在matplotlib中如何基于给定数值列表和对应十六进制颜色值生成色阶条
自定义数值-颜色映射色阶条生成方案
以下是基于Python Matplotlib库的实现方案,可直接用你提供的数值和颜色生成精准对应的色阶条:
可直接运行的实现代码
import matplotlib.pyplot as plt import matplotlib.colors as mcolors import numpy as np # 你提供的数值与对应十六进制颜色列表 vals = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 42, 43, 44, 45, 46, 47, 49, 50, 52, 53, 54, 55, 57, 58, 59, 60, 61, 62, 63, 65, 66, 67, 69, 78, 81, 84, 91, 139, 187, 203, 296] cols = ['#b3b3b3', '#fefe6d', '#fefb6a', '#fefb6a', '#fefb6a', '#fef968', '#fef968', '#fef968', '#fef665', '#fef665', '#fef665', '#fef462', '#fef462', '#fef462', '#fef25f', '#fef25f', '#fef25f', '#fef05c', '#fef05c', '#fef05c', '#feed5a', '#feed5a', '#feed5a', '#feeb57', '#feeb57', '#feeb57', '#fee954', '#fee954', '#fee954', '#fee751', '#fee751', '#fee751', '#fee54f', '#fee54f', '#fee54f', '#fee34c', '#fee34c', '#fee34c', '#fee149', '#fee149', '#fee047', '#fee047', '#fede44', '#fede44', '#fede44', '#fedc42', '#fedc42', '#feda3f', '#feda3f', '#fed83d', '#fed83d', '#fed83d', '#fed63b', '#fed63b', '#fed438', '#fed438', '#fed438', '#fed236', '#fed236', '#fed236', '#fed034', '#fed034', '#fece31', '#fece31', '#fec82b', '#fec529', '#fec327', '#febd22', '#fc940d', '#ec6504', '#de5502', '#652200'] # 构建自定义离散颜色映射 cmap = mcolors.ListedColormap(cols) # 生成数值边界,保证每个数值区间对应唯一颜色,避免插值偏差 bounds = np.append(vals, vals[-1] + 1) norm = mcolors.BoundaryNorm(bounds, cmap.N) # 绘制色阶条 fig, ax = plt.subplots(figsize=(12, 1)) fig.subplots_adjust(bottom=0.5) # 隐藏无关坐标轴 ax.set_axis_off() # 生成色阶条,可自行调整ticks参数控制刻度显示密度 cb = fig.colorbar(plt.cm.ScalarMappable(norm=norm, cmap=cmap), cax=ax, orientation='horizontal', ticks=vals[::10], label='对应数值') plt.show()
关键参数说明
ListedColormap会直接按你给出的颜色列表生成专属色板,不会修改原始颜色值BoundaryNorm实现离散数值到对应颜色的精准绑定,不会出现自动插值导致的颜色偏移- 你可以自行修改
ticks参数,传入自定义刻度列表调整色阶条上显示的刻度数量,避免刻度拥挤
内容的提问来源于stack exchange,提问作者Daniel Berman
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