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.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](https://istack.dev59.com/GRUOL.webp)
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](https://istack.dev59.com/HV0jo.webp)
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](https://istack.dev59.com/EfjZ3.webp)