create a custom disctrete levels python matplotlib colormap with no data

colormap_demo.py

def custom_cmap(colors, padding=1.05):
    """ Create a custom colormap from a dictionary
    
    Args: 
        colors <dict>: Levels to colornames
        padding <float>: Offset levels
    """
    assert(isinstance(colors, dict))
    assert(None in colors)
    
    labels = sorted(colors.keys())
    clrs = [colors[l] for l in labels]
    levels = sorted([-1000, 0] + map(lambda x: x * padding, filter(None, labels)))
    cmap, norm = matplotlib.colors.from_levels_and_colors(levels, clrs)
    cmap.set_bad(colors[None], 1.)
    return cmap, norm, labels

def custom_cbar(cmap, labels, label='CUSTOMCOLORBAR', orientation="horizontal"):
    """ Create a custom discrete colobar 
    Args:
        cmap <matplotlib.cmap>: Colormap being used
        labels <list>: Labels to apply to discrete colormap
    """
    ncolors = len(labels)
    mappable = cm.ScalarMappable(cmap=cmap)
    mappable.set_array([])
    mappable.set_clim(-0.5, ncolors+0.5)
    colorbar = plt.colorbar(mappable, label=label, orientation=orientation)
    colorbar.set_ticks(np.linspace(0, ncolors, ncolors))
    colorbar.set_ticklabels(labels)


#================================

colors = {
    1500: "#87096c",
    2000: "#d7191c",
    3000: "#e75b3a",
    4000: "#f89d59",
    5000: "#fdc980",
    5500: "#feedaa",
    6000: "#ebf6ac",
    6500: "#c3e586",
    7000: "#96d165",
    9999: "#58b353",
    None: '#1f78b4'
}


fig, ax = plt.subplots(figsize=(10,10))
masked_array = np.ma.array(MY2DMATRiX, mask=np.isnan(MY2DMATRiX))
cmap, norm, labels = custom_cmap(colors)
ax.pcolorfast(masked_array, cmap=cmap, norm=norm)
custom_cbar(cmap, labels)

priority.png