|
39 | 39 | }, |
40 | 40 | { |
41 | 41 | "cell_type": "code", |
42 | | - "execution_count": 425, |
| 42 | + "execution_count": 629, |
43 | 43 | "metadata": {}, |
44 | 44 | "outputs": [], |
45 | 45 | "source": [ |
|
50 | 50 | }, |
51 | 51 | { |
52 | 52 | "cell_type": "code", |
53 | | - "execution_count": 426, |
| 53 | + "execution_count": 630, |
54 | 54 | "metadata": {}, |
55 | 55 | "outputs": [], |
56 | 56 | "source": [ |
|
66 | 66 | "from mapie.metrics import regression_coverage_score, regression_mean_width_score, coverage_width_based\n", |
67 | 67 | "from mapie.subsample import BlockBootstrap\n", |
68 | 68 | "from mapie.time_series_regression import MapieTimeSeriesRegressor\n", |
69 | | - "from mapie.conformity_scores import ConformityScore\n", |
| 69 | + "from mapie.conformity_scores.regression import BaseRegressionScore\n", |
| 70 | + "from mapie.conformity_scores.regression import BaseConformityScore\n", |
70 | 71 | "\n", |
71 | 72 | "%reload_ext autoreload\n", |
72 | 73 | "%autoreload 2\n", |
|
83 | 84 | }, |
84 | 85 | { |
85 | 86 | "cell_type": "code", |
86 | | - "execution_count": 427, |
| 87 | + "execution_count": 631, |
87 | 88 | "metadata": {}, |
88 | 89 | "outputs": [], |
89 | 90 | "source": [ |
|
112 | 113 | }, |
113 | 114 | { |
114 | 115 | "cell_type": "code", |
115 | | - "execution_count": 428, |
| 116 | + "execution_count": 632, |
116 | 117 | "metadata": {}, |
117 | 118 | "outputs": [], |
118 | 119 | "source": [ |
|
132 | 133 | }, |
133 | 134 | { |
134 | 135 | "cell_type": "code", |
135 | | - "execution_count": 429, |
| 136 | + "execution_count": 633, |
136 | 137 | "metadata": {}, |
137 | 138 | "outputs": [ |
138 | 139 | { |
|
141 | 142 | "Text(0, 0.5, 'Hourly demand (GW)')" |
142 | 143 | ] |
143 | 144 | }, |
144 | | - "execution_count": 429, |
| 145 | + "execution_count": 633, |
145 | 146 | "metadata": {}, |
146 | 147 | "output_type": "execute_result" |
147 | 148 | }, |
|
173 | 174 | }, |
174 | 175 | { |
175 | 176 | "cell_type": "code", |
176 | | - "execution_count": 430, |
| 177 | + "execution_count": 634, |
177 | 178 | "metadata": {}, |
178 | 179 | "outputs": [], |
179 | 180 | "source": [ |
|
214 | 215 | }, |
215 | 216 | { |
216 | 217 | "cell_type": "code", |
217 | | - "execution_count": 431, |
| 218 | + "execution_count": 635, |
218 | 219 | "metadata": {}, |
219 | 220 | "outputs": [], |
220 | 221 | "source": [ |
|
241 | 242 | }, |
242 | 243 | { |
243 | 244 | "cell_type": "code", |
244 | | - "execution_count": 432, |
| 245 | + "execution_count": 636, |
245 | 246 | "metadata": {}, |
246 | 247 | "outputs": [ |
247 | 248 | { |
|
271 | 272 | }, |
272 | 273 | { |
273 | 274 | "cell_type": "code", |
274 | | - "execution_count": 433, |
| 275 | + "execution_count": 637, |
275 | 276 | "metadata": {}, |
276 | 277 | "outputs": [ |
277 | 278 | { |
|
310 | 311 | }, |
311 | 312 | { |
312 | 313 | "cell_type": "code", |
313 | | - "execution_count": 434, |
| 314 | + "execution_count": 638, |
314 | 315 | "metadata": {}, |
315 | 316 | "outputs": [ |
316 | 317 | { |
|
357 | 358 | }, |
358 | 359 | { |
359 | 360 | "cell_type": "code", |
360 | | - "execution_count": 435, |
| 361 | + "execution_count": 639, |
361 | 362 | "metadata": {}, |
362 | 363 | "outputs": [ |
363 | 364 | { |
|
411 | 412 | }, |
412 | 413 | { |
413 | 414 | "cell_type": "code", |
414 | | - "execution_count": 436, |
| 415 | + "execution_count": 640, |
415 | 416 | "metadata": {}, |
416 | 417 | "outputs": [ |
417 | 418 | { |
|
436 | 437 | }, |
437 | 438 | { |
438 | 439 | "cell_type": "code", |
439 | | - "execution_count": 437, |
| 440 | + "execution_count": 641, |
440 | 441 | "metadata": {}, |
441 | 442 | "outputs": [], |
442 | 443 | "source": [ |
|
448 | 449 | }, |
449 | 450 | { |
450 | 451 | "cell_type": "code", |
451 | | - "execution_count": 438, |
| 452 | + "execution_count": 642, |
452 | 453 | "metadata": {}, |
453 | 454 | "outputs": [], |
454 | 455 | "source": [ |
|
460 | 461 | }, |
461 | 462 | { |
462 | 463 | "cell_type": "code", |
463 | | - "execution_count": 439, |
| 464 | + "execution_count": 643, |
464 | 465 | "metadata": {}, |
465 | 466 | "outputs": [], |
466 | 467 | "source": [ |
|
495 | 496 | }, |
496 | 497 | { |
497 | 498 | "cell_type": "code", |
498 | | - "execution_count": 440, |
| 499 | + "execution_count": 644, |
499 | 500 | "metadata": {}, |
500 | 501 | "outputs": [ |
501 | 502 | { |
|
515 | 516 | }, |
516 | 517 | { |
517 | 518 | "cell_type": "code", |
518 | | - "execution_count": 441, |
| 519 | + "execution_count": 645, |
519 | 520 | "metadata": {}, |
520 | 521 | "outputs": [ |
521 | 522 | { |
|
559 | 560 | }, |
560 | 561 | { |
561 | 562 | "cell_type": "code", |
562 | | - "execution_count": 442, |
| 563 | + "execution_count": 646, |
563 | 564 | "metadata": {}, |
564 | 565 | "outputs": [], |
565 | 566 | "source": [ |
|
569 | 570 | }, |
570 | 571 | { |
571 | 572 | "cell_type": "code", |
572 | | - "execution_count": 443, |
| 573 | + "execution_count": 647, |
573 | 574 | "metadata": {}, |
574 | 575 | "outputs": [], |
575 | 576 | "source": [ |
|
589 | 590 | }, |
590 | 591 | { |
591 | 592 | "cell_type": "code", |
592 | | - "execution_count": 444, |
| 593 | + "execution_count": 648, |
593 | 594 | "metadata": {}, |
594 | 595 | "outputs": [ |
595 | 596 | { |
596 | 597 | "data": { |
597 | 598 | "text/plain": [ |
598 | | - "[<matplotlib.lines.Line2D at 0x184c64760>]" |
| 599 | + "[<matplotlib.lines.Line2D at 0x186d0b730>]" |
599 | 600 | ] |
600 | 601 | }, |
601 | | - "execution_count": 444, |
| 602 | + "execution_count": 648, |
602 | 603 | "metadata": {}, |
603 | 604 | "output_type": "execute_result" |
604 | 605 | }, |
|
630 | 631 | }, |
631 | 632 | { |
632 | 633 | "cell_type": "code", |
633 | | - "execution_count": 445, |
| 634 | + "execution_count": 649, |
634 | 635 | "metadata": {}, |
635 | 636 | "outputs": [ |
636 | 637 | { |
|
660 | 661 | }, |
661 | 662 | { |
662 | 663 | "cell_type": "code", |
663 | | - "execution_count": 446, |
| 664 | + "execution_count": 650, |
664 | 665 | "metadata": {}, |
665 | 666 | "outputs": [ |
666 | 667 | { |
|
699 | 700 | }, |
700 | 701 | { |
701 | 702 | "cell_type": "code", |
702 | | - "execution_count": 447, |
| 703 | + "execution_count": 651, |
703 | 704 | "metadata": {}, |
704 | 705 | "outputs": [], |
705 | 706 | "source": [ |
706 | 707 | "def compute_quantiles(conformity_scores, alpha_np):\n", |
707 | 708 | "\n", |
708 | | - " beta_np = ConformityScore._beta_optimize(\n", |
| 709 | + " beta_np = BaseRegressionScore._beta_optimize(\n", |
709 | 710 | " alpha_np,\n", |
710 | 711 | " conformity_scores.reshape(1, -1),\n", |
711 | 712 | " conformity_scores.reshape(1, -1),\n", |
712 | 713 | " )\n", |
713 | 714 | " alpha_low, alpha_up = beta_np, 1 - alpha_np + beta_np\n", |
714 | 715 | "\n", |
715 | | - " lower_quantiles = ConformityScore.get_quantile(\n", |
| 716 | + " lower_quantiles = BaseConformityScore.get_quantile(\n", |
716 | 717 | " conformity_scores[..., np.newaxis],\n", |
717 | 718 | " alpha_low, axis=0, reversed=True,\n", |
718 | 719 | " unbounded=False\n", |
719 | 720 | " )\n", |
720 | 721 | "\n", |
721 | | - " higher_quantiles = ConformityScore.get_quantile(\n", |
| 722 | + " higher_quantiles = BaseConformityScore.get_quantile(\n", |
722 | 723 | " conformity_scores[..., np.newaxis],\n", |
723 | 724 | " alpha_up, axis=0,\n", |
724 | 725 | " unbounded=False\n", |
|
729 | 730 | }, |
730 | 731 | { |
731 | 732 | "cell_type": "code", |
732 | | - "execution_count": 448, |
| 733 | + "execution_count": 652, |
733 | 734 | "metadata": {}, |
734 | 735 | "outputs": [ |
735 | 736 | { |
|
786 | 787 | }, |
787 | 788 | { |
788 | 789 | "cell_type": "code", |
789 | | - "execution_count": 449, |
| 790 | + "execution_count": 653, |
790 | 791 | "metadata": {}, |
791 | 792 | "outputs": [ |
792 | 793 | { |
|
864 | 865 | }, |
865 | 866 | { |
866 | 867 | "cell_type": "code", |
867 | | - "execution_count": 458, |
| 868 | + "execution_count": 654, |
868 | 869 | "metadata": {}, |
869 | 870 | "outputs": [], |
870 | 871 | "source": [ |
|
876 | 877 | }, |
877 | 878 | { |
878 | 879 | "cell_type": "code", |
879 | | - "execution_count": 459, |
| 880 | + "execution_count": 655, |
880 | 881 | "metadata": {}, |
881 | 882 | "outputs": [], |
882 | 883 | "source": [ |
|
890 | 891 | }, |
891 | 892 | { |
892 | 893 | "cell_type": "code", |
893 | | - "execution_count": 460, |
| 894 | + "execution_count": 656, |
894 | 895 | "metadata": {}, |
895 | 896 | "outputs": [ |
896 | 897 | { |
|
910 | 911 | }, |
911 | 912 | { |
912 | 913 | "cell_type": "code", |
913 | | - "execution_count": 461, |
| 914 | + "execution_count": 657, |
914 | 915 | "metadata": {}, |
915 | 916 | "outputs": [ |
916 | 917 | { |
|
930 | 931 | }, |
931 | 932 | { |
932 | 933 | "cell_type": "code", |
933 | | - "execution_count": 462, |
| 934 | + "execution_count": 658, |
934 | 935 | "metadata": {}, |
935 | 936 | "outputs": [], |
936 | 937 | "source": [ |
|
965 | 966 | }, |
966 | 967 | { |
967 | 968 | "cell_type": "code", |
968 | | - "execution_count": 463, |
| 969 | + "execution_count": 659, |
969 | 970 | "metadata": {}, |
970 | 971 | "outputs": [ |
971 | 972 | { |
972 | 973 | "data": { |
973 | 974 | "text/plain": [ |
974 | | - "[<matplotlib.lines.Line2D at 0x1854c75e0>]" |
| 975 | + "[<matplotlib.lines.Line2D at 0x18672cd30>]" |
975 | 976 | ] |
976 | 977 | }, |
977 | | - "execution_count": 463, |
| 978 | + "execution_count": 659, |
978 | 979 | "metadata": {}, |
979 | 980 | "output_type": "execute_result" |
980 | 981 | }, |
|
1012 | 1013 | }, |
1013 | 1014 | { |
1014 | 1015 | "cell_type": "code", |
1015 | | - "execution_count": 464, |
| 1016 | + "execution_count": 660, |
1016 | 1017 | "metadata": {}, |
1017 | 1018 | "outputs": [ |
1018 | 1019 | { |
1019 | 1020 | "data": { |
1020 | 1021 | "text/plain": [ |
1021 | | - "<matplotlib.legend.Legend at 0x18551cdf0>" |
| 1022 | + "<matplotlib.legend.Legend at 0x186665900>" |
1022 | 1023 | ] |
1023 | 1024 | }, |
1024 | | - "execution_count": 464, |
| 1025 | + "execution_count": 660, |
1025 | 1026 | "metadata": {}, |
1026 | 1027 | "output_type": "execute_result" |
1027 | 1028 | }, |
|
1054 | 1055 | }, |
1055 | 1056 | { |
1056 | 1057 | "cell_type": "code", |
1057 | | - "execution_count": 465, |
| 1058 | + "execution_count": 661, |
1058 | 1059 | "metadata": {}, |
1059 | 1060 | "outputs": [ |
1060 | 1061 | { |
1061 | 1062 | "data": { |
1062 | 1063 | "text/plain": [ |
1063 | | - "<matplotlib.legend.Legend at 0x185621690>" |
| 1064 | + "<matplotlib.legend.Legend at 0x1854386a0>" |
1064 | 1065 | ] |
1065 | 1066 | }, |
1066 | | - "execution_count": 465, |
| 1067 | + "execution_count": 661, |
1067 | 1068 | "metadata": {}, |
1068 | 1069 | "output_type": "execute_result" |
1069 | 1070 | }, |
|
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