关于python:自定义matplotlib中的颜色 – 热图

Customizing colors in matplotlib - heatmap

如何在heatmap中指定颜色。在本例中,数据是4个值中唯一的一个{0,1,2,3}

1
2
3
4
5
6
7
8
9
Index= ['aaa', 'bbb', 'ccc', 'ddd', 'eee']
Cols = ['A', 'B', 'C', 'D']

data= [[ 0, 3, 1, 1],[ 0, 1, 1, 1],[ 0, 1, 2, 1],[ 0, 2, 1, 2],[ 0, 1, 1, 1]]
print data
df = pd.DataFrame(data, index=Index, columns=Cols)
heatmap = plt.pcolor(np.array(data))
plt.colorbar(heatmap)
plt.show()

我如何用一种表示的方式来指定那些颜色颜色=0:'绿色',1:'红色',2:'黑色',3:'黄色'


创建自定义颜色映射并将刻度设置为整数

1
2
3
4
5
6
from matplotlib import colors
cmap = colors.ListedColormap(['green','red','black','yellow'])
bounds=[-0.5, 0.5, 1.5, 2.5, 3.5]
norm = colors.BoundaryNorm(bounds, cmap.N)
heatmap = plt.pcolor(np.array(data), cmap=cmap, norm=norm)
plt.colorbar(heatmap, ticks=[0, 1, 2, 3])

这就是你想要的吗?注意,您的data显示为"颠倒"。listed colormap


我修改了这个代码,显示了9个节点的3个红色/黄色/绿色状态

1
2
3
4
5
6
7
8
9
10
11
import matplotlib.pyplot as plt
from matplotlib.colors
import LinearSegmentedColormap
colors = [(1, 0, 0), (1, 1, 0), (0, 1, 0)]  # Red, yellow, green
n_bins = [3]  # Discretizes the interpolation into bins
cmap_name = 'my_list'
cm = LinearSegmentedColormap.from_list(cmap_name, colors, N=3)
threshold = 3  # max value
data = [[1, 1, 2], [1, 1, 3], [1, 1, 2]]
img = plt.imshow(data, interpolation='nearest', vmax=threshold, cmap=cm)
plt.show()