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swiss_roll example added, BGPLVM_oil now working
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5 changed files with 137 additions and 173 deletions
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@ -4,6 +4,7 @@ import numpy as np
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import GPy
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import scipy.sparse
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import scipy.io
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import cPickle as pickle
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data_path = os.path.join(os.path.dirname(__file__), 'datasets')
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default_seed = 10000
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@ -96,6 +97,19 @@ def stick():
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lbls = 'connect'
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return {'Y': Y, 'connect' : connect, 'info': "Stick man data from Ohio."}
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def swiss_roll_generated(N=1000, sigma=0.0):
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with open(os.path.join(data_path, 'swiss_roll.pickle')) as f:
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data = pickle.load(f)
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Na = data['Y'].shape[0]
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perm = np.random.permutation(np.r_[:Na])[:N]
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Y = data['Y'][perm, :]
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t = data['t'][perm]
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c = data['colors'][perm, :]
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so = np.argsort(t)
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Y = Y[so, :]
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t = t[so]
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c = c[so, :]
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return {'Y':Y, 't':t, 'colors':c}
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def swiss_roll_1000():
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mat_data = scipy.io.loadmat(os.path.join(data_path, 'swiss_roll_data'))
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@ -105,8 +119,7 @@ def swiss_roll_1000():
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def swiss_roll(N=3000):
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mat_data = scipy.io.loadmat(os.path.join(data_path, 'swiss_roll_data.mat'))
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Y = mat_data['X_data'][:, 0:N].transpose()
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import ipdb;ipdb.set_trace()
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return {'Y': Y, 'info': "The first 3,000 points from the swiss roll data of Tennenbaum, de Silva and Langford (2001)."}
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return {'Y': Y, 'X': mat_data['X_data'], 'info': "The first 3,000 points from the swiss roll data of Tennenbaum, de Silva and Langford (2001)."}
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def toy_rbf_1d(seed=default_seed):
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np.random.seed(seed=seed)
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