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Published inJul 2021
Reading LevelIntermediate
PublisherPackt
ISBN-139781838822323
Edition2nd Edition
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Authors (3):
Claus Führer
Claus Führer
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Claus Führer

Claus Führer is a professor of scientific computations at Lund University, Sweden. He has an extensive teaching record that includes intensive programming courses in numerical analysis and engineering mathematics across various levels in many different countries and teaching environments. Claus also develops numerical software in research collaboration with industry and received Lund University's Faculty of Engineering Best Teacher Award in 2016.
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Compressed sparse column format (CSC)

The CSR format has a column-oriented twin – the compressed sparse column (CSC) format. The only difference in it compared to the CSR format is the definition of the indptr and indices arrays, which are now column-related. The type for the CSC format is csc_matrix and its use corresponds to csr_matrix, explained previously in this subsection.

Continuing the same example in CSC format:

import scipy.sparse as sp
A = array([[1,0,2,0],[0,0,0,0],[3.,0.,0.,0.],[1.,0.,0.,4.]])
AS = sp.csc_matrix(A)
AS.data         # returns array([ 1., 3., 1., 2., 4.]) 
AS.indptr       # returns array([0, 3, 3, 4, 5])
AS.indices      # returns array([0, 2, 3, 0, 3])
AS.nnz          # returns 5
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Scientific Computing with Python - Second Edition
Published in: Jul 2021Publisher: PacktISBN-13: 9781838822323

Authors (3)

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Claus Führer

Claus Führer is a professor of scientific computations at Lund University, Sweden. He has an extensive teaching record that includes intensive programming courses in numerical analysis and engineering mathematics across various levels in many different countries and teaching environments. Claus also develops numerical software in research collaboration with industry and received Lund University's Faculty of Engineering Best Teacher Award in 2016.
Read more about Claus Führer