unique plot marker for each plot in matplotlib

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走了就别回头了 2021-01-03 18:04

I have a loop where i create some plots and I need unique marker for each plot. I think about creating function, which returns random symbol, and use it in my program in thi

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  • 2021-01-03 18:25

    itertools.cycle will iterate over a list or tuple indefinitely. This is preferable to a function which randomly picks markers for you.

    Python 2.x

    import itertools
    marker = itertools.cycle((',', '+', '.', 'o', '*')) 
    for n in y:
        plt.plot(x,n, marker = marker.next(), linestyle='')
    

    Python 3.x

    import itertools
    marker = itertools.cycle((',', '+', '.', 'o', '*')) 
    for n in y:
        plt.plot(x,n, marker = next(marker), linestyle='')
    

    You can use that to produce a plot like this (Python 2.x):

    import numpy as np
    import matplotlib.pyplot as plt
    import itertools
    
    x = np.linspace(0,2,10)
    y = np.sin(x)
    
    marker = itertools.cycle((',', '+', '.', 'o', '*')) 
    
    fig = plt.figure()
    ax = fig.add_subplot(111)
    
    for q,p in zip(x,y):
        ax.plot(q,p, linestyle = '', marker=marker.next())
        
    plt.show()
    

    Example plot

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  • 2021-01-03 18:28

    You can also use marker generation by tuple e.g. as

    import matplotlib.pyplot as plt
    markers = [(i,j,0) for i in range(2,10) for j in range(1, 3)]
    [plt.plot(i, 0, marker = markers[i], ms=10) for i in range(16)]
    

    See Matplotlib markers doc site for details.

    In addition, this can be combined with itertools.cycle looping mentioned above

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  • 2021-01-03 18:28

    Just manually create an array that contains marker characters and use that, e.g.:

     markers=[',', '+', '-', '.', 'o', '*']
    
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  • 2021-01-03 18:36

    It appears that nobody has mentioned the built-in pyplot method for cycling properties yet. So here it is:

    import numpy as np
    import matplotlib.pyplot as plt
    from cycler import cycler
    
    x = np.linspace(0,3,20)
    y = np.sin(x)
    
    fig = plt.figure()
    plt.gca().set_prop_cycle(marker=['o', '+', 'x', '*', '.', 'X']) # gca()=current axis
    
    for q,p in zip(x,y):
        plt.plot(q,p, linestyle = '')
    
    plt.show()
    

    However, this way you lose the color cycle. You can add back color by multiplying a color cycler and a marker cycler object, like this:

    fig = plt.figure()
    
    markercycle = cycler(marker=['o', '+', 'x', '*', '.', 'X'])
    colorcycle = cycler(color=['blue', 'orange', 'green', 'magenta'])
    # Or use the default color cycle:
    # colorcycle = cycler(color=plt.rcParams['axes.prop_cycle'].by_key()['color'])
    
    plt.gca().set_prop_cycle(colorcycle * markercycle) # gca()=current axis
    
    for q,p in zip(x,y):
        plt.plot(q,p, linestyle = '')
    
    plt.show()
    

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  • 2021-01-03 18:47
    import matplotlib.pyplot as plt
    fig = plt.figure()
    markers=['^', 's', 'p', 'h', '8']
    for i in range(5):
        plt.plot(x[i], y[i], c='green', marker=markers[i])
        plt.xlabel('X Label')
        plt.ylabel('Y Label') 
    plt.show()
    
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