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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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Univariate polynomials


Polynomials are defined in SciPy as a NumPy class, poly1d. This class has a handful of methods associated to compute the coefficients of the polynomial (coeffs or simply c), to compute the roots of the polynomial (r), to compute its derivative (deriv), to compute the symbolic integral (integ), and to obtain the degree (order or simply o), as well as a method (variable) that provides a string holding the name of the variable we would like to use in the proper definition of the polynomial (see the example involving P2).

In order to define a polynomial, we must indicate either its coefficients or its roots:

>>> import numpy
>>> P1=numpy.poly1d([1,0,1])           # using coefficients
>>> print (P1)

The output is as follows:

   2
1 x + 1

Now let's find roots, order, and derivative of P1:

>>> print (P1.r); print (P1.o); print (P1.deriv())

The output is as follows:

[ 0.+1.j  0.-1.j]
2
2 x

Let's use the poly1d class:

>>> P2=numpy.poly1d...
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