Newer
Older
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
{
"cells": [
{
"attachments": {
"SVM_margin.png": {
"image/png": "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"
}
},
"cell_type": "markdown",
"id": "71a8e7d5",
"metadata": {},
"source": [
"# Support Vector Machines\n",
"\n",
"Support Vector Machines (SVM) are supervised classification and regression methods which are extremely robust to outliers.\n",
"\n",
"Let us start with a linear classification: in this case, we try to choose a line or hyper-plane that separates the data in two classes. The SVM model chooses this hyperplane based only on the data points close to the decision boundary and any point in time and not based on the entire dataset. Because the method focus only on points close to the decision boundary, any outlier away from the decision boundary does not have a strong influence on the choice of the boundary itself.\n",
"\n",
"Let us assume we have some data points $x_1, x_2, x_3, \\ldots, x_N$ and each of them belong to either class $-1$ or class $1$. Their true class is informed by the known target classes $t_1, t_2, t_3, \\ldots, t_N$. We want to choose the parameters $w$ and $b$ of a line (or hyperplane in more than 2 dimensions) such that we can easily estimate the unknown class of a new data point $x^\\prime$. For that, we define the decision boundary as:\n",
"\n",
"$y(x) = w^T x + b$,\n",
"\n",
"and we say that if $y(x^\\prime) > 0$, the data point belongs to class $1$, otherwise it belongs to class $-1$. The equation of the decision boundary is then $y(x) = 0$. See the figure below (from Wikipedia).\n",
"\n",
"\n"
]
},
{
"attachments": {
"linear_classifier.png": {
"image/png": "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"
}
},
"cell_type": "markdown",
"id": "6a764d92",
"metadata": {},
"source": [
"\n",
"Because of our choice of $t_i \\in \\{+1, -1\\}$, we can also write for all data points for which we know the true class: $t_i y(x_i) > 0$, since $y(x_i) < 0$ if $t_i = -1$ and $y (x_i) > 0$ if $t_i > 0$. The idea in SVMs is choose $w$ and $b$ to maximize the distance between the boundary points and the line. What is this distance between a given point and the decision boundary? This can be seen from simple geometrical calculations in the figure below (from Bishop (2006)). Given a known decision boundary, this distance for a point $x$ shall be $\\frac{|y(x)|}{|w|}$.\n",
"\n",
"\n",
"\n",
"As we want that $t_i y(x_i) > 0$ be true for all points close to the boundary, we can use $t_i y(x_i)$ instead of $|y(x_i)|$, using $t_i$ to guarantee that the numerator is always positive, instead of relying on the absolute value. To focus only on the points close to the decision boundary, we try to find $w$ and $b$ which *maximize* the *minimum distance* between the decision boundary and the data points. As the minimum distance is determined only by the points close to the boundary, this makes the method insensitive to what happens away from the decision boundary. Our objective is then to find $w$ and $b$ that satisfy:\n",
"\n",
"$\\text{argmax}_{w, b} \\left[\\frac{1}{|w|} \\min_{i} t_i \\left(w^T x + b\\right) \\right]$.\n",
"\n",
"This is a very hard problem, but notice that we only care about the distance between the points and the boundary, and if $w$ and $b$ are both multiplied by the same number, this distance does not change. We can therefore choose a normalisation so that $t_i (w^T x_i + b) = 1$ for the point closest to the boundary. This implies that $t_k (w^T x_k + b) \\geq 1$ for all points in the dataset. Since there is always one point closest, the condition is to maximize $\\frac{1}{|w|}$ (that is, the remaining factor) for that point, which is equivalent to minimize $|w|^2$ for the closest point while miximizing the condition above.\n",
"\n",
"This can be summarized in simpler form using the Lagrange multiplier formalism, which translates this complex constrained optimization into a simpler unconstrained optimization problem. In that formalism we need to minimize a cost function $\\mathcal{L}$, which introduces the Lagrange multipliers $a_i$:\n",
"\n",
"$\\mathcal{L}(w, b, a) = \\frac{1}{2} |w|^2 - \\sum_i a_i \\left[ t_i \\left(w^T x_i + b\\right) - 1\\right]$\n",
"\n",
"One can set the derivative of $\\mathcal{L}$ to zero with respect to $w$, $b$ and $a$ to obtain a simpler version of this optimization problem. Further details can be consulted in Bishop (2006) or in the Wikipedia description.\n",
"\n",
"It is interesting to note that by using the Kernel trick, one can choose the function $y(x) = w^T \\phi(x) + b$ and with an appropriate choise of $\\phi$, we can apply a linear classification after a non-linear transformation which allows this method to be expanded into non-linear classification. It can be shown following the procedure above that the final algorithm does not depend on $\\phi(x)$, but only on $k(x, x^\\prime) = \\phi(x)\\phi(x^\\prime)$, so one needs only to specify the kernel function $k$.\n",
"\n",
"Similar logic can be used for regression, on which only the *worse* prediction of the feature becomes relevant.\n",
"\n",
"Fortunately the details of the algorithm are not needed to implement this for classification. In the following example, we show how the algorithm can be easily used from the scikit-learn modules."
]
},
{
"cell_type": "markdown",
"id": "fce4d8e8",
"metadata": {},
"source": [
"We start by loading the necessary Python modules. If you have not yet installed them, run the following cell to install them with pip:"
]
},
{
"cell_type": "code",
Danilo Ferreira de Lima
committed
"execution_count": 1,
"id": "44ca341e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Requirement already satisfied: numpy in /home/daniloefl/miniconda3/envs/ml2/lib/python3.6/site-packages (1.19.2)\r\n",
"Requirement already satisfied: scikit-learn in /home/daniloefl/miniconda3/envs/ml2/lib/python3.6/site-packages (0.24.2)\r\n",
"Requirement already satisfied: pandas in /home/daniloefl/miniconda3/envs/ml2/lib/python3.6/site-packages (1.1.5)\r\n",
"Requirement already satisfied: matplotlib in /home/daniloefl/miniconda3/envs/ml2/lib/python3.6/site-packages (3.3.4)\r\n",
"Requirement already satisfied: scipy>=0.19.1 in /home/daniloefl/miniconda3/envs/ml2/lib/python3.6/site-packages (from scikit-learn) (1.5.2)\r\n",
"Requirement already satisfied: threadpoolctl>=2.0.0 in /home/daniloefl/miniconda3/envs/ml2/lib/python3.6/site-packages (from scikit-learn) (2.2.0)\r\n",
"Requirement already satisfied: joblib>=0.11 in /home/daniloefl/miniconda3/envs/ml2/lib/python3.6/site-packages (from scikit-learn) (1.0.1)\r\n",
"Requirement already satisfied: python-dateutil>=2.7.3 in /home/daniloefl/miniconda3/envs/ml2/lib/python3.6/site-packages (from pandas) (2.8.2)\r\n",
"Requirement already satisfied: pytz>=2017.2 in /home/daniloefl/miniconda3/envs/ml2/lib/python3.6/site-packages (from pandas) (2021.3)\r\n",
"Requirement already satisfied: cycler>=0.10 in /home/daniloefl/miniconda3/envs/ml2/lib/python3.6/site-packages (from matplotlib) (0.11.0)\r\n",
"Requirement already satisfied: pillow>=6.2.0 in /home/daniloefl/miniconda3/envs/ml2/lib/python3.6/site-packages (from matplotlib) (8.3.1)\r\n",
"Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.3 in /home/daniloefl/miniconda3/envs/ml2/lib/python3.6/site-packages (from matplotlib) (3.0.4)\r\n",
"Requirement already satisfied: kiwisolver>=1.0.1 in /home/daniloefl/miniconda3/envs/ml2/lib/python3.6/site-packages (from matplotlib) (1.3.1)\r\n",
"Requirement already satisfied: six>=1.5 in /home/daniloefl/miniconda3/envs/ml2/lib/python3.6/site-packages (from python-dateutil>=2.7.3->pandas) (1.16.0)\r\n"
]
}
],
"source": [
"!pip install numpy scikit-learn pandas matplotlib"
]
},
{
"cell_type": "code",
Danilo Ferreira de Lima
committed
"execution_count": 2,
"id": "300cf8d3",
"metadata": {},
"outputs": [],
"source": [
Danilo Ferreira de Lima
committed
"%matplotlib notebook\n",
"\n",
"import matplotlib.pyplot as plt\n",
"\n",
"import pandas as pd\n",
"import numpy as np\n",
"from sklearn import svm"
]
},
{
"cell_type": "markdown",
"id": "0ecd6a69",
"metadata": {},
"source": [
"Let's generate the fake data now to have something to cluster."
]
},
{
"cell_type": "code",
Danilo Ferreira de Lima
committed
"execution_count": 3,
"id": "4959a292",
"metadata": {},
"outputs": [],
"source": [
"def generate_data(N: int) ->np.ndarray:\n",
" assert N > 1\n",
" loc = [np.array([2.0, 2.0]), np.array([-1.0, 1.0])]\n",
" scale = [np.array([0.5, 0.5]), np.array([0.5, 0.2])]\n",
" data = np.concatenate([np.random.default_rng().laplace(loc=l, scale=s, size=(N, 2))\n",
" for l, s in zip(loc, scale)], axis=0)\n",
" source = np.concatenate([k*np.ones([N, 1]) for k in range(len(loc))], axis=0)\n",
" return np.concatenate([data, source], axis=1)\n"
]
},
{
"cell_type": "code",
Danilo Ferreira de Lima
committed
"execution_count": 4,
"id": "82929490",
"metadata": {},
"outputs": [],
"source": [
"data = generate_data(N=1000)\n",
"data = pd.DataFrame(data, columns=[\"x\", \"y\", \"source\"])"
]
},
{
"cell_type": "markdown",
"id": "d8295e8a",
"metadata": {},
"source": [
"Let's print out the dataset read first."
]
},
{
"cell_type": "code",
Danilo Ferreira de Lima
committed
"execution_count": 5,
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
"id": "024fb65a",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>x</th>\n",
" <th>y</th>\n",
" <th>source</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2.436622</td>\n",
" <td>1.957346</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <td>1.878620</td>\n",
" <td>2.124196</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2.007272</td>\n",
" <td>1.786319</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2.611975</td>\n",
" <td>2.631215</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>1.954943</td>\n",
" <td>0.788590</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1995</th>\n",
" <td>0.632186</td>\n",
" <td>1.040653</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1996</th>\n",
" <td>-1.535309</td>\n",
" <td>0.852659</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1997</th>\n",
" <td>-0.707959</td>\n",
" <td>0.742690</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1998</th>\n",
" <td>-0.505297</td>\n",
" <td>1.010079</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1999</th>\n",
" <td>-2.061489</td>\n",
" <td>0.947031</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>2000 rows × 3 columns</p>\n",
"</div>"
],
"text/plain": [
" x y source\n",
"0 2.436622 1.957346 0.0\n",
"1 1.878620 2.124196 0.0\n",
"2 2.007272 1.786319 0.0\n",
"3 2.611975 2.631215 0.0\n",
"4 1.954943 0.788590 0.0\n",
"1995 0.632186 1.040653 1.0\n",
"1996 -1.535309 0.852659 1.0\n",
"1997 -0.707959 0.742690 1.0\n",
"1998 -0.505297 1.010079 1.0\n",
"1999 -2.061489 0.947031 1.0\n",
"\n",
"[2000 rows x 3 columns]"
]
},
Danilo Ferreira de Lima
committed
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data"
]
},
{
"cell_type": "markdown",
"id": "1c178424",
"metadata": {},
"source": [
"We can plot this fairly easily using Matplotlib."
]
},
{
"cell_type": "code",
Danilo Ferreira de Lima
committed
"execution_count": 6,
"id": "e63b38c5",
"metadata": {},
"outputs": [
{
"data": {
Danilo Ferreira de Lima
committed
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
1001
1002
1003
1004
1005
1006
1007
1008
1009
1010
1011
1012
1013
1014
1015
1016
1017
1018
1019
1020
1021
1022
1023
1024
1025
1026
1027
1028
1029
1030
1031
1032
1033
1034
1035
1036
1037
1038
1039
1040
1041
1042
1043
1044
1045
1046
1047
1048
1049
1050
1051
1052
1053
1054
1055
1056
1057
1058
1059
1060
1061
1062
1063
1064
1065
1066
1067
1068
1069
1070
1071
1072
1073
1074
1075
1076
1077
1078
1079
1080
1081
1082
1083
1084
1085
1086
1087
1088
1089
1090
1091
1092
1093
1094
1095
1096
1097
1098
1099
1100
1101
1102
1103
1104
1105
1106
1107
1108
1109
1110
1111
1112
1113
1114
1115
1116
1117
1118
1119
1120
1121
1122
1123
1124
1125
1126
1127
1128
1129
1130
1131
1132
1133
1134
1135
1136
1137
1138
1139
1140
1141
1142
1143
1144
1145
1146
1147
1148
1149
1150
1151
1152
1153
1154
1155
1156
1157
1158
1159
1160
1161
1162
1163
1164
1165
1166
1167
1168
1169
1170
1171
1172
1173
1174
1175
1176
1177
1178
1179
1180
1181
1182
1183
1184
1185
1186
1187
1188
1189
1190
1191
1192
1193
1194
1195
1196
1197
1198
1199
1200
1201
1202
1203
1204
1205
1206
1207
1208
1209
1210
1211
1212
1213
1214
1215
1216
1217
1218
1219
1220
1221
1222
1223
1224
1225
1226
1227
1228
1229
1230
1231
1232
1233
1234
1235
1236
1237
1238
1239
1240
1241
1242
1243
1244
1245
1246
1247
1248
1249
1250
1251
1252
1253
1254
1255
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"/* global mpl */\n",
"window.mpl = {};\n",
"\n",
"mpl.get_websocket_type = function () {\n",
" if (typeof WebSocket !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof MozWebSocket !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert(\n",
" 'Your browser does not have WebSocket support. ' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.'\n",
" );\n",
" }\n",
"};\n",
"\n",
"mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = this.ws.binaryType !== undefined;\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById('mpl-warnings');\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent =\n",
" 'This browser does not support binary websocket messages. ' +\n",
" 'Performance may be slow.';\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = document.createElement('div');\n",
" this.root.setAttribute('style', 'display: inline-block');\n",
" this._root_extra_style(this.root);\n",
"\n",
" parent_element.appendChild(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message('supports_binary', { value: fig.supports_binary });\n",
" fig.send_message('send_image_mode', {});\n",
" if (fig.ratio !== 1) {\n",
" fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
" }\n",
" fig.send_message('refresh', {});\n",
" };\n",
"\n",
" this.imageObj.onload = function () {\n",
" if (fig.image_mode === 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function () {\n",
" fig.ws.close();\n",
" };\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"};\n",
"\n",
"mpl.figure.prototype._init_header = function () {\n",
" var titlebar = document.createElement('div');\n",
" titlebar.classList =\n",
" 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
" var titletext = document.createElement('div');\n",
" titletext.classList = 'ui-dialog-title';\n",
" titletext.setAttribute(\n",
" 'style',\n",
" 'width: 100%; text-align: center; padding: 3px;'\n",
" );\n",
" titlebar.appendChild(titletext);\n",
" this.root.appendChild(titlebar);\n",
" this.header = titletext;\n",
"};\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
"\n",
"mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
"\n",
"mpl.figure.prototype._init_canvas = function () {\n",
" var fig = this;\n",
"\n",
" var canvas_div = (this.canvas_div = document.createElement('div'));\n",
" canvas_div.setAttribute(\n",
" 'style',\n",
" 'border: 1px solid #ddd;' +\n",
" 'box-sizing: content-box;' +\n",
" 'clear: both;' +\n",
" 'min-height: 1px;' +\n",
" 'min-width: 1px;' +\n",
" 'outline: 0;' +\n",
" 'overflow: hidden;' +\n",
" 'position: relative;' +\n",
" 'resize: both;'\n",
" );\n",
"\n",
" function on_keyboard_event_closure(name) {\n",
" return function (event) {\n",
" return fig.key_event(event, name);\n",
" };\n",
" }\n",
"\n",
" canvas_div.addEventListener(\n",
" 'keydown',\n",
" on_keyboard_event_closure('key_press')\n",
" );\n",
" canvas_div.addEventListener(\n",
" 'keyup',\n",
" on_keyboard_event_closure('key_release')\n",
" );\n",
"\n",
" this._canvas_extra_style(canvas_div);\n",
" this.root.appendChild(canvas_div);\n",
"\n",
" var canvas = (this.canvas = document.createElement('canvas'));\n",
" canvas.classList.add('mpl-canvas');\n",
" canvas.setAttribute('style', 'box-sizing: content-box;');\n",
"\n",
" this.context = canvas.getContext('2d');\n",
"\n",
" var backingStore =\n",
" this.context.backingStorePixelRatio ||\n",
" this.context.webkitBackingStorePixelRatio ||\n",
" this.context.mozBackingStorePixelRatio ||\n",
" this.context.msBackingStorePixelRatio ||\n",
" this.context.oBackingStorePixelRatio ||\n",
" this.context.backingStorePixelRatio ||\n",
" 1;\n",
"\n",
" this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
" 'canvas'\n",
" ));\n",
" rubberband_canvas.setAttribute(\n",
" 'style',\n",
" 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
" );\n",
"\n",
" // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
" if (this.ResizeObserver === undefined) {\n",
" if (window.ResizeObserver !== undefined) {\n",
" this.ResizeObserver = window.ResizeObserver;\n",
" } else {\n",
" var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
" this.ResizeObserver = obs.ResizeObserver;\n",
" }\n",
" }\n",
"\n",
" this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
" var nentries = entries.length;\n",
" for (var i = 0; i < nentries; i++) {\n",
" var entry = entries[i];\n",
" var width, height;\n",
" if (entry.contentBoxSize) {\n",
" if (entry.contentBoxSize instanceof Array) {\n",
" // Chrome 84 implements new version of spec.\n",
" width = entry.contentBoxSize[0].inlineSize;\n",
" height = entry.contentBoxSize[0].blockSize;\n",
" } else {\n",
" // Firefox implements old version of spec.\n",
" width = entry.contentBoxSize.inlineSize;\n",
" height = entry.contentBoxSize.blockSize;\n",
" }\n",
" } else {\n",
" // Chrome <84 implements even older version of spec.\n",
" width = entry.contentRect.width;\n",
" height = entry.contentRect.height;\n",
" }\n",
"\n",
" // Keep the size of the canvas and rubber band canvas in sync with\n",
" // the canvas container.\n",
" if (entry.devicePixelContentBoxSize) {\n",
" // Chrome 84 implements new version of spec.\n",
" canvas.setAttribute(\n",
" 'width',\n",
" entry.devicePixelContentBoxSize[0].inlineSize\n",
" );\n",
" canvas.setAttribute(\n",
" 'height',\n",
" entry.devicePixelContentBoxSize[0].blockSize\n",
" );\n",
" } else {\n",
" canvas.setAttribute('width', width * fig.ratio);\n",
" canvas.setAttribute('height', height * fig.ratio);\n",
" }\n",
" canvas.setAttribute(\n",
" 'style',\n",
" 'width: ' + width + 'px; height: ' + height + 'px;'\n",
" );\n",
"\n",
" rubberband_canvas.setAttribute('width', width);\n",
" rubberband_canvas.setAttribute('height', height);\n",
"\n",
" // And update the size in Python. We ignore the initial 0/0 size\n",
" // that occurs as the element is placed into the DOM, which should\n",
" // otherwise not happen due to the minimum size styling.\n",
" if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
" fig.request_resize(width, height);\n",
" }\n",
" }\n",
" });\n",
" this.resizeObserverInstance.observe(canvas_div);\n",
"\n",
" function on_mouse_event_closure(name) {\n",
" return function (event) {\n",
" return fig.mouse_event(event, name);\n",
" };\n",
" }\n",
"\n",
" rubberband_canvas.addEventListener(\n",
" 'mousedown',\n",
" on_mouse_event_closure('button_press')\n",
" );\n",
" rubberband_canvas.addEventListener(\n",
" 'mouseup',\n",
" on_mouse_event_closure('button_release')\n",
" );\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband_canvas.addEventListener(\n",
" 'mousemove',\n",
" on_mouse_event_closure('motion_notify')\n",
" );\n",
"\n",
" rubberband_canvas.addEventListener(\n",
" 'mouseenter',\n",
" on_mouse_event_closure('figure_enter')\n",
" );\n",
" rubberband_canvas.addEventListener(\n",
" 'mouseleave',\n",
" on_mouse_event_closure('figure_leave')\n",
" );\n",
"\n",
" canvas_div.addEventListener('wheel', function (event) {\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" on_mouse_event_closure('scroll')(event);\n",
" });\n",
"\n",
" canvas_div.appendChild(canvas);\n",
" canvas_div.appendChild(rubberband_canvas);\n",
"\n",
" this.rubberband_context = rubberband_canvas.getContext('2d');\n",
" this.rubberband_context.strokeStyle = '#000000';\n",
"\n",
" this._resize_canvas = function (width, height, forward) {\n",
" if (forward) {\n",
" canvas_div.style.width = width + 'px';\n",
" canvas_div.style.height = height + 'px';\n",
" }\n",
" };\n",
"\n",
" // Disable right mouse context menu.\n",
" this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
" event.preventDefault();\n",
" return false;\n",
" });\n",
"\n",
" function set_focus() {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"};\n",
"\n",
"mpl.figure.prototype._init_toolbar = function () {\n",
" var fig = this;\n",
"\n",
" var toolbar = document.createElement('div');\n",
" toolbar.classList = 'mpl-toolbar';\n",
" this.root.appendChild(toolbar);\n",
"\n",
" function on_click_closure(name) {\n",
" return function (_event) {\n",
" return fig.toolbar_button_onclick(name);\n",
" };\n",
" }\n",
"\n",
" function on_mouseover_closure(tooltip) {\n",
" return function (event) {\n",
" if (!event.currentTarget.disabled) {\n",
" return fig.toolbar_button_onmouseover(tooltip);\n",
" }\n",
" };\n",
" }\n",
"\n",
" fig.buttons = {};\n",
" var buttonGroup = document.createElement('div');\n",
" buttonGroup.classList = 'mpl-button-group';\n",
" for (var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" /* Instead of a spacer, we start a new button group. */\n",
" if (buttonGroup.hasChildNodes()) {\n",
" toolbar.appendChild(buttonGroup);\n",
" }\n",
" buttonGroup = document.createElement('div');\n",
" buttonGroup.classList = 'mpl-button-group';\n",
" continue;\n",
" }\n",
"\n",
" var button = (fig.buttons[name] = document.createElement('button'));\n",
" button.classList = 'mpl-widget';\n",
" button.setAttribute('role', 'button');\n",
" button.setAttribute('aria-disabled', 'false');\n",
" button.addEventListener('click', on_click_closure(method_name));\n",
" button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
"\n",
" var icon_img = document.createElement('img');\n",
" icon_img.src = '_images/' + image + '.png';\n",
" icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
" icon_img.alt = tooltip;\n",
" button.appendChild(icon_img);\n",
"\n",
" buttonGroup.appendChild(button);\n",
" }\n",
"\n",
" if (buttonGroup.hasChildNodes()) {\n",
" toolbar.appendChild(buttonGroup);\n",
" }\n",
"\n",
" var fmt_picker = document.createElement('select');\n",
" fmt_picker.classList = 'mpl-widget';\n",
" toolbar.appendChild(fmt_picker);\n",
" this.format_dropdown = fmt_picker;\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = document.createElement('option');\n",
" option.selected = fmt === mpl.default_extension;\n",
" option.innerHTML = fmt;\n",
" fmt_picker.appendChild(option);\n",
" }\n",
"\n",
" var status_bar = document.createElement('span');\n",
" status_bar.classList = 'mpl-message';\n",
" toolbar.appendChild(status_bar);\n",
" this.message = status_bar;\n",
"};\n",
"\n",
"mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
"};\n",
"\n",
"mpl.figure.prototype.send_message = function (type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"};\n",
"\n",
"mpl.figure.prototype.send_draw_message = function () {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1], msg['forward']);\n",
" fig.send_message('refresh', {});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
" var x0 = msg['x0'] / fig.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
" var x1 = msg['x1'] / fig.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0,\n",
" 0,\n",
" fig.canvas.width / fig.ratio,\n",
" fig.canvas.height / fig.ratio\n",
" );\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch (cursor) {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_message = function (fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
" for (var key in msg) {\n",
" if (!(key in fig.buttons)) {\n",
" continue;\n",
" }\n",
" fig.buttons[key].disabled = !msg[key];\n",
" fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
" if (msg['mode'] === 'PAN') {\n",
" fig.buttons['Pan'].classList.add('active');\n",
" fig.buttons['Zoom'].classList.remove('active');\n",
" } else if (msg['mode'] === 'ZOOM') {\n",
" fig.buttons['Pan'].classList.remove('active');\n",
" fig.buttons['Zoom'].classList.add('active');\n",
" } else {\n",
" fig.buttons['Pan'].classList.remove('active');\n",
" fig.buttons['Zoom'].classList.remove('active');\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function () {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message('ack', {});\n",
"};\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function (fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = 'image/png';\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src\n",
" );\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data\n",
" );\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" } else if (\n",
" typeof evt.data === 'string' &&\n",
" evt.data.slice(0, 21) === 'data:image/png;base64'\n",
" ) {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig['handle_' + msg_type];\n",
" } catch (e) {\n",
" console.log(\n",
" \"No handler for the '\" + msg_type + \"' message type: \",\n",
" msg\n",
" );\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\n",
" \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
" e,\n",
" e.stack,\n",
" msg\n",
" );\n",
" }\n",
" }\n",
" };\n",
"};\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function (e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e) {\n",
" e = window.event;\n",
" }\n",
" if (e.target) {\n",
" targ = e.target;\n",
" } else if (e.srcElement) {\n",
" targ = e.srcElement;\n",
" }\n",
" if (targ.nodeType === 3) {\n",
" // defeat Safari bug\n",
" targ = targ.parentNode;\n",
" }\n",
"\n",
" // pageX,Y are the mouse positions relative to the document\n",
" var boundingRect = targ.getBoundingClientRect();\n",
" var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
" var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
"\n",
" return { x: x, y: y };\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys(original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object') {\n",
" obj[key] = original[key];\n",
" }\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function (event, name) {\n",
" var canvas_pos = mpl.findpos(event);\n",
"\n",
" if (name === 'button_press') {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * this.ratio;\n",
" var y = canvas_pos.y * this.ratio;\n",
"\n",
" this.send_message(name, {\n",
" x: x,\n",
" y: y,\n",
" button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event),\n",
" });\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"};\n",
"\n",
"mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"};\n",
"\n",
"mpl.figure.prototype.key_event = function (event, name) {\n",
" // Prevent repeat events\n",
" if (name === 'key_press') {\n",
" if (event.which === this._key) {\n",
" return;\n",
" } else {\n",
" this._key = event.which;\n",
" }\n",
" }\n",
" if (name === 'key_release') {\n",
" this._key = null;\n",
" }\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which !== 17) {\n",
" value += 'ctrl+';\n",
" }\n",
" if (event.altKey && event.which !== 18) {\n",
" value += 'alt+';\n",
" }\n",
" if (event.shiftKey && event.which !== 16) {\n",
" value += 'shift+';\n",
" }\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
" return false;\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
" if (name === 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message('toolbar_button', { name: name });\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"\n",
"///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
"// prettier-ignore\n",
"var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";/* global mpl */\n",
"\n",
"var comm_websocket_adapter = function (comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function () {\n",
" comm.close();\n",
" };\n",
" ws.send = function (m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function (msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data']);\n",
" });\n",
" return ws;\n",
"};\n",
"\n",
"mpl.mpl_figure_comm = function (comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = document.getElementById(id);\n",
" var ws_proxy = comm_websocket_adapter(comm);\n",
"\n",
" function ondownload(figure, _format) {\n",
" window.open(figure.canvas.toDataURL());\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element;\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error('Failed to find cell for figure', id, fig);\n",
" return;\n",
" }\n",
" fig.cell_info[0].output_area.element.on(\n",
" 'cleared',\n",
" { fig: fig },\n",
" fig._remove_fig_handler\n",
" );\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function (fig, msg) {\n",
" var width = fig.canvas.width / fig.ratio;\n",
" fig.cell_info[0].output_area.element.off(\n",
" 'cleared',\n",
" fig._remove_fig_handler\n",
" );\n",
" fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable();\n",
" fig.parent_element.innerHTML =\n",
" '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
" fig.close_ws(fig, msg);\n",
"};\n",
"\n",
"mpl.figure.prototype.close_ws = function (fig, msg) {\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"};\n",
"\n",
"mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width / this.ratio;\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] =\n",
" '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"};\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function () {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message('ack', {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () {\n",
" fig.push_to_output();\n",
" }, 1000);\n",
"};\n",
"\n",
"mpl.figure.prototype._init_toolbar = function () {\n",
" var fig = this;\n",
"\n",
" var toolbar = document.createElement('div');\n",
" toolbar.classList = 'btn-toolbar';\n",
" this.root.appendChild(toolbar);\n",
"\n",
" function on_click_closure(name) {\n",
" return function (_event) {\n",
" return fig.toolbar_button_onclick(name);\n",
" };\n",
" }\n",
"\n",
" function on_mouseover_closure(tooltip) {\n",
" return function (event) {\n",
" if (!event.currentTarget.disabled) {\n",
" return fig.toolbar_button_onmouseover(tooltip);\n",
" }\n",
" };\n",
" }\n",
"\n",
" fig.buttons = {};\n",
" var buttonGroup = document.createElement('div');\n",
" buttonGroup.classList = 'btn-group';\n",
" var button;\n",
" for (var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" /* Instead of a spacer, we start a new button group. */\n",
" if (buttonGroup.hasChildNodes()) {\n",
" toolbar.appendChild(buttonGroup);\n",
" }\n",
" buttonGroup = document.createElement('div');\n",
" buttonGroup.classList = 'btn-group';\n",
" continue;\n",
" }\n",
"\n",
" button = fig.buttons[name] = document.createElement('button');\n",
" button.classList = 'btn btn-default';\n",
" button.href = '#';\n",
" button.title = name;\n",
" button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
" button.addEventListener('click', on_click_closure(method_name));\n",
" button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
" buttonGroup.appendChild(button);\n",
" }\n",
"\n",
" if (buttonGroup.hasChildNodes()) {\n",
" toolbar.appendChild(buttonGroup);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = document.createElement('span');\n",
" status_bar.classList = 'mpl-message pull-right';\n",
" toolbar.appendChild(status_bar);\n",
" this.message = status_bar;\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = document.createElement('div');\n",
" buttongrp.classList = 'btn-group inline pull-right';\n",
" button = document.createElement('button');\n",
" button.classList = 'btn btn-mini btn-primary';\n",
" button.href = '#';\n",
" button.title = 'Stop Interaction';\n",
" button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
" button.addEventListener('click', function (_evt) {\n",
" fig.handle_close(fig, {});\n",
" });\n",
" button.addEventListener(\n",
" 'mouseover',\n",
" on_mouseover_closure('Stop Interaction')\n",
" );\n",
" buttongrp.appendChild(button);\n",
" var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
" titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
"};\n",
"\n",
"mpl.figure.prototype._remove_fig_handler = function (event) {\n",
" var fig = event.data.fig;\n",
" if (event.target !== this) {\n",
" // Ignore bubbled events from children.\n",
" return;\n",
" }\n",
" fig.close_ws(fig, {});\n",
"};\n",
"\n",
"mpl.figure.prototype._root_extra_style = function (el) {\n",
" el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
"};\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function (el) {\n",
" // this is important to make the div 'focusable\n",
" el.setAttribute('tabindex', 0);\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" } else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager) {\n",
" manager = IPython.keyboard_manager;\n",
" }\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which === 13) {\n",
" this.canvas_div.blur();\n",
" // select the cell after this one\n",
" var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
" IPython.notebook.select(index + 1);\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
" fig.ondownload(fig, null);\n",
"};\n",
"\n",
"mpl.find_output_cell = function (html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i = 0; i < ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code') {\n",
" for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] === html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"};\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel !== null) {\n",
" IPython.notebook.kernel.comm_manager.register_target(\n",
" 'matplotlib',\n",
" mpl.mpl_figure_comm\n",
" );\n",
"}\n"
],
Danilo Ferreira de Lima
committed
"<IPython.core.display.Javascript object>"
Danilo Ferreira de Lima
committed
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"<img src=\"data:image/png;base64,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\" width=\"800\">"
Danilo Ferreira de Lima
committed
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
Danilo Ferreira de Lima
committed
"metadata": {},
1273
1274
1275
1276
1277
1278
1279
1280
1281
1282
1283
1284
1285
1286
1287
1288
1289
1290
1291
1292
1293
1294
"output_type": "display_data"
}
],
"source": [
"fig, ax = plt.subplots(figsize=(8, 8))\n",
"data.plot.scatter(x=\"x\", y=\"y\", c=\"source\", colormap='viridis', ax=ax)\n",
"ax.set(xlabel=\"x\", ylabel=r\"y\", title=\"\")\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"id": "a376636d",
"metadata": {},
"source": [
"The usage of the scikit-learn interface is very standard, and one does not even need to know the details of how the SVM algorithm operates. It is however important to understand the basics, to understand how it operates.\n",
"\n",
"The kernel choice is effectively changing the choice for $\\phi(x)$ in the explanation above."
]
},
{
"cell_type": "code",
Danilo Ferreira de Lima
committed
"execution_count": 7,
"id": "0837b3ff",
"metadata": {},
"outputs": [],
"source": [
"clf = svm.SVC(kernel=\"linear\")"
]
},
{
"cell_type": "code",
Danilo Ferreira de Lima
committed
"execution_count": 8,
"id": "8798f857",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"SVC(kernel='linear')"
]
},
Danilo Ferreira de Lima
committed
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"clf.fit(data.loc[:, [\"x\", \"y\"]], data.loc[:, \"source\"])"
]
},
{
"cell_type": "markdown",
"id": "e928f498",
"metadata": {},
"source": [
"Only a few vectors are needed to choose the decision boundary, since only they contribute to the minimum distance shown before. Those vectors are called the support vectors and give the name to the method. They can be accessed using the following attribute:"
]
},
{
"cell_type": "code",
Danilo Ferreira de Lima
committed
"execution_count": 9,
"id": "fb5796e5",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
1341
1342
1343
1344
1345
1346
1347
1348
1349
1350
1351
1352
1353
1354
1355
1356
1357
1358
1359
1360
1361
1362
1363
1364
1365
1366
1367
1368
1369
1370
1371
1372
1373
1374
1375
1376
1377
1378
1379
1380
1381
1382
1383
1384
1385
1386
1387
1388
1389
1390
1391
1392
1393
1394
1395
1396
1397
1398
1399
1400
1401
1402
1403
1404
1405
1406
1407
1408
1409
1410
1411
1412
1413
1414
1415
1416
1417
1418
1419
1420
1421
1422
1423
1424
1425
1426
1427
1428
1429
1430
1431
1432
1433
1434
1435
1436
1437
1438
1439
1440
"array([[ 0.89928785, 1.61606784],\n",
" [ 1.84037763, -2.32486989],\n",
" [-0.85012761, 2.07658104],\n",
" [ 1.61122172, -0.01876249],\n",
" [ 1.07403321, 0.76558405],\n",
" [ 0.43013287, 2.43109401],\n",
" [ 0.71153203, 1.50870089],\n",
" [ 0.06577072, 1.77949588],\n",
" [ 0.91708157, -0.55767733],\n",
" [ 0.47773916, 1.98320156],\n",
" [ 0.59810349, 1.73526173],\n",
" [ 1.87216163, -0.44833316],\n",
" [ 0.64268313, 1.6935894 ],\n",
" [ 0.87829617, 0.46285076],\n",
" [ 0.38943866, 2.50118221],\n",
" [ 0.53677061, 2.25152824],\n",
" [ 1.82660042, -0.74727926],\n",
" [ 0.48036068, 1.86553217],\n",
" [ 1.07335641, -0.11085592],\n",
" [-0.1356701 , 3.26030995],\n",
" [-1.14220795, 1.62584103],\n",
" [ 0.62475565, 1.88079418],\n",
" [ 0.24008992, 2.36889566],\n",
" [ 1.1000249 , 0.63344773],\n",
" [ 1.79081249, -0.55555364],\n",
" [ 0.25963498, 2.19522536],\n",
" [ 0.51889272, 2.09203194],\n",
" [-0.97212198, 1.37607816],\n",
" [ 0.45909929, 1.63157132],\n",
" [ 1.04817098, 0.55451166],\n",
" [ 0.48560402, 1.6224829 ],\n",
" [ 2.22717977, -0.99949498],\n",
" [ 1.03835295, 0.367851 ],\n",
" [-0.86651085, 3.01169281],\n",
" [ 0.56361431, 2.03734301],\n",
" [ 1.97669747, -1.05778857],\n",
" [ 0.16327411, 1.93753657],\n",
" [ 0.77428196, 1.58457934],\n",
" [ 2.27218539, -1.22831925],\n",
" [ 1.08093087, -0.56819249],\n",
" [-0.15974512, 1.64246367],\n",
" [ 0.96478678, 1.1520126 ],\n",
" [ 0.53759381, 2.03858827],\n",
" [ 1.18807228, 0.45547861],\n",
" [ 1.8365105 , -0.29140191],\n",
" [ 0.79957624, 1.76059461],\n",
" [ 0.20475928, 2.41247614],\n",
" [ 2.10020248, -0.55754422],\n",
" [ 0.30463063, 1.78432726],\n",
" [ 1.22839638, 0.79236676],\n",
" [ 1.00215375, 0.79922968],\n",
" [ 1.40221792, 0.26836893],\n",
" [ 0.48763803, 1.23830378],\n",
" [ 2.52164685, 0.82634304],\n",
" [ 1.23250426, 0.86360466],\n",
" [ 0.71705271, 1.03992881],\n",
" [ 0.57605515, 1.24897513],\n",
" [ 0.49619766, 0.92405942],\n",
" [ 0.50231277, 0.90332292],\n",
" [ 0.50455527, 1.07879308],\n",
" [ 0.65138811, 1.38005541],\n",
" [ 0.25814932, 1.30653239],\n",
" [ 0.74630687, 0.86643677],\n",
" [ 0.13615888, 1.55662294],\n",
" [ 0.6181835 , 0.8467661 ],\n",
" [ 0.54933302, 1.00859502],\n",
" [ 1.04188396, 1.14305184],\n",
" [ 1.04538562, 1.43403958],\n",
" [ 0.43897389, 0.7340289 ],\n",
" [ 0.5150014 , 0.94374412],\n",
" [ 0.63920018, 0.76406757],\n",
" [ 0.75274053, 0.50039519],\n",
" [ 0.0119005 , 1.44963954],\n",
" [ 0.70260639, 0.87638051],\n",
" [ 0.17608685, 1.24928585],\n",
" [ 0.45680766, 0.90496486],\n",
" [ 0.93662357, 1.14382119],\n",
" [ 0.57005431, 0.93968902],\n",
" [ 0.37356342, 1.00858314],\n",
" [ 1.65400377, 0.72307583],\n",
" [ 0.18707016, 1.18492355],\n",
" [ 0.68643523, 0.69175251],\n",
" [ 0.76929988, 0.95231351],\n",
" [ 0.55064555, 1.26084806],\n",
" [ 1.1907255 , 1.11458574],\n",
" [ 0.8074369 , 0.96826258],\n",
" [ 0.07631502, 1.49669736],\n",
" [ 0.38150452, 0.81388246],\n",
" [ 0.81430289, 1.15183828],\n",
" [ 1.9930756 , 1.35720369],\n",
" [ 0.44041726, 1.10341311],\n",
" [ 1.53124252, 1.01215856],\n",
" [ 0.86827844, 1.50258859],\n",
" [ 0.39904218, 1.03292531],\n",
" [ 0.20662781, 1.15137498],\n",
" [ 0.44149257, 0.91728447],\n",
" [ 0.19784503, 1.51204837],\n",
" [ 1.13155102, 0.97878786],\n",
" [ 0.12850521, 1.48109897],\n",
" [ 0.63218559, 1.04065258]])"
Danilo Ferreira de Lima
committed
"execution_count": 9,
1444
1445
1446
1447
1448
1449
1450
1451
1452
1453
1454
1455
1456
1457
1458
1459
1460
1461
1462
1463
1464
1465
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"clf.support_vectors_"
]
},
{
"cell_type": "markdown",
"id": "b54001fc",
"metadata": {},
"source": [
"We can now predict to which class a new data point belongs to using `clf.predict(new_data_samples)`. It is however interesting to visualize the decision boundary itself.\n",
"\n",
"(Taken from https://scikit-learn.org/stable/auto_examples/svm/plot_separating_hyperplane.html#sphx-glr-auto-examples-svm-plot-separating-hyperplane-py -- take a look there for more resources and more examples)\n",
"\n",
"The code below also highlights the support vectors."
]
},
{
"cell_type": "code",
Danilo Ferreira de Lima
committed
"execution_count": 10,
"id": "cc8fc1f1",
"metadata": {},
"outputs": [
{
"data": {
Danilo Ferreira de Lima
committed
1472
1473
1474
1475
1476
1477
1478
1479
1480
1481
1482
1483
1484
1485
1486
1487
1488
1489
1490
1491
1492
1493
1494
1495
1496
1497
1498
1499
1500
1501
1502
1503
1504
1505
1506
1507
1508
1509
1510
1511
1512
1513
1514
1515
1516
1517
1518
1519
1520
1521
1522
1523
1524
1525
1526
1527
1528
1529
1530
1531
1532
1533
1534
1535
1536
1537
1538
1539
1540
1541
1542
1543
1544
1545
1546
1547
1548
1549
1550
1551
1552
1553
1554
1555
1556
1557
1558
1559
1560
1561
1562
1563
1564
1565
1566
1567
1568
1569
1570
1571
1572
1573
1574
1575
1576
1577
1578
1579
1580
1581
1582
1583
1584
1585
1586
1587
1588
1589
1590
1591
1592
1593
1594
1595
1596
1597
1598
1599
1600
1601
1602
1603
1604
1605
1606
1607
1608
1609
1610
1611
1612
1613
1614
1615
1616
1617
1618
1619
1620
1621
1622
1623
1624
1625
1626
1627
1628
1629
1630
1631
1632
1633
1634
1635
1636
1637
1638
1639
1640
1641
1642
1643
1644
1645
1646
1647
1648
1649
1650
1651
1652
1653
1654
1655
1656
1657
1658
1659
1660
1661
1662
1663
1664
1665
1666
1667
1668
1669
1670
1671
1672
1673
1674
1675
1676
1677
1678
1679
1680
1681
1682
1683
1684
1685
1686
1687
1688
1689
1690
1691
1692
1693
1694
1695
1696
1697
1698
1699
1700
1701
1702
1703
1704
1705
1706
1707
1708
1709
1710
1711
1712
1713
1714
1715
1716
1717
1718
1719
1720
1721
1722
1723
1724
1725
1726
1727
1728
1729
1730
1731
1732
1733
1734
1735
1736
1737
1738
1739
1740
1741
1742
1743
1744
1745
1746
1747
1748
1749
1750
1751
1752
1753
1754
1755
1756
1757
1758
1759
1760
1761
1762
1763
1764
1765
1766
1767
1768
1769
1770
1771
1772
1773
1774
1775
1776
1777
1778
1779
1780
1781
1782
1783
1784
1785
1786
1787
1788
1789
1790
1791
1792
1793
1794
1795
1796
1797
1798
1799
1800
1801
1802
1803
1804
1805
1806
1807
1808
1809
1810
1811
1812
1813
1814
1815
1816
1817
1818
1819
1820
1821
1822
1823
1824
1825
1826
1827
1828
1829
1830
1831
1832
1833
1834
1835
1836
1837
1838
1839
1840
1841
1842
1843
1844
1845
1846
1847
1848
1849
1850
1851
1852
1853
1854
1855
1856
1857
1858
1859
1860
1861
1862
1863
1864
1865
1866
1867
1868
1869
1870
1871
1872
1873
1874
1875
1876
1877
1878
1879
1880
1881
1882
1883
1884
1885
1886
1887
1888
1889
1890
1891
1892
1893
1894
1895
1896
1897
1898
1899
1900
1901
1902
1903
1904
1905
1906
1907
1908
1909
1910
1911
1912
1913
1914
1915
1916
1917
1918
1919
1920
1921
1922
1923
1924
1925
1926
1927
1928
1929
1930
1931
1932
1933
1934
1935
1936
1937
1938
1939
1940
1941
1942
1943
1944
1945
1946
1947
1948
1949
1950
1951
1952
1953
1954
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
2038
2039
2040
2041
2042
2043
2044
2045
2046
2047
2048
2049
2050
2051
2052
2053
2054
2055
2056
2057
2058
2059
2060
2061
2062
2063
2064
2065
2066
2067
2068
2069
2070
2071
2072
2073
2074
2075
2076
2077
2078
2079
2080
2081
2082
2083
2084
2085
2086
2087
2088
2089
2090
2091
2092
2093
2094
2095
2096
2097
2098
2099
2100
2101
2102
2103
2104
2105
2106
2107
2108
2109
2110
2111
2112
2113
2114
2115
2116
2117
2118
2119
2120
2121
2122
2123
2124
2125
2126
2127
2128
2129
2130
2131
2132
2133
2134
2135
2136
2137
2138
2139
2140
2141
2142
2143
2144
2145
2146
2147
2148
2149
2150
2151
2152
2153
2154
2155
2156
2157
2158
2159
2160
2161
2162
2163
2164
2165
2166
2167
2168
2169
2170
2171
2172
2173
2174
2175
2176
2177
2178
2179
2180
2181
2182
2183
2184
2185
2186
2187
2188
2189
2190
2191
2192
2193
2194
2195
2196
2197
2198
2199
2200
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"/* global mpl */\n",
"window.mpl = {};\n",
"\n",
"mpl.get_websocket_type = function () {\n",
" if (typeof WebSocket !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof MozWebSocket !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert(\n",
" 'Your browser does not have WebSocket support. ' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.'\n",
" );\n",
" }\n",
"};\n",
"\n",
"mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = this.ws.binaryType !== undefined;\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById('mpl-warnings');\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent =\n",
" 'This browser does not support binary websocket messages. ' +\n",
" 'Performance may be slow.';\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = document.createElement('div');\n",
" this.root.setAttribute('style', 'display: inline-block');\n",
" this._root_extra_style(this.root);\n",
"\n",
" parent_element.appendChild(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message('supports_binary', { value: fig.supports_binary });\n",
" fig.send_message('send_image_mode', {});\n",
" if (fig.ratio !== 1) {\n",
" fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
" }\n",
" fig.send_message('refresh', {});\n",
" };\n",
"\n",
" this.imageObj.onload = function () {\n",
" if (fig.image_mode === 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function () {\n",
" fig.ws.close();\n",
" };\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"};\n",
"\n",
"mpl.figure.prototype._init_header = function () {\n",
" var titlebar = document.createElement('div');\n",
" titlebar.classList =\n",
" 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
" var titletext = document.createElement('div');\n",
" titletext.classList = 'ui-dialog-title';\n",
" titletext.setAttribute(\n",
" 'style',\n",
" 'width: 100%; text-align: center; padding: 3px;'\n",
" );\n",
" titlebar.appendChild(titletext);\n",
" this.root.appendChild(titlebar);\n",
" this.header = titletext;\n",
"};\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
"\n",
"mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
"\n",
"mpl.figure.prototype._init_canvas = function () {\n",
" var fig = this;\n",
"\n",
" var canvas_div = (this.canvas_div = document.createElement('div'));\n",
" canvas_div.setAttribute(\n",
" 'style',\n",
" 'border: 1px solid #ddd;' +\n",
" 'box-sizing: content-box;' +\n",
" 'clear: both;' +\n",
" 'min-height: 1px;' +\n",
" 'min-width: 1px;' +\n",
" 'outline: 0;' +\n",
" 'overflow: hidden;' +\n",
" 'position: relative;' +\n",
" 'resize: both;'\n",
" );\n",
"\n",
" function on_keyboard_event_closure(name) {\n",
" return function (event) {\n",
" return fig.key_event(event, name);\n",
" };\n",
" }\n",
"\n",
" canvas_div.addEventListener(\n",
" 'keydown',\n",
" on_keyboard_event_closure('key_press')\n",
" );\n",
" canvas_div.addEventListener(\n",
" 'keyup',\n",
" on_keyboard_event_closure('key_release')\n",
" );\n",
"\n",
" this._canvas_extra_style(canvas_div);\n",
" this.root.appendChild(canvas_div);\n",
"\n",
" var canvas = (this.canvas = document.createElement('canvas'));\n",
" canvas.classList.add('mpl-canvas');\n",
" canvas.setAttribute('style', 'box-sizing: content-box;');\n",
"\n",
" this.context = canvas.getContext('2d');\n",
"\n",
" var backingStore =\n",
" this.context.backingStorePixelRatio ||\n",
" this.context.webkitBackingStorePixelRatio ||\n",
" this.context.mozBackingStorePixelRatio ||\n",
" this.context.msBackingStorePixelRatio ||\n",
" this.context.oBackingStorePixelRatio ||\n",
" this.context.backingStorePixelRatio ||\n",
" 1;\n",
"\n",
" this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
" 'canvas'\n",
" ));\n",
" rubberband_canvas.setAttribute(\n",
" 'style',\n",
" 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
" );\n",
"\n",
" // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
" if (this.ResizeObserver === undefined) {\n",
" if (window.ResizeObserver !== undefined) {\n",
" this.ResizeObserver = window.ResizeObserver;\n",
" } else {\n",
" var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
" this.ResizeObserver = obs.ResizeObserver;\n",
" }\n",
" }\n",
"\n",
" this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
" var nentries = entries.length;\n",
" for (var i = 0; i < nentries; i++) {\n",
" var entry = entries[i];\n",
" var width, height;\n",
" if (entry.contentBoxSize) {\n",
" if (entry.contentBoxSize instanceof Array) {\n",
" // Chrome 84 implements new version of spec.\n",
" width = entry.contentBoxSize[0].inlineSize;\n",
" height = entry.contentBoxSize[0].blockSize;\n",
" } else {\n",
" // Firefox implements old version of spec.\n",
" width = entry.contentBoxSize.inlineSize;\n",
" height = entry.contentBoxSize.blockSize;\n",
" }\n",
" } else {\n",
" // Chrome <84 implements even older version of spec.\n",
" width = entry.contentRect.width;\n",
" height = entry.contentRect.height;\n",
" }\n",
"\n",
" // Keep the size of the canvas and rubber band canvas in sync with\n",
" // the canvas container.\n",
" if (entry.devicePixelContentBoxSize) {\n",
" // Chrome 84 implements new version of spec.\n",
" canvas.setAttribute(\n",
" 'width',\n",
" entry.devicePixelContentBoxSize[0].inlineSize\n",
" );\n",
" canvas.setAttribute(\n",
" 'height',\n",
" entry.devicePixelContentBoxSize[0].blockSize\n",
" );\n",
" } else {\n",
" canvas.setAttribute('width', width * fig.ratio);\n",
" canvas.setAttribute('height', height * fig.ratio);\n",
" }\n",
" canvas.setAttribute(\n",
" 'style',\n",
" 'width: ' + width + 'px; height: ' + height + 'px;'\n",
" );\n",
"\n",
" rubberband_canvas.setAttribute('width', width);\n",
" rubberband_canvas.setAttribute('height', height);\n",
"\n",
" // And update the size in Python. We ignore the initial 0/0 size\n",
" // that occurs as the element is placed into the DOM, which should\n",
" // otherwise not happen due to the minimum size styling.\n",
" if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
" fig.request_resize(width, height);\n",
" }\n",
" }\n",
" });\n",
" this.resizeObserverInstance.observe(canvas_div);\n",
"\n",
" function on_mouse_event_closure(name) {\n",
" return function (event) {\n",
" return fig.mouse_event(event, name);\n",
" };\n",
" }\n",
"\n",
" rubberband_canvas.addEventListener(\n",
" 'mousedown',\n",
" on_mouse_event_closure('button_press')\n",
" );\n",
" rubberband_canvas.addEventListener(\n",
" 'mouseup',\n",
" on_mouse_event_closure('button_release')\n",
" );\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband_canvas.addEventListener(\n",
" 'mousemove',\n",
" on_mouse_event_closure('motion_notify')\n",
" );\n",
"\n",
" rubberband_canvas.addEventListener(\n",
" 'mouseenter',\n",
" on_mouse_event_closure('figure_enter')\n",
" );\n",
" rubberband_canvas.addEventListener(\n",
" 'mouseleave',\n",
" on_mouse_event_closure('figure_leave')\n",
" );\n",
"\n",
" canvas_div.addEventListener('wheel', function (event) {\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" on_mouse_event_closure('scroll')(event);\n",
" });\n",
"\n",
" canvas_div.appendChild(canvas);\n",
" canvas_div.appendChild(rubberband_canvas);\n",
"\n",
" this.rubberband_context = rubberband_canvas.getContext('2d');\n",
" this.rubberband_context.strokeStyle = '#000000';\n",
"\n",
" this._resize_canvas = function (width, height, forward) {\n",
" if (forward) {\n",
" canvas_div.style.width = width + 'px';\n",
" canvas_div.style.height = height + 'px';\n",
" }\n",
" };\n",
"\n",
" // Disable right mouse context menu.\n",
" this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
" event.preventDefault();\n",
" return false;\n",
" });\n",
"\n",
" function set_focus() {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"};\n",
"\n",
"mpl.figure.prototype._init_toolbar = function () {\n",
" var fig = this;\n",
"\n",
" var toolbar = document.createElement('div');\n",
" toolbar.classList = 'mpl-toolbar';\n",
" this.root.appendChild(toolbar);\n",
"\n",
" function on_click_closure(name) {\n",
" return function (_event) {\n",
" return fig.toolbar_button_onclick(name);\n",
" };\n",
" }\n",
"\n",
" function on_mouseover_closure(tooltip) {\n",
" return function (event) {\n",
" if (!event.currentTarget.disabled) {\n",
" return fig.toolbar_button_onmouseover(tooltip);\n",
" }\n",
" };\n",
" }\n",
"\n",
" fig.buttons = {};\n",
" var buttonGroup = document.createElement('div');\n",
" buttonGroup.classList = 'mpl-button-group';\n",
" for (var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" /* Instead of a spacer, we start a new button group. */\n",
" if (buttonGroup.hasChildNodes()) {\n",
" toolbar.appendChild(buttonGroup);\n",
" }\n",
" buttonGroup = document.createElement('div');\n",
" buttonGroup.classList = 'mpl-button-group';\n",
" continue;\n",
" }\n",
"\n",
" var button = (fig.buttons[name] = document.createElement('button'));\n",
" button.classList = 'mpl-widget';\n",
" button.setAttribute('role', 'button');\n",
" button.setAttribute('aria-disabled', 'false');\n",
" button.addEventListener('click', on_click_closure(method_name));\n",
" button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
"\n",
" var icon_img = document.createElement('img');\n",
" icon_img.src = '_images/' + image + '.png';\n",
" icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
" icon_img.alt = tooltip;\n",
" button.appendChild(icon_img);\n",
"\n",
" buttonGroup.appendChild(button);\n",
" }\n",
"\n",
" if (buttonGroup.hasChildNodes()) {\n",
" toolbar.appendChild(buttonGroup);\n",
" }\n",
"\n",
" var fmt_picker = document.createElement('select');\n",
" fmt_picker.classList = 'mpl-widget';\n",
" toolbar.appendChild(fmt_picker);\n",
" this.format_dropdown = fmt_picker;\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = document.createElement('option');\n",
" option.selected = fmt === mpl.default_extension;\n",
" option.innerHTML = fmt;\n",
" fmt_picker.appendChild(option);\n",
" }\n",
"\n",
" var status_bar = document.createElement('span');\n",
" status_bar.classList = 'mpl-message';\n",
" toolbar.appendChild(status_bar);\n",
" this.message = status_bar;\n",
"};\n",
"\n",
"mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
"};\n",
"\n",
"mpl.figure.prototype.send_message = function (type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"};\n",
"\n",
"mpl.figure.prototype.send_draw_message = function () {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1], msg['forward']);\n",
" fig.send_message('refresh', {});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
" var x0 = msg['x0'] / fig.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
" var x1 = msg['x1'] / fig.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0,\n",
" 0,\n",
" fig.canvas.width / fig.ratio,\n",
" fig.canvas.height / fig.ratio\n",
" );\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch (cursor) {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_message = function (fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
" for (var key in msg) {\n",
" if (!(key in fig.buttons)) {\n",
" continue;\n",
" }\n",
" fig.buttons[key].disabled = !msg[key];\n",
" fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
" if (msg['mode'] === 'PAN') {\n",
" fig.buttons['Pan'].classList.add('active');\n",
" fig.buttons['Zoom'].classList.remove('active');\n",
" } else if (msg['mode'] === 'ZOOM') {\n",
" fig.buttons['Pan'].classList.remove('active');\n",
" fig.buttons['Zoom'].classList.add('active');\n",
" } else {\n",
" fig.buttons['Pan'].classList.remove('active');\n",
" fig.buttons['Zoom'].classList.remove('active');\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function () {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message('ack', {});\n",
"};\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function (fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = 'image/png';\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src\n",
" );\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data\n",
" );\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" } else if (\n",
" typeof evt.data === 'string' &&\n",
" evt.data.slice(0, 21) === 'data:image/png;base64'\n",
" ) {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig['handle_' + msg_type];\n",
" } catch (e) {\n",
" console.log(\n",
" \"No handler for the '\" + msg_type + \"' message type: \",\n",
" msg\n",
" );\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\n",
" \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
" e,\n",
" e.stack,\n",
" msg\n",
" );\n",
" }\n",
" }\n",
" };\n",
"};\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function (e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e) {\n",
" e = window.event;\n",
" }\n",
" if (e.target) {\n",
" targ = e.target;\n",
" } else if (e.srcElement) {\n",
" targ = e.srcElement;\n",
" }\n",
" if (targ.nodeType === 3) {\n",
" // defeat Safari bug\n",
" targ = targ.parentNode;\n",
" }\n",
"\n",
" // pageX,Y are the mouse positions relative to the document\n",
" var boundingRect = targ.getBoundingClientRect();\n",
" var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
" var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
"\n",
" return { x: x, y: y };\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys(original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object') {\n",
" obj[key] = original[key];\n",
" }\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function (event, name) {\n",
" var canvas_pos = mpl.findpos(event);\n",
"\n",
" if (name === 'button_press') {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * this.ratio;\n",
" var y = canvas_pos.y * this.ratio;\n",
"\n",
" this.send_message(name, {\n",
" x: x,\n",
" y: y,\n",
" button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event),\n",
" });\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"};\n",
"\n",
"mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"};\n",
"\n",
"mpl.figure.prototype.key_event = function (event, name) {\n",
" // Prevent repeat events\n",
" if (name === 'key_press') {\n",
" if (event.which === this._key) {\n",
" return;\n",
" } else {\n",
" this._key = event.which;\n",
" }\n",
" }\n",
" if (name === 'key_release') {\n",
" this._key = null;\n",
" }\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which !== 17) {\n",
" value += 'ctrl+';\n",
" }\n",
" if (event.altKey && event.which !== 18) {\n",
" value += 'alt+';\n",
" }\n",
" if (event.shiftKey && event.which !== 16) {\n",
" value += 'shift+';\n",
" }\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
" return false;\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
" if (name === 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message('toolbar_button', { name: name });\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"\n",
"///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
"// prettier-ignore\n",
"var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";/* global mpl */\n",
"\n",
"var comm_websocket_adapter = function (comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function () {\n",
" comm.close();\n",
" };\n",
" ws.send = function (m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function (msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data']);\n",
" });\n",
" return ws;\n",
"};\n",
"\n",
"mpl.mpl_figure_comm = function (comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = document.getElementById(id);\n",
" var ws_proxy = comm_websocket_adapter(comm);\n",
"\n",
" function ondownload(figure, _format) {\n",
" window.open(figure.canvas.toDataURL());\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
Loading
Loading full blame...