Is Independent Creation of AxesSubPlot Objects Possible?
As the matplotlib documentation suggests, creating AxesSubPlot instances within a figure is typically achieved through Figure.add_subplot. However, it can be desirable to create these objects independently of a figure, allowing for their reuse in multiple figures.
Reusing AxesSubPlots in Different Figures
Despite not being able to fully decouple the creation of axes from figures, it is possible to reuse previously created axes in new or existing figures. This can be accomplished with a simple function:
def plot_axes(ax, fig=None, geometry=(1, 1, 1)): if fig is None: fig = plt.figure() if ax.get_geometry() != geometry: ax.change_geometry(*geometry) ax = fig.axes.append(ax) return fig
This function takes an existing axis instance ax and optionally adds it to a new or existing figure fig, ensuring that it has the specified geometry (rows, columns, number within group).
Example Usage
To demonstrate this functionality, consider the following code:
import numpy as np import matplotlib.pyplot as plt x = np.linspace(0, 6 * np.pi, 100) # Create axes subplots independently ax1 = plt.axes() ax2 = plt.axes() # Add ax1 to figure 1 fig1 = plt.figure() plt.axes.append(ax1) # Add ax2 to figure 2 fig2 = plt.figure() plt.axes.append(ax2) # Plot data on ax1 ax1.plot(x, np.sin(x)) ax1.set_ylabel("Sin(x)") # Plot data on ax2 ax2.plot(x, np.cos(x)) ax2.set_ylabel("Cos(x)") plt.show()
In this example, two axes subplots are created independently, then added to two separate figures. Each subplot contains its own data and labels.
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