Book Image

Scientific Computing with Python 3

By : Claus Führer, Jan Erik Solem, Olivier Verdier
Book Image

Scientific Computing with Python 3

By: Claus Führer, Jan Erik Solem, Olivier Verdier

Overview of this book

Python can be used for more than just general-purpose programming. It is a free, open source language and environment that has tremendous potential for use within the domain of scientific computing. This book presents Python in tight connection with mathematical applications and demonstrates how to use various concepts in Python for computing purposes, including examples with the latest version of Python 3. Python is an effective tool to use when coupling scientific computing and mathematics and this book will teach you how to use it for linear algebra, arrays, plotting, iterating, functions, polynomials, and much more.
Table of Contents (23 chapters)
Scientific Computing with Python 3
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Acknowledgement
Preface
References

Exercises


Ex 1 → Write a function polar_to_comp, which takes two arguments r and and returns the complex number Use the NumPy function exp for the exponential function.

Ex 2 → In the description of the Python module functools, (refer to [8] for more detail on functools) you find the following Python function:

def partial(func, *args, **keywords):
    def newfunc(*fargs, **fkeywords):
        newkeywords = keywords.copy()
        newkeywords.update(fkeywords)
        return func(*(args + fargs), **newkeywords)
    newfunc.func = func
    newfunc.args = args
    newfunc.keywords = keywords
    return newfunc

Explain and test this function.

Ex 3 → Write a decorator for the function how_sparse,  which cleans the input matrix A by setting the elements that are less than 1.e-16 to zero (consider example in section Function as decorators).

Ex 4 → A continuous function f with f(a)f(b) < 0 changes its sign in the interval [a, b] and has at least one root...