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coregionalization example
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GPy/examples/coreg_example.py
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GPy/examples/coreg_example.py
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import numpy as np
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import pylab as pb
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import GPy
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pb.ion()
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X1 = 100 * np.random.rand(100)[:,None]
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X2 = 100 * np.random.rand(100)[:,None]
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#X1.sort()
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#X2.sort()
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Y1 = np.sin(X1/10.) + np.random.rand(100)[:,None]
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Y2 = np.cos(X2/10.) + np.random.rand(100)[:,None]
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Mlist = [GPy.kern.Matern32(1,lengthscale=20.,name="Mat")]
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kern = GPy.util.multioutput.LCM(input_dim=1,num_outputs=12,kernels_list=Mlist,name='H')
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m = GPy.models.GPCoregionalizedRegression(X_list=[X1,X2], Y_list=[Y1,Y2], kernel=kern)
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m.optimize()
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fig = pb.figure()
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ax0 = fig.add_subplot(211)
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ax1 = fig.add_subplot(212)
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slices = GPy.util.multioutput.get_slices([Y1,Y2])
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m.plot(fixed_inputs=[(1,0)],which_data_rows=slices[0],ax=ax0)
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m.plot(fixed_inputs=[(1,1)],which_data_rows=slices[1],ax=ax1)
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