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 images


SciPy comes with some basic functions for handling images. The module function will read images to NumPy arrays. The function will save an array as an image. The following will read a JPEG image to an array, print the shape and type, then create a new array with a resized image, and write the new image to file:

import scipy.misc as sm

# read image to array
im = sm.imread("test.jpg") 
print(im.shape)   # (128, 128, 3)
print(im.dtype)   # uint8

# resize image
im_small = sm.imresize(im, (64,64))
print(im_small.shape)   # (64, 64, 3)

# write result to new image file
sm.imsave("test_small.jpg", im_small)

Note the data type. Images are almost always stored with pixel values in the range 0...255  as 8-bit unsigned integers. The third shape value shows how many color channels the image has. In this case, 3 means it is a color image with values stored in this order: red im[0], green im[1], blue im[2]. A gray scale...