When to use cla(), clf() or close() for clearing a plot in matplotlib?

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北荒
北荒 2020-11-22 09:03

Matplotlib offers there functions:

cla()   # Clear axis
clf()   # Clear figure
close() # Close a figure window

The documentation doesn\'t o

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  • 2020-11-22 09:25

    There is just a caveat that I discovered today. If you have a function that is calling a plot a lot of times you better use plt.close(fig) instead of fig.clf() somehow the first does not accumulate in memory. In short if memory is a concern use plt.close(fig) (Although it seems that there are better ways, go to the end of this comment for relevant links).

    So the the following script will produce an empty list:

    for i in range(5):
        fig = plot_figure()
        plt.close(fig)
    # This returns a list with all figure numbers available
    print(plt.get_fignums())
    

    Whereas this one will produce a list with five figures on it.

    for i in range(5):
        fig = plot_figure()
        fig.clf()
    # This returns a list with all figure numbers available
    print(plt.get_fignums())
    

    From the documentation above is not clear to me what is the difference between closing a figure and closing a window. Maybe that will clarify.

    If you want to try a complete script there you have:

    import numpy as np
    import matplotlib.pyplot as plt
    x = np.arange(1000)
    y = np.sin(x)
    
    for i in range(5):
        fig = plt.figure()
        ax = fig.add_subplot(1, 1, 1)
        ax.plot(x, y)
        plt.close(fig)
    
    print(plt.get_fignums())
    
    for i in range(5):
        fig = plt.figure()
        ax = fig.add_subplot(1, 1, 1)
        ax.plot(x, y)
        fig.clf()
    
    print(plt.get_fignums())
    

    If memory is a concern somebody already posted a work-around in SO see: Create a figure that is reference counted

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  • 2020-11-22 09:27

    They all do different things, since matplotlib uses a hierarchical order in which a figure window contains a figure which may consist of many axes. Additionally, there are functions from the pyplot interface and there are methods on the Figure class. I will discuss both cases below.

    pyplot interface

    pyplot is a module that collects a couple of functions that allow matplotlib to be used in a functional manner. I here assume that pyplot has been imported as import matplotlib.pyplot as plt. In this case, there are three different commands that remove stuff:

    plt.cla() clears an axes, i.e. the currently active axes in the current figure. It leaves the other axes untouched.

    plt.clf() clears the entire current figure with all its axes, but leaves the window opened, such that it may be reused for other plots.

    plt.close() closes a window, which will be the current window, if not specified otherwise.

    Which functions suits you best depends thus on your use-case.

    The close() function furthermore allows one to specify which window should be closed. The argument can either be a number or name given to a window when it was created using figure(number_or_name) or it can be a figure instance fig obtained, i.e., usingfig = figure(). If no argument is given to close(), the currently active window will be closed. Furthermore, there is the syntax close('all'), which closes all figures.

    methods of the Figure class

    Additionally, the Figure class provides methods for clearing figures. I'll assume in the following that fig is an instance of a Figure:

    fig.clf() clears the entire figure. This call is equivalent to plt.clf() only if fig is the current figure.

    fig.clear() is a synonym for fig.clf()

    Note that even del fig will not close the associated figure window. As far as I know the only way to close a figure window is using plt.close(fig) as described above.

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  • 2020-11-22 09:32

    plt.cla() means clear current axis

    plt.clf() means clear current figure

    also, there's plt.gca() (get current axis) and plt.gcf() (get current figure)

    Read more here: Matplotlib, Pyplot, Pylab etc: What's the difference between these and when to use each?

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