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Replaced Q by input_dim

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This commit is contained in:
Alan Saul 2013-06-05 11:17:15 +01:00
parent 312cfebcb1
commit 97f3357b6d
22 changed files with 271 additions and 271 deletions
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10
GPy/util/linalg.py
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@ -162,19 +162,19 @@ def multiple_pdinv(A):
return np.dstack(invs),np.array(halflogdets)
def PCA(Y, Q):
def PCA(Y, input_dim):
"""
Principal component analysis: maximum likelihood solution by SVD
Arguments
---------
:param Y: NxD np.array of data
:param Q: int, dimension of projection
:param input_dim: int, dimension of projection
Returns
-------
:rval X: - NxQ np.array of dimensionality reduced data
W - QxD mapping from X to Y
:rval X: - Nxinput_dim np.array of dimensionality reduced data
W - input_dimxD mapping from X to Y
"""
if not np.allclose(Y.mean(axis=0), 0.0):
print "Y is not zero mean, centering it locally (GPy.util.linalg.PCA)"
@ -182,7 +182,7 @@ def PCA(Y, Q):
#Y -= Y.mean(axis=0)
Z = linalg.svd(Y-Y.mean(axis=0), full_matrices = False)
[X, W] = [Z[0][:,0:Q], np.dot(np.diag(Z[1]), Z[2]).T[:,0:Q]]
[X, W] = [Z[0][:,0:input_dim], np.dot(np.diag(Z[1]), Z[2]).T[:,0:input_dim]]
v = X.std(axis=0)
X /= v;
W *= v;