# 可视化命名颜色

这绘制了matplotlib中支持的命名颜色列表。 请注意,也支持xkcd颜色,但为简洁起见,此处未列出。

有关matplotlib中颜色的更多信息,请参阅:

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()

可视化命名颜色示例

可视化命名颜色示例2

可视化命名颜色示例3

# 参考

此示例中显示了以下函数,方法,类和模块的使用:

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

# 下载这个示例