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Scientific Computing with Python - Second Edition

You're reading from  Scientific Computing with Python - Second Edition

Product type Book
Published in Jul 2021
Publisher Packt
ISBN-13 9781838822323
Pages 392 pages
Edition 2nd Edition
Languages
Authors (3):
Claus Führer Claus Führer
Profile icon Claus Führer
Jan Erik Solem Jan Erik Solem
Olivier Verdier Olivier Verdier
View More author details

Table of Contents (23) Chapters

Preface Getting Started Variables and Basic Types Container Types Linear Algebra - Arrays Advanced Array Concepts Plotting Functions Classes Iterating Series and Dataframes - Working with Pandas Communication by a Graphical User Interface Error and Exception Handling Namespaces, Scopes, and Modules Input and Output Testing Symbolic Computations - SymPy Interacting with the Operating System Python for Parallel Computing Comprehensive Examples About Packt Other Books You May Enjoy References

4.4.2 Altering an array using slices

You may alter an array using slices or by direct access. The following changes only one element in a  matrix :

M[1, 2] = 2.0 # scalar

Also, we may change one full row of the matrix:

M[2, :] = [1., 2., 3.] # vector

Similarly, we may also replace a full submatrix:

M[1:3, :] = array([[1., 2., 3.],[-1.,-2., -3.]])

There is a distinction between a column matrix and a vector. The following assignment with a column matrix returns no error: 

M[1:4, 1:2] = array([[1.],[0.],[-1.0]]) 

while the assignment with a vector returns a ValueError:

M[1:4, 1:2] = array([1., 0., -1.0]) #  error

The general slicing rules are shown in Table 4.3. The matrices and vectors in the preceding examples must have the right size to fit into matrix . You may also make use of the broadcasting rules (see Section 5.5Broadcasting) to determine the allowed size of the replacement arrays. If the replacement array does not have...

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