This PR adds two main things to GPy:
- to- and from-dict functions for the kernels listed belop
- a fix for the appveyor CI
Please see the squashed commit messages listed below.
Authors: @gehbiszumeis @ppk42 respectively
Reviewer: @ekalosak
---
* new: added to_dict() method to Coregionalize kernel class
* new: added to_dict() method to MixedNoise likelihood class
* fix: made Y_metadata dict content serializable
* fix: typo
* added additional needed parameters to to_dict() method for Coregionalize kernel + added _build_from_input dict method
* new: added possibility to build MixedNoise likelihood from input_dict
* Y_metadata conversion from serializable to np.array when loading from dict
* fix: rework Y_metadata part for compatibility with unittests !minor
* conda cleanup in appveyors pipeline
* conda clean up after conda update
* conda clean before conda update
* try pinning packages for conda
* revert all conda changes
* conda clean all (not only packages)
* use conda update anaconda
* pin conda package
* pin conda package
* try installing charset-normalizer beforehand
* try to get from conda-forge
* revert all conda changes
* Try to fix the conda update challange.
See: https://community.intel.com/t5/Intel-Distribution-for-Python/Conda-update-Conda-fails/td-p/1126174
It is just a try for a different context/(conda version).
* Still fixing build error on appveyor
I also use a newer miniconda version for greater python versions.
* Update appveyor.yml
Thinking it over it decided to use miniconda38 for all python versions unless python 3.5.
* revert miniconda versioning changes
* adjust GPy version in appveyor.yml
* 1st attempt bring the appveyor build to life again
* #955 fixing ci build on appveyor
After bringing the miniconda env to work again, the wrong matplotlib version was used. This commit should fix that.
* #955 Fix CI build
Freezing numpy and scipy was a bad idea.
I freeze matplotlib dependend on the python version only.
* add: built_from_dict method for White Kernel
Co-authored-by: Peter Paul Kiefer <ppk42@users.noreply.github.com>
Co-authored-by: Peter Paul Kiefer <dafisppk@gmail.com>
Changes to avoid numerical issues and improve the performance:
- Keep value of the EP parameters between calls
- Enforce positivity of tau_tilde
- Stable computation of the EP moments for the Bernoulli likelihood
- Compute marginal in the GP model without directly inverting tau_tilde
Changes to improve the flexibility:
- Add parameter for maximum number of iterations
- Distinguish between alternated/nested mode
- Distinguish between sequential/parallel updates in EP
Changes to avoid numerical issues and improve the performance:
- Keep value of the EP parameters between calls
- Enforce positivity of tau_tilde
- Stable computation of the EP moments for the Bernoulli likelihood
- Compute marginal in the GP model without directly inverting tau_tilde
Changes to improve the flexibility:
- Add parameter for maximum number of iterations
- Distinguish between alternated/nested mode
- Distinguish between sequential/parallel updates in EP
