如何在seaborn中将离散值映射到热力图上?

4

我将使用seaborn绘制离散值的热力图。这是我需要绘制的列表:

xa = [[5, 4, 4, 4, 13, 4, 4],
 [1, 9, 4, 3, 9, 1, 4],
 [4, 1, 7, 1, 5, 3, 7],
 [1, 9, 4, 3, 9, 5, 4],
 [2, 1, 4, 1, 9, 4, 3],
 [9, 4, 8, 1, 7, 1, 9],
 [4, 8, 1, 7, 1, 4, 8]]

这是我用来绘制热力图的代码:

import numpy as np
import seaborn as sns
from matplotlib.colors import ListedColormap
data = np.asarray(xa)
sns.heatmap( data,cmap=ListedColormap(['green', 'yellow', 'red']))

我的问题是如何将每个数字绘制为特定颜色。值的范围将从1-17。因此,有17种不同的颜色,每个数字对应一种颜色。我读过一些其他答案,但没有一个解释如何给数字分配特定值的方法。谢谢!
1个回答

3
如果我理解正确,您可以做类似于这样的事情:
import numpy as np
from matplotlib import pyplot as plt
import matplotlib.colors as c
data = np.asarray(xa)
colors = {"white":1, "gray":2, "yellow":3, "lightgreen":4, "green":5, "lightblue":6, "blue":7, "lightcoral":8, "red":9, "brown":10,
          "violet":11, "blueviolet":12, "indigo":13, "khaki":14, "orange":15, "pink":16, "black":17}
l_colors = sorted(colors, key=colors.get)
cMap = c.ListedColormap(l_colors)
fig, ax = plt.subplots()
ax.pcolor(data[::-1], cmap=cMap, vmin=1, vmax=len(colors))
# plt.axis('off') # if you don't want the axis
plt.show()

对于每个数字都对应一种颜色,从1(白色)开始,2(灰色),直到17(黑色)。正如您所看到的,在图像中没有黑色,因为在您的数组中没有17,并且颜色映射未归一化。

enter image description here

或者使用 seaborn:
data = np.asarray(xa)
colors = {"white":1,"gray":2,"yellow":3,"lightgreen":4, "green":5, "lightblue":6, "blue":7, "lightcoral":8, "red":9, "brown":10,
          "violet":11, "blueviolet":12,"indigo":13, "khaki":14, "orange":15, "pink":16, "black":17}
l_colors = sorted(colors, key=colors.get)
cMap = c.ListedColormap(l_colors)
sns.heatmap(data,cmap=l_colors, vmin=1, vmax=len(colors))

enter image description here

如果您想在图例上显示所有刻度,请添加以下内容:
ax = sns.heatmap(data,cmap=l_colors, vmin=1, vmax=len(colors))
colorbar = ax.collections[0].colorbar
colorbar.set_ticks([1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17])

enter image description here


网页内容由stack overflow 提供, 点击上面的
可以查看英文原文,
原文链接