5 Best Ways to Change Figure Window Title in Pylab Python

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πŸ’‘ 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 plotβ€”which is often used as the figure titleβ€”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.