フィルターのクリア

I have this gaussian curve, and I am trying to find the area for one part of the peak. How would I go about calculating it? I've tried many methods, but they all do not seem to work (or they give me a 0 value). I appreciate any advise.

2 ビュー (過去 30 日間)
I have uploaded my x and y data. I want to find the area underneath the curve between x=1.8845 and x=2.1053. I would also like to find the area underneath x=2.1053 and x=2.2878. I would greatly appreciate any help.
  1 件のコメント
Trishal Zaveri
Trishal Zaveri 2018 年 5 月 10 日
I will just copy and paste the x and y data since the files are not clearly showing up. I apologize in advance for the data amount. xdata= 1.3778 1.3793 1.3809 1.3824 1.3839 1.3855 1.3870 1.3886 1.3901 1.3917 1.3933 1.3948 1.3964 1.3980 1.3996 1.4012 1.4027 1.4043 1.4059 1.4075 1.4091 1.4107 1.4123 1.4139 1.4155 1.4172 1.4188 1.4204 1.4220 1.4237 1.4253 1.4269 1.4286 1.4302 1.4319 1.4335 1.4352 1.4368 1.4385 1.4402 1.4419 1.4435 1.4452 1.4469 1.4486 1.4503 1.4520 1.4537 1.4554 1.4571 1.4588 1.4605 1.4622 1.4640 1.4657 1.4675 1.4692 1.4709 1.4727 1.4744 1.4762 1.4779 1.4797 1.4815 1.4832 1.4850 1.4868 1.4886 1.4904 1.4922 1.4939 1.4958 1.4976 1.4994 1.5012 1.5030 1.5048 1.5067 1.5085 1.5103 1.5122 1.5141 1.5159 1.5178 1.5196 1.5215 1.5234 1.5252 1.5271 1.5289 1.5308 1.5327 1.5346 1.5365 1.5385 1.5404 1.5423 1.5442 1.5461 1.5480 1.5500 1.5519 1.5539 1.5558 1.5578 1.5598 1.5617 1.5637 1.5656 1.5676 1.5696 1.5716 1.5736 1.5756 1.5776 1.5796 1.5817 1.5836 1.5857 1.5877 1.5897 1.5918 1.5938 1.5959 1.5979 1.6000 1.6020 1.6042 1.6062 1.6083 1.6104 1.6125 1.6146 1.6167 1.6188 1.6209 1.6230 1.6251 1.6273 1.6294 1.6316 1.6337 1.6359 1.6381 1.6402 1.6424 1.6446 1.6468 1.6489 1.6511 1.6534 1.6555 1.6577 1.6599 1.6622 1.6644 1.6667 1.6689 1.6712 1.6734 1.6757 1.6779 1.6802 1.6825 1.6847 1.6871 1.6894 1.6917 1.6940 1.6963 1.6986 1.7010 1.7033 1.7056 1.7080 1.7103 1.7127 1.7151 1.7174 1.7198 1.7222 1.7246 1.7270 1.7294 1.7318 1.7343 1.7367 1.7391 1.7416 1.7441 1.7464 1.7489 1.7514 1.7539 1.7564 1.7589 1.7614 1.7638 1.7664 1.7689 1.7714 1.7740 1.7765 1.7790 1.7816 1.7842 1.7867 1.7893 1.7919 1.7945 1.7971 1.7997 1.8024 1.8049 1.8076 1.8103 1.8128 1.8155 1.8181 1.8208 1.8236 1.8262 1.8289 1.8317 1.8343 1.8371 1.8397 1.8425 1.8452 1.8480 1.8507 1.8535 1.8562 1.8591 1.8618 1.8647 1.8674 1.8703 1.8731 1.8760 1.8788 1.8817 1.8845 1.8874 1.8903 1.8931 1.8961 1.8989 1.9019 1.9048 1.9077 1.9107 1.9136 1.9165 1.9195 1.9225 1.9254 1.9285 1.9315 1.9345 1.9375 1.9406 1.9436 1.9466 1.9496 1.9528 1.9558 1.9589 1.9620 1.9652 1.9683 1.9714 1.9745 1.9776 1.9809 1.9840 1.9872 1.9904 1.9935 1.9967 2.0001 2.0033 2.0065 2.0097 2.0130 2.0163 2.0195 2.0228 2.0261 2.0294 2.0327 2.0361 2.0395 2.0429 2.0463 2.0496 2.0530 2.0564 2.0598 2.0633 2.0667 2.0702 2.0736 2.0771 2.0805 2.0840 2.0875 2.0910 2.0946 2.0981 2.1017 2.1053 2.1089 2.1125 2.1161 2.1197 2.1232 2.1269 2.1306 2.1342 2.1380 2.1417 2.1454 2.1490 2.1528 2.1565 2.1603 2.1641 2.1678 2.1716 2.1754 2.1793 2.1832 2.1869 2.1908 2.1947 2.1987 2.2025 2.2064 2.2104 2.2142 2.2182 2.2222 2.2263 2.2302 2.2343 2.2383 2.2423 2.2464 2.2505 2.2545 2.2587 2.2627 2.2669 2.2711 2.2752 2.2794 2.2837 2.2878 2.2921 2.2962 2.3006 2.3049 2.3091 2.3135 2.3177 2.3221 2.3264 2.3308 2.3351 2.3396 2.3440 2.3485 2.3529 2.3574 2.3620 2.3664 2.3709 2.3755 2.3800 2.3846 2.3891 2.3939 2.3984 2.4031 2.4077 2.4125 2.4171 2.4218 2.4266 2.4313 2.4362 2.4409 2.4459 2.4506 2.4554 2.4604 2.4652 2.4700 2.4751 2.4800 2.4849 2.4900 2.4949 2.4999 2.5051 2.5101 2.5151 2.5204 2.5254 2.5305 2.5359 2.5410 2.5461 2.5515 2.5567 2.5620 2.5672 2.5727 2.5780 2.5833 2.5887 2.5942 2.5996 2.6050 2.6105 2.6161 2.6216 2.6271 2.6327 2.6382 2.6440 2.6496 2.6553 2.6609 2.6666 2.6723 2.6783 2.6840 2.6898 2.6956 2.7015 2.7074 2.7132 2.7194 2.7253 2.7313 2.7373 2.7434 2.7494 2.7555 2.7616 2.7678 2.7739 2.7804 2.7866 2.7929 2.7991 2.8055 2.8118 2.8182 2.8246 2.8310 2.8375 2.8440 2.8505 2.8571 2.8637 2.8703 2.8770 2.8837 2.8904 2.8971 2.9039 2.9108 2.9176 2.9245 2.9314 2.9384 2.9454 2.9524 2.9594 2.9665 2.9737 2.9808 2.9880 2.9953 3.0025 3.0098 3.0169 3.0243 3.0317 3.0392 3.0467 3.0542 3.0618 3.0694 3.0770 3.0847 3.0921 3.0999 3.1077 3.1156 3.1235 3.1314 3.1394 3.1471 3.1551 3.1632 3.1714 3.1796 3.1878 3.1957 3.2040 3.2124 3.2208 3.2293 3.2378 3.2460 3.2546 3.2632 3.2719 3.2803 3.2890 3.2979 3.3067 3.3157 3.3243 3.3333 3.3424 3.3515 3.3603 3.3695 3.3788 3.3881 3.3971 3.4066 3.4161 3.4256 3.4348 3.4445 3.4542 3.4636 3.4734 3.4832 3.4928 3.5028 3.5128 3.5229 3.5327 3.5429 y data:
0.0091
0.0091
0.0091
0.0087
0.0094
0.0093
0.0091
0.0089
0.0090
0.0090
0.0093
0.0091
0.0088
0.0087
0.0086
0.0089
0.0084
0.0085
0.0083
0.0082
0.0078
0.0078
0.0089
0.0080
0.0086
0.0089
0.0089
0.0085
0.0085
0.0087
0.0086
0.0092
0.0095
0.0087
0.0093
0.0098
0.0092
0.0090
0.0089
0.0077
0.0094
0.0090
0.0090
0.0100
0.0089
0.0076
0.0088
0.0083
0.0082
0.0085
0.0083
0.0089
0.0081
0.0087
0.0083
0.0084
0.0079
0.0088
0.0083
0.0083
0.0084
0.0084
0.0087
0.0081
0.0084
0.0085
0.0084
0.0089
0.0081
0.0081
0.0080
0.0080
0.0083
0.0085
0.0082
0.0082
0.0082
0.0082
0.0083
0.0080
0.0080
0.0083
0.0078
0.0087
0.0082
0.0082
0.0083
0.0085
0.0088
0.0081
0.0076
0.0085
0.0079
0.0084
0.0083
0.0088
0.0084
0.0083
0.0077
0.0088
0.0078
0.0081
0.0080
0.0085
0.0075
0.0089
0.0079
0.0083
0.0082
0.0081
0.0084
0.0082
0.0081
0.0089
0.0086
0.0080
0.0085
0.0081
0.0092
0.0082
0.0087
0.0089
0.0081
0.0084
0.0085
0.0081
0.0087
0.0077
0.0081
0.0085
0.0083
0.0087
0.0082
0.0087
0.0086
0.0084
0.0086
0.0084
0.0085
0.0091
0.0085
0.0082
0.0083
0.0090
0.0087
0.0087
0.0086
0.0085
0.0088
0.0087
0.0088
0.0091
0.0088
0.0091
0.0094
0.0088
0.0089
0.0089
0.0091
0.0093
0.0092
0.0094
0.0093
0.0093
0.0096
0.0097
0.0095
0.0098
0.0095
0.0098
0.0097
0.0098
0.0099
0.0101
0.0101
0.0103
0.0100
0.0105
0.0104
0.0102
0.0106
0.0106
0.0108
0.0108
0.0109
0.0109
0.0114
0.0113
0.0115
0.0117
0.0115
0.0120
0.0124
0.0121
0.0126
0.0127
0.0127
0.0132
0.0129
0.0129
0.0135
0.0139
0.0137
0.0142
0.0145
0.0148
0.0145
0.0152
0.0156
0.0163
0.0160
0.0163
0.0167
0.0171
0.0175
0.0175
0.0183
0.0186
0.0192
0.0195
0.0199
0.0207
0.0211
0.0214
0.0223
0.0230
0.0234
0.0241
0.0252
0.0256
0.0267
0.0273
0.0286
0.0295
0.0308
0.0320
0.0328
0.0346
0.0358
0.0375
0.0397
0.0418
0.0441
0.0466
0.0489
0.0522
0.0558
0.0593
0.0633
0.0680
0.0732
0.0802
0.0865
0.0927
0.1023
0.1125
0.1233
0.1348
0.1480
0.1617
0.1792
0.1968
0.2139
0.2343
0.2559
0.2828
0.3050
0.3271
0.3553
0.3850
0.4139
0.4426
0.4677
0.4940
0.5273
0.5588
0.5831
0.6110
0.6338
0.6615
0.6870
0.7050
0.7236
0.7403
0.7562
0.7681
0.7766
0.7826
0.7880
0.7906
0.7913
0.7904
0.7879
0.7817
0.7755
0.7705
0.7628
0.7557
0.7466
0.7367
0.7284
0.7195
0.7108
0.7030
0.6948
0.6880
0.6818
0.6754
0.6711
0.6675
0.6666
0.6660
0.6664
0.6685
0.6718
0.6767
0.6828
0.6899
0.6992
0.7091
0.7198
0.7304
0.7433
0.7554
0.7680
0.7781
0.7907
0.8031
0.8133
0.8248
0.8329
0.8414
0.8506
0.8567
0.8616
0.8648
0.8679
0.8692
0.8695
0.8681
0.8664
0.8634
0.8592
0.8544
0.8498
0.8448
0.8382
0.8325
0.8262
0.8206
0.8151
0.8088
0.8039
0.7996
0.7959
0.7929
0.7892
0.7869
0.7857
0.7864
0.7866
0.7876
0.7897
0.7926
0.7960
0.7996
0.8049
0.8109
0.8160
0.8211
0.8278
0.8339
0.8407
0.8474
0.8534
0.8596
0.8650
0.8724
0.8773
0.8825
0.8881
0.8929
0.8991
0.9041
0.9076
0.9126
0.9173
0.9221
0.9271
0.9312
0.9361
0.9421
0.9462
0.9520
0.9562
0.9609
0.9679
0.9749
0.9794
0.9863
0.9921
0.9996
1.0080
1.0144
1.0204
1.0278
1.0363
1.0448
1.0509
1.0568
1.0652
1.0738
1.0807
1.0857
1.0925
1.1008
1.1057
1.1112
1.1166
1.1222
1.1274
1.1333
1.1373
1.1412
1.1448
1.1483
1.1524
1.1551
1.1584
1.1602
1.1628
1.1646
1.1668
1.1685
1.1695
1.1707
1.1710
1.1722
1.1725
1.1731
1.1722
1.1710
1.1703
1.1691
1.1673
1.1663
1.1632
1.1610
1.1579
1.1546
1.1513
1.1469
1.1426
1.1381
1.1333
1.1288
1.1227
1.1168
1.1122
1.1059
1.0983
1.0933
1.0849
1.0783
1.0713
1.0641
1.0556
1.0478
1.0394
1.0314
1.0211
1.0127
1.0037
0.9953
0.9860
0.9760
0.9667
0.9562
0.9475
0.9388
0.9283
0.9180
0.9079
0.8986
0.8889
0.8778
0.8673
0.8571
0.8479
0.8390
0.8271
0.8169
0.8056
0.7959
0.7872
0.7756
0.7642
0.7533
0.7424
0.7343
0.7228
0.7117
0.7011
0.6907
0.6828
0.6723
0.6622
0.6518
0.6423
0.6340
0.6239
0.6137
0.6047
0.5956
0.5878
0.5788
0.5689
0.5598
0.5509
0.5433
0.5351
0.5248
0.5165
0.5080
0.5004
0.4929
0.4837
0.4754
0.4674
0.4605
0.4538
0.4459
0.4382
0.4313
0.4243
0.4192
0.4111
0.4039
0.3982
0.3924
0.3876
0.3808
0.3748
0.3697
0.3641
0.3599
0.3537
0.3477
0.3422
0.3376
0.3336

サインインしてコメントする。

回答 (1 件)

John D'Errico
John D'Errico 2018 年 5 月 10 日
編集済み: John D'Errico 2018 年 5 月 10 日
So, when I stop laughing, "I have this Gaussian curve..."
plot(x2,y2)
Yeah, right. In what universe is that a Gaussian curve? Or, perhaps are you thinking about Gauss's younger brother, Harvey Cornelius Rumpelstiltskin Gauss? He had very poor vision, so that might look vaguely like a Gaussian curve to him. You may have read about him, where he earned his fame in the field of textile manufacturing. ;-)
spl = pchip(x2,y2);
splint = fnint(spl);
diff(ppval(splint,[1.8845, 2.1053]))
ans =
0.10858092934252
FNINT lives in the curve fitting toolbox, I believe. If you don't have that, I have a viable replacement.

カテゴリ

Help Center および File ExchangeStartup and Shutdown についてさらに検索

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by