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matplotlib Plotting Cookbook

You're reading from   matplotlib Plotting Cookbook Discover how easy it can be to create great scientific visualizations with Python. This cookbook includes over sixty matplotlib recipes together with clarifying explanations to ensure you can produce plots of high quality.

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Product type Paperback
Published in Mar 2014
Publisher Packt
ISBN-13 9781849513265
Length 222 pages
Edition Edition
Languages
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Author (1):
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Alexandre Devert Alexandre Devert
Author Profile Icon Alexandre Devert
Alexandre Devert
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Table of Contents (15) Chapters Close

matplotlib Plotting Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. First Steps FREE CHAPTER 2. Customizing the Color and Styles 3. Working with Annotations 4. Working with Figures 5. Working with a File Output 6. Working with Maps 7. Working with 3D Figures 8. User Interface Index

Generating PDF or SVG documents


An output to a bitmap picture is not always ideal. Bitmap pictures represent pictures as an array of pixels at one given scale. Zoom in and you will get some well-known artifacts (jaggies, staircases, blur, and so on), depending on the sampling algorithm employed. Vector pictures are scale invariant; no matter at which scale you observe them, no loss of details or artifacts will show up. As such, vector pictures are desirable when composing a larger document, such as a journal article. We do not need to generate new pictures when adjusting the scale of a figure. matplotlib can output vector pictures such as PDF and SVG pictures.

How to do it...

The output to a PDF document is a simple affair, as shown in the following script:

import numpy as np
from matplotlib import pyplot as plt

X = np.linspace(-10, 10, 1024)
Y = np.sinc(X)

plt.plot(X, Y)
plt.savefig('sinc.pdf')

The preceding script will draw a figure and save it to a file named sinc.pdf.

How it works...

We...

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