How to make heatmap square in Seaborn FacetGrid

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野趣味
野趣味 2021-02-07 00:16

I\'m using Seaborn\'s FacetGrid class to plot a set of matrices using the heatmap function, also from Seaborn. However, I cannot adjust the aspect rati

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  • 2021-02-07 00:45

    You could use the square=True parameter substituting this in your code:

    fg.map_dataframe(draw_heatmap, 'label1', 'label2', 'value', cbar=False, square=True)
    
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  • 2021-02-07 00:49

    When you set aspect argument of FacetGrid not only axis limits but the sizes and positions of axis labels and titles are also took into consideration to calculate proper axis geometry. Therefore heatmaps are rectangles.

    To adjust quadratic heatmap and axis you may set corrected axis bounding box position manually with function set_bbox.

    Another way is a little bit tricky. Function ax.set_aspect with the second argument box_forced would try to adjust heatmap and axis. However to completely remove remain gray borders you may hide it by setting axis background color according to figure face color like here:

    import seaborn as sns
    import numpy as np
    import pandas as pd
    import matplotlib.pylab as plt
    
    # Generate a set of sample data
    np.random.seed(0)
    indices = pd.MultiIndex.from_product((range(5), range(5), range(5)),
     names=('label0', 'label1', 'label2'))
    data = pd.DataFrame(np.random.uniform(0, 100, size=len(indices)),
     index=indices, columns=('value',)).reset_index()
    
    def draw_heatmap(*args, **kwargs):
        data = kwargs.pop('data')
        d = data.pivot(index=args[1], columns=args[0], values=args[2])
        sns.heatmap(d, **kwargs)
    
    fg = sns.FacetGrid(data, col='label0')
    fg.map_dataframe(draw_heatmap, 'label1', 'label2', 'value', cbar=False, square = True)
    # get figure background color
    facecolor=plt.gcf().get_facecolor()
    for ax in fg.axes.flat:
        # set aspect of all axis
        ax.set_aspect('equal','box-forced')
        # set background color of axis instance
        ax.set_axis_bgcolor(facecolor)
    plt.show()
    

    Result:

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