mirror of
https://github.com/SheffieldML/GPy.git
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Merge branch 'devel' into plotting_tests
This commit is contained in:
mzwiessele
commit
218840d05c
14 changed files with 156 additions and 46 deletions
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@ -15,7 +15,7 @@ addons:
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env:
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- PYTHON_VERSION=2.7
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- PYTHON_VERSION=3.3
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#- PYTHON_VERSION=3.3
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- PYTHON_VERSION=3.4
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- PYTHON_VERSION=3.5
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@ -61,7 +61,6 @@ deploy:
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password:
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secure: "vMEOlP7DQhFJ7hQAKtKC5hrJXFl5BkUt4nXdosWWiw//Kg8E+PPLg88XPI2gqIosir9wwgtbSBBbbwCxkM6uxRNMpoNR8Ixyv9fmSXp4rLl7bbBY768W7IRXKIBjpuEy2brQjoT+CwDDSzUkckHvuUjJDNRvUv8ab4P/qYO1LG4="
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on:
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tags: true
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branch: deploy
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distributions: $DIST
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skip_cleanup: true
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@ -1 +1 @@
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__version__ = "1.0.9"
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__version__ = "1.2.0"
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@ -7,4 +7,6 @@ from .mlp import MLP
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from .additive import Additive
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from .compound import Compound
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from .constant import Constant
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from .identity import Identity
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from .piecewise_linear import PiecewiseLinear
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@ -17,7 +17,7 @@ class GPCoregionalizedRegression(GP):
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:type X_list: list of numpy arrays
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:param Y_list: list of observed values related to the different noise models
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:type Y_list: list of numpy arrays
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:param kernel: a GPy kernel, defaults to RBF ** Coregionalized
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:param kernel: a GPy kernel ** Coregionalized, defaults to RBF ** Coregionalized
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:type kernel: None | GPy.kernel defaults
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:likelihoods_list: a list of likelihoods, defaults to list of Gaussian likelihoods
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:type likelihoods_list: None | a list GPy.likelihoods
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@ -19,7 +19,7 @@ class SparseGPCoregionalizedRegression(SparseGP):
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:type Y_list: list of numpy arrays
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:param Z_list: list of inducing inputs (optional)
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:type Z_list: empty list | list of numpy arrays
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:param kernel: a GPy kernel, defaults to RBF ** Coregionalized
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:param kernel: a GPy kernel ** Coregionalized, defaults to RBF ** Coregionalized
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:type kernel: None | GPy.kernel defaults
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:likelihoods_list: a list of likelihoods, defaults to list of Gaussian likelihoods
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:type likelihoods_list: None | a list GPy.likelihoods
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@ -34,7 +34,7 @@ def plot(parameterized, fignum=None, ax=None, colors=None, figsize=(12, 6)):
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else:
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raise ValueError("Need one ax per latent dimension input_dim")
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bg_lines.append(a.plot(means, c='k', alpha=.3))
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lines.extend(a.plot(x, means.T[i], c=colors.next(), label=r"$\mathbf{{X_{{{}}}}}$".format(i)))
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lines.extend(a.plot(x, means.T[i], c=next(colors), label=r"$\mathbf{{X_{{{}}}}}$".format(i)))
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fills.append(a.fill_between(x,
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means.T[i] - 2 * np.sqrt(variances.T[i]),
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means.T[i] + 2 * np.sqrt(variances.T[i]),
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@ -86,7 +86,7 @@ def plot_SpikeSlab(parameterized, fignum=None, ax=None, colors=None, side_by_sid
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# mean and variance plot
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a = fig.add_subplot(*sub1)
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a.plot(means, c='k', alpha=.3)
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plots.extend(a.plot(x, means.T[i], c=colors.next(), label=r"$\mathbf{{X_{{{}}}}}$".format(i)))
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plots.extend(a.plot(x, means.T[i], c=next(colors), label=r"$\mathbf{{X_{{{}}}}}$".format(i)))
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a.fill_between(x,
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means.T[i] - 2 * np.sqrt(variances.T[i]),
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means.T[i] + 2 * np.sqrt(variances.T[i]),
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@ -127,6 +127,7 @@ class SparseGPMinibatchTest(unittest.TestCase):
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def test_sparsegp_init(self):
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# Test if the different implementations give the exact same likelihood as the full model.
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# All of the following settings should give the same likelihood and gradients as the full model:
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try:
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np.random.seed(1234)
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Z = self.X[np.random.choice(self.X.shape[0], replace=False, size=10)].copy()
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Q = Z.shape[1]
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@ -149,6 +150,9 @@ class SparseGPMinibatchTest(unittest.TestCase):
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assert(m.checkgrad())
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m.optimize('adadelta', max_iters=10)
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assert(m.checkgrad())
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except ImportError:
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from nose import SkipTest
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raise SkipTest('climin not installed, skipping stochastic gradients')
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def test_predict_missing_data(self):
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m = GPy.models.bayesian_gplvm_minibatch.BayesianGPLVMMiniBatch(self.Y, self.Q, X_variance=False, missing_data=True, stochastic=True, batchsize=self.Y.shape[1])
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@ -23,7 +23,7 @@ local_file = os.path.abspath(os.path.join(os.path.dirname( __file__ ), '..', 'in
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# This specifies configurations specific to the user (it is found in the user home directory)
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home = os.getenv('HOME') or os.getenv('USERPROFILE')
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user_file = os.path.join(home,'.config','gpy', 'user.cfg')
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user_file = os.path.join(home,'.config','GPy', 'user.cfg')
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# Read in the given files.
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config.readfp(open(default_file))
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@ -131,7 +131,7 @@ class PCA(object):
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kwargs.update(dict(s=s))
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plots = list()
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for i, l in enumerate(ulabels):
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kwargs.update(dict(color=colors.next(), marker=marker[i % len(marker)]))
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kwargs.update(dict(color=next(colors), marker=marker[i % len(marker)]))
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plots.append(ax.scatter(*X_[labels == l, :].T, label=str(l), **kwargs))
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ax.set_xlabel(r"PC$_1$")
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ax.set_ylabel(r"PC$_2$")
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@ -9,7 +9,7 @@ The Gaussian processes framework in Python.
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* Travis-CI [unit-tests](https://travis-ci.org/SheffieldML/GPy)
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* [](http://opensource.org/licenses/BSD-3-Clause)
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[](https://travis-ci.org/SheffieldML/GPy) [](http://codecov.io/github/SheffieldML/GPy?branch=devel) [](http://depsy.org/package/python/GPy) [](https://landscape.io/github/SheffieldML/GPy/devel)
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[](https://travis-ci.org/SheffieldML/GPy) [](https://ci.appveyor.com/project/mzwiessele/gpy/branch/deploy) [](http://codecov.io/github/SheffieldML/GPy?branch=devel) [](http://depsy.org/package/python/GPy) [](https://landscape.io/github/SheffieldML/GPy/devel)
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## Updated Structure
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89
appveyor.yml
Normal file
89
appveyor.yml
Normal file
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@ -0,0 +1,89 @@
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environment:
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pip_access:
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secure: 8/ZjXFwtd1S7ixd7PJOpptupKKEDhm2da/q3unabJ00=
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gpy_version: 1.2.0
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matrix:
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- PYTHON_VERSION: 2.7
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MINICONDA: C:\Miniconda-x64
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- PYTHON_VERSION: 3.5
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MINICONDA: C:\Miniconda35-x64
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#configuration:
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# - Debug
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# - Release
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install:
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- "set PATH=%MINICONDA%;%MINICONDA%\\Scripts;%PATH%"
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- conda config --set always_yes yes --set changeps1 no
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- conda update -q conda
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- conda info -a
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- "conda create -q -n build-environment python=%PYTHON_VERSION% numpy scipy matplotlib"
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- activate build-environment
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# We need wheel installed to build wheels
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- python -m pip install wheel
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# GPy needs paramz
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- python -m pip install paramz
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- python -m pip install nose-show-skipped
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- python -m pip install coverage
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- python -m pip install codecov
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- python -m pip install twine
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- "python setup.py develop"
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build: off
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test_script:
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# Put your test command here.
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# If you don't need to build C extensions on 64-bit Python 3.3 or 3.4,
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# you can remove "build.cmd" from the front of the command, as it's
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# only needed to support those cases.
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# Note that you must use the environment variable %PYTHON% to refer to
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# the interpreter you're using - Appveyor does not do anything special
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# to put the Python evrsion you want to use on PATH.
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#- "build.cmd %PYTHON%\\python.exe setup.py test"
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- "coverage run travis_tests.py"
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after_test:
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# This step builds your wheels.
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- "python setup.py bdist_wheel bdist_wininst"
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- codecov
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artifacts:
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# bdist_wheel puts your built wheel in the dist directory
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- path: dist\*
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deploy_script:
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- echo [distutils] > %USERPROFILE%\\.pypirc
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- echo index-servers = >> %USERPROFILE%\\.pypirc
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- echo pypi >> %USERPROFILE%\\.pypirc
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- echo test >> %USERPROFILE%\\.pypirc
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- echo[
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- echo [pypi] >> %USERPROFILE%\\.pypirc
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- echo username:maxz >> %USERPROFILE%\\.pypirc
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- echo password:%pip_access% >> %USERPROFILE%\\.pypirc
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- echo[
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- echo [test] >> %USERPROFILE%\\.pypirc
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- echo repository:https://testpypi.python.org/pypi >> %USERPROFILE%\\.pypirc
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- echo username:maxz >> %USERPROFILE%\\.pypirc
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- echo password:%pip_access% >> %USERPROFILE%\\.pypirc
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- ps: >-
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if ($env:APPVEYOR_REPO_BRANCH -eq 'devel') {
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twine upload -r test dist/*
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}
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elseif ($env:APPVEYOR_REPO_BRANCH -eq 'deploy') {
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twine upload dist/*
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}
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else {
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echo not deploying on other branches
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}
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# deploy:
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# - provider: GitHub
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# release: GPy-v$(gpy_version)
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# description: 'GPy windows install'
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# artifact: dist/*.exe # upload wininst to GitHub
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# draft: false
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# prerelease: false
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# on:
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# branch: deploy # release from deploy branch only
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# appveyor_repo_tag: true # deploy on tag push only
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24
codecov.yml
Normal file
24
codecov.yml
Normal file
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@ -0,0 +1,24 @@
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codecov:
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branch: devel
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coverage:
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precision: 2
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round: down
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range: "40...100"
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status:
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project:
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default:
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target: auto
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if_no_uploads: error
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patch:
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default:
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if_no_uploads: error
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changes: true
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comment:
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layout: "header, diff, changes, suggestions"
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behavior: default
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@ -1,12 +1,11 @@
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[bumpversion]
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current_version = 1.0.9
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current_version = 1.2.0
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tag = False
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commit = True
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[bumpversion:file:GPy/__version__.py]
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[bdist_wheel]
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universal = 1
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[bumpversion:file:appveyor.yml]
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[upload_docs]
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upload-dir = doc/build/html
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11
setup.py
11
setup.py
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@ -59,14 +59,7 @@ def read_to_rst(fname):
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desc = """
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- `GPy homepage <http://sheffieldml.github.io/GPy/>`_
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- `Tutorial notebooks <http://nbviewer.ipython.org/github/SheffieldML/notebook/blob/master/GPy/index.ipynb>`_
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- `User mailing-list <https://lists.shef.ac.uk/sympa/subscribe/gpy-users>`_
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- `Developer documentation <http://gpy.readthedocs.org/en/devel/>`_
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- `Travis-CI unit-tests <https://travis-ci.org/SheffieldML/GPy>`_
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- `License <https://opensource.org/licenses/BSD-3-Clause>`_
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For full description and installation instructions please refer to the github page.
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Please refer to the github homepage for detailed instructions on installation and usage.
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"""
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@ -116,6 +109,7 @@ setup(name = 'GPy',
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author = read_to_rst('AUTHORS.txt'),
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author_email = "gpy.authors@gmail.com",
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description = ("The Gaussian Process Toolbox"),
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long_description = desc,
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license = "BSD 3-clause",
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keywords = "machine-learning gaussian-processes kernels",
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url = "http://sheffieldml.github.com/GPy/",
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@ -154,7 +148,6 @@ setup(name = 'GPy',
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include_package_data = True,
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py_modules = ['GPy.__init__'],
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test_suite = 'GPy.testing',
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long_description=desc,
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install_requires = ['numpy>=1.7', 'scipy>=0.16', 'six', 'paramz>=0.5.2'],
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extras_require = {'docs':['sphinx'],
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'optional':['mpi4py',
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