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Learning SciPy for Numerical and Scientific Computing Second Edition

You're reading from   Learning SciPy for Numerical and Scientific Computing Second Edition Quick solutions to complex numerical problems in physics, applied mathematics, and science with SciPy

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Product type Paperback
Published in Feb 2015
Publisher Packt
ISBN-13 9781783987702
Length 188 pages
Edition 2nd Edition
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Creating a matrix

In SciPy, a matrix structure is given to any one- or two-dimensional ndarray, with either the matrix or mat command. The complete syntax is as follows:

numpy.matrix(data=object, dtype=None, copy=True)

Creating matrices, the data may be given as ndarray, a string or a Python list (as the second example below), which is very convenient. When using strings, the semicolon denotes change of row and the comma, change of column:

>>> A=numpy.matrix("1,2,3;4,5,6")
>>> A

The output is shown a follows s:

matrix([[1, 2, 3],
        [4, 5, 6]])

Let's look at another example:

>>> A=numpy.matrix([[1,2,3],[4,5,6]])
>>> A

The output is shown as follows:

matrix([[1, 2, 3],
        [4, 5, 6]])

Another technique to create a matrix from a two-dimensional array is to enforce the matrix structure on a new object, copying the data of the former with the asmatrix routine.

A matrix is said to be sparse (http://en.wikipedia.org/wiki/Sparse_matrix) if most...

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