code :
import numpy
from matplotlib.mlab import PCA
file_name = \"store1_pca_matrix.txt\"
ori_data = numpy.loadtxt(file_name,dtype=\'float\', comments=\'#\', de
I do not have an answer to this question but I have the reproduction scenario with no nans and infs. Unfortunately the datataset is pretty large (96MB gzipped).
import numpy as np
from StringIO import StringIO
from scipy import linalg
import urllib2
import gzip
url = 'http://physics.muni.cz/~vazny/gauss/X.gz'
X = np.loadtxt(gzip.GzipFile(fileobj=StringIO(urllib2.urlopen(url).read())), delimiter=',')
linalg.svd(X, full_matrices=False)
which rise:
LinAlgError: SVD did not converge
on:
>>> np.__version__
'1.8.1'
>>> import scipy
>>> scipy.__version__
'0.10.1'
but did not raise an exception on:
>>> np.__version__
'1.8.2'
>>> import scipy
>>> scipy.__version__
'0.14.0'