论文配色参考

采用淡雅柔和色块，整体明度高，减少视觉疲劳。

#F7CFCD - 247,207,205
#FEF4CE - 254,244,206
#D6E9D4 - 214,233,212
#E2D5E7 - 226,213,231

主要为蓝紫色系，整体色彩搭配适合用于营造冷静、专业且富有层次感的视觉环境。

#9594C0 - 149,148,192
#6665A5 - 102,101,165
#30569F - 48,86,159
#4968A9 - 73,104,169
#4585BE - 69,133,190
#10B4DD - 16,180,221
#81C8E4 - 129,200,228
#6AC2D2 - 106,194,210
#BFDEE5 - 191,222,229

暗色调带来稳重感，浅淡柔和色则增添了些明快与温馨，适用于营造既有深度又不失舒适感的视觉氛围。

#963634 - 150,54,52
#D35400 - 211,84,0
#F5E0E0 - 245,224,224
#DACDE6 - 194,189,150
#3E68A6 - 60,104,166
#1E78B5 - 30,120,181
#E0E7F3 - 224,231,243
#7F7F7F - 127,127,127

涵盖了从沉稳到淡雅的多种色调，简约、平和且不失格调。

#C0908C - 192,144,140
#2E4971 - 46,73,113
#848E9F - 132,142,159
#FCF8ED - 252,248,237
#D9EEF0 - 217,238,240
#F9EFF7 - 249,239,247

兼具深度与柔和感，既神秘又清新。

#A35C72 - 163,92,114
#3C779F - 60,119,159
#86D2B2 - 134,210,178
#A08EA0 - 160,142,160
#F1E4E8 - 241,228,232
#E1E8F1 - 225,232,241
#CAE4D8 - 202,228,226
#A0B3BC - 160,179,188

主要为绿色系及其相近色调，适合营造自然、清新且富有层次感的视觉效果。

#D7E065 - 215,224,101
#BAB063 - 186,176,99
#A4BA7E - 164,186,126
#659A6F - 101,154,111
#46A6A1 - 70,166,161

涵盖了从冷到暖、从深到浅的多种色调，整体色彩组合丰富多样，适用于打造风格多变的视觉效果。

#7bbdd3 - 123,189,211
#afd1dd - 175,209,221
#dce9ef - 220,233,239
#c9b8e5 - 201,184,229
#dbd5ef - 219,213,239
#a50000 - 165,0,0
#d16694 - 209,102,148
#f4d1e9 - 244,209,233
#fce8f4 - 252,232,244
#eddbd9 - 237,219,217

生成色块图的脚本

import matplotlib.pyplot as plt
import numpy as np

hex_colors = ['#', '#', '#', '#']
rgb_colors = [tuple(int(color[i:i+2], 16) / 255.0 for i in (1, 3, 5)) for color in hex_colors]

num_colors = len(rgb_colors)
square_size = 1
fig, ax = plt.subplots(figsize=(num_colors * square_size, square_size))
matrix = np.array([rgb_colors] * 1)

ax.imshow(matrix, aspect='auto', interpolation='nearest')
ax.set_yticks([])
ax.set_xticklabels([])
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['bottom'].set_visible(False)
ax.spines['left'].set_visible(False)
ax.grid(False)
ax.tick_params(axis='both', which='both', length=0)

plt.show()

Color_r

论文配色参考