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31 lines
874 B
Python
31 lines
874 B
Python
'''
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Created on 24 Feb 2014
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@author: maxz
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'''
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import numpy as np
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from ..util.pca import PCA
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def initialize_latent(init, input_dim, Y):
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Xr = np.asfortranarray(np.random.normal(0, 1, (Y.shape[0], input_dim)))
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if 'PCA' in init:
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p = PCA(Y)
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PC = p.project(Y, min(input_dim, Y.shape[1]))
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Xr[:PC.shape[0], :PC.shape[1]] = PC
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var = .1*p.fracs[:input_dim]
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elif init in 'empirical_samples':
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from ..util.linalg import tdot
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from ..util import diag
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YYT = tdot(Y)
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diag.add(YYT, 1e-6)
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EMP = np.asfortranarray(np.random.multivariate_normal(np.zeros(Y.shape[0]), YYT, min(input_dim, Y.shape[1])).T)
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Xr[:EMP.shape[0], :EMP.shape[1]] = EMP
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var = np.random.uniform(0.5, 1.5, input_dim)
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else:
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var = Xr.var(0)
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Xr -= Xr.mean(0)
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Xr /= Xr.std(0)
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return Xr, var/var.max()
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