Revision 48270681afc13081094f7f398a1e194c6b07ba9b authored by vdutor on 03 January 2018, 17:44:53 UTC, committed by Mark van der Wilk on 03 January 2018, 17:44:53 UTC 
Expectations framework (#591)
 
* Outline of new expectations code.

* Quadrature code now uses TensorFlow shape inference.

* General expectations work.

* Expectations RBF kern, not tested

* Add Identity mean function

* General unittests for Expectations

* Add multipledispatch package to travis

* Update tests_expectations

* Expectations of mean functions

* Mean function uncertain conditional

* Uncertain conditional with mean_function. Tested.

* Support for Add and Prod kernels and quadrature fallback decorator

* Refactor expectations unittests

* Psi stats Linear kernel

* Split expectations in different files

* Expectation Linear kernel and Linear mean function

* Remove None's from expectations api

* Removed old ekernels framework

* Add multipledispatch to setup file

* Work on PR feedback, not finished

* Addressed PR feedback

* Support for pairwise xKxz

* Enable expectations unittests

* Renamed `TimeseriesGaussian` to `MarkovGaussian` and added tests.

* Rename some variable, plus note for later test of <x Kxz>_q.

* Update conditionals.py

Add comment

* Change order of inputs to (feat, kern)

* Stef/expectations (#601)

* adding gaussmarkov quad

* don't override the markvogaussian in the quadrature

* can't test

* adding external test

* quadrature code done and works for MarkovGauss

* MarkovGaussian with quad implemented. All tests pass

* Shape comments.

* Removed superfluous autoflow functions for kernel expectations

* Update kernels.py

* Update quadrature.py
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# Copyright 2016 The GPflow authors
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

#USAGE:
#To run from prebuilt version use:
#docker run -it -p 8888:8888 gpflow/gpflow

#To replicate build use:
#docker build -t gpflow/gpflow .
#Assumes you are running from within cloned repo.

#Uses official Tensorflow docker for cpu only.
FROM tensorflow/tensorflow:1.0.0
COPY ./ /usr/local/GPflow/
RUN cd /usr/local/GPflow && \
    python setup.py develop && \
    rm /notebooks/*  && \
    apt-get clean  && \
    rm -rf /var/lib/apt/lists/*
COPY doc/source/notebooks/ LICENSE README.md /notebooks/
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