Seaborn Confusion Matrix (heatmap) 2 color schemes (correct diagonal vs wrong rest)

Question

Background

In a confusion matrix, the diagonal represents the cases that the predicted label matches the correct label. So the diagonal is good, while all other cel

Answer 1

You could first plot the heatmap with colormap 'OrRd' and then overlay it with a heatmap with colormap 'Blues', with the upper and lower triangle values replaced with NaN's, see the following example:

def diagonal_heatmap(m):

    vmin = np.min(m)
    vmax = np.max(m)    
    
    sns.heatmap(cf_matrix, annot=True, cmap='OrRd', vmin=vmin, vmax=vmax)

    diag_nan = np.full_like(m, np.nan, dtype=float)
    np.fill_diagonal(diag_nan, np.diag(m))
    
    sns.heatmap(diag_nan, annot=True, cmap='Blues', vmin=vmin, vmax=vmax, cbar_kws={'ticks':[]}) 




cf_matrix = np.array([[50, 2, 38],
                      [7, 43, 32],
                      [9,  4, 76]])

diagonal_heatmap(cf_matrix)