海运热图自定义色彩映射表

Seaborn Heatmap Custom colormap(海运热图自定义色彩映射表)

问题描述

import seaborn as sns
import numpy as np 
import matplotlib
import matplotlib.pyplot as plt

matrix = np.array([[149030, 34],[7442, 12]])
norm = matplotlib.colors.Normalize(matrix.min(), matrix.max())
boundaries = [value for value in matrix.flatten().tolist()]
list.sort(boundaries)

colors = [[norm(boundaries[0]), "#90AFC5"], 
          [norm(boundaries[1]), "#336B87"], 
          [norm(boundaries[2]), "#2a3132"], 
          [norm(boundaries[3]), "#763626"]]
    
    
cmap = matplotlib.colors.LinearSegmentedColormap.from_list("", colors)

fig = plt.figure(figsize=(6, 6))
ax = plt.subplot() 
    

annot = np.array([[f"{matrix[0,0]}", f"{matrix[0,1]}"],
                  [f"{matrix[1,0]}", f"{matrix[1,1]}"]], dtype=object)    

sns.heatmap(matrix,
            annot=annot,
            annot_kws={"size": 11},
            fmt="",
            ax=ax,
            vmin=matrix.min(),
            vmax=matrix.max(),
            cmap=cmap,
            cbar=True,
            cbar_kws={'format': '%.0f%%', 'ticks': boundaries, 'drawedges': True},
            xticklabels=False,
            yticklabels=False)

我的输出如您所见，有两个蓝色列，但我定义了不同的颜色：

推荐答案

如果使用BoundaryNorm，则可以为边界之间的范围指定颜色。要获得4个范围，您需要5个边界。一种方法是在末端添加一个额外的边界。在这个问题中，不清楚您希望如何处理与边界不一致的颜色值。在下面的代码中，颜色用于边界值和直到下一个边界的范围。

import seaborn as sns
import numpy as np
import matplotlib
import matplotlib.pyplot as plt

matrix = np.array([[149030, 34], [7442, 12]])
boundaries = [value for value in matrix.flatten().tolist()]
list.sort(boundaries)
colors = ["#90AFC5", "#336B87", "#2a3132", "#763626"]
norm = matplotlib.colors.BoundaryNorm(boundaries=boundaries + [boundaries[-1]], ncolors=256)

cmap = matplotlib.colors.LinearSegmentedColormap.from_list("", colors)

fig = plt.figure(figsize=(6, 6))
ax = plt.subplot()

annot = np.array([[f"{matrix[0, 0]}", f"{matrix[0, 1]}"],
                  [f"{matrix[1, 0]}", f"{matrix[1, 1]}"]], dtype=object)

sns.heatmap(matrix,
            annot=annot,
            annot_kws={"size": 11},
            fmt="",
            ax=ax,
            cmap=cmap,
            norm=norm,
            cbar=True,
            cbar_kws={'format': '%.0f%%', 'ticks': boundaries, 'drawedges': True},
            xticklabels=False,
            yticklabels=False)
plt.show()