Colormap for errorbars in x-y scatter plot using matplotlib

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情书的邮戳
情书的邮戳 2020-12-06 05:28

I have a time series of data for which I have the quantity, y, and its error, yerr. I would now like to create a plot that shows y against phase (i.e. time / period % 1) wit

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  •  时光说笑
    2020-12-06 06:04

    Sorry to dig this back up, but just run into something similar myself and this was my solution based on previous responses.

    This sets the marker, errorbars, and caps as the same colour in the colormap:

    import matplotlib.pyplot as plt
    import numpy as np
    
    #data
    time = np.arange(100.)
    signal = time**2
    error = np.ones(len(time))*1000
    
    #create a scatter plot
    sc = plt.scatter(time,signal,s=20,c=time)
    
    #create colorbar according to the scatter plot
    clb = plt.colorbar(sc)
    
    #convert time to a color tuple using the colormap used for scatter
    time_color = clb.to_rgba(time)
    
    #loop over each data point to plot
    for x, y, e, color in zip(time, signal, error, time_color):
        plt.errorbar(x, y, e, lw=1, capsize=3, color=color)
    

    EDIT: After changing to matplotlib v3.1.1 the above stopped working, but here's a workaround:

    import matplotlib.pyplot as plt
    import numpy as np
    
    #data
    time = np.arange(100.)
    signal = time**2
    error = np.ones(len(time))*1000
    
    #create a scatter plot
    sc = plt.scatter(time,signal,s=0,c=time)
    
    #create colorbar according to the scatter plot
    clb = plt.colorbar(sc)
    
    #convert time to a color tuple using the colormap used for scatter
    import matplotlib
    import matplotlib.cm as cm
    norm = matplotlib.colors.Normalize(vmin=min(signal), vmax=max(signal), clip=True)
    mapper = cm.ScalarMappable(norm=norm, cmap='viridis')
    time_color = np.array([(mapper.to_rgba(v)) for v in signal])
    
    #loop over each data point to plot
    for x, y, e, color in zip(time, signal, error, time_color):
        plt.plot(x, y, 'o', color=color)
        plt.errorbar(x, y, e, lw=1, capsize=3, color=color)
    

    Finally for completeness, here's a plot of what it should produce:

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