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[plotting] still testing the testing
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parent
1376113405
commit
0116b03f3c
7 changed files with 32 additions and 28 deletions
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@ -28,14 +28,16 @@ from .core.parameterization import Param, Parameterized, ObsAr, transformations
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from .__version__ import __version__
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from .__version__ import __version__
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from numpy.testing import Tester
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from numpy.testing import Tester
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#@nottest
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try:
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with warnings.catch_warnings():
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warnings.simplefilter('ignore')
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try:
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#Get rid of nose dependency by only ignoring if you have nose installed
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#Get rid of nose dependency by only ignoring if you have nose installed
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from nose.tools import nottest
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from nose.tools import nottest
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@nottest
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@nottest
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def tests(verbose=10):
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def tests(verbose=10):
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Tester(testing).test(verbose=verbose)
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Tester(testing).test(verbose=verbose)
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except:
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except:
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def tests(verbose=10):
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def tests(verbose=10):
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Tester(testing).test(verbose=verbose)
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Tester(testing).test(verbose=verbose)
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@ -22,7 +22,7 @@ class VarDTC(LatentFunctionInference):
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"""
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"""
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const_jitter = 1e-8
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const_jitter = 1e-8
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def __init__(self, limit=3):
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def __init__(self, limit=1):
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from paramz.caching import Cacher
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from paramz.caching import Cacher
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self.limit = limit
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self.limit = limit
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self.get_trYYT = Cacher(self._get_trYYT, limit)
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self.get_trYYT = Cacher(self._get_trYYT, limit)
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@ -30,7 +30,7 @@ class SparseGPRegression(SparseGP_MPI):
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"""
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"""
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def __init__(self, X, Y, kernel=None, Z=None, num_inducing=10, X_variance=None, normalizer=None, mpi_comm=None):
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def __init__(self, X, Y, kernel=None, Z=None, num_inducing=10, X_variance=None, normalizer=None, mpi_comm=None, name='sparse_gp'):
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num_data, input_dim = X.shape
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num_data, input_dim = X.shape
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# kern defaults to rbf (plus white for stability)
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# kern defaults to rbf (plus white for stability)
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@ -55,7 +55,7 @@ class SparseGPRegression(SparseGP_MPI):
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else:
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else:
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infr = VarDTC()
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infr = VarDTC()
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SparseGP_MPI.__init__(self, X, Y, Z, kernel, likelihood, inference_method=infr, normalizer=normalizer, mpi_comm=mpi_comm)
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SparseGP_MPI.__init__(self, X, Y, Z, kernel, likelihood, inference_method=infr, normalizer=normalizer, mpi_comm=mpi_comm, name=name)
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def parameters_changed(self):
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def parameters_changed(self):
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from ..inference.latent_function_inference.var_dtc_parallel import update_gradients_sparsegp,VarDTC_minibatch
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from ..inference.latent_function_inference.var_dtc_parallel import update_gradients_sparsegp,VarDTC_minibatch
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@ -43,7 +43,7 @@ it gives back an empty default, when defaults are not defined.
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'''
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'''
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# Data plots:
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# Data plots:
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data_1d = dict(lw=1.5, marker='x', edgecolor='k')
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data_1d = dict(lw=1.5, marker='x', color='k')
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data_2d = dict(s=35, edgecolors='none', linewidth=0., cmap=cm.get_cmap('hot'), alpha=.5)
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data_2d = dict(s=35, edgecolors='none', linewidth=0., cmap=cm.get_cmap('hot'), alpha=.5)
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inducing_1d = dict(lw=0, s=500, facecolors=Tango.colorsHex['darkRed'])
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inducing_1d = dict(lw=0, s=500, facecolors=Tango.colorsHex['darkRed'])
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inducing_2d = dict(s=14, edgecolors='k', linewidth=.4, facecolors='white', alpha=.5, marker='^')
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inducing_2d = dict(s=14, edgecolors='k', linewidth=.4, facecolors='white', alpha=.5, marker='^')
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@ -394,7 +394,7 @@ class KernelTestsNonContinuous(unittest.TestCase):
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self.X2[:(N0*2), -1] = 0
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self.X2[:(N0*2), -1] = 0
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self.X2[(N0*2):, -1] = 1
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self.X2[(N0*2):, -1] = 1
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@unittest.expectedFailure
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#@unittest.expectedFailure
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def test_IndependentOutputs(self):
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def test_IndependentOutputs(self):
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k = GPy.kern.RBF(self.D, active_dims=range(self.D))
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k = GPy.kern.RBF(self.D, active_dims=range(self.D))
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kern = GPy.kern.IndependentOutputs(k, -1, 'ind_single')
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kern = GPy.kern.IndependentOutputs(k, -1, 'ind_single')
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@ -403,7 +403,7 @@ class KernelTestsNonContinuous(unittest.TestCase):
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kern = GPy.kern.IndependentOutputs(k, -1, name='ind_split')
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kern = GPy.kern.IndependentOutputs(k, -1, name='ind_split')
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self.assertTrue(check_kernel_gradient_functions(kern, X=self.X, X2=self.X2, verbose=verbose, fixed_X_dims=-1))
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self.assertTrue(check_kernel_gradient_functions(kern, X=self.X, X2=self.X2, verbose=verbose, fixed_X_dims=-1))
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@unittest.expectedFailure
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#@unittest.expectedFailure
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def test_Hierarchical(self):
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def test_Hierarchical(self):
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k = [GPy.kern.RBF(2, active_dims=[0,2], name='rbf1'), GPy.kern.RBF(2, active_dims=[0,2], name='rbf2')]
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k = [GPy.kern.RBF(2, active_dims=[0,2], name='rbf1'), GPy.kern.RBF(2, active_dims=[0,2], name='rbf2')]
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kern = GPy.kern.IndependentOutputs(k, -1, name='ind_split')
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kern = GPy.kern.IndependentOutputs(k, -1, name='ind_split')
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@ -32,8 +32,8 @@
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#===============================================================================
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#===============================================================================
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# SKIPPING PLOTTING BECAUSE IT BEHAVES DIFFERENTLY ON DIFFERENT
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# SKIPPING PLOTTING BECAUSE IT BEHAVES DIFFERENTLY ON DIFFERENT
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# SYSTEMS, AND WILL MISBEHAVE
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# SYSTEMS, AND WILL MISBEHAVE
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#from nose import SkipTest
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from nose import SkipTest
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#raise SkipTest("Skipping Matplotlib testing")
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raise SkipTest("Skipping Matplotlib testing")
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#===============================================================================
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#===============================================================================
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try:
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try:
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@ -33,6 +33,8 @@
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import matplotlib
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import matplotlib
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matplotlib.use('agg')
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matplotlib.use('agg')
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import nose
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import nose, warnings
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nose.main('GPy', defaultTest='GPy/testing/')
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with warnings.catch_warnings():
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warnings.simplefilter("ignore")
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nose.main('GPy', defaultTest='GPy/testing/')
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