Getting the names of colors from matplotlib colormap object

Question

I want to get english names of colors from a colormaps object. So far I read that you can get numeric values of colors. For example -

import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
from matplotlib.colors import ListedColormap, LinearSegmentedColormap

viridis = cm.get_cmap('viridis', 12)
print(viridis)
print(viridis(0.56))

OUTPUTS

<matplotlib.colors.ListedColormap object at 0x7fb112c73ba8>

(0.119512, 0.607464, 0.540218, 1.0)

It is also clear that LineSegColor is a tuple that matches a string and a dict containing a hash between strings and matrices. Matrices are representing a gradient in some n*m space for the expression of particular color.

cdict1 = {'red':   ((0.0, 0.0, 0.0),
                    (0.5, 0.0, 0.1),
                    (1.0, 1.0, 1.0)),

          'green': ((0.0, 0.0, 0.0),
                    (1.0, 0.0, 0.0)),

          'blue':  ((0.0, 0.0, 1.0),
                    (0.5, 0.1, 0.0),
                    (1.0, 0.0, 0.0))
          }
    blue_red1 = LinearSegmentedColormap('BlueRed1', cdict1)

How to reverse engineer the creation of color to Virdis?

Here are few links I visited -

Why do you think Viridis is a `LinearSegmentedColormap`? It is a carefully constructed `ListedColormap` starting from specific rgb values, not from named colors. Also note that to create a `LinearSegmentedColormap` it is much more convenient to use `LinearSegmentedColormap.from_list()` instead of the archaic rgb value juggling. — JohanC, Apr 05 '22 at 18:30
How to I get the names of colors from viridis.colors array output? — Paritosh Kulkarni, Apr 05 '22 at 20:09
See [Convert RGB color to English color name, like 'green'](https://stackoverflow.com/questions/9694165/convert-rgb-color-to-english-color-name-like-green-with-python) to convert rgb values to a name, provided there exists an exact match (or you are happy with the name of a neighboring color). To get all 256 colors in rgba format, `plt.get_cmap('viridis')(np.arange(256))` should do the trick. There is also a function `matplotlib.colors.to_hex()` that converts rgba values to hexadecimal strings. E.g. `[to_hex(rgba) for rgba in plt.get_cmap('viridis')(np.arange(256))]` to get 256 strings. — JohanC, Apr 05 '22 at 20:12

JohanC · Accepted Answer · 2022-04-05T22:12:53.327

Viridis wasn't created as a LinearSegmentedColormap. It is a carefully constructed list of 256 rgb values. You could create such a colormap via

import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap
import numpy as np

viridis = plt.get_cmap('viridis')
new_viridis = ListedColormap(viridis(np.arange(256)))

None of the 256 individual colors corresponds to a named color (at least not in the 148 long CSS4 list). Here is some code to create a list of close colors (the principal code comes from Convert RGB color to English color name, like 'green'):

import matplotlib.pyplot as plt
from matplotlib.colors import to_hex, to_rgb
import numpy as np

def find_closest_name(col):
    rv, gv, bv = to_rgb(col)
    min_colors = {}
    for col in CSS4_COLORS:
        rc, gc, bc = to_rgb(col)
        min_colors[(rc - rv) ** 2 + (gc - gv) ** 2 + (bc - bv) ** 2] = col
    closest = min(min_colors.keys())
    return min_colors[closest], np.sqrt(closest)

viridis = plt.get_cmap('viridis')
for i in range(256):
    closest_name, dist = find_closest_name(viridis(i))
    print(f'{i:3d} {to_hex((rv, gv, bv))} closest:{closest_name})  dist:{dist:.3f}')

Which gives the following list:

  0 #fde725 closest:indigo)  dist:0.182
  1 #fde725 closest:indigo)  dist:0.177
  2 #fde725 closest:indigo)  dist:0.171
  3 #fde725 closest:indigo)  dist:0.165
  4 #fde725 closest:indigo)  dist:0.160
  5 #fde725 closest:indigo)  dist:0.156
  6 #fde725 closest:indigo)  dist:0.151
  7 #fde725 closest:indigo)  dist:0.148
  8 #fde725 closest:indigo)  dist:0.144
  9 #fde725 closest:indigo)  dist:0.141
 10 #fde725 closest:indigo)  dist:0.139
 11 #fde725 closest:indigo)  dist:0.137
 12 #fde725 closest:indigo)  dist:0.135
 13 #fde725 closest:indigo)  dist:0.134
 14 #fde725 closest:indigo)  dist:0.133
 15 #fde725 closest:indigo)  dist:0.133
 16 #fde725 closest:indigo)  dist:0.133
 17 #fde725 closest:indigo)  dist:0.134
 18 #fde725 closest:indigo)  dist:0.135
 19 #fde725 closest:indigo)  dist:0.136
 20 #fde725 closest:indigo)  dist:0.138
 21 #fde725 closest:indigo)  dist:0.140
 22 #fde725 closest:indigo)  dist:0.142
 23 #fde725 closest:darkslateblue)  dist:0.145
 24 #fde725 closest:darkslateblue)  dist:0.138
 25 #fde725 closest:darkslateblue)  dist:0.132
 26 #fde725 closest:darkslateblue)  dist:0.125
 27 #fde725 closest:darkslateblue)  dist:0.119
 28 #fde725 closest:darkslateblue)  dist:0.113
 29 #fde725 closest:darkslateblue)  dist:0.107
 30 #fde725 closest:darkslateblue)  dist:0.101
 31 #fde725 closest:darkslateblue)  dist:0.095
 32 #fde725 closest:darkslateblue)  dist:0.089
 33 #fde725 closest:darkslateblue)  dist:0.083
 34 #fde725 closest:darkslateblue)  dist:0.077
 35 #fde725 closest:darkslateblue)  dist:0.072
 36 #fde725 closest:darkslateblue)  dist:0.067
 37 #fde725 closest:darkslateblue)  dist:0.061
 38 #fde725 closest:darkslateblue)  dist:0.056
 39 #fde725 closest:darkslateblue)  dist:0.052
 40 #fde725 closest:darkslateblue)  dist:0.047
 41 #fde725 closest:darkslateblue)  dist:0.043
 42 #fde725 closest:darkslateblue)  dist:0.039
 43 #fde725 closest:darkslateblue)  dist:0.036
 44 #fde725 closest:darkslateblue)  dist:0.034
 45 #fde725 closest:darkslateblue)  dist:0.032
 46 #fde725 closest:darkslateblue)  dist:0.032
 47 #fde725 closest:darkslateblue)  dist:0.032
 48 #fde725 closest:darkslateblue)  dist:0.033
 49 #fde725 closest:darkslateblue)  dist:0.035
 50 #fde725 closest:darkslateblue)  dist:0.038
 51 #fde725 closest:darkslateblue)  dist:0.041
 52 #fde725 closest:darkslateblue)  dist:0.045
 53 #fde725 closest:darkslateblue)  dist:0.049
 54 #fde725 closest:darkslateblue)  dist:0.053
 55 #fde725 closest:darkslateblue)  dist:0.057
 56 #fde725 closest:darkslateblue)  dist:0.062
 57 #fde725 closest:darkslateblue)  dist:0.066
 58 #fde725 closest:darkslateblue)  dist:0.071
 59 #fde725 closest:darkslateblue)  dist:0.075
 60 #fde725 closest:darkslateblue)  dist:0.080
 61 #fde725 closest:darkslateblue)  dist:0.085
 62 #fde725 closest:darkslateblue)  dist:0.089
 63 #fde725 closest:darkslateblue)  dist:0.094
 64 #fde725 closest:darkslateblue)  dist:0.098
 65 #fde725 closest:darkslateblue)  dist:0.103
 66 #fde725 closest:darkslateblue)  dist:0.108
 67 #fde725 closest:darkslateblue)  dist:0.112
 68 #fde725 closest:darkslateblue)  dist:0.117
 69 #fde725 closest:darkslateblue)  dist:0.121
 70 #fde725 closest:darkslateblue)  dist:0.126
 71 #fde725 closest:darkslateblue)  dist:0.130
 72 #fde725 closest:darkslateblue)  dist:0.135
 73 #fde725 closest:darkslateblue)  dist:0.139
 74 #fde725 closest:darkslateblue)  dist:0.144
 75 #fde725 closest:darkslateblue)  dist:0.148
 76 #fde725 closest:darkslateblue)  dist:0.153
 77 #fde725 closest:darkslateblue)  dist:0.157
 78 #fde725 closest:darkslateblue)  dist:0.162
 79 #fde725 closest:darkslateblue)  dist:0.166
 80 #fde725 closest:darkslateblue)  dist:0.170
 81 #fde725 closest:darkslateblue)  dist:0.175
 82 #fde725 closest:darkslateblue)  dist:0.179
 83 #fde725 closest:darkslateblue)  dist:0.183
 84 #fde725 closest:darkslateblue)  dist:0.187
 85 #fde725 closest:darkslateblue)  dist:0.192
 86 #fde725 closest:darkslateblue)  dist:0.196
 87 #fde725 closest:steelblue)  dist:0.197
 88 #fde725 closest:steelblue)  dist:0.196
 89 #fde725 closest:steelblue)  dist:0.195
 90 #fde725 closest:steelblue)  dist:0.194
 91 #fde725 closest:steelblue)  dist:0.193
 92 #fde725 closest:steelblue)  dist:0.192
 93 #fde725 closest:steelblue)  dist:0.191
 94 #fde725 closest:steelblue)  dist:0.191
 95 #fde725 closest:steelblue)  dist:0.190
 96 #fde725 closest:teal)  dist:0.189
 97 #fde725 closest:teal)  dist:0.187
 98 #fde725 closest:teal)  dist:0.184
 99 #fde725 closest:teal)  dist:0.182
100 #fde725 closest:teal)  dist:0.180
101 #fde725 closest:teal)  dist:0.178
102 #fde725 closest:teal)  dist:0.176
103 #fde725 closest:teal)  dist:0.174
104 #fde725 closest:teal)  dist:0.172
105 #fde725 closest:teal)  dist:0.170
106 #fde725 closest:teal)  dist:0.168
107 #fde725 closest:darkcyan)  dist:0.166
108 #fde725 closest:darkcyan)  dist:0.164
109 #fde725 closest:darkcyan)  dist:0.161
110 #fde725 closest:darkcyan)  dist:0.159
111 #fde725 closest:darkcyan)  dist:0.156
112 #fde725 closest:darkcyan)  dist:0.154
113 #fde725 closest:darkcyan)  dist:0.152
114 #fde725 closest:darkcyan)  dist:0.150
115 #fde725 closest:darkcyan)  dist:0.148
116 #fde725 closest:darkcyan)  dist:0.146
117 #fde725 closest:darkcyan)  dist:0.144
118 #fde725 closest:darkcyan)  dist:0.142
119 #fde725 closest:darkcyan)  dist:0.140
120 #fde725 closest:darkcyan)  dist:0.138
121 #fde725 closest:darkcyan)  dist:0.137
122 #fde725 closest:darkcyan)  dist:0.135
123 #fde725 closest:darkcyan)  dist:0.134
124 #fde725 closest:darkcyan)  dist:0.133
125 #fde725 closest:darkcyan)  dist:0.132
126 #fde725 closest:darkcyan)  dist:0.131
127 #fde725 closest:darkcyan)  dist:0.130
128 #fde725 closest:darkcyan)  dist:0.130
129 #fde725 closest:darkcyan)  dist:0.129
130 #fde725 closest:darkcyan)  dist:0.129
131 #fde725 closest:darkcyan)  dist:0.129
132 #fde725 closest:darkcyan)  dist:0.129
133 #fde725 closest:darkcyan)  dist:0.129
134 #fde725 closest:darkcyan)  dist:0.130
135 #fde725 closest:darkcyan)  dist:0.130
136 #fde725 closest:darkcyan)  dist:0.131
137 #fde725 closest:darkcyan)  dist:0.132
138 #fde725 closest:darkcyan)  dist:0.133
139 #fde725 closest:darkcyan)  dist:0.135
140 #fde725 closest:darkcyan)  dist:0.137
141 #fde725 closest:darkcyan)  dist:0.139
142 #fde725 closest:darkcyan)  dist:0.141
143 #fde725 closest:darkcyan)  dist:0.143
144 #fde725 closest:darkcyan)  dist:0.146
145 #fde725 closest:darkcyan)  dist:0.148
146 #fde725 closest:lightseagreen)  dist:0.151
147 #fde725 closest:lightseagreen)  dist:0.151
148 #fde725 closest:lightseagreen)  dist:0.151
149 #fde725 closest:mediumseagreen)  dist:0.148
150 #fde725 closest:mediumseagreen)  dist:0.145
151 #fde725 closest:mediumseagreen)  dist:0.141
152 #fde725 closest:mediumseagreen)  dist:0.137
153 #fde725 closest:mediumseagreen)  dist:0.132
154 #fde725 closest:mediumseagreen)  dist:0.128
155 #fde725 closest:mediumseagreen)  dist:0.124
156 #fde725 closest:mediumseagreen)  dist:0.119
157 #fde725 closest:mediumseagreen)  dist:0.114
158 #fde725 closest:mediumseagreen)  dist:0.109
159 #fde725 closest:mediumseagreen)  dist:0.104
160 #fde725 closest:mediumseagreen)  dist:0.099
161 #fde725 closest:mediumseagreen)  dist:0.093
162 #fde725 closest:mediumseagreen)  dist:0.088
163 #fde725 closest:mediumseagreen)  dist:0.082
164 #fde725 closest:mediumseagreen)  dist:0.077
165 #fde725 closest:mediumseagreen)  dist:0.071
166 #fde725 closest:mediumseagreen)  dist:0.065
167 #fde725 closest:mediumseagreen)  dist:0.059
168 #fde725 closest:mediumseagreen)  dist:0.054
169 #fde725 closest:mediumseagreen)  dist:0.049
170 #fde725 closest:mediumseagreen)  dist:0.044
171 #fde725 closest:mediumseagreen)  dist:0.039
172 #fde725 closest:mediumseagreen)  dist:0.036
173 #fde725 closest:mediumseagreen)  dist:0.035
174 #fde725 closest:mediumseagreen)  dist:0.034
175 #fde725 closest:mediumseagreen)  dist:0.036
176 #fde725 closest:mediumseagreen)  dist:0.040
177 #fde725 closest:mediumseagreen)  dist:0.044
178 #fde725 closest:mediumseagreen)  dist:0.050
179 #fde725 closest:mediumseagreen)  dist:0.057
180 #fde725 closest:mediumseagreen)  dist:0.064
181 #fde725 closest:mediumseagreen)  dist:0.071
182 #fde725 closest:mediumseagreen)  dist:0.079
183 #fde725 closest:mediumseagreen)  dist:0.087
184 #fde725 closest:mediumseagreen)  dist:0.096
185 #fde725 closest:mediumseagreen)  dist:0.105
186 #fde725 closest:mediumseagreen)  dist:0.114
187 #fde725 closest:mediumseagreen)  dist:0.123
188 #fde725 closest:mediumseagreen)  dist:0.132
189 #fde725 closest:mediumseagreen)  dist:0.141
190 #fde725 closest:mediumseagreen)  dist:0.151
191 #fde725 closest:mediumseagreen)  dist:0.161
192 #fde725 closest:mediumseagreen)  dist:0.171
193 #fde725 closest:mediumseagreen)  dist:0.181
194 #fde725 closest:mediumseagreen)  dist:0.191
195 #fde725 closest:mediumseagreen)  dist:0.201
196 #fde725 closest:mediumseagreen)  dist:0.211
197 #fde725 closest:mediumseagreen)  dist:0.222
198 #fde725 closest:mediumseagreen)  dist:0.232
199 #fde725 closest:yellowgreen)  dist:0.229
200 #fde725 closest:yellowgreen)  dist:0.219
201 #fde725 closest:yellowgreen)  dist:0.208
202 #fde725 closest:yellowgreen)  dist:0.198
203 #fde725 closest:yellowgreen)  dist:0.187
204 #fde725 closest:yellowgreen)  dist:0.177
205 #fde725 closest:yellowgreen)  dist:0.166
206 #fde725 closest:yellowgreen)  dist:0.156
207 #fde725 closest:yellowgreen)  dist:0.145
208 #fde725 closest:yellowgreen)  dist:0.135
209 #fde725 closest:yellowgreen)  dist:0.124
210 #fde725 closest:yellowgreen)  dist:0.114
211 #fde725 closest:yellowgreen)  dist:0.104
212 #fde725 closest:yellowgreen)  dist:0.095
213 #fde725 closest:yellowgreen)  dist:0.086
214 #fde725 closest:yellowgreen)  dist:0.078
215 #fde725 closest:yellowgreen)  dist:0.071
216 #fde725 closest:yellowgreen)  dist:0.066
217 #fde725 closest:yellowgreen)  dist:0.062
218 #fde725 closest:yellowgreen)  dist:0.061
219 #fde725 closest:yellowgreen)  dist:0.062
220 #fde725 closest:yellowgreen)  dist:0.065
221 #fde725 closest:yellowgreen)  dist:0.071
222 #fde725 closest:yellowgreen)  dist:0.078
223 #fde725 closest:yellowgreen)  dist:0.087
224 #fde725 closest:yellowgreen)  dist:0.096
225 #fde725 closest:yellowgreen)  dist:0.106
226 #fde725 closest:yellowgreen)  dist:0.116
227 #fde725 closest:yellowgreen)  dist:0.127
228 #fde725 closest:greenyellow)  dist:0.138
229 #fde725 closest:greenyellow)  dist:0.141
230 #fde725 closest:greenyellow)  dist:0.146
231 #fde725 closest:greenyellow)  dist:0.151
232 #fde725 closest:greenyellow)  dist:0.157
233 #fde725 closest:greenyellow)  dist:0.163
234 #fde725 closest:greenyellow)  dist:0.170
235 #fde725 closest:greenyellow)  dist:0.178
236 #fde725 closest:greenyellow)  dist:0.186
237 #fde725 closest:greenyellow)  dist:0.194
238 #fde725 closest:greenyellow)  dist:0.202
239 #fde725 closest:gold)  dist:0.199
240 #fde725 closest:gold)  dist:0.189
241 #fde725 closest:gold)  dist:0.180
242 #fde725 closest:gold)  dist:0.171
243 #fde725 closest:gold)  dist:0.163
244 #fde725 closest:gold)  dist:0.156
245 #fde725 closest:gold)  dist:0.150
246 #fde725 closest:gold)  dist:0.145
247 #fde725 closest:gold)  dist:0.141
248 #fde725 closest:gold)  dist:0.139
249 #fde725 closest:gold)  dist:0.137
250 #fde725 closest:gold)  dist:0.137
251 #fde725 closest:gold)  dist:0.139
252 #fde725 closest:gold)  dist:0.142
253 #fde725 closest:gold)  dist:0.146
254 #fde725 closest:gold)  dist:0.151
255 #fde725 closest:gold)  dist:0.157

Here is some code to create a LinearSegmentedColormap from 12 colors close to viridis. The first example uses the closest named colors, the second uses the hexadecimal form of the exact colors. Both are just an approximation, but one can notice that the named colors differ a lot (especially because the 12 closest colors aren't unique).

import matplotlib.pyplot as plt
from matplotlib.colors import to_hex, to_rgb, CSS4_COLORS, LinearSegmentedColormap, ListedColormap
from matplotlib.cm import ScalarMappable

def find_closest_name(col):
    rv, gv, bv = to_rgb(col)
    min_colors = {}
    for col in CSS4_COLORS:
        rc, gc, bc = to_rgb(col)
        min_colors[(rc - rv) ** 2 + (gc - gv) ** 2 + (bc - bv) ** 2] = col
    closest = min(min_colors.keys())
    return min_colors[closest], np.sqrt(closest)

vals = np.linspace(0, 1, 12)
[(val, to_hex(viridis(val))) for val in vals]

semi_viridis_colors = [find_closest_name(viridis(val))[0] for val in vals]
# ['indigo', 'darkslateblue', 'darkslateblue', 'darkslateblue', 'steelblue', 'darkcyan', 'darkcyan', 'mediumseagreen', 'mediumseagreen', 'yellowgreen', 'greenyellow', 'gold']
semi_viridis = LinearSegmentedColormap.from_list('semi_viridis',
                                                 [(val, col) for val, col in zip(vals, semi_viridis_colors)])
semi_viridis_hex_colors = [to_hex(viridis(val)) for val in vals]
# ['#440154', '#482173', '#433e85', '#38588c', '#2d708e', '#25858e', '#1e9b8a', '#2ab07f', '#52c569', '#86d549', '#c2df23', '#fde725']
semi_viridis_hex = LinearSegmentedColormap.from_list('semi_viridis_hex',
                                                     [(val, col) for val, col in zip(vals, semi_viridis_hex_colors)])

fig, (ax1, ax2, ax3) = plt.subplots(3, 1, figsize=(16, 5))
plt.colorbar(ScalarMappable(cmap=viridis), label='viridis', orientation='horizontal', cax=ax1)
plt.colorbar(ScalarMappable(cmap=semi_viridis), label='semi viridis', orientation='horizontal', cax=ax2)
plt.colorbar(ScalarMappable(cmap=semi_viridis_hex), label='semi viridis hex', orientation='horizontal', cax=ax3)
plt.tight_layout()
plt.show()

Thanks, Johann, this clarifies. The subjective human names for colors mapped with HEX or RGB was suitable in the Seaborn palate for my application. — Paritosh Kulkarni, Aug 02 '22 at 01:58

Getting the names of colors from matplotlib colormap object

1 Answers1