Matplotlib imshow/matshow display values on plot

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-上瘾入骨i
-上瘾入骨i 2020-12-05 03:31

I am trying to create a 10x10 grid using either imshow or matshow in Matplotlib. The function below takes a numpy array as input, and plots the gri

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  •  予麋鹿
    予麋鹿 (楼主)
    2020-12-05 04:03

    Can you do something like:

    import numpy as np
    import matplotlib.pyplot as plt
    
    fig, ax = plt.subplots()
    
    min_val, max_val = 0, 10
    ind_array = np.arange(min_val + 0.5, max_val + 0.5, 1.0)
    x, y = np.meshgrid(ind_array, ind_array)
    
    for i, (x_val, y_val) in enumerate(zip(x.flatten(), y.flatten())):
        c = 'x' if i%2 else 'o' 
        ax.text(x_val, y_val, c, va='center', ha='center')
    #alternatively, you could do something like
    #for x_val, y_val in zip(x.flatten(), y.flatten()):
    #    c = 'x' if (x_val + y_val)%2 else 'o'
    
    ax.set_xlim(min_val, max_val)
    ax.set_ylim(min_val, max_val)
    ax.set_xticks(np.arange(max_val))
    ax.set_yticks(np.arange(max_val))
    ax.grid()
    

    enter image description here


    Edit:

    Here is an updated example with an imshow background.

    import numpy as np
    import matplotlib.pyplot as plt
    
    fig, ax = plt.subplots()
    
    min_val, max_val, diff = 0., 10., 1.
    
    #imshow portion
    N_points = (max_val - min_val) / diff
    imshow_data = np.random.rand(N_points, N_points)
    ax.imshow(imshow_data, interpolation='nearest')
    
    #text portion
    ind_array = np.arange(min_val, max_val, diff)
    x, y = np.meshgrid(ind_array, ind_array)
    
    for x_val, y_val in zip(x.flatten(), y.flatten()):
        c = 'x' if (x_val + y_val)%2 else 'o'
        ax.text(x_val, y_val, c, va='center', ha='center')
    
    #set tick marks for grid
    ax.set_xticks(np.arange(min_val-diff/2, max_val-diff/2))
    ax.set_yticks(np.arange(min_val-diff/2, max_val-diff/2))
    ax.set_xticklabels([])
    ax.set_yticklabels([])
    ax.set_xlim(min_val-diff/2, max_val-diff/2)
    ax.set_ylim(min_val-diff/2, max_val-diff/2)
    ax.grid()
    plt.show()
    

    enter image description here

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