Asymmetric Color Bar with Fair Diverging Color Map

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隐瞒了意图╮
隐瞒了意图╮ 2021-01-28 03:33

I\'m trying to plot an asymmetric color range in a scatter plot. I want the colors to be a fair representation of the intensity using a diverging color map. I am having trouble

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  •  梦如初夏
    2021-01-28 04:11

    If I get you correctly, the issue at hand is that your midpoint-centered map is scaling the color evenly from -2 to 0 (blue) and similarly (red) from 0 to 10.

    Instead of scaling [self.vmin, self.midpoint, self.vmax] = [-2, 0, 10], you should rather rescale between [-v_ext, self.midpoint, v_ext] = [-10, 0, 10] where:

    v_ext = np.max( [ np.abs(self.vmin), np.abs(self.vmax) ] )  ## = np.max( [ 2, 10 ] )
    

    The complete code could look like:

    import numpy as np
    import matplotlib.pyplot as plt
    import matplotlib.colors as mcolors
    
    x = np.arange( 0, 1, 1e-1 )
    xlen = x.shape[ 0 ]
    z = np.random.random( xlen**2 )*12 - 2
    
    class MidpointNormalize(mcolors.Normalize):
        def __init__(self, vmin=None, vmax=None, midpoint=None, clip=False):
            self.midpoint = midpoint
            mcolors.Normalize.__init__(self, vmin, vmax, clip)
    
        def __call__(self, value, clip=None):
            v_ext = np.max( [ np.abs(self.vmin), np.abs(self.vmax) ] )
            x, y = [-v_ext, self.midpoint, v_ext], [0, 0.5, 1]
            return np.ma.masked_array(np.interp(value, x, y))
    
    x = np.arange( 0, 1, 1e-1 )
    xlen = x.shape[ 0 ]
    z = np.random.random( xlen**2 )*12 - 2
    
    norm = MidpointNormalize( midpoint = 0 )
    
    splt = plt.scatter( 
        np.repeat( x, xlen ), 
        np.tile( x, xlen ), 
        c = z, cmap = 'seismic', s = 400,
        norm = norm
    )
    
    plt.colorbar( splt )
    plt.show()
    

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