控制Seaborn热图中的单个线宽 [英] Control individual linewidths in seaborn heatmap

问题描述

是否可以加宽海洋热图中单独列和行的线宽?

Is it possible to widen the linewidth for sepcific columns and rows in a seaborn heatmap?

例如，此热图可以

import numpy as np; np.random.seed(0)
import seaborn as sns; sns.set()
uniform_data = np.random.rand(10, 12)
ax = sns.heatmap(uniform_data, linewidths=1.0)

被转变成这样的东西:

推荐答案

可能，但可能需要很多工作.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.

It's possible, but may be a lot of work. A possible solution might look like shown below. It involves plotting 6 different heatmaps and adjusting the spacings such that it looks okish. One then also needs to synchronize the colorscaling and manually set the colorbar.

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()

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