如何创建自定义colormap并解决colorbar扩展端颜色匹配问题

问题说明 #

基于从图像提取的颜色-值字典创建与原图一致的自定义colormap，启用extend='both'后，颜色条上下扩展箭头区域颜色不符合预期，要求100对应的灰色显示在顶部箭头区域，底部匹配对应颜色。

提取的颜色-值字典 #

{
    100: "RGB(170, 170, 170)",
    75: "RGB(90, 0, 0)",
    50: "RGB(180, 0, 0)", 
    30: "RGB(255, 150, 0)",
    20: "RGB(255, 250, 0)",
    10:"RGB(0, 210, 0)",
    5: "RGB(0, 120, 0)",
    2.5: "RGB(70, 70, 200)",
    1: "RGB(150, 150, 255)",
    0.5: "RGB(220, 220, 255)",
    0.1: "RGB(230, 230, 230)",
    0:'RGB(255,255,255)'
}

原实现代码 #

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors

# Generate random data
np.random.seed(42)  # for reproducibility
x, y, c = zip(*np.random.rand(30, 3) * 105 - 2)
# Define the color dictionary
color_dict = {
    0: 'white', 
    0.1: "blue",
    0.5: "pink",
    1: "lightblue",
    2.5: "blue",
    5: "darkgreen",
    10: "green",
    20: "yellow",
    30: "orange",
    50: "red",
    75: "brown",
    100: "grey",
    105: "grey"  
}
cvals = list(color_dict.keys())
colors = list(color_dict.values())

cmap = mcolors.ListedColormap(colors)
norm = mcolors.BoundaryNorm(boundaries=cvals, ncolors=len(colors))
plt.figure(figsize=(10, 6))
scatter = plt.scatter(x, y, c=c, cmap=cmap, norm=norm)
cbar = plt.colorbar(scatter, extend='both')
cbar.set_ticks(cvals[1:-1]) 
cbar.set_ticklabels([str(val) for val in cvals[1:-1]])  

plt.title("Custom ListedColormap with Pointy Ends")
plt.show()

效果对比图 #

预期效果：

当前问题效果：

解决方案 #

问题核心是ListedColormap默认不会将首尾颜色绑定到扩展区域，需手动指定over和under属性，同时修正颜色字典的顺序问题：

修改后的代码 #

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors

# 生成随机数据
np.random.seed(42)
x, y, c = zip(*np.random.rand(30, 3) * 105 - 2)

# 使用提取的真实颜色字典
color_dict = {
    0: "RGB(255,255,255)",
    0.1: "RGB(230, 230, 230)",
    0.5: "RGB(220, 220, 255)",
    1: "RGB(150, 150, 255)",
    2.5: "RGB(70, 70, 200)",
    5: "RGB(0, 120, 0)",
    10: "RGB(0, 210, 0)",
    20: "RGB(255, 250, 0)",
    30: "RGB(255, 150, 0)",
    50: "RGB(180, 0, 0)",
    75: "RGB(90, 0, 0)",
    100: "RGB(170, 170, 170)"
}

# 按数值升序排序，确保边界与颜色顺序匹配
sorted_items = sorted(color_dict.items(), key=lambda item: item[0])
cvals = [item[0] for item in sorted_items]
colors = [item[1] for item in sorted_items]

# 创建Colormap并设置扩展区域颜色
cmap = mcolors.ListedColormap(colors)
cmap.set_over(colors[-1])  # 顶部扩展箭头用最大值对应的灰色
cmap.set_under(colors[0])  # 底部扩展箭头用最小值对应的白色

# 创建边界归一化器
norm = mcolors.BoundaryNorm(boundaries=cvals, ncolors=len(colors))

# 绘制图形
plt.figure(figsize=(10, 6))
scatter = plt.scatter(x, y, c=c, cmap=cmap, norm=norm)
cbar = plt.colorbar(scatter, extend='both')
cbar.set_ticks(cvals)
cbar.set_ticklabels([str(val) for val in cvals])

plt.title("Custom ListedColormap with Correct Extended Ends")
plt.show()

关键修改点 #

• 对颜色字典按数值升序排序，避免因字典无序导致的颜色映射错误
• 通过cmap.set_over()和cmap.set_under()直接指定扩展箭头区域的颜色
• 调整刻度设置，显示所有边界值，更清晰反映颜色映射区间

内容的提问来源于stack exchange，提问作者Samman Amgain