如何将一个数组中的元素数据与另一个数组中的索引进行匹配

Question

我试图设置一个函数，将一个数组中的元素数据与另一个数组中的索引相匹配。如何提取元素数据并将其与另一个数组的索引相匹配

def TD_TO_angles(demands):
    hp = demands['HP'][:,0]
    fk = demands['FK'][:,0]
    aa = demands['AA'][:,0]

    val = (demands['StridePeaks'][:,0])

    for A in set(val):
        aast = aa[A]
        fkst = fk[A]
        hpst = hp[A]

    TD_TO_angles = {aast, fkst, hpst};     
    aast = {aast}
    fkst = {fkst}
    hpst = {hpst}    
    return TD_TO_angles

这是我正在使用的时间序列数据集中aa数据或踝关节角度的一个示例

126.913 64.9917
115.747 60.747
105.081 60.6108
95.5951 58.756
87.7298 55.262
75.2953 54.5783
64.4113 56.3024
67.4142 58.1884
69.8556 63.5886
66.1612 58.2711
66.8794 65.3997
71.5744 97.2196
75.1093 77.5634
70.2835 60.561
64.9662 106.959
66.2361 124.251
66.7195 117.595
67.2747 126.61
68.7487 133.717
69.6168 134.667
68.715  123.954
66.5187 112.372
66.4452 97.9355
70.1027 78.7449
80.8875 75.6673
88.2306 73.5378
88.646  62.6714
94.7493 65.0229
95.7316 70.4663
97.5397 70.8766
123.33  73.2429
146.752 70.5142
141.524 66.9745
124.008 66.9764
109.693 67.3567
107.806 66.4611
114.989 63.964
118.584 63.0383
119.871 62.7758
109.938 62.3356
93.1381 62.3409
87.695  57.281
78.8009 49.251
71.3187 57.7732
74.7947 64.0268
68.8221 49.1146
63.3999 51.7764
66.3156 55.4616
67.0368 56.9664
67.353  91.0168
67.3452 107.917
67.4118 99.5158
67.8044 94.5887
67.2836 88.5042
69.1169 97.0538
71.5333 112.515
67.2238 112.648
67.8359 110.888
68.025  107.303
67.0573 84.8197
73.0241 66.1374
69.5523 68.0887
75.2818 75.8326
84.7714 71.1051
89.3946 60.7323
102.608 63.7635
108.157 67.2678
121.655 71.8214
149.797 78.452
160.753 75.6991
143.018 73.4939
122.73  72.2725
120.783 70.8374
125.067 70.3499
127.07  67.9424
123.192 68.774
117.508 69.9937
113.908 68.2499
101.202 64.3081
84.9734 57.6481
74.0624 54.3493
67.4081 58.4066
69.1534 64.7296
69.2645 59.9548
61.2198 54.1205
61.2781 54.8994
65.2354 61.2534
61.9545 96.9395
59.9729 96.9271
60.5106 52.6817
61.8656 64.5963
66.5464 87.6025
70.6323 90.7524
69.5487 97.7691
69.9812 96.3687
67.1833 96.1859
64.6258 77.9894
71.9143 59.6561
71.5766 64.8557
71.0716 72.2691
82.5832 67.4291
92.0625 59.7929
92.7647 66.3665
98.577  69.64
113.311 70.7322
129.344 75.2588
145.001 72.3384
136.318 73.4568
121.839 75.7549
128.682 72.6917
122.414 72.4189
115.226 71.8492
124.144 68.9574
122.214 65.0117
113.31  60.8247
101.814 58.7774
90.7953 55.5742
79.2945 53.7234
62.306  53.5492
61.6952 53.2101
68.9737 54.62
66.9535 58.6022
65.0989 64.2755
64.9855 58.7944
65.8662 69.2094
65.5722 101.701
65.0224 101.078
64.8123 97.2873
63.5927 118.717
65.4883 128.856
66.9872 132.338
65.9113 126.532
64.356  108.679
66.1521 91.8618
70.9633 72.7211
71.85   66.7186
79.1704 69.8345
93.0986 62.3635
102.413 60.743
107.014 66.084
112.258 67.4913
138.277 70.2375
159.418 71.2789
143.831 69.9808
128.129 71.0585
123.844 72.9921
120.988 72.5712
121.988 71.1181
120.763 69.6273
120.61  67.3827
113.613 65.7147
101.623 61.895
90.044  56.6662
79.1135 53.7075
74.1369 56.7108
65.9015 63.4439
63.9854 58.104
63.2365 48.0476
64.453  51.5662
74.8462 66.0012
69.5068 81.6284
61.6704 67.697
62.0323 45.6094
61.0095 67.4746
63.3932 94.3209
65.686  101.401
66.968  108.934
69.8169 119.024
68.419  114.822
66.6576 99.3486
70.3232 89.5742
73.4096 67.3281
79.4871 79.9525
82.4616 100.366
84.9018 66.7296
103.625 60.8615
120.631 72.1137
133.217 67.9522
153.088 71.6755
152.747 68.0102
131.308 66.3889
124.293 67.6835
128.496 66.9757
128.556 68.4795
132.032 68.91
134.686 67.4453
128.471 66.9862
119.646 69.2053
106.664 65.5094
87.4494 58.339
75.2079 54.7077
70.8553 56.2065
64.6084 59.6224
61.6766 55.5894
63.483  55.865
65.7799 62.073
68.8149 60.6132
68.5561 74.9788
64.5631 92.484
63.1321 80.7293
63.8825 89.0422
63.7444 119.109
66.1641 123.689
69.0017 125.045
68.5749 130.385
64.8502 127.132
64.0108 117.407
68.5745 97.0441
69.2469 77.6339
66.7267 67.5156
68.4488 68.1756
78.4439 71.0865
87.5962 64.1182
91.3575 63.7998
98.3089 70.1873
108.693 72.303
126.505 71.8651
139.419 67.3619
126.974 67.2866
110.433 69.1856
106.059 69.3434
111.236 70.2082
123.546 69.5986
123.905 71.9274
120.399 68.313
115.463 61.0997
100.391 59.7942
93.8934 55.44
85.1524 51.5527
71.1082 51.5783
67.7683 56.5315
65.7711 54.0512
64.7643 50.7951
69.364  76.9613
71.9385 93.873
70.3837 94.5523
70.4789 102.732
71.2028 95.5289
69.5797 102.202
70.9279 117.283
71.4974 109.402
68.0692 113.861
69.3574 124.082
70.7289 121.854
68.8606 114.04
68.5058 99.8618
70.4022 82.3816
75.2312 66.5385
76.0801 72.9831
79.2255 78.5438
87.0668 61.7534
89.5446 59.9742
98.1421 66.0796
106.714 67.2484
114.188 72.4226
137.202 71.1241
140.27  69.2302
119.593 71.4355
116.916 73.1483
117.445 74.4986
113.805 76.149
117.051 75.4814
115.555 70.2956
109.325 68.4843
98.1318 64.563
87.8107 58.5121
79.001  56.9422
66.6023 56.1807
66.6998 65.9684

这是我想和角度数据匹配的数据

15  1458.46
33  -1341.3
51  1438.37
73  -1478.02
88  1319.48
109 -1484.34
125 1406.37
145 -1480.24
161 1481.32
182 -1517.04
200 1409.71
222 -1403.54
238 1485.07
259 -1395.48

基本上，我试图从特定时间点的hp、aa和fk的时间序列数据中提取一个特定的角度，与我所拥有的数据相匹配。更准确地说，我想从与这些峰值匹配的角度数据中提取索引15、33、51、73等