如何在Seaborn中将离散值映射到热图?

时间:2019-09-11 15:33:43

标签: python python-3.x matplotlib seaborn

我正在尝试使用seaborn在热图中绘制离散值。这是我要绘制的列表:

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的颜色。值的范围是1-17。因此,每个数字有17种不同的颜色。我确实读过其他一些答案,但是没有一个人谈论如何为数字分配特定的值。谢谢!

1 个答案:

答案 0 :(得分:1)

如果我对您的理解正确,则可以执行以下操作:

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()

每个数字对应一个颜色,从1(白色),2(灰色)到17(黑色)开始。如您所见,图像中没有黑色,因为阵列中没有17,而且色图未标准化。

enter image description here

或使用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

如果要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

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