Improve the CI support and improve building and testing wheels across more platforms and architectures.

Changes to the build system

• Require cython to build the code to avoid brokens builds with newer version of python/cython
• Use cibuildwheel to build and test wheels.
• Tidy up test cases to work with cibuildwheel
• Build wheels for platforms linux (archs x86_64 and aarch64) and macOS (archs x86_64 and arm64)

Improve the CI support and support building and deploying wheels

Fixed issues

#62

changes to the build system

• Require cython to build the code to avoid brokens builds with newer version of python/cython
• move to xenial and test on python 3.7
• add doc and deploy stages
• test mpi with just one process due to travis limitations
• build wheels for linux and deploy to Pypi
• declare pypmc stable on pypi

Changes to the functional core of pypmc

None

No change to the actual source code was done but it is now easier to install pypmc from pypi. If numpy is not available, it will be properly installed before at attempt is made to build pypmc itself.

The basic ground work for binary wheels for multiple platforms via cibuild is done, too. It requires a final tweak and travis to actually build and deploy.

Version 1.1.1

This is a maintenance release.

Infrastructure

pypmc now runs on travis and the docs are automatically built and deployed to http://fredros.github.io/pypmc/html/. Every release is tagged on zenodo.

Fixes

• explicit integer/float handling for compatibility with numpy v1.13
• update color map for compatibility with matplotlib v2.0

New features

• ImportanceSampler optionally stores the values of the target density
• plot_mixture can color components based on their weight rather than their index
• the new PMC class can run multiple EM updates until convergence

Fixes

• fix installation on mac without cython
• compatible to newer version of numpy
• fix too large a prune value in GaussianInference

Breaking changes

• remove DeterministicIS. No class was needed, all the functionality is now contained in combine_weights
• MarkovChain and ImportanceSampler don't have a combined history anymore, weights and samples are accessible as their own History objects

The code has matured and represents the state at the end of Stephan Jahn's master's thesis.