directory once everything
is installed correctly.
On most current linux distributions and macOS, a recent enough version of the suitesparse source package is available through the package manager. For instance on Fedora
yum install libsuitesparse-dev
The PyBaMM KLU solver requires Sundials >= 4.0. Because most Linux distribution provide older versions through their respective package manager, it is recommended to build and install Sundials manually.
First, download and extract the sundials 5.0.0 source
wget https://computing.llnl.gov/projects/sundials/download/sundials-5.0.0.tar.gz .
tar -xvf sundials-5.0.0.tar.gz
Then, create a temporary build directory and navigate into it
mkdir build_sundials
cd build_sundials
You can now configure the build, by running
cmake -DLAPACK_ENABLE=ON\
-DSUNDIALS_INDEX_SIZE=32\
-DBUILD_ARKODE=OFF\
-DBUILD_CVODE=OFF\
-DBUILD_CVODES=OFF\
-DBUILD_IDAS=OFF\
-DBUILD_KINSOL=OFF\
-DEXAMPLES_ENABLE:BOOL=OFF\
-DKLU_ENABLE=ON\
-DKLU_INCLUDE_DIR=path/to/suitesparse/headers\
-DKLU_LIBRARY_DIR=path/to/suitesparse/libraries\
../sundials-5.0.0
Be careful set the two variables KLU_INCLUDE_DIR and
KLU_LIBRARY_DIR to the correct installation location of the
SuiteSparse libary on your system. If you installed SuiteSparse through
your package manager, this is likely to be something similar to:
-DKLU_INCLUDE_DIR=/usr/include/suitesparse\
-DKLU_LIBRARY_DIR=/usr/lib/x86_64-linux-gnu\
By default, Sundials will be installed on your system under
/usr/local (this varies depending on the distribution). Should you
wish to install sundials in a specific location, set the following
variable
-DCMAKE_INSTALL_PREFIX=install/location\
Finally, build the library:
make install
You may be asked to run this command as a super-user, depending on the installation location.
By default, it is assumed that the SuiteSparse and Sundials libraries
are installed in your home directory under ~/.local. If you
installed the libraries to (a) different location(s), you must set the
options suitesparse-root or/and sundials-root when installing
PyBaMM. Examples:
python setup.py install --suitesparse-root=path/to/suitesparse
or
pip install . --install-option="--sundials-root=path/to/sundials"
If the above dependencies are correctly installed, any of the following
commands will install PyBaMM with the idaklu solver module:
pip install .
pip install -e .
python setup.py install
python setup.py develop
...
Note that it doesn’t matter if pybamm is already installed. The above
commands will update your exisitng installation by adding the idaklu
module.
If you install PyBaMM in editable
mode
using the -e pip switch or if you use the
python setup.py install command, a log file will be located in the
project directory (next to the setup.py file).
cat setup.log
020-03-24 11:33:50,645 - PyBaMM setup - INFO - Starting PyBaMM setup
2020-03-24 11:33:50,653 - PyBaMM setup - INFO - Not running on windows
2020-03-24 11:33:50,654 - PyBaMM setup - INFO - Could not find CMake. Skipping compilation of KLU module.
2020-03-24 11:33:50,655 - PyBaMM setup - INFO - Could not find pybind11 directory (/io/pybind11). Skipping compilation of KLU module.
If the KLU sparse solver is correctly installed, then the following
command should return True.
$ python -c "import pybamm; print(pybamm.have_idaklu())"