(preds: dict, bins, TOA=False, surface=False,
title="", show=True, figsize=(16, 12), axes=None,
label="", **kwargs)
| 363 | |
| 364 | |
| 365 | def prediction_bars(preds: dict, bins, TOA=False, surface=False, |
| 366 | title="", show=True, figsize=(16, 12), axes=None, |
| 367 | label="", **kwargs): |
| 368 | n_vars = len(preds.keys()) |
| 369 | n_cols = 3 if TOA and surface else 2 if (TOA or surface) else 1 |
| 370 | |
| 371 | surface_ax = 1 |
| 372 | TOA_ax = 2 if surface else 1 |
| 373 | |
| 374 | if axes is None: |
| 375 | fig, axs = plt.subplots(n_vars, n_cols, figsize=figsize) |
| 376 | fig.suptitle("Prediction magnitudes" if title == "" else title) |
| 377 | axs[0, 0].set_title('Mean') |
| 378 | |
| 379 | if surface: |
| 380 | axs[0, surface_ax].set_title('Surface') |
| 381 | if TOA: |
| 382 | axs[0, TOA_ax].set_title('TOA') |
| 383 | else: |
| 384 | axs = axes |
| 385 | |
| 386 | for i, ((var_name, var_preds), ax_row) in enumerate(zip(preds.items(), axs)): |
| 387 | |
| 388 | if False: # i == 1: |
| 389 | kwargs['tick_label'] = ['{} - {}'.format(bins[i], bins[i + 1]) for i, j in enumerate(hist)] |
| 390 | |
| 391 | hist, bin_edges = np.histogram(np.mean(var_preds, axis=1), bins) |
| 392 | ax_row[0].bar(range(len(hist)), hist, width=1, align='center', label=label, **kwargs) |
| 393 | ax_row[0].set_ylabel(f"{var_name.upper()}", fontsize=20) |
| 394 | if surface: |
| 395 | hist, bin_edges = np.histogram(var_preds[:, -1], bins) |
| 396 | ax_row[surface_ax].bar(range(len(hist)), hist, width=1, align='center', label=label, **kwargs) |
| 397 | if TOA: |
| 398 | hist, bin_edges = np.histogram(var_preds[:, 0], bins) |
| 399 | ax_row[TOA_ax].bar(range(len(hist)), hist, width=1, align='center', label=label, **kwargs) |
| 400 | |
| 401 | axs[0, 0].legend() |
| 402 | if show: |
| 403 | plt.show() |
| 404 | |
| 405 | return axs |
nothing calls this directly
no outgoing calls
no test coverage detected