Error using scatteredInterpolant on missing data

Hello everyone,

I would like to use function scatteredInterpolant or interp1 to compare results with fillmissing function and inpaint_nans on the leading or trailing missing values (NaN)/ peak at the edge as attached file.

However, it has this error when I tried to input the data. I tried to read some instruction on MATLAB, but my data, it does not have any functions of x and y for z. Could anyone please help me figure out the reason to input the data properly?.

Thank you very much!

T = readtable ('data.csv') 

T = 48×78 table
    Var1    Var2     Var3      Var4      Var5      Var6      Var7      Var8      Var9     Var10     Var11     Var12     Var13     Var14     Var15     Var16     Var17     Var18     Var19     Var20     Var21     Var22     Var23     Var24     Var25     Var26     Var27     Var28     Var29     Var30     Var31     Var32     Var33     Var34     Var35     Var36     Var37     Var38     Var39     Var40     Var41     Var42     Var43     Var44     Var45     Var46     Var47     Var48     Var49     Var50     Var51     Var52     Var53     Var54     Var55     Var56     Var57     Var58     Var59     Var60     Var61     Var62     Var63     Var64     Var65     Var66     Var67     Var68     Var69     Var70     Var71     Var72     Var73     Var74     Var75     Var76     Var77     Var78 
    ____    ____    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______    ______

    NaN     220        225       230       235       240       245       250       255       260       265       270       275       280       285       290       295       300       305       310       315       320       325       330       335       340       345       350       355       360       365       370       375       380       385       390       395       400       405       410       415       420       425       430       435       440       445       450       455       460       465       470       475       480       485       490       495       500       505       510       515       520       525       530       535       540       545       550       555       560       565       570       575       580       585       590       595       600
    220       0     2.5291    4.9719    7.3376    9.6358    11.876    14.067    16.142    18.555    19.379    22.763    27.167    33.454     39.96    49.029    58.273    70.904    80.704    92.344    111.66    140.53    176.26    222.44    284.14    357.17    492.42    876.46       NaN       NaN       NaN       NaN       NaN       NaN       NaN       NaN    860.63    842.97    839.29    857.11     856.6     851.1    833.65    815.51    795.43    775.14    756.35    740.79    730.19    726.27    738.09    713.27    652.12    574.65    500.84    450.67    426.03    375.58    349.23    323.76    296.29     272.8       255    227.99    204.68    186.53    170.45    158.08    144.13    134.67    117.42    106.98    94.146    79.954    70.347    62.752    53.511    47.649
    225       0     2.3454    4.5736    6.6946    8.7186    10.656    12.516    14.309    15.938    16.093    18.621     23.33    28.919    34.137    46.978    56.433    63.981     75.15    86.962    104.25     132.6    176.47    213.42    268.34    338.89    449.63    758.19       NaN       NaN       NaN       NaN       NaN       NaN       NaN    928.86    816.35    807.32    798.92    832.64    831.66    821.93    801.63    777.59    762.99    750.44    740.69    731.62    721.11    707.05    687.31    659.79    549.98     501.4    458.02    416.97    379.09    345.25    317.29    292.13    269.32    240.14    220.56    198.53    179.09     166.2    149.51    135.39    122.35    111.93    102.98    88.039    77.718     65.74    57.572    51.801    46.011     42.86
    230       0          0    3.9109    5.7736    7.5808     9.337    11.047    12.716    14.347    15.947    17.441    19.855    21.406    28.783    37.509    49.468    58.689    68.949    79.181    91.367    118.75    153.91     193.5     237.6    300.07    391.26    632.38       NaN       NaN       NaN       NaN       NaN       NaN       NaN    860.19     773.2    782.34    784.78     804.8    808.58    819.79    784.53    771.31    748.79     735.4    709.82    680.97    650.52    618.53    585.04    550.09    513.73    476.01    433.86    394.32     359.2       326     295.6    268.87    247.35    218.56    200.03    180.53    160.23    142.44    129.75     116.7    105.83    97.123    86.956    74.889    65.953    54.317    51.251    43.055    38.219     34.51
    235       0          0         0    3.1716    4.5806    6.1327    7.8085    9.5882    11.452    13.381    15.355     17.75    19.162    23.332    29.925    37.485    46.616     56.52    67.022    82.487    104.15    131.02    164.82    208.68    266.96    349.06    545.05    778.52       NaN       NaN       NaN       NaN       NaN    955.73    817.79    764.31    771.01    785.21    794.13    807.57    805.07    783.83    770.46    745.19     732.3    714.69    718.82     663.1    618.79    579.52    543.52    509.06    474.39    437.74    397.37       351    314.75    285.32    258.57    233.93    210.85    188.75    168.68    150.78    133.83    117.69    109.39    96.963     85.78    76.735    65.421    57.772    48.761      41.9    38.387    32.356    30.457
    240       0          0         0         0    5.6491    7.1198    8.6101    10.118    11.641    13.178    14.727    16.285    17.898    21.401     26.73    33.952     42.49    52.109    61.606     76.14    98.263    121.18    157.81    193.05     242.9    322.26    484.51    676.64       NaN       NaN       NaN       NaN    985.89    877.68     775.7    746.03    751.08    762.72    782.31    784.97    791.79    765.72    758.44    736.49    724.08    698.22    692.23    650.91    620.06    601.13     571.9    533.69    489.46    442.18    394.79    350.27    311.56    279.78    248.99    227.41    205.74    183.97    163.05    143.96    127.65    113.72    102.26    91.154    78.479    70.941    59.505    52.924    43.815    38.886    35.072    30.524    26.523
    245       0          0         0         0         0    10.141      11.8    13.348    14.789    16.128    17.369    18.519    19.581    20.424    24.843     32.37    40.192    47.656    59.313    76.853    99.512    127.69     160.8    198.44    244.47    307.94     445.2    603.33    795.54       968       NaN       NaN    878.93    799.51    710.65    699.07    714.35    721.21    736.32    747.03    744.09     736.3    725.43    709.28    695.49    681.77    667.95    628.15    599.09     582.3    547.76    484.39    440.01    401.38    367.16    336.04    306.69    277.78    247.99    218.93    193.69    175.84    158.53    141.46    125.06    109.77     96.23    85.268    76.698    66.312    55.993    48.141    40.773    35.997    29.842    26.896    24.102
    250       0          0         0         0         0         0    5.7471    7.6197    9.6875    11.926    14.309    16.814    19.414    22.085    26.094    32.257    40.324    49.966    63.624    79.413    108.35    140.88    173.12     215.2    259.57    317.13    427.94    563.26    701.74    838.27    905.88    842.11     767.2    706.82    645.53    635.28    649.79    664.95    682.03    687.74    694.07    685.87    677.66    664.54    660.16    639.59     634.4    594.13    567.51    547.43    519.32    456.69    421.65    386.05    355.43     326.8     299.7    273.68    248.26    222.98    197.38    172.05    148.93    130.57    115.81    103.58    92.528    82.083    71.673    61.369    52.675    43.936     37.22    31.482    28.787    25.601    22.098
    255       0          0         0         0         0         0         0    13.147    15.399    17.717     20.09    22.511     24.83    27.201    30.068    33.875    40.921     50.95    63.297    86.155    121.46    159.66    200.13     243.3    288.83    345.43    432.18    537.99    644.45    742.26    788.51     735.9    675.18    632.05    586.72    582.59     589.9    602.46    625.03    638.41    642.82    641.27    635.56    625.74    615.81    603.58    595.49    564.08     537.1    517.58    485.15    433.37    396.29    364.84    333.44     301.3    275.93    253.24    232.45    212.75    193.35    173.43    152.22    129.54    110.37    98.219    86.191    76.037     66.75    58.023    49.548    41.512    35.523    30.885    26.593    23.008    20.573
    260       0          0         0         0         0         0         0         0     12.09    14.812    17.681    20.662    23.718    27.311    31.929    37.572    44.241    54.036    69.094    93.649    141.22    185.95    228.84    281.06    334.29    378.58    455.19    536.27    617.95    689.11    710.84    676.11    630.61    587.88    560.13    555.17    557.89    566.54    586.38     593.9    600.28    594.72    587.41    581.56    576.95    562.71    549.64    522.13    499.21    480.67    452.48    402.61    371.29    340.44    305.48    279.24    250.43    227.03    208.88    193.24     179.1    165.45     151.3    135.64    117.45    93.956    81.441     70.85    62.039    54.505    47.456     40.89    34.804    29.195    24.381    21.413     18.64
    265       0          0         0         0         0         0         0         0         0    15.374    18.592    22.027    25.655    29.454     34.39    41.311    50.016    60.304     75.71    108.89    163.97    215.79    270.21    328.43    381.08    424.46    489.76     555.5    619.44    662.87    677.98    647.35    617.62    584.48    553.01    544.97    545.49     548.1    562.54    567.48    569.99     565.8    557.58    550.66    542.62    528.08    514.36     484.6    460.56    444.32    418.49     373.3    342.77    310.63    282.57    256.62    229.34    205.06    184.86     168.5     156.1    145.82    136.68    127.72    117.97    106.46    92.228     70.22    58.324    49.899    40.844    35.388    31.099    27.255    23.941    21.245    19.315
    270       0          0         0         0         0         0         0         0         0         0    22.194    26.438    30.966    35.759    40.795        47    55.826    68.049     84.44    120.32    188.05    246.86    305.15    368.98    424.16     468.2    529.19    588.33    638.95    676.56    683.98    656.79    633.06    598.83    568.67       556    553.15    556.65    563.52    568.49     562.4    555.19    546.31    534.13    521.44    506.68     491.3    464.62     439.5    416.84    393.26    351.43    321.65     291.4    265.02    238.03    212.13       191    170.85    154.38    137.63    125.47    116.55    109.39    103.14    96.975    90.041    81.502    70.516    51.168    39.531    33.596    29.356    25.667    22.962     20.72    19.255
    275       0          0         0         0         0         0         0         0         0         0         0    29.345    34.854    40.824    47.253    54.136    64.313    81.058    105.03    136.87    207.97    275.51    340.03    404.38    467.57    510.47    567.36     616.7    660.51    687.88     700.3    675.69    662.33    632.65       603    590.46    583.15    581.42    584.94    588.29    581.63    565.11    555.86    539.92    521.63    503.61     486.3    456.31    430.26    407.14    382.57    340.47    309.47    282.72     256.7    229.41    205.72    183.46     163.6    147.16    129.79    114.97    102.02    93.206    86.973    82.165    78.075        74    69.235    63.074    54.814     37.64    29.709    25.357    22.391    19.823    19.071
    280       0          0         0         0         0         0         0         0         0         0         0         0    38.313     44.39    50.817    57.571    64.634     77.24    109.76    163.79     228.6    293.45    360.77    431.26     492.5    539.37    595.26    652.41    696.22    722.16     729.6    712.24    696.71    672.62    648.27    629.15    621.33    621.41    623.67    619.72    608.63    590.71    577.85    558.83    542.86     517.1    496.14       465    434.97    406.96    380.21    339.34    308.75    279.95    252.31    227.19    200.86    178.01    159.88    141.35    125.63    111.26    98.806    88.658    78.356    71.912    67.631    64.527    62.003    59.459    56.299    51.923    45.734    28.751    22.519    19.661    17.736
    285       0          0         0         0         0         0         0         0         0         0         0         0         0    37.127    43.677    50.777     58.43     66.64    86.215    131.37    202.21    284.08    362.35    435.72    497.17     547.7    603.16    655.12    697.84    725.92    740.72    736.13    732.92    714.36    694.89    680.33    669.25    666.62    669.66    662.25    652.66    633.38    613.54    591.86    569.24    542.29    519.53    483.45    448.44    418.63     388.3    345.38    313.72     282.8    252.29    228.26    201.18    178.85    160.01    141.91    124.93    111.03    96.574    87.272     76.31     67.68    59.457    55.295    52.367    50.217    48.425     46.57    44.229    40.983     36.41    23.103    17.934
    290       0          0         0         0         0         0         0         0         0         0         0         0         0         0    36.699    44.272    52.738    62.141    72.523    118.74    182.71    259.56    339.64    413.31    476.88     527.6    585.93    644.91    694.51    731.39    747.82     760.9    766.53    753.46    739.73    727.94    720.07    720.82    723.52    713.97    701.85    683.92    660.94    636.53    611.03    579.21    547.99    510.45    470.17    439.36    405.67    359.38    322.97    290.68     259.3    231.35    203.94    180.72    159.97    142.58     125.2    111.54    96.505    85.595    75.318     67.29    58.558    50.707    44.885     40.93    38.996    37.287     35.83     34.65    33.774    33.229    33.042

data = table2array(T) ; 
x = data(1,:) ; x(1) = [] ;
y = data(:,1) ; y(1) = [] ;
z = data(2:end,2:end) ; 
F = scatteredInterpolant(x,y,z)

Error using scatteredInterpolant
The input points must be specified in column-vector format.

Error using scatteredInterpolant

The input points must be specified in column-vector format.

Answer 1

[Cris LaPierre]

When using the syntax F = scatteredInterpolant(x,y,v), your inputs must all be vectors. That means v=z(:), and that x and y are the same length as v. Try something like this.

T = readtable ('https://www.mathworks.com/matlabcentral/answers/uploaded_files/1203033/data.csv');
data = table2array(T) ; 
x = data(1,:) ; x(1) = [] ;
y = data(:,1) ; y(1) = [] ;
z = data(2:end,2:end) ; 

[X,Y] = meshgrid(x,y);
F = scatteredInterpolant(X(:),Y(:),z(:))

F = 
  scatteredInterpolant with properties:

                 Points: [3619×2 double]
                 Values: [3619×1 double]
                 Method: 'linear'
    ExtrapolationMethod: 'linear'

% visualize the result
[xq,yq] = meshgrid(linspace(400,450),linspace(150,200));
vq = F(xq,yq);
plot3(X(:),Y(:),z(:),'b.',xq,yq,vq,'r.')

[Gem]

Dear Cris LaPierre,

Thank you very much for your kind explanation, now I truly understand the data input and differences of results among functions to interpolate/extrapolate query points or missing data.

Best regards,

Nguyen Ngoc

Answer 2

[Kai]

Hi Ngoc, so for the scatteredInterpolant function, it's goal is to get the interpolant based on given x y z coordinates and the corresponding values on these coordinates. Based on your csv file, I am assuming you are trying to interpolate 2D data. In this case will be F = scatteredInterpolant (x,y,v), which the function itself is trying to get the F in v = F(x,y). After F is calculated, you can bring in the sampled point coordinate (x_s,y_s) in to F(x_s,y_s) to get the interpolate values.

As for the column-vector error, the scatteredInterpolant’s input data must be in sizes of m x 1, you can use transpose or reshape to change it into column-vector format to solve the error.

Also based on your code, you only extracted the values of x and y, but didn't match them into coordinate (x,y), and that is why the size of x and y arrays are different. I will recommend checking this example in the link and specifically the size differences of the sample array used in it: 2D interpolant sample

[Gem]

Dear Kai,

Thank you very much for your understandable comment.

I can learn a lot from your explanation, combined with Cris LaPierre 's comment. I can solve my problem.

Best regards,

Nguyen Ngoc