Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Applying Math with Python

You're reading from   Applying Math with Python Practical recipes for solving computational math problems using Python programming and its libraries

Arrow left icon
Product type Paperback
Published in Jul 2020
Publisher Packt
ISBN-13 9781838989750
Length 358 pages
Edition 1st Edition
Languages
Arrow right icon
Authors (2):
Arrow left icon
Sam Morley Sam Morley
Author Profile Icon Sam Morley
Sam Morley
Sam Morley Sam Morley
Author Profile Icon Sam Morley
Sam Morley
Arrow right icon
View More author details
Toc

Table of Contents (12) Chapters Close

Preface 1. Basic Packages, Functions, and Concepts 2. Mathematical Plotting with Matplotlib FREE CHAPTER 3. Calculus and Differential Equations 4. Working with Randomness and Probability 5. Working with Trees and Networks 6. Working with Data and Statistics 7. Regression and Forecasting 8. Geometric Problems 9. Finding Optimal Solutions 10. Miscellaneous Topics 11. Other Books You May Enjoy

Saving Matplotlib figures

When you work in an interactive environment, such as an IPython console or a Jupyter notebook, displaying a figure at runtime is perfectly normal. However, there are plenty of situations where it would be more appropriate to store a figure directly to a file, rather than rendering it on screen. In this recipe, we will see how to save a figure directly to a file, rather than displaying it on screen.

Getting ready

You will need the data to be plotted and the path or file object in which you wish to store the output. We store the result in savingfigs.png in the current directory. In this example, we will plot the following data:

x = np.arange(1, 5, 0.1)
y = x*x

How to do it...

The following steps show how to save a Matplotlib plot directly to a file:

  1. The first step is to create the figure, as usual, and add any labels, titles, and annotations that are necessary. The figure will be written to the file in its current state, so any changes to the figure should be made before saving:
fig, ax = plt.subplots()
ax.plot(x, y)
ax.set_title("Graph of $y = x^2$", usetex=True)
ax.set_xlabel("$x$", usetex=True)
ax.set_ylabel("$y$", usetex=True)
  1. Then, we use the savefigmethod on fig to save this figure to a file. The only required argument is the path to output to or a file-like object that the figure can be written to. We can adjust various settings for the output format, such as the resolution, by providing the appropriate keyword arguments. We'll set the Dots per Inch (DPI) of the output figure to 300, which is a reasonable resolution for most applications:
fig.savefig("savingfigs.png", dpi=300)

Matplotlib will infer that we wish to save the image in the Portable Network Graphics (PNG) format from the extension of the file given. Alternatively, a format can be explicitly provided as a keyword argument (by using the formatkeyword), or it will fall back to the default from the configuration file.

How it works...

The savefig method chooses the appropriate backend for the output format and then renders the current figure in that format. The resulting image data is written to the specified path or file-like object. If you have manually created a Figure instance, the same effect can be achieved by calling the savefig method on that instance.

There's more...

The savefig routine takes a number of additional optional keyword arguments to customize the output image. For example, the resolution of the image can be specified using the dpi keyword. The plots in this chapter have been produced by saving the Matplotlib figures to the file.

The output formats available include PNG, Scalable Vector Graphics (SVG), PostScript (PS), Encapsulated PostScript (EPS), and Portable Document Format (PDF). You can also save to JPEG format if the Pillow package is installed, but Matplotlib does not support this natively since version 3.1. There are additional customization keyword arguments for JPEG images, such as quality and optimize. A dictionary of image metadata can be passed to the metadata keyword, which will be written as image metadata when saving.

See also

The examples gallery on the Matplotlib website includes examples of embedding Matplotlib figures into a Graphical User Interface (GUI) application using several common Python GUI frameworks.

You have been reading a chapter from
Applying Math with Python
Published in: Jul 2020
Publisher: Packt
ISBN-13: 9781838989750
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image