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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setup.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-

# pylint: skip-file

from setuptools import setup
from setuptools import find_packages

import re
import os
import sys
from pkg_resources import parse_version

# load version form _version.py
exec(open("gpflow/_version.py").read())

# Dependencies of GPflow
requirements = [
    'numpy>=1.10.0',
    'scipy>=0.18.0',
    'pandas>=0.18.1',
    'multipledispatch>=0.4.9'
]

min_tf_version = '1.4.0'
tf_cpu = 'tensorflow>={}'.format(min_tf_version)
tf_gpu = 'tensorflow-gpu>={}'.format(min_tf_version)

# Only detect TF if not installed or outdated. If not, do not do not list as
# requirement to avoid installing over e.g. tensorflow-gpu
# To avoid this, rely on importing rather than the package name (like pip).

try:
    # If tf not installed, import raises ImportError
    import tensorflow as tf
    if parse_version(tf.VERSION) < parse_version(min_tf_version):
        # TF pre-installed, but below the minimum required version
        raise DeprecationWarning("TensorFlow version below minimum requirement")
except (ImportError, DeprecationWarning) as e:
    # Add TensorFlow to dependencies to trigger installation/update
    requirements.append(tf_cpu)

packages = find_packages('.')
package_data={'gpflow': ['gpflow/gpflowrc']}

setup(name='gpflow',
      version=__version__,
      author="James Hensman, Alex Matthews",
      author_email="james.hensman@gmail.com",
      description=("Gaussian process methods in tensorflow"),
      license="Apache License 2.0",
      keywords="machine-learning gaussian-processes kernels tensorflow",
      url="http://github.com/GPflow/GPflow",
      packages=packages,
      install_requires=requirements,
      tests_require=['pytest'],
      package_data=package_data,
      include_package_data=True,
      test_suite='tests',
      extras_require={'Tensorflow with GPU': [tf_gpu]},
      classifiers=[
          'License :: OSI Approved :: Apache Software License',
          'Natural Language :: English',
          'Operating System :: MacOS :: MacOS X',
          'Operating System :: Microsoft :: Windows',
          'Operating System :: POSIX :: Linux',
          'Programming Language :: Python :: 3.5',
          'Programming Language :: Python :: 3.6',
          'Topic :: Scientific/Engineering :: Artificial Intelligence'
      ])
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