heatmap_w_pca.py

import seaborn as sns
sns.set()
sns.despine(left=True)

fig, axes = plt.subplots(2, 2, figsize=(15, 10), gridspec_kw=dict(hspace=.4, wspace=.3))
title_settings={'fontsize':16}
subtitles=['Inversed samples with {} components']*3

# Plot Heatmap 1
ax = sns.heatmap(digits.data, cbar=False, ax=axes[0, 0])
ax.set_title('Original samples', **title_settings)

# Plot Heatmap 2, 3, and 4
plot_ind=[[0,1],[1,0],[1,1]]
n_components=[2,20,40]
for nc, title, i in zip(n_components, subtitles, plot_ind):
    pca = PCA(n_components=nc)
    PC = pca.fit_transform(digits.data)
    inversed = pca.inverse_transform(PC)
    ax = sns.heatmap(inversed, cbar=False, ax=axes[i[0],i[1]])
    ax.set_title(title.format(nc), **title_settings)