[plotting] tests
Max Zwiessele
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@ -122,7 +122,7 @@ def test_figure():
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from GPy.plotting import plotting_library as pl
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#import matplotlib
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matplotlib.rcParams.update(matplotlib.rcParamsDefault)
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matplotlib.rcParams[u'figure.figsize'] = (4,3)
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#matplotlib.rcParams[u'figure.figsize'] = (4,3)
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matplotlib.rcParams[u'text.usetex'] = False
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import warnings
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with warnings.catch_warnings():
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@ -166,7 +166,7 @@ def test_kernel():
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np.random.seed(1239847)
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#import matplotlib
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matplotlib.rcParams.update(matplotlib.rcParamsDefault)
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matplotlib.rcParams[u'figure.figsize'] = (4,3)
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#matplotlib.rcParams[u'figure.figsize'] = (4,3)
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matplotlib.rcParams[u'text.usetex'] = False
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import warnings
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with warnings.catch_warnings():
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@ -189,7 +189,7 @@ def test_plot():
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np.random.seed(111)
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import matplotlib
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matplotlib.rcParams.update(matplotlib.rcParamsDefault)
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matplotlib.rcParams[u'figure.figsize'] = (4,3)
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#matplotlib.rcParams[u'figure.figsize'] = (4,3)
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matplotlib.rcParams[u'text.usetex'] = False
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import warnings
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with warnings.catch_warnings():
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@ -216,7 +216,7 @@ def test_twod():
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np.random.seed(11111)
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import matplotlib
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matplotlib.rcParams.update(matplotlib.rcParamsDefault)
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matplotlib.rcParams[u'figure.figsize'] = (4,3)
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#matplotlib.rcParams[u'figure.figsize'] = (4,3)
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matplotlib.rcParams[u'text.usetex'] = False
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X = np.random.uniform(-2, 2, (40, 2))
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f = .2 * np.sin(1.3*X[:,[0]]) + 1.3*np.cos(2*X[:,[1]])
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@ -239,7 +239,7 @@ def test_threed():
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np.random.seed(11111)
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import matplotlib
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matplotlib.rcParams.update(matplotlib.rcParamsDefault)
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matplotlib.rcParams[u'figure.figsize'] = (4,3)
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#matplotlib.rcParams[u'figure.figsize'] = (4,3)
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matplotlib.rcParams[u'text.usetex'] = False
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X = np.random.uniform(-2, 2, (40, 2))
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f = .2 * np.sin(1.3*X[:,[0]]) + 1.3*np.cos(2*X[:,[1]])
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@ -264,7 +264,7 @@ def test_sparse():
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np.random.seed(11111)
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import matplotlib
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matplotlib.rcParams.update(matplotlib.rcParamsDefault)
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matplotlib.rcParams[u'figure.figsize'] = (4,3)
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#matplotlib.rcParams[u'figure.figsize'] = (4,3)
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matplotlib.rcParams[u'text.usetex'] = False
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X = np.random.uniform(-2, 2, (40, 1))
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f = .2 * np.sin(1.3*X) + 1.3*np.cos(2*X)
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@ -280,7 +280,7 @@ def test_classification():
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np.random.seed(11111)
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import matplotlib
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matplotlib.rcParams.update(matplotlib.rcParamsDefault)
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matplotlib.rcParams[u'figure.figsize'] = (4,3)
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#matplotlib.rcParams[u'figure.figsize'] = (4,3)
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matplotlib.rcParams[u'text.usetex'] = False
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X = np.random.uniform(-2, 2, (40, 1))
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f = .2 * np.sin(1.3*X) + 1.3*np.cos(2*X)
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@ -304,7 +304,7 @@ def test_sparse_classification():
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np.random.seed(11111)
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import matplotlib
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matplotlib.rcParams.update(matplotlib.rcParamsDefault)
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matplotlib.rcParams[u'figure.figsize'] = (4,3)
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#matplotlib.rcParams[u'figure.figsize'] = (4,3)
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matplotlib.rcParams[u'text.usetex'] = False
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X = np.random.uniform(-2, 2, (40, 1))
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f = .2 * np.sin(1.3*X) + 1.3*np.cos(2*X)
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@ -325,7 +325,7 @@ def test_gplvm():
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from ..models import GPLVM
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np.random.seed(12345)
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matplotlib.rcParams.update(matplotlib.rcParamsDefault)
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matplotlib.rcParams[u'figure.figsize'] = (4,3)
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#matplotlib.rcParams[u'figure.figsize'] = (4,3)
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matplotlib.rcParams[u'text.usetex'] = False
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Q = 3
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# Define dataset
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@ -364,7 +364,7 @@ def test_bayesian_gplvm():
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from ..models import BayesianGPLVM
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np.random.seed(12345)
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matplotlib.rcParams.update(matplotlib.rcParamsDefault)
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matplotlib.rcParams[u'figure.figsize'] = (4,3)
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#matplotlib.rcParams[u'figure.figsize'] = (4,3)
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matplotlib.rcParams[u'text.usetex'] = False
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Q = 3
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# Define dataset
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@ -402,4 +402,4 @@ def test_bayesian_gplvm():
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if __name__ == '__main__':
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import nose
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nose.main()
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nose.main(defaultTest='./plotting_tests.py')
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