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