代码

import matplotlib.pyplot as pltfrom matplotlib import cmdef Hotmap():datas=[[1,2,3],[4,5,6],[7,8,9]]#热图数据(可根据需要修改)x_tick=['a','b','c']#横坐标（可根据需要修改）y_tick=['A','B','C']#纵坐标ax=plt.subplot()im=ax.imshow(datas,cmap=cm.binary)#绘制 可通过更改cmap改变颜色ax.set_xticks(np.arange(len(x_tick)), labels=x_tick)#设置标签ax.set_yticks(np.arange(len(y_tick)), labels=y_tick)#np.arrange产生的数组是标签的位置如果热图为400*400矩阵则[100,200,300,400]就是对应的位置，据此可以随意划分热图并根据需要产生间隔#如ax.set_yticks(np.arange(0,300,100), labels=y_tick)即把'A','B','C'放在0,100,200位置处plt.colorbar(im)#添加颜色条plt.show()#显示def main():Hotmap()

效果

补充

cmap内置参数

上图选用的为 cm.binary

1）Accent, Blues, BrBG, BuGn, BuPu, CMRmap, Dark2, GnBu, Greens, Greys, OrRd, Oranges, PRGn, Paired, Pastel1, Pastel2, PiYG, PuBu, PuBuGn, PuOr, PuRd, Purples, RdBu RdGy, RdPu, RdYlBu, RdYlGn, Reds, Set1, Set2, Set3, Spectral, Wistia, YlGn, YlGnBu, YlOrBr, YlOrRd

2）afmhot, autumn,binary, bone, brg bwr, cividis, cool, coolwarm, copper, cubehelix, flag, gist_earth, gist_gray, gist_heat, gist_ncar gist_rainbow, gist_stern, gist_yarg, gnuplot, gnuplot2, gray, hot, hsv, inferno, jet, magma, nipy_spectral, ocean, pink, plasma, prism, rainbow, seismic, spring, summer, tab10, tab20, tab20b, tab20c, terrain, twilight, twilight_shifted, viridis, winter

具体颜色可参考

matplotlib.pyplot——cmap直观理解