title: Matlab: Interpolating two different datasets to read graphs between plotted lines
body: <p>I am working on my thesis and I am trying to read off an empirical graph which has been digitalized. This can be done by a data cursor of course. However I need to automate this process since the data in the graphs is going to be used for some other equations in an iterative manner. </p>
  
  <p>This graph contains different sets of data. The X-axis has a constant range while the Y values depend on the thickness of an airfoil. Hence, 30% thickness has a different data set compared to that of an airfoil having 35% thickness.</p>
  
  <p>Now I know how to read the graphs with a written code. But I only know it when my calculated airfoil thickness is either 30% or %35 exactly since I have the numerical data sets.</p>
  
  <p>Sometimes, I calculate an airfoil thickness between 30% and 35% and for this case I don't have a concrete dataset, See the space between the red and blue line in the link below:</p>
  
  <p>blue line corresponds to the 30% thickness data set and the red line corresponds to the 35% thickness dataset.</p>
  
  <p><a href="http://i.imgur.com/YUs6RYO.jpg" rel="nofollow">http://i.imgur.com/YUs6RYO.jpg</a></p>
  
  <p>So how would one interpolate this three dimensional problem? I don't really need an extra data set for say a thickness of 32% just the Y value would be enough.</p>
  
  <p>(for example, say I've calculated a thickness of 32%, I need the Y value corresponding to X = 4). X is also calculated so its a constant for each iteration. Also, the interpolated value should not necessarily be saved. </p>
  
  <p>And here are the datasets for the 30%:</p>
  
  <p><code>-0.003287690575036084  0.8053924336902605
  0.043171086183339424    0.8050602124925952
  0.08963141038123656 0.8049872858882297
  0.1360917345791337  0.804914359283864
  0.18255205877703085 0.8048414326794985
  0.22901393041444962 0.8050278006684327
  0.2754727071728251  0.8046955794707673
  0.32193303137072227 0.8046226528664018
  0.3683933555686194  0.8045497262620362
  0.41485367976651655 0.8044767996576706
  0.4613140039644137  0.8044038730533051
  0.5077928974365709  0.807442481568537
  0.554253221634468   0.8073695549641714
  0.6007135458323651  0.8072966283598059
  0.6471738700302623  0.8072237017554403
  0.6936341942281594  0.8071507751510747
  0.7400945184260566  0.8070778485467092
  0.7865548426239537  0.8070049219423436
  0.8330151668218508  0.806931995337978
  0.879475491019748   0.8068590687336125
  0.9259358152176451  0.8067861421292469
  0.9723914970969771  0.805935331744982
  1.0188580110529613  0.8068995835138155
  1.0653616635574645  0.8140869055218445
  1.1118746006990976  0.8228299950896718
  1.1556231476667052  0.8317626359505925
  1.2029940294916959  0.8452458101065382
  1.2514872249891795  0.8614276158935545
  1.2980594290644916  0.8801016883847644
  1.3428742623455985  0.8991957518202068
  1.3834632352399387  0.9179287180691845
  1.4240523769458633  0.9366899710010677
  1.4670993309116496  0.9544431793698794
  1.5108094611858853  0.9771597061348987
  1.5560453105579366  0.996026813137967
  1.599090576407881   1.0134971546777245
  1.6396876522582617  1.033587881706163
  1.6802729112977504  1.0516985409312212
  1.721977391140349   1.0686193915565696
  1.759264865239414   1.0885371057408935
  1.8027351648960062  1.106453713901426
  1.8475635031038473  1.127810711969303
  1.8899200176903397  1.1478279599191006
  1.9329627513665215  1.1648740012152765
  1.9743393991126437  1.185840399970377
  2.007525709721886   1.1997514536139606
  2.04520726180335        1.2178772782578813
  2.0882668766379497  1.2377519878446006
  2.12885563007723        1.2564481814058013
  2.169441108571778   1.2745956133186365
  2.214272434744659   1.2964532856739395
  2.254879183498814   1.3181648396328591
  2.2979393047681658  1.3381244092682947
  2.3385460028788447  1.3598274772223429
  2.3773808546019755  1.3795249530614826
  2.416215706325106   1.3992224289006225
  2.4568104188133093  1.418917142368385
  2.501617655573127   1.4367383050730829
  2.548189395416583   1.4553345891863025
  2.593000852466006   1.4738629189636363
  2.641319257635704   1.490245364991704
  2.6840014566601855  1.5058571953458966
  2.7334538841264777  1.5205811105296216
  2.780967627778736   1.534832690900812
  2.8274836597994124  1.5440943696552392
  2.875656557422194   1.5529459809557538
  2.9205079866431563  1.5613212541975945
  2.9670069968290953  1.567730692425724
  3.013495174938382   1.5723250685007546
  3.0599771632895827  1.5758822662025862
  3.106451414443174   1.5781429909379188
  3.1529287604758096  1.580922304859851
  3.1994030116294008  1.5831830295951836
  3.2458849999806016  1.5867402272970152
  3.2923499664970635  1.587445184472549
  3.338818027892569   1.5886687308346825
  3.38527216233238        1.5875586258571177
  3.4317108223769734  1.583855574946555
  3.4781726940143933  1.5840419429354893
  3.5246314707727677  1.5837097217378238
  3.5710763205754494  1.5810438492004604
  3.6175258126966945  1.579155860442996
  3.6639675676203325  1.5759713987190331
  3.7131639859552887  1.5709675339726639
  3.7568433402699988  1.5683060023046078
  3.8032742631169842  1.563306478427546
  3.8497082808430134  1.558825543737084
  3.896136108810956   1.5533074306734227
  3.94256548421842        1.5480486122030612
  3.988994859625884   1.5427897937326998
  4.035421140154305   1.5370123860757385
  4.081836588606075   1.529419916265679
  4.128252037057845   1.5218274464556192
  4.174667485509614   1.5142349766455596
  4.221086028840427   1.5071610960220996
  4.264731118422872   1.4987580412166908
  4.31392156806253        1.4927540401818795
  4.360340111393343   1.4856801595584195
  4.406757107284634   1.4783469843416595
  4.453175650615448   1.4712731037181994
  4.499600383704346   1.4652364014679387
  4.546023569353724   1.458940404624378
  4.592451397321666   1.4534222915607167
  4.638882320168652   1.4484227676836547
  4.685311695576116   1.4431639492132935
  4.73173952354406        1.437645836149632
  4.778173541270088   1.43316490145917
  4.824602916677553   1.4279060829888084
  4.871050861359277   1.4257587996380445
  4.917486426524827   1.4215371595408821
  4.963921991690379   1.41731551944372
  5.010357556855929   1.4130938793465577
  5.056800859219089   1.4101687122158943
  5.103258088537942   1.409577196424929
  5.149710675538231   1.4082077968540645
  5.188422196331486   1.407239493607210</code></p>
  
  <p>and the 35% case</p>
  
  <p><code>0.006168966650546004   0.8044498654339525
  0.05251074466351513 0.8041649550926027
  0.09885097179873537 0.8041405922130573
  0.1451911989339556  0.8041162293335119
  0.19153142606917584 0.8040918664539666
  0.2378701023266474  0.8043280510362257
  0.28421188033961653 0.8040431406948759
  0.33055210747483676 0.8040187778153305
  0.376892334610057   0.8039944149357852
  0.42323256174527746 0.8039700520562398
  0.4695727888804977  0.8039456891766945
  0.5158944054827321  0.8070478958388025
  0.5622346326179524  0.8070235329592572
  0.6085748597531726  0.8069991700797119
  0.6549150868883928  0.8069748072001666
  0.7012553140236131  0.8069504443206211
  0.7475955411588333  0.8069260814410758
  0.7939357682940535  0.8069017185615305
  0.8402759954292742  0.8068773556819852
  0.8866162225644945  0.8068529928024398
  0.9329564496997147  0.8068286299228944
  0.9793013294681812  0.8060226246579357
  1.0256369039701552  0.8067799041638037
  1.071932155650659   0.8143114176765875
  1.1187799629176767  0.8216937568912026
  1.1617476956110715  0.8321674748214614
  1.20883433805141        0.8457655870362711
  1.2570081679490785  0.8620765348918837
  1.3032362666230588  0.8808897535008002
  1.347706558159841   0.9001231394982395
  1.3879672317285157  0.9188329081527227
  1.4282258750572274  0.9378837571208412
  1.472706881749366   0.9553169970185403
  1.5124760398627677  0.9779636470492524
  1.551459748890828   0.9949497419759024
  1.5941903785600746  1.0115548900587519
  1.6344423390155782  1.0317284617259186
  1.6747003901909685  1.0508787924521803
  1.71742594426031        1.0683366413191173
  1.7594253491698706  1.0898309763652727
  1.8021487038125867  1.1076583289053143
  1.8423992261814504  1.1280734991279724
  1.8826578695101626  1.1471243480960909
  1.9271326726913052  1.1655997778410079
  1.972291271970799   1.1871540357272572
  2.00704079571732        1.202828964772921
  2.0444053954250387  1.2215082798279724
  2.0871182604946177  1.2410978806551278
  2.127378223479305   1.2599270274193834
  2.167638930885312   1.2786311114019728
  2.2120949825445826  1.3002567968214347
  2.2565756226656166  1.3177516206646513
  2.2968395953742293  1.335907133809478
  2.3370983232962734  1.3549437710978616
  2.381577849605106   1.3726257153909196
  2.427805638103535   1.391491043492197
  2.4778943367576924  1.4104846150844144
  2.5171966806686945  1.42505456449785
  2.5645930555508722  1.44222572502541
  2.6111147353827078  1.458057391232824
  2.6590291034329954  1.4716178473302413
  2.7036702332173843  1.4790013466819776
  2.751618055916255   1.4869414218176131
  2.801789183722762   1.492086895814924
  2.8414799006551674  1.4970182761743256
  2.890545684656986   1.5025011808872442
  2.936856445114978   1.5074272197819834
  2.9831823266310216  1.5098129209241293
  3.0294888221752045  1.5154554653388308
  3.079683755955156   1.5166015357974434
  3.1221351571351703  1.521138783739438
  3.168472282514893   1.5216355157835015
  3.2147985517503748  1.5239560800601961
  3.261134126252348   1.5247133595660642
  3.3074743533875686  1.524688996686519
  3.353805275256295   1.5262279185778003
  3.4001361971250232  1.5277668404690816
  3.4464841786489866  1.5264397402805139
  3.492839914561696   1.5238099027829242
  3.539192548718906   1.5217011602089432
  3.585549835509364   1.5188107752495488
  3.631899367911078   1.5172231275991768
  3.6810223128356383  1.5131029972913028
  3.724610839736495   1.5119634526039971
  3.770966575649203   1.5093336151064072
  3.8173285150729073  1.5056615877615995
  3.8636904544966115  1.5019895604167919
  3.909506484952725   1.4973500753909907
  3.9580866226651925  1.4917413924785146
  4.002793332422961   1.4881074563025198
  4.049172331501902   1.4815694068778633
  4.0955466779475955  1.4758129998386198
  4.141921024393291   1.4700565927993767
  4.188298472594484   1.4637790908365245
  4.234679022551173   1.4569804939500635
  4.28106267426336        1.4496608021399933
  4.327446325975549   1.4423411103299233
  4.373831528565486   1.434760871058049
  4.420213629399925   1.4277017267097833
  4.4665972811121115  1.4203820348997134
  4.512984034579798   1.4125412481660344
  4.559364584536487   1.4057426512795734
  4.606304779806543   1.3976038059838376
  4.652133438838613   1.390842720197629
  4.69851553967305    1.3837835758493635
  4.7448991913852385  1.3764638840392935
  4.794049165893421   1.3678027836828277
  4.826065929248319   1.3644360657570844</code></p>
  
  <p>first column is X and second column is Y</p>
  
  <p>I hope I'm clear enough. Let me know if you need more information</p>
  
  <p>Thank you very much!</p>
  
  <p>I know that both datasets should be interpolated with interp1 to obtain a data set which has the same size and has the same X axis range.</p>