plotting 3d scatter in matplotlib

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悲哀的现实
悲哀的现实 2021-02-07 16:13

I have a collection of Nx3 matrices in scipy/numpy and I\'d like to make a 3 dimensional scatter of it, where the X and Y axes are determined by the values of first and second c

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  •  南笙
    南笙 (楼主)
    2021-02-07 17:08

    Try replacing 'ax.scatter' with ax.plot', possibly with the 'o' parameter to get similar circles. This fixes the transparency and the legend.

    import matplotlib as mpl
    from mpl_toolkits.mplot3d import Axes3D
    import numpy as np
    import matplotlib.pyplot as plt
    from numpy.random import random
    
    mpl.rcParams['legend.fontsize'] = 10
    
    fig = plt.figure(1)
    fig.clf()
    ax = Axes3D(fig)
    datasets = random((8,100,3))*512
    my_labels = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h']
    
    colors = ['k', "#B3C95A", 'b', '#63B8FF', 'g', "#FF3300",
              'r', 'k']
    index = 0
    for data, curr_color in zip(datasets, colors):
        ax.plot(np.log2(data[:, 0]), np.log2(data[:, 1]), 
                       np.log2(data[:, 2]), 'o', c=curr_color, label=my_labels[index])
        index += 1
    
    ax.set_zlim3d([-1, 9])
    ax.set_ylim3d([-1, 9])
    ax.set_xlim3d([-1, 9])
    
    ax.set_xticks(range(0,11))
    ax.set_yticks([1,2,8])
    ax.set_zticks(np.arange(0,9,.5))
    
    ax.legend(loc = 'upper left')
        
    plt.draw()
    
    plt.show()
    

    I added a few lines and tweaks to get some sample data and get the rest of your demo working. I assume you'll be able to get it to work.

    Setting the ticks requires the August 2010 update to mplot3d as described here. I got the latest mplot3d from Sourceforge. I'm not quite sure if Matplotlib 1.0.1 contains this latest update as I'm still running Python 2.6 with Matplotlib 1.0.0.

    Edit

    A quick and dirty dummy plot for the legends while keeping the 3d transparency effect you get from scatter:

    index = 0
    for data, curr_color in zip(datasets, colors):
        ax.scatter(np.log2(data[:, 0]), np.log2(data[:, 1]), 
                       np.log2(data[:, 2]), 'o', c=curr_color, label=my_labels[index])
        ax.plot([], [], 'o', c = curr_color, label=my_labels[index])                    
        index += 1
    

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