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

Reading and writing Matlab data files


SciPy has the ability to read and write data in Matlab’s .mat file format using the module. The commands are loadmat and savemat. To load data, use the following syntax:

import scipy.io
data = scipy.io.loadmat('datafile.mat')

The variable data now contains a dictionary, with keys corresponding to the variable names saved in the .mat file. The variables are in NumPy array format. Saving to .mat files involves creating a dictionary with all the variables you want to save (variable name and value). The command is then savemat:

data = {}
data['x'] = x
data['y'] = y
scipy.io.savemat('datafile.mat',data)

This saves the NumPy arrays x and y with the same names when read into Matlab.