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Slycot: a wrapper for the SLICOT control and systems library

Project description

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Python wrapper for selected SLICOT routines, notably including solvers for Riccati, Lyapunov, and Sylvester equations.

Dependencies

Slycot supports Python versions 2.7, and 3.5 or later.

To run the compiled Slycot package, the following must be installed as dependencies:

  • Python 2.7, 3.5+
  • NumPy

If you are compiling and installing Slycot from source, you will need the following dependencies:

  • Python 2.7, 3.5+
  • NumPy
  • scikit-build >= 0.10.0
  • CMake
  • C compiler (e.g. gcc, MS Visual C++)
  • FORTRAN compiler (e.g. gfortran, ifort, flang)
  • BLAS/LAPACK (e.g. OpenBLAS, ATLAS, MKL)

To run the Slycot unit tests and examples, you’ll also need scipy and pytest.

There are a variety of ways to install these dependencies on different operating systems. See the individual packages’ documentation for options.

Installing

The easiest way to get started with Slycot is to install pre-compiled binaries from conda-forge (see below); these are available for Linux, OSX, and Windows.

Compiling the Slycot source is unfortunately a bit tricky, especially on Windows, but we give some pointers further below for doing this.

Using conda and conda-forge

First install Miniconda or Anaconda. Slycot can then be installed from the conda-forge channel with the following command:

conda install -c conda-forge slycot

From source without conda (Linux, macOS, Windows)

Unpack the source code to a directory of your choice, e.g. /path/to/slycot_src/

If you need to specify a specific compiler, set the environment variable FC before running the install:

# Linux/OSX:
export FC=/path/to/my/fortran

# Windows:
set FC=D:\path\to\my\fortran.exe

To build and install, execute:

cd /path/to/slycot_src/
python setup.py install

From source using a conda recipe (Linux and macOS)

You can also use conda to build and install Slycot from source, but you’ll have to choose the right recipe directory.

On Linux you can choose between conda-recipe-openblas and conda-recipe-mkl

On macOS you should use conda-recipe-apple. See the conda-build documentation how to get the required macOS SDK.

For example, to build with the OpenBLAS recipe:

conda build -c conda-forge conda-recipe-openblas
conda install -c conda-forge --use-local slycot

From source in a conda environment (Windows)

A similar method can be used for Linux and macOS, but is detailed here for Windows. This method uses conda and conda-forge to get most build dependencies, except for the C compiler.

This procedure has been tested on Python 3.7 and 3.8.

First, install the correct Visual Studio compiler for the Python version you wish to build for.

To build, you’ll need a command shell setup for both conda and the Visual Studio build tools. See conda activation and Microsoft Visual Studio setup for information on this.

In such a command shell, run the following commands to build and install Slycot (this example creates a Python 3.8 environment):

conda create --channel conda-forge --name build-slycot python=3.8 numpy scipy libblas=*=*netlib liblapack=*=*netlib scikit-build flang pytest
conda activate build-slycot

python setup.py install

Testing

To test if the installation was successful, you can run the slycot unit tests:

pytest --pyargs slycot

Running pytest without --pyargs slycot from inside the source directory will fail, unless either setup.cfg or the compiled wrapper library have been installed into that directory.

General notes on compiling

Additional tips for how to install Slycot from source can be found in the .travis.yml (commands used for Travis CI) and the conda-recipe-*/ directories (conda pre-requisites) both which are included in the source code repository.

The hardest part about installing from source is getting a working version of FORTRAN and LAPACK (provided by OpenBLAS, MKL, etc.) installed on your system, and working properly with Python.

Note that in some cases you may need to set the LIBRARY_PATH environment variable to pick up dependencies such as -lpythonN.m (where N.m is the version of python you are using).

Using pip

We publish Slycot to the Python package index, but only as a source package, so to install using pip you’ll first need to install the build prerequisites (compilers, libraries, etc.)

If you have these build prerequisites, install in the standard way with:

pip install slycot

Project details


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