5 Best Ways to Save a Figure as File from IPython Notebook Using Matplotlib

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πŸ’‘ Problem Formulation: When working with data in IPython notebooks, a common need is to generate visualizations using Matplotlib and save them to files for reports, presentations or further analysis. Users are looking for ways to efficiently export these figures from their notebooks. For instance, a user may generate a plot in their IPython notebook and wish to save it as a ‘png’, ‘pdf’ or ‘svg’ file to their filesystem. This article provides concrete solutions to perform this task.

Method 1: Using savefig()

This method involves the use of Matplotlib’s savefig() function, which is a straightforward way to save figures to a file in various formats (e.g., PNG, PDF, SVG, EPS). The function takes the filename and file format as arguments and can also handle advanced options like dpi (dots per inch) settings.

Here’s an example:

import matplotlib.pyplot as plt

# Let's plot a simple bar chart.
plt.bar(['A','B','C'], [3, 5, 2])
plt.title('Simple Bar Chart')

# Save the figure to a file.
plt.savefig('bar_chart.png', format='png', dpi=300)

Output: A file named ‘bar_chart.png’ with the bar chart saved at 300 dpi resolution.

In this example, we first create a simple bar chart using Matplotlib’s plotting capabilities and then save the graph to a PNG file named ‘bar_chart.png’ with a resolution of 300 dpi, which gives a high-quality image suitable for print and digital media.

Method 2: Saving Inline Figures

IPython notebooks can display figures inline. When in a Jupyter notebook, it’s possible to configure Matplotlib to save the figures automatically by using the %matplotlib inline magic command with the appropriate backend settings to write to the disk.

Here’s an example:

%config InlineBackend.figure_format = 'svg'
%matplotlib inline
import matplotlib.pyplot as plt

plt.plot([1, 3, 2])
plt.savefig('line_chart.svg')

Output: An SVG file named ‘line_chart.svg’ containing the plot.

The given code snippet sets the inline backend to store figures in SVG format, which is a vector format, and then saves the figure as an SVG file. This ensures that your plot is saved in high-quality vector graphic form without needing additional commands.

Method 3: Saving Figures from Figure Objects

If you have a Figure object in Matplotlib, you can call its savefig() method directly. This is particularly useful if you’ve created multiple figures and wish to save them at later points in your code.

Here’s an example:

import matplotlib.pyplot as plt

# Create a figure object and then plot data.
fig = plt.figure()
plt.plot([0, 1, 4, 9, 16])

# Save from the figure object.
fig.savefig('squared_plot.pdf', format='pdf')

Output: A PDF file named ‘squared_plot.pdf’ containing the plot.

In this approach, the `Figure` object `fig` is directly used to save the plot to a PDF file. This allows for a clean separation of figure creation and saving, which can improve the structure of your code when working with complex plots.

Method 4: Saving Transparent Figures

Sometimes you may want the background of your figures to be transparent when saving, which can be quite useful for embedding images into documents without a white box around them. The savefig() function provides an argument for this purpose.

Here’s an example:

import matplotlib.pyplot as plt

# Plotting a simple pie chart
plt.pie([10, 20, 30, 40], labels=['A', 'B', 'C', 'D'], autopct='%1.1f%%')

# Save the figure with a transparent background.
plt.savefig('pie_chart.png', transparent=True)

Output: A PNG file named ‘pie_chart.png’ with a transparent background.

This code snippet demonstrates how to save a pie chart with a transparent background by setting the `transparent` parameter to `True`. This is beneficial when incorporating figures into other documents where you do not want a colored background to interfere.

Bonus One-Liner Method 5: Using IPython’s Display and Image Functions

IPython notebooks have built-in display capabilities which can be used to save Matplotlib figures as image files using a one-liner. This combines the display and Image functions from the IPython.display module.

Here’s an example:

from IPython.display import display, Image
import matplotlib.pyplot as plt

plt.plot([5,15,25,35])
plt.title("One-Liner Save")
# Save the figure using IPython's display tools
png = plt.savefig("oneliner_plot.png")
display(Image('oneliner_plot.png'))

Output: The figure is saved as a PNG file named ‘oneliner_plot.png’ and then displayed back in the IPython notebook.

This concise method showcases the ability to both save and display a figure within the notebook environment using a fluid and abbreviated syntax, which is great for quick saves and checks.

Summary/Discussion

  • Method 1: Using savefig(). Easy and straightforward. Works in any context where Matplotlib is available. May not have the most concise syntax in certain situations.
  • Method 2: Saving Inline Figures. Integrates seamlessly with IPython notebooks. Automatically displays figures as they’re saved. Limited to the inline backend settings.
  • Method 3: Saving Figures from Figure Objects. Offers fine control over the exact point in code where figures are saved. Useful when dealing with multiple figure objects. Slightly more verbose.
  • Method 4: Saving Transparent Figures. Useful for creating figures without backgrounds. Requires understanding of the transparent parameter. Not needed for every figure.
  • Bonus One-Liner Method 5: Using IPython’s Display and Image Functions. Quick and effortless within the IPython notebook. Not as versatile as savefig() for batch-processing or scriptable environments.