run_fast_ica.py

# Author: Denis A. Engemann <d.engemann@fz-juelich.de>
#
# License: BSD (3-clause)

""" Profile FastICA options

Dependencies
------------
scikit-learn
https://github.com/fabianp/memory_profiler

Usage
-----

mprof run --python run_fast_ica.py
mprof plot

"""

import numpy as np

n_samples = 1e6/4
n_features = 250
rng = np.random.RandomState(42)
W = rng.random_sample([n_features, n_features])
X = rng.random_sample([n_samples, n_features])

print 'estimated data size in memory'
print '%i MB' % (X.size * X.itemsize / 1e6)
print '%s' % X.dtype

from sklearn.decomposition import FastICA

with profile.timestamp('FastICA-SVD-false'):
    est = FastICA(n_components=50, whiten=True, svd_decorr=False)
    est.fit(X)

with profile.timestamp('FastICA-SVD-true'):
    est = FastICA(n_components=50, whiten=True, svd_decorr=True)
    est.fit(X)