BenoitDamota

## light_pca.py
"""
LightPCA : PCA with little memory footprint, but can only fit_transform()
the data (no transform(), no inverse_transform()).
targeted data (be sure to have at least 5-6GB of free memory):
>>> import numpy as np
>>> from light_pca import LightPCA
>>> X = np.random.randn(1301, 500000) # ~5GB
>>> pca = LightPCA(copy=False, n_components=1300)
>>> X = pca.fit_transform(X)
"""
	"""
	LightPCA : PCA with little memory footprint, but can only fit_transform()
	the data (no transform(), no inverse_transform()).
	targeted data (be sure to have at least 5-6GB of free memory):
	>>> import numpy as np
	>>> from light_pca import LightPCA
	>>> X = np.random.randn(1301, 500000) # ~5GB
	>>> pca = LightPCA(copy=False, n_components=1300)
	>>> X = pca.fit_transform(X)
	"""