named_colors.py

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors


RGBS = np.asarray([mcolors.hex2color(h) for h in mcolors.cnames.values()])

# Mapping from color-component name to array index
HSV_INDEX = dict(hue=0, saturation=1, value=2)

# Dividing values used to separate hues based on trial and error.
HUE_DIVS = [0, 0.017, 0.108, 0.2, 0.44, 0.56, 0.72, 0.9]
HUE_SEQUENCE = ['reds', 'oranges', 'yellows', 'greens',
                'cyans', 'blues', 'violets']

NUM_COLUMNS = 3


def luminance_from_rgbs(rgbs):
    return np.sum(rgbs * np.array([[0.2126, 0.7152, 0.0722]]), axis=1)


def hsvs_from_rgbs(rgbs):
    rgbs = np.reshape(rgbs, (1, -1, 3))
    hsvs = mcolors.rgb_to_hsv(rgbs)[0]
    return np.transpose(hsvs)


rgbs_idx = np.arange(0, len(RGBS))
hues, sats, values = hsvs_from_rgbs(RGBS)
lums = luminance_from_rgbs(RGBS)
# Low saturation colors look gray
grays = (sats < 0.05)

# Initialize dictionary of colors grouped by hue (with gray as its own "hue").
color_dict = dict(grays=rgbs_idx[grays])
# Build dictionary of colors based on hue.
for n, a, b in zip(HUE_SEQUENCE, HUE_DIVS[:-1], HUE_DIVS[1:]):
    color_dict[n] = rgbs_idx[(hues >= a) & (hues < b) & ~grays]
# Add reds with high "hue" values (above maximum violet hue, but below 1) to
# those with a low "hue" value. (Necessary because the hue wraps around).
reds_high = rgbs_idx[(hues >= HUE_DIVS[-1]) & ~grays]
color_dict['reds'] = np.hstack([color_dict['reds'], reds_high])


def plot_color_dict(color_dict, sort_by=None, dx=0.2):
    fig, ax = plt.subplots(figsize=(7, 10))
    y = 0
    color_names = HUE_SEQUENCE + ['grays']
    for cname in color_names:
        rgbs_idx = color_dict[cname]
        ax.text(0, y, cname, fontsize=12,
                horizontalalignment='left', verticalalignment='center')
        rgbs = sorted_colors(rgbs_idx, sort_by=sort_by)
        y -= 1
        plot_section(ax, rgbs, dx, y0=y)
        y -= np.ceil(len(rgbs) / float(NUM_COLUMNS))

    nrows = sum(1 + np.ceil(len(v) / 3.) for v in color_dict.itervalues())

    ax.set_xlim(0, NUM_COLUMNS)
    ax.set_ylim(-nrows, 1)
    ax.set_axis_off()

    fig.subplots_adjust(left=0.1, right=1, top=1, bottom=0)
    fig.set_facecolor('w')


def sorted_colors(rgbs_idx, sort_by=None):
    idxs = rgbs_idx[np.argsort(sort_by[rgbs_idx])]
    rgbs = mcolors.cnames.keys()
    return [rgbs[i] for i in idxs]


def plot_section(ax, rgbs, dx, y0=0):
    for i in range(NUM_COLUMNS):
        rgbs_column = rgbs[i::NUM_COLUMNS]
        x0 = i
        for j, cname in enumerate(rgbs_column):
            y = -j + y0
            plot_color_swatch(ax, cname, x0, y, dx)


def plot_color_swatch(ax, color_name, x, y, dx):
    """Plot color line and name of color"""
    pad = dx * 0.2
    ax.hlines(y, x, x + dx, color=color_name, linewidth=4)
    ax.text(x + dx + pad, y, color_name, fontsize=10,
            horizontalalignment='left', verticalalignment='center')


plot_color_dict(color_dict, sort_by=lums)
plt.show()