有可能,但可能需要做很多工作.可能的解决方案可能如下所示.它涉及绘制6个不同的热图,并调整间距以使其看起来不错.然后,还需要同步颜色缩放并手动设置颜色栏.

import matplotlib

import matplotlib.pyplot as plt

import numpy as np; np.random.seed(0)

import seaborn as sns; sns.set()

data = np.random.rand(10, 12)

asp = data.shape[0]/float(data.shape[1])

figw = 8

figh = figw*asp

cmap = plt.cm.copper

norm = matplotlib.colors.Normalize(vmin= data.min(), vmax= data.max())

gridspec_kw = {"height_ratios":[9,1], "width_ratios" : [4,5,3]}

heatmapkws = dict(square=False, cbar=False, cmap = cmap, linewidths=1.0, vmin= data.min(), vmax= data.max() )

tickskw = dict(xticklabels=False, yticklabels=False)

left = 0.07; right=0.87

bottom = 0.1; top = 0.9

fig, axes = plt.subplots(ncols=3, nrows=2, figsize=(figw, figh), gridspec_kw=gridspec_kw)

plt.subplots_adjust(left=left, right=right,bottom=bottom, top=top, wspace=0.1, hspace=0.1*asp )

sns.heatmap(data[:9,0:4], ax=axes[0,0], xticklabels=False, yticklabels=True, **heatmapkws)

sns.heatmap(data[:9,4:9], ax=axes[0,1], xticklabels=False, yticklabels=False, **heatmapkws)

sns.heatmap(data[:9,9:12], ax=axes[0,2],xticklabels=False, yticklabels=False, **heatmapkws)

sns.heatmap(data[9:,:4], ax=axes[1,0], xticklabels=True, yticklabels=True, **heatmapkws)

sns.heatmap(data[9:,4:9], ax=axes[1,1], xticklabels=True, yticklabels=False, **heatmapkws)

sns.heatmap(data[9:,9:12], ax=axes[1,2], xticklabels=True, yticklabels=False,**heatmapkws)

axes[1,0].set_yticklabels([9])

axes[1,1].set_xticklabels([4,5,6,7,8])

axes[1,2].set_xticklabels([9,10,11])

cax = fig.add_axes([0.9,0.1,0.03,0.8])

sm = matplotlib.cm.ScalarMappable(cmap=cmap, norm=norm)

sm.set_array([])

fig.colorbar(sm, cax=cax)

plt.show()