[matplotlib] Color name, RGB 색상 정보 출력 하기

matplotlib에서 사용하는 color 정보 입니다.

matplotlib 사이트에 있는 프로그램 소스를 가져와 color 명칭을 복사해서 사용하기 위해 몇 줄 추가를 했습니다.

 

https://matplotlib.org/examples/color/named_colors.html

이곳에 가시면 좀더 깔끔한 원본을 볼 수 있습니다.

여기는 개인적으로 컬러 값 복사용으로 사용하려고 만들어 봤습니다.

 

1. Color Table

2. Color Name

black(#000000)	k(0,0,0)	dimgray(#696969)	dimgrey(#696969)
gray(#808080)	grey(#808080)	darkgray(#A9A9A9)	darkgrey(#A9A9A9)
silver(#C0C0C0)	lightgray(#D3D3D3)	lightgrey(#D3D3D3)	gainsboro(#DCDCDC)
whitesmoke(#F5F5F5)	w(1,1,1)	white(#FFFFFF)	snow(#FFFAFA)
rosybrown(#BC8F8F)	lightcoral(#F08080)	indianred(#CD5C5C)	brown(#A52A2A)
firebrick(#B22222)	maroon(#800000)	darkred(#8B0000)	r(1,0,0)
red(#FF0000)	mistyrose(#FFE4E1)	salmon(#FA8072)	tomato(#FF6347)
darksalmon(#E9967A)	coral(#FF7F50)	orangered(#FF4500)	lightsalmon(#FFA07A)
sienna(#A0522D)	seashell(#FFF5EE)	chocolate(#D2691E)	saddlebrown(#8B4513)
sandybrown(#F4A460)	peachpuff(#FFDAB9)	peru(#CD853F)	linen(#FAF0E6)
bisque(#FFE4C4)	darkorange(#FF8C00)	burlywood(#DEB887)	antiquewhite(#FAEBD7)
tan(#D2B48C)	navajowhite(#FFDEAD)	blanchedalmond(#FFEBCD)	papayawhip(#FFEFD5)
moccasin(#FFE4B5)	orange(#FFA500)	wheat(#F5DEB3)	oldlace(#FDF5E6)
floralwhite(#FFFAF0)	darkgoldenrod(#B8860B)	goldenrod(#DAA520)	cornsilk(#FFF8DC)
gold(#FFD700)	lemonchiffon(#FFFACD)	khaki(#F0E68C)	palegoldenrod(#EEE8AA)
darkkhaki(#BDB76B)	ivory(#FFFFF0)	beige(#F5F5DC)	lightyellow(#FFFFE0)
lightgoldenrodyellow(#FAFAD2)	olive(#808000)	y(0.75,0.75,0)	yellow(#FFFF00)
olivedrab(#6B8E23)	yellowgreen(#9ACD32)	darkolivegreen(#556B2F)	greenyellow(#ADFF2F)
chartreuse(#7FFF00)	lawngreen(#7CFC00)	honeydew(#F0FFF0)	darkseagreen(#8FBC8F)
palegreen(#98FB98)	lightgreen(#90EE90)	forestgreen(#228B22)	limegreen(#32CD32)
darkgreen(#006400)	g(0,0.5,0)	green(#008000)	lime(#00FF00)
seagreen(#2E8B57)	mediumseagreen(#3CB371)	springgreen(#00FF7F)	mintcream(#F5FFFA)
mediumspringgreen(#00FA9A)	mediumaquamarine(#66CDAA)	aquamarine(#7FFFD4)	turquoise(#40E0D0)
lightseagreen(#20B2AA)	mediumturquoise(#48D1CC)	azure(#F0FFFF)	lightcyan(#E0FFFF)
paleturquoise(#AFEEEE)	darkslategray(#2F4F4F)	darkslategrey(#2F4F4F)	teal(#008080)
darkcyan(#008B8B)	c(0,0.75,0.75)	aqua(#00FFFF)	cyan(#00FFFF)
darkturquoise(#00CED1)	cadetblue(#5F9EA0)	powderblue(#B0E0E6)	lightblue(#ADD8E6)
deepskyblue(#00BFFF)	skyblue(#87CEEB)	lightskyblue(#87CEFA)	steelblue(#4682B4)
aliceblue(#F0F8FF)	dodgerblue(#1E90FF)	lightslategray(#778899)	lightslategrey(#778899)
slategray(#708090)	slategrey(#708090)	lightsteelblue(#B0C4DE)	cornflowerblue(#6495ED)
royalblue(#4169E1)	ghostwhite(#F8F8FF)	lavender(#E6E6FA)	midnightblue(#191970)
navy(#000080)	darkblue(#00008B)	mediumblue(#0000CD)	b(0,0,1)
blue(#0000FF)	slateblue(#6A5ACD)	darkslateblue(#483D8B)	mediumslateblue(#7B68EE)
mediumpurple(#9370DB)	rebeccapurple(#663399)	blueviolet(#8A2BE2)	indigo(#4B0082)
darkorchid(#9932CC)	darkviolet(#9400D3)	mediumorchid(#BA55D3)	thistle(#D8BFD8)
plum(#DDA0DD)	violet(#EE82EE)	purple(#800080)	darkmagenta(#8B008B)
m(0.75,0,0.75)	fuchsia(#FF00FF)	magenta(#FF00FF)	orchid(#DA70D6)
mediumvioletred(#C71585)	deeppink(#FF1493)	hotpink(#FF69B4)	lavenderblush(#FFF0F5)
palevioletred(#DB7093)	crimson(#DC143C)	pink(#FFC0CB)	lightpink(#FFB6C1)

3. Source Code

"""
========================
Visualizing named colors
========================

Simple plot example with the named colors and its visual representation.
"""
from __future__ import division

import matplotlib.pyplot as plt
from matplotlib import colors as mcolors


colors = dict(mcolors.BASE_COLORS, **mcolors.CSS4_COLORS)

# Sort colors by hue, saturation, value and name.
by_hsv = sorted((tuple(mcolors.rgb_to_hsv(mcolors.to_rgba(color)[:3])), name)
                for name, color in colors.items())
sorted_names = [name for hsv, name in by_hsv]

n = len(sorted_names)
ncols = 4
nrows = n // ncols + 1

fig, ax = plt.subplots(figsize=(8, 5))

# Get height and width
X, Y = fig.get_dpi() * fig.get_size_inches()
h = Y / (nrows + 1)
w = X / ncols

for i, name in enumerate(sorted_names):
    col = i % ncols
    row = i // ncols
    y = Y - (row * h) - h

    xi_line = w * (col + 0.05)
    xf_line = w * (col + 0.25)
    xi_text = w * (col + 0.3)

    color_name = name + '(' + str(colors[name]) +')'
    if col == 3:
        print("{:35}".format( color_name ), end='\n')
    else:
        print("{:35}".format( color_name ), end = "")
    ax.text(xi_text, y, name, fontsize=(h * 0.8), horizontalalignment='left',verticalalignment='center')
    ax.hlines(y + h * 0.1, xi_line, xf_line, color=colors[name], linewidth=(h * 0.6))
   
ax.set_xlim(0, X)
ax.set_ylim(0, Y)
ax.set_axis_off()

fig.subplots_adjust(left=0, right=1, top=1, bottom=0,hspace=0, wspace=0)
plt.show()

- copy coding -