(item_idx)
| 207 | |
| 208 | |
| 209 | def make_plot(item_idx): |
| 210 | title, X = distributions[item_idx] |
| 211 | ax_zoom_out, ax_zoom_in, ax_colorbar = create_axes(title) |
| 212 | axarr = (ax_zoom_out, ax_zoom_in) |
| 213 | plot_distribution( |
| 214 | axarr[0], |
| 215 | X, |
| 216 | y, |
| 217 | hist_nbins=200, |
| 218 | x0_label=feature_mapping[features[0]], |
| 219 | x1_label=feature_mapping[features[1]], |
| 220 | title="Full data", |
| 221 | ) |
| 222 | |
| 223 | # zoom-in |
| 224 | zoom_in_percentile_range = (0, 99) |
| 225 | cutoffs_X0 = np.percentile(X[:, 0], zoom_in_percentile_range) |
| 226 | cutoffs_X1 = np.percentile(X[:, 1], zoom_in_percentile_range) |
| 227 | |
| 228 | non_outliers_mask = np.all(X > [cutoffs_X0[0], cutoffs_X1[0]], axis=1) & np.all( |
| 229 | X < [cutoffs_X0[1], cutoffs_X1[1]], axis=1 |
| 230 | ) |
| 231 | plot_distribution( |
| 232 | axarr[1], |
| 233 | X[non_outliers_mask], |
| 234 | y[non_outliers_mask], |
| 235 | hist_nbins=50, |
| 236 | x0_label=feature_mapping[features[0]], |
| 237 | x1_label=feature_mapping[features[1]], |
| 238 | title="Zoom-in", |
| 239 | ) |
| 240 | |
| 241 | norm = mpl.colors.Normalize(y_full.min(), y_full.max()) |
| 242 | mpl.colorbar.ColorbarBase( |
| 243 | ax_colorbar, |
| 244 | cmap=cmap, |
| 245 | norm=norm, |
| 246 | orientation="vertical", |
| 247 | label="Color mapping for values of y", |
| 248 | ) |
| 249 | |
| 250 | |
| 251 | # %% |
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