Interploate between rows in a matrix when the corresponding columns of vector R_f with values ranging between 0 and 1 are less or equal to 0.5

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Hi, I have a matrix "mat_up" (231*201 complex double). I also have a vector R_f (1x231 complex double). When abs(R_f) is less or equal to 0.5, I want the data in the corresponding rows of mat_up to be interpolated based on the row above and below. For example, if at positions 91,92 abs(R_f)<=0.5, then interpolate the data between rows 90 and 93 in matrix mat_up.
Thanks

Accepted Answer

Voss
Voss on 26 Oct 2022
load('R_f.mat')
load('mat_up.mat')
idx = abs(R_f) <= 0.5;
mat_up(idx,:) % check old values
ans =
-0.0326 + 0.0266i -0.0345 + 0.0205i -0.0259 + 0.0221i -0.0263 + 0.0262i -0.0253 + 0.0177i -0.0173 + 0.0158i -0.0158 + 0.0122i -0.0142 + 0.0036i -0.0147 - 0.0021i -0.0213 - 0.0086i -0.0142 - 0.0155i -0.0193 - 0.0176i -0.0367 - 0.0306i -0.0294 - 0.0239i -0.0317 - 0.0159i -0.0395 - 0.0310i -0.0374 - 0.0305i -0.0423 - 0.0176i -0.0440 - 0.0278i -0.0408 - 0.0229i -0.0461 - 0.0118i -0.0397 - 0.0230i -0.0357 - 0.0235i -0.0510 - 0.0215i -0.0442 - 0.0265i -0.0416 - 0.0183i -0.0517 - 0.0193i -0.0472 - 0.0271i -0.0473 - 0.0170i -0.0591 - 0.0241i -0.0573 - 0.0189i -0.0628 - 0.0097i -0.0644 - 0.0062i -0.0603 - 0.0032i -0.0621 + 0.0054i -0.0645 + 0.0136i -0.0541 + 0.0226i -0.0516 + 0.0267i -0.0499 + 0.0282i -0.0392 + 0.0329i -0.0387 + 0.0332i -0.0387 + 0.0294i -0.0319 + 0.0396i -0.0301 + 0.0369i -0.0208 + 0.0333i -0.0156 + 0.0387i -0.0139 + 0.0297i -0.0113 + 0.0297i -0.0130 + 0.0314i -0.0079 + 0.0251i -0.0050 + 0.0275i -0.0101 + 0.0310i -0.0005 + 0.0266i 0.0001 + 0.0274i -0.0015 + 0.0272i 0.0099 + 0.0243i 0.0126 + 0.0218i 0.0114 + 0.0204i 0.0172 + 0.0190i 0.0226 + 0.0113i 0.0211 + 0.0131i 0.0243 + 0.0074i 0.0333 + 0.0005i 0.0258 + 0.0012i 0.0264 - 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mat_up(idx,:) = NaN;
mat_up = fillmissing(mat_up,'linear');
mat_up(idx,:) % check new values
ans =
-0.0414 + 0.0846i -0.0581 + 0.0878i -0.0452 + 0.0763i -0.0387 + 0.0917i -0.0576 + 0.0846i -0.0403 + 0.0791i -0.0275 + 0.0834i -0.0419 + 0.0656i -0.0396 + 0.0522i -0.0461 + 0.0603i -0.0519 + 0.0383i -0.0552 + 0.0328i -0.0859 + 0.0407i -0.0722 + 0.0315i -0.0683 + 0.0352i -0.1006 + 0.0249i -0.0984 + 0.0253i -0.0885 + 0.0439i -0.1074 + 0.0304i -0.1010 + 0.0349i -0.0923 + 0.0537i -0.0967 + 0.0325i -0.0967 + 0.0227i -0.1134 + 0.0393i -0.1071 + 0.0295i -0.1032 + 0.0350i -0.1138 + 0.0374i -0.1176 + 0.0207i -0.1113 + 0.0260i -0.1358 + 0.0208i -0.1343 + 0.0274i -0.1430 + 0.0389i -0.1409 + 0.0454i -0.1384 + 0.0435i -0.1416 + 0.0528i -0.1437 + 0.0720i -0.1326 + 0.0805i -0.1227 + 0.0821i -0.1260 + 0.0883i -0.1071 + 0.0902i -0.1027 + 0.0834i -0.1108 + 0.0752i -0.1010 + 0.0893i -0.0940 + 0.0801i -0.0827 + 0.0713i -0.0784 + 0.0743i -0.0740 + 0.0560i -0.0757 + 0.0494i -0.0881 + 0.0533i -0.0722 + 0.0399i -0.0703 + 0.0465i -0.0961 + 0.0327i -0.0692 + 0.0343i -0.0733 + 0.0386i -0.0853 + 0.0145i -0.0606 + 0.0315i -0.0632 + 0.0380i -0.0599 + 0.0046i -0.0556 + 0.0202i -0.0627 + 0.0204i -0.0445 - 0.0013i -0.0474 + 0.0013i -0.0635 - 0.0071i -0.0394 - 0.0142i -0.0444 - 0.0158i -0.0525 - 0.0343i -0.0421 - 0.0308i -0.0457 - 0.0358i -0.0464 - 0.0590i -0.0413 - 0.0444i -0.0525 - 0.0463i -0.0443 - 0.0620i -0.0437 - 0.0509i -0.0493 - 0.0542i -0.0319 - 0.0680i -0.0462 - 0.0528i -0.0454 - 0.0592i -0.0268 - 0.0684i -0.0432 - 0.0600i -0.0441 - 0.0657i -0.0224 - 0.0636i -0.0357 - 0.0665i -0.0408 - 0.0827i -0.0175 - 0.0683i -0.0321 - 0.0732i -0.0356 - 0.0923i -0.0214 - 0.0672i -0.0343 - 0.0637i -0.0331 - 0.0822i -0.0226 - 0.0526i -0.0255 - 0.0512i -0.0112 - 0.0593i -0.0048 - 0.0419i -0.0041 - 0.0517i 0.0168 - 0.0496i 0.0108 - 0.0439i 0.0097 - 0.0560i 0.0260 - 0.0494i 0.0180 - 0.0487i 0.0285 - 0.0590i 0.0410 - 0.0483i 0.0267 - 0.0527i 0.0364 - 0.0612i 0.0423 - 0.0490i 0.0315 - 0.0656i 0.0323 - 0.0639i 0.0407 - 0.0474i 0.0339 - 0.0670i 0.0384 - 0.0613i 0.0303 - 0.0418i 0.0453 - 0.0503i 0.0482 - 0.0556i 0.0356 - 0.0467i 0.0456 - 0.0447i 0.0533 - 0.0427i 0.0476 - 0.0432i 0.0549 - 0.0403i 0.0622 - 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0.0349i -0.0169 - 0.0320i -0.0189 - 0.0342i -0.0098 - 0.0398i -0.0201 - 0.0349i -0.0193 - 0.0385i -0.0080 - 0.0424i -0.0199 - 0.0407i -0.0214 - 0.0445i -0.0092 - 0.0423i -0.0187 - 0.0455i -0.0240 - 0.0559i -0.0103 - 0.0459i -0.0222 - 0.0493i -0.0265 - 0.0629i -0.0185 - 0.0452i -0.0281 - 0.0417i -0.0298 - 0.0535i -0.0217 - 0.0329i -0.0242 - 0.0316i -0.0163 - 0.0363i -0.0106 - 0.0254i -0.0117 - 0.0315i 0.0013 - 0.0317i -0.0024 - 0.0265i -0.0036 - 0.0343i 0.0064 - 0.0328i 0.0026 - 0.0292i 0.0065 - 0.0362i 0.0146 - 0.0333i 0.0051 - 0.0318i 0.0092 - 0.0380i 0.0154 - 0.0328i 0.0071 - 0.0404i 0.0082 - 0.0381i 0.0141 - 0.0311i 0.0085 - 0.0412i 0.0102 - 0.0358i 0.0097 - 0.0255i 0.0177 - 0.0294i 0.0180 - 0.0313i 0.0156 - 0.0275i 0.0199 - 0.0266i 0.0244 - 0.0254i 0.0237 - 0.0250i 0.0276 - 0.0257i 0.0349 - 0.0271i 0.0298 - 0.0344i 0.0314 - 0.0293i 0.0390 - 0.0299i 0.0356 - 0.0292i 0.0356 - 0.0327i 0.0432 - 0.0313i 0.0428 - 0.0334i 0.0412 - 0.0370i 0.0483 - 0.0371i 0.0477 - 0.0355i 0.0433 - 0.0411i 0.0485 - 0.0429i 0.0560 - 0.0469i 0.0506 - 0.0506i 0.0505 - 0.0497i 0.0521 - 0.0464i 0.0515 - 0.0553i 0.0450 - 0.0571i 0.0445 - 0.0521i 0.0451 - 0.0575i 0.0441 - 0.0567i 0.0468 - 0.0504i 0.0441 - 0.0584i 0.0483 - 0.0607i 0.0392 - 0.0545i 0.0446 - 0.0549i 0.0447 - 0.0519i 0.0348 - 0.0528i 0.0351 - 0.0499i 0.0316 - 0.0532i 0.0359 - 0.0489i 0.0308 - 0.0455i 0.0355 - 0.0397i 0.0325 - 0.0479i 0.0326 - 0.0395i 0.0356 - 0.0437i 0.0283 - 0.0376i 0.0251 - 0.0288i 0.0357 - 0.0321i 0.0311 - 0.0293i 0.0288 - 0.0244i 0.0382 - 0.0199i 0.0337 - 0.0195i 0.0329 - 0.0187i 0.0372 - 0.0164i 0.0337 - 0.0140i 0.0292 - 0.0148i 0.0259 - 0.0039i 0.0333 - 0.0037i 0.0316 + 0.0033i 0.0339 + 0.0148i 0.0319 + 0.0212i 0.0410 + 0.0196i 0.0427 + 0.0183i 0.0398 + 0.0094i 0.0464 + 0.0163i 0.0500 + 0.0215i 0.0616 + 0.0233i 0.0648 + 0.0277i 0.0664 + 0.0233i 0.0650 + 0.0283i 0.0704 + 0.0257i 0.0743 + 0.0117i 0.0673 + 0.0158i 0.0684 + 0.0205i 0.0737 + 0.0091i 0.0688 + 0.0116i 0.0663 + 0.0130i 0.0722 + 0.0097i 0.0626 + 0.0103i 0.0618 + 0.0108i 0.0618 + 0.0159i 0.0572 + 0.0098i 0.0609 + 0.0028i 0.0575 + 0.0092i 0.0604 + 0.0055i 0.0566 + 0.0065i 0.0513 + 0.0166i 0.0552 + 0.0082i 0.0529 + 0.0062i 0.0452 + 0.0049i 0.0366 + 0.0216i 0.0478 + 0.0107i
  4 Comments
Voss
Voss on 27 Oct 2022
I'm not sure how you'd use interp for this, but here it is using interp1:
load('R_f.mat')
load('mat_up.mat')
idx = abs(R_f) <= 0.5;
mat_up(idx,:) % check old values
ans =
-0.0326 + 0.0266i -0.0345 + 0.0205i -0.0259 + 0.0221i -0.0263 + 0.0262i -0.0253 + 0.0177i -0.0173 + 0.0158i -0.0158 + 0.0122i -0.0142 + 0.0036i -0.0147 - 0.0021i -0.0213 - 0.0086i -0.0142 - 0.0155i -0.0193 - 0.0176i -0.0367 - 0.0306i -0.0294 - 0.0239i -0.0317 - 0.0159i -0.0395 - 0.0310i -0.0374 - 0.0305i -0.0423 - 0.0176i -0.0440 - 0.0278i -0.0408 - 0.0229i -0.0461 - 0.0118i -0.0397 - 0.0230i -0.0357 - 0.0235i -0.0510 - 0.0215i -0.0442 - 0.0265i -0.0416 - 0.0183i -0.0517 - 0.0193i -0.0472 - 0.0271i -0.0473 - 0.0170i -0.0591 - 0.0241i -0.0573 - 0.0189i -0.0628 - 0.0097i -0.0644 - 0.0062i -0.0603 - 0.0032i -0.0621 + 0.0054i -0.0645 + 0.0136i -0.0541 + 0.0226i -0.0516 + 0.0267i -0.0499 + 0.0282i -0.0392 + 0.0329i -0.0387 + 0.0332i -0.0387 + 0.0294i -0.0319 + 0.0396i -0.0301 + 0.0369i -0.0208 + 0.0333i -0.0156 + 0.0387i -0.0139 + 0.0297i -0.0113 + 0.0297i -0.0130 + 0.0314i -0.0079 + 0.0251i -0.0050 + 0.0275i -0.0101 + 0.0310i -0.0005 + 0.0266i 0.0001 + 0.0274i -0.0015 + 0.0272i 0.0099 + 0.0243i 0.0126 + 0.0218i 0.0114 + 0.0204i 0.0172 + 0.0190i 0.0226 + 0.0113i 0.0211 + 0.0131i 0.0243 + 0.0074i 0.0333 + 0.0005i 0.0258 + 0.0012i 0.0264 - 0.0073i 0.0332 - 0.0108i 0.0250 - 0.0136i 0.0262 - 0.0198i 0.0357 - 0.0170i 0.0227 - 0.0202i 0.0232 - 0.0272i 0.0274 - 0.0222i 0.0195 - 0.0266i 0.0205 - 0.0294i 0.0261 - 0.0242i 0.0144 - 0.0304i 0.0169 - 0.0324i 0.0223 - 0.0261i 0.0127 - 0.0347i 0.0117 - 0.0364i 0.0150 - 0.0293i 0.0082 - 0.0343i 0.0068 - 0.0416i 0.0097 - 0.0304i 0.0014 - 0.0345i 0.0005 - 0.0448i -0.0010 - 0.0297i -0.0101 - 0.0285i -0.0093 - 0.0337i -0.0089 - 0.0190i -0.0120 - 0.0181i -0.0069 - 0.0180i -0.0060 - 0.0112i -0.0072 - 0.0146i -0.0011 - 0.0121i -0.0044 - 0.0076i -0.0065 - 0.0116i -0.0024 - 0.0091i -0.0034 - 0.0085i 0.0005 - 0.0105i -0.0005 - 0.0078i -0.0015 - 0.0080i -0.0029 - 0.0073i -0.0016 - 0.0097i -0.0014 - 0.0089i -0.0039 - 0.0074i -0.0003 - 0.0065i -0.0033 - 0.0073i -0.0043 - 0.0039i -0.0030 - 0.0017i 0.0030 - 0.0008i 0.0001 + 0.0021i 0.0027 - 0.0015i 0.0035 + 0.0020i 0.0061 + 0.0030i 0.0101 + 0.0005i 0.0124 + 0.0031i 0.0144 - 0.0015i 0.0152 - 0.0080i 0.0154 - 0.0069i 0.0232 - 0.0070i 0.0208 - 0.0078i 0.0200 - 0.0125i 0.0257 - 0.0099i 0.0265 - 0.0144i 0.0267 - 0.0182i 0.0336 - 0.0203i 0.0328 - 0.0205i 0.0306 - 0.0263i 0.0371 - 0.0310i 0.0391 - 0.0342i 0.0384 - 0.0362i 0.0375 - 0.0400i 0.0365 - 0.0390i 0.0382 - 0.0479i 0.0303 - 0.0505i 0.0319 - 0.0479i 0.0311 - 0.0536i 0.0291 - 0.0555i 0.0333 - 0.0504i 0.0291 - 0.0576i 0.0344 - 0.0604i 0.0278 - 0.0574i 0.0295 - 0.0595i 0.0310 - 0.0584i 0.0211 - 0.0587i 0.0197 - 0.0585i 0.0193 - 0.0623i 0.0184 - 0.0554i 0.0154 - 0.0576i 0.0181 - 0.0534i 0.0128 - 0.0576i 0.0151 - 0.0552i 0.0115 - 0.0579i 0.0062 - 0.0460i 0.0042 - 0.0429i 0.0122 - 0.0442i 0.0057 - 0.0416i 0.0068 - 0.0318i 0.0157 - 0.0318i 0.0086 - 0.0283i 0.0084 - 0.0277i 0.0143 - 0.0242i 0.0121 - 0.0167i 0.0050 - 0.0199i 0.0079 - 0.0099i 0.0152 - 0.0085i 0.0071 - 0.0060i 0.0197 + 0.0018i 0.0124 + 0.0122i 0.0173 + 0.0086i 0.0264 + 0.0013i 0.0205 - 0.0057i 0.0306 + 0.0061i 0.0298 + 0.0119i 0.0446 + 0.0131i 0.0451 + 0.0156i 0.0495 + 0.0120i 0.0459 + 0.0183i 0.0528 + 0.0176i 0.0556 + 0.0033i 0.0527 + 0.0055i 0.0538 + 0.0087i 0.0615 - 0.0032i 0.0564 + 0.0002i 0.0529 + 0.0010i 0.0581 - 0.0043i 0.0507 + 0.0025i 0.0519 - 0.0005i 0.0533 + 0.0025i 0.0415 - 0.0063i 0.0493 - 0.0162i 0.0470 - 0.0045i 0.0468 - 0.0152i 0.0426 - 0.0050i 0.0433 + 0.0035i 0.0462 - 0.0074i 0.0448 - 0.0087i 0.0397 - 0.0137i 0.0256 - 0.0016i 0.0487 - 0.0092i -0.0154 - 0.0592i 0.0059 - 0.0779i 0.0073 - 0.0573i -0.0033 - 0.0714i 0.0278 - 0.0806i 0.0206 - 0.0769i 0.0058 - 0.0931i 0.0310 - 0.0876i 0.0260 - 0.0811i 0.0192 - 0.1106i 0.0444 - 0.0934i 0.0368 - 0.0913i 0.0417 - 0.1333i 0.0359 - 0.1047i 0.0243 - 0.0912i 0.0545 - 0.1122i 0.0549 - 0.1116i 0.0285 - 0.1076i 0.0525 - 0.1126i 0.0503 - 0.1074i 0.0247 - 0.1084i 0.0463 - 0.1042i 0.0561 - 0.0903i 0.0439 - 0.1105i 0.0515 - 0.1078i 0.0512 - 0.0976i 0.0423 - 0.1038i 0.0590 - 0.0980i 0.0496 - 0.0806i 0.0571 - 0.0899i 0.0592 - 0.0863i 0.0586 - 0.0813i 0.0506 - 0.0824i 0.0566 - 0.0725i 0.0566 - 0.0660i 0.0543 - 0.0735i 0.0625 - 0.0643i 0.0558 - 0.0554i 0.0650 - 0.0606i 0.0633 - 0.0513i 0.0578 - 0.0410i 0.0704 - 0.0372i 0.0732 - 0.0337i 0.0673 - 0.0260i 0.0732 - 0.0217i 0.0801 - 0.0132i 0.0775 - 0.0083i 0.0861 + 0.0018i 0.1014 + 0.0025i 0.0900 + 0.0060i 0.0946 + 0.0025i 0.1204 + 0.0334i 0.1034 + 0.0191i 0.1120 + 0.0149i 0.1243 + 0.0528i 0.1173 + 0.0183i 0.1286 + 0.0025i 0.1180 + 0.0487i 0.1273 + 0.0222i 0.1520 + 0.0036i 0.1189 + 0.0396i 0.1317 + 0.0219i 0.1781 + 0.0196i 0.1226 + 0.0289i 0.1319 + 0.0108i 0.1594 + 0.0313i 0.1231 + 0.0185i 0.1315 + 0.0110i 0.1531 + 0.0540i 0.1147 + 0.0221i 0.1329 + 0.0096i 0.1291 + 0.0447i 0.1094 + 0.0167i 0.1209 + 0.0154i 0.1063 + 0.0477i 0.1012 + 0.0098i 0.1053 + 0.0152i 0.0902 + 0.0421i 0.0920 + 0.0099i 0.0903 + 0.0141i 0.0656 + 0.0263i 0.0690 + 0.0188i 0.0713 + 0.0261i 0.0440 + 0.0298i 0.0448 + 0.0280i 0.0458 + 0.0321i 0.0224 + 0.0299i 0.0202 + 0.0286i 0.0178 + 0.0435i 0.0059 + 0.0343i 0.0028 + 0.0346i -0.0077 + 0.0463i -0.0131 + 0.0360i -0.0179 + 0.0428i -0.0344 + 0.0433i -0.0327 + 0.0461i -0.0361 + 0.0544i -0.0505 + 0.0477i -0.0401 + 0.0513i -0.0496 + 0.0608i -0.0684 + 0.0477i -0.0513 + 0.0575i -0.0694 + 0.0697i -0.0723 + 0.0458i -0.0589 + 0.0730i -0.0643 + 0.0751i -0.0679 + 0.0507i -0.0660 + 0.0782i -0.0752 + 0.0790i -0.0567 + 0.0547i -0.0670 + 0.0695i -0.0782 + 0.0841i -0.0503 + 0.0629i -0.0642 + 0.0668i -0.0700 + 0.0661i -0.0515 + 0.0624i -0.0572 + 0.0611i -0.0606 + 0.0539i -0.0498 + 0.0615i -0.0512 + 0.0471i -0.0431 + 0.0488i -0.0464 + 0.0416i -0.0451 + 0.0354i -0.0444 + 0.0351i -0.0434 + 0.0285i -0.0353 + 0.0233i -0.0296 + 0.0182i -0.0284 + 0.0103i -0.0244 + 0.0068i -0.0247 - 0.0036i -0.0261 - 0.0098i -0.0214 - 0.0113i -0.0230 - 0.0232i -0.0227 - 0.0333i -0.0192 - 0.0373i -0.0292 - 0.0446i -0.0244 - 0.0456i -0.0253 - 0.0557i -0.0307 - 0.0641i -0.0183 - 0.0668i -0.0301 - 0.0715i -0.0294 - 0.0822i -0.0230 - 0.0789i -0.0243 - 0.0867i -0.0253 - 0.0977i -0.0291 - 0.0935i -0.0378 - 0.1017i -0.0373 - 0.1140i -0.0323 - 0.0916i -0.0435 - 0.1066i -0.0334 - 0.1076i -0.0445 - 0.1133i -0.0401 - 0.1169i -0.0572 - 0.1186i -0.0620 - 0.1086i -0.0551 - 0.0982i -0.0505 - 0.1083i -0.0653 - 0.1063i -0.0616 - 0.0852i -0.0479 - 0.1011i -0.0547 - 0.0859i -0.0545 - 0.0713i -0.0413 - 0.0814i -0.0461 - 0.0677i -0.0515 - 0.0716i -0.0303 - 0.0650i -0.0401 - 0.0646i -0.0327 - 0.0550i -0.0088 - 0.0550i -0.0225 - 0.0547i -0.0187 - 0.0658i -0.0166 - 0.0594i -0.0057 - 0.0662i -0.0078 - 0.0573i -0.0050 - 0.0530i 0.0147 - 0.0582i 0.0143 - 0.0553i 0.0198 - 0.0618i 0.0253 - 0.0527i 0.0318 - 0.0578i 0.0319 - 0.0681i 0.0366 - 0.0662i 0.0426 - 0.0638i 0.0439 - 0.0777i 0.0414 - 0.0754i 0.0382 - 0.0772i 0.0466 - 0.0883i 0.0334 - 0.0676i 0.0393 - 0.0687i 0.0448 - 0.0716i 0.0350 - 0.0852i 0.0398 - 0.0875i 0.0488 - 0.0809i 0.0349 - 0.0877i 0.0338 - 0.0791i 0.0486 - 0.0655i 0.0577 - 0.0669i 0.0497 - 0.0818i 0.0570 - 0.0799i 0.0415 - 0.0695i 0.0605 - 0.0865i
mat_up(idx,:) = NaN;
mat_up(idx,:) = interp1(find(~idx),mat_up(~idx,:),find(idx));
mat_up(idx,:) % check new values
ans =
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