Matplotlib的subplot画图， 共享colorbar

Python画图，利用Matplotlib中subplot画3*3的heatmap图，所有热力图共享一个colorbar。

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import numpy as np import matplotlib matplotlib.use('AGG') import matplotlib.pyplot as plt import csv import pandas as pd    fig, axs = plt.subplots(3, 3, sharex=True, sharey=True, constrained_layout=True, figsize=(6, 6)) fig.subplots_adjust(hspace=0.1) datasets = ['envi', 'enfr','enge'] types = ['enc', 'enc-dec' ,'dec'] Datasets = ['En-Vi', 'En-Fr','En-Ge']   def draw_map(ax,xlabels, ylabels, tt, attns, index):   #画热力图     im = ax.imshow(attns,interpolation='none',  cmap='Blues', vmin=0, vmax=1)     ax.set_title(tt, fontsize=10) style='italic' )     return im xlabels = '0 1 2 3 4 5'.split() ylabels = '5 4 3 2 1 0'.split()   for i, data in enumerate(datasets):     datafile = '{}.csv'.format(data) #读取数据     data = pd.read_csv(datafile, delimiter='\t', header=None)     for j, tt in enumerate(types):         A = data.values[:,j*6:(j+1)*6] #取出所需热力图的数据         ax = axs[i, j]         im = draw_map(ax, xlabels,ylabels, '%s (%s)'%(Datasets[i],tt), A, j)                     plt.xticks(range(len(xlabels)),xlabels)    #设置横坐标label plt.yticks(range(len(ylabels)),ylabels)    #设置纵坐标label   cb_ax = fig.add_axes([1.0, 0.1, 0.02, 0.8]) #设置colarbar位置 cbar = fig.colorbar(im, cax=cb_ax)     #共享colorbar plt.tight_layout() plt.show() fig.savefig('weights_visualization.pdf', bbox_inches='tight', dpi=500)

 

画图结果：