Difference between revisions of "Numpy linalg"

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http://stackoverflow.com/questions/772124/what-does-the-python-ellipsis-object-do
 
http://stackoverflow.com/questions/772124/what-does-the-python-ellipsis-object-do
  
'''...''' Is designed to mean at this point, insert as many full slices (:) to extend the multi-dimensional slice to all dimensions.
+
"'''...'''" Is designed to mean at this point, insert as many full slices (:) to extend the multi-dimensional slice to all dimensions.

Revision as of 12:09, 19 June 2014

How to transpose higher dimension arrays

http://jameshensman.wordpress.com/2010/06/14/multiple-matrix-multiplication-in-numpy/

Faster dot product using BLAS

http://www.huyng.com/posts/faster-numpy-dot-product/

http://stackoverflow.com/questions/5990577/speeding-up-numpy-dot

http://wiki.scipy.org/PerformanceTips

http://thread.gmane.org/gmane.comp.python.numeric.general/28135/

Multi dot

http://wiki.scipy.org/Cookbook/MultiDot

Einsum

http://chintaksheth.wordpress.com/2013/07/31/numpy-the-tricks-of-the-trade-part-ii/

http://stackoverflow.com/questions/14758283/is-there-a-numpy-scipy-dot-product-calculating-only-the-diagonal-entries-of-the

a = np.arange(4).reshape(2,2)
print a
print "np.einsum('ii', a), row i multiplied downwards"
print np.einsum('ii', a)

print "np.einsum('ij', a), same matrix ?"
print np.einsum('ij', a)

print "np.einsum('ji', a), transpose"
print np.einsum('ji', a)

print "np.einsum('ij,jk', a, a), dot product"
print np.einsum('ij,jk', a, a)
print np.dot(a, a)

Ellipsis broadcasting in numpy.einsum

http://stackoverflow.com/questions/16591696/ellipsis-broadcasting-in-numpy-einsum

http://stackoverflow.com/questions/118370/how-do-you-use-the-ellipsis-slicing-syntax-in-python

http://stackoverflow.com/questions/772124/what-does-the-python-ellipsis-object-do

"..." Is designed to mean at this point, insert as many full slices (:) to extend the multi-dimensional slice to all dimensions.