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"""
========================
Visualizing named colors
========================
This plots a list of the named colors supported in matplotlib. Note that
:ref:`xkcd colors <xkcd-colors>` are supported as well, but are not listed here
for brevity.
For more information on colors in matplotlib see
* the :doc:`/tutorials/colors/colors` tutorial;
* the `matplotlib.colors` API;
* the :doc:`/gallery/color/color_demo`.
"""
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors
def plot_colortable(colors, title, sort_colors=True, emptycols=0):
cell_width = 212
cell_height = 22
swatch_width = 48
margin = 12
topmargin = 40
# Sort colors by hue, saturation, value and name.
by_hsv = ((tuple(mcolors.rgb_to_hsv(mcolors.to_rgba(color)[:3])), name)
for name, color in colors.items())
if sort_colors is True:
by_hsv = sorted(by_hsv)
names = [name for hsv, name in by_hsv]
n = len(names)
ncols = 4 - emptycols
nrows = n // ncols + int(n % ncols > 0)
width = cell_width * 4 + 2 * margin
height = cell_height * nrows + margin + topmargin
dpi = 72
fig, ax = plt.subplots(figsize=(width / dpi, height / dpi), dpi=dpi)
fig.subplots_adjust(margin/width, margin/height,
(width-margin)/width, (height-topmargin)/height)
ax.set_xlim(0, cell_width * 4)
ax.set_ylim(cell_height * (nrows-0.5), -cell_height/2.)
ax.yaxis.set_visible(False)
ax.xaxis.set_visible(False)
ax.set_axis_off()
ax.set_title(title, fontsize=24, loc="left", pad=10)
for i, name in enumerate(names):
row = i % nrows
col = i // nrows
y = row * cell_height
swatch_start_x = cell_width * col
swatch_end_x = cell_width * col + swatch_width
text_pos_x = cell_width * col + swatch_width + 7
ax.text(text_pos_x, y, name, fontsize=14,
horizontalalignment='left',
verticalalignment='center')
ax.hlines(y, swatch_start_x, swatch_end_x,
color=colors[name], linewidth=18)
return fig
plot_colortable(mcolors.BASE_COLORS, "Base Colors",
sort_colors=False, emptycols=1)
plot_colortable(mcolors.TABLEAU_COLORS, "Tableau Palette",
sort_colors=False, emptycols=2)
#sphinx_gallery_thumbnail_number = 3
plot_colortable(mcolors.CSS4_COLORS, "CSS Colors")
# Optionally plot the XKCD colors (Caution: will produce large figure)
#xkcd_fig = plot_colortable(mcolors.XKCD_COLORS, "XKCD Colors")
#xkcd_fig.savefig("XKCD_Colors.png")
plt.show()
#############################################################################
#
# ------------
#
# References
# """"""""""
#
# The use of the following functions, methods, classes and modules is shown
# in this example:
import matplotlib
matplotlib.colors
matplotlib.colors.rgb_to_hsv
matplotlib.colors.to_rgba
matplotlib.figure.Figure.get_size_inches
matplotlib.figure.Figure.subplots_adjust
matplotlib.axes.Axes.text
matplotlib.axes.Axes.hlines
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