New documentation, error function, and subprocess calling

This release adds an error function in case the model fails due to odd parameter combinations, for example, allowing the continuation of the calling process such as an optimizer. It also uses Python's relatively new subprocess.run() function now instead of the earlier subprocess.check_call() and subprocess.check_output().

The documentation was heavily rewritten. It changed from markdown format to reStructuredText and the hosting moved from ReadTheDocs to Github Pages. All docstrings were revisited and edited for better comprehension.

Use pyproject.toml structure and Github actions

This release moved to the pyproject.toml structure instead of setup.py.
It also uses Github actions for continuous integration instead of travis-ci.com.

Use pyproject.toml structure and Github actions

This release moved to the pyproject.toml structure instead of setup.py.
It also uses Github actions for continuous integration instead of travis-ci.com.

More general treatment of right-hand side in sub_params_names routines.

Fixes for a more general use of substitution functions, i.e. respect spaces and replace all non-space characters on the right-hand side of the equal sign.

Initial public release of partialwrap on Zenodo.

partialwrap is a small Python library providing wrappers for external executables and Python
functions so that they can easily be partialised with Python's functools.partial.

It allows to use any external executable as well as any Python function with
arbitrary arguments and keywords to be used with libraries that call functions
simply in the form func(x). This includes the functions of the scipy.optimize package or external packages such as emcee or pyeee, and allows the use of distributed function evaluations with Python's
multiprocessing library or MPI.

Initial public release of partialwrap.

partialwrap is a small Python library providing wrappers for external executables and Python
functions so that they can easily be partialised with Python's functools.partial.

It allows to use any external executable as well as any Python function with
arbitrary arguments and keywords to be used with libraries that call functions
simply in the form func(x). This includes the functions of the scipy.optimize package or external packages such as emcee or pyeee, and allows the use of distributed function evaluations with Python's
multiprocessing library or MPI.