5 Best Ways to Change Figure Window Title in Pylab Python

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💡 Problem Formulation: When using Pylab, a part of the Matplotlib library in Python, setting a specific title for the figure window is a common need for distinguishing between multiple plots or for providing context. Users want to go from a default window title such as “Figure 1” to a custom one such as “My Data Visualization”. This article shows several methods to achieve this.

Method 1: Using the matplotlib.pyplot Interface

Matplotlib’s pyplot interface includes a function specifically for setting the figure window title. This approach is straightforward and is typically done after a figure has been created and before it is shown.

Here’s an example:

import matplotlib.pyplot as plt

plt.figure()
plt.plot([0, 1, 2], [0, 1, 4])
plt.gcf().canvas.set_window_title('My Data Visualization')
plt.show()

Output: A window displaying a plot with the title “My Data Visualization”.

This code snippet first creates a plot, then retrieves the current figure using plt.gcf(), accesses the canvas attribute, and sets the window title using set_window_title(). Finally, plt.show() displays the figure.

Method 2: Setting Title at Figure Creation

When creating a new figure, the title can be set directly using the num parameter, which accepts a string argument. Not only does this create a concise line of code, but it also ensures the title is set right at the figure initialization step.

Here’s an example:

import matplotlib.pyplot as plt

plt.figure(num='My Data Visualization')
plt.plot([0, 1, 2], [0, 1, 4])
plt.show()

Output: A window with the title “My Data Visualization” showcasing a simple line plot.

In this example, the figure() function takes a num argument that defines the figure window title immediately upon creation, before any data is plotted. This method simplifies window titling if you’re starting with a new figure.

Method 3: Utilizing Figure Methods After Creation

An alternative approach involves using the figure object’s methods once it has been created. A figure instance has a method called set_tight_layout() whereby passing a dictionary with the key ‘pad’ can indirectly influence the window title space.

Here’s an example:

import matplotlib.pyplot as plt

fig, ax = plt.subplots()
ax.plot([0, 1, 2], [0, 1, 4])
fig.canvas.set_window_title('My Data Visualization')
fig.set_tight_layout({'pad': 3.0})
plt.show()

Output: A plot within a window titled “My Data Visualization”, with additional padding ensured by the tight layout configuration.

After creating a subplot, this code uses the figure instance to set the window title. The set_tight_layout() method is then called with a padding configuration to allow for any external title space requirements, providing more control over the figure appearance.

Method 4: Using the Figure Class Directly

For more control, one can utilize the Figure class constructor from Matplotlib to set the window title directly. This is a more object-oriented approach and is recommended when you need fine-grained control over your figure properties.

Here’s an example:

from matplotlib.figure import Figure
from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas

fig = Figure()
FigureCanvas(fig)
fig.suptitle('My Data Visualization')
fig.show()

Output: A figure with the title “My Data Visualization”

This script begins by instantiating a Figure object directly and then associates it with a specific canvas. It sets the super title of the plot—which is often used as the figure title—and then displays the figure. This method is less common but ideal for complex customizations.

Bonus One-Liner Method 5: Setting Figure Title in IPython or Jupyter Notebook

When working within an IPython or Jupyter Notebook environment, you can also set the figure window title using a backend-specific one-liner, which is convenient for quick visualization tasks.

Here’s an example:

%matplotlib inline
from IPython.display import set_matplotlib_formats
set_matplotlib_formats('svg')
plt.figure(num='My Data Visualization')

Output: An inline SVG-format plot within the notebook with the title “My Data Visualization”.

This method uses an IPython magic function to set the Matplotlib backend to inline rendering, and the set_matplotlib_formats function is called to prefer SVG format for better quality images. The figure title is then set as before.

Summary/Discussion

  • Method 1: Using matplotlib.pyplot. Straightforward and easily implemented post figure creation. Limited only by the need to set before showing the figure.
  • Method 2: Setting Title at Figure Creation. Efficient when the title is known beforehand. Not suitable for dynamic title changes after figure creation.
  • Method 3: Utilizing Figure Methods. Offers additional layout control. Requires a bit more understanding of the Matplotlib library’s structure.
  • Method 4: Using the Figure Class. Ideal for complex customizations, but may be overkill for simple applications. Philosophically fits an object-oriented coding style.
  • Method 5: IPython/Jupyter Notebook One-Liner. Excellent for notebooks; not usable in scripts intended for standalone execution.