Function to lighten any color in matplotlib

lighten_color.py

def lighten_color(color, amount=0.5):
    """
    Lightens the given color by multiplying (1-luminosity) by the given amount.
    Input can be matplotlib color string, hex string, or RGB tuple.
    
    Examples:
    >> lighten_color('g', 0.3)
    >> lighten_color('#F034A3', 0.6)
    >> lighten_color((.3,.55,.1), 0.5)
    """
    import matplotlib.colors as mc
    import colorsys
    try:
        c = mc.cnames[color]
    except:
        c = color
    c = np.array(colorsys.rgb_to_hls(*mc.to_rgb(c)))
    return colorsys.hls_to_rgb(c[0],1-amount * (1-c[1]),c[2])

Made a version of it that takes RGB values from 0-255

def adjust_lightness(input_color, amount):
	color = (input_color[0]/255, input_color[1]/255, input_color[2]/255)
	try:
		c = mc.cnames[color]
	except:
		c = color
	c = colorsys.rgb_to_hls(*mc.to_rgb(c))
	float_color = colorsys.hls_to_rgb(c[0], max(0, min(1, amount * c[1])), c[2])
	return list(round(i*255) for i in float_color)

Found this Gist thanks to this StackOverflow link

In case you need to new custom LinearSegmentedColormap like I did. The original Stackoverflow Question

def custom_cmap_lightness(color, under=0.8, over=1.3):
    color_ligten = []
    
    for amount in np.linspace(under,over,1000):
        
        try:
            c = mc.cnames[color]
        except:
            c = color
        c = colorsys.rgb_to_hls(*mc.to_rgb(c))
        new_color = colorsys.hls_to_rgb(c[0], max(0, min(1, amount * c[1])), c[2])
        color_ligten.append(new_color)
        
    color_ligten.reverse()
    new_cmp = LinearSegmentedColormap.from_list('testCmap', colors=color_ligten, N=256)
    return new_cmp