how to solve if interpolated data also contains NaN values

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Ismita
Ismita 2024-3-13
评论： Ismita 2024-3-13
I was trying to interpolate 'lat' and 'long' columns but even after interpolation first 4 data are still showing as NaN. For other data, interpolation is ok. I request for help /suggestion for the first 4 data. Thanks!
% Initialize lat_clean and long_clean with NaN values
lat_clean = NaN(size(lat));
long_clean = NaN(size(long));
% Update lat_clean and long_clean if the corresponding values in lat and long are not 9999.9
for i = 1:length(lat)
if (lat(i) ~= 9999.9) && (long(i) ~= 9999.9)
lat_clean(i) = lat(i);
long_clean(i) = long(i);
end
end
% Linear interpolation of NaN data
t_lat = 1:numel(lat_clean);
nan_lat = isnan(lat_clean);
lat_clean(nan_lat) = interp1(t_lat(~nan_lat), lat_clean(~nan_lat), t_lat(nan_lat));
t_long = 1:numel(long_clean);
nan_long = isnan(long_clean);
long_clean(nan_long) = interp1(t_long(~nan_long), long_clean(~nan_long), t_long(nan_long));
% Concatenate data to form new matrix
new_data = [time_numeric, density_dir, speed_dir, temperature_dir, distance_AU, lat_clean, long_clean];
% Write the new data to a text file
NHVOY2_Data = 'NH_VOY2_Data.txt'; % Replace with the desired output file path
dlmwrite(NHVOY2_Data, new_data, 'delimiter', '\t', 'precision', '%.6f');
result showing as
lat_clean =
NaN
NaN
NaN
NaN
-1.4000
-1.2000
-0.9000
-1.0000
-0.3000
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Ismita
Ismita 2024-3-13
移动：Sam Chak 2024-3-13
Thank you. In the attached file of the data, last column is for long and second last column is for lat.

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采纳的回答

Chunru
Chunru 2024-3-13
Ran in:
a = readmatrix("https://www.mathworks.com/matlabcentral/answers/uploaded_files/1641181/V2_small.txt");
a(a>9999.8) = nan
a = 24x6
1.0e+03 * 1.9920 0.1230 0 0.0372 NaN NaN 1.9920 0.1230 0.0010 0.0372 NaN NaN 1.9920 0.1230 0.0020 0.0372 NaN NaN 1.9920 0.1230 0.0030 0.0372 NaN NaN 1.9920 0.1230 0.0040 0.0372 -0.0014 0.0006 1.9920 0.1230 0.0050 0.0372 -0.0012 0.0008 1.9920 0.1230 0.0060 0.0372 -0.0009 0.0008 1.9920 0.1230 0.0070 0.0372 -0.0010 0.0007 1.9920 0.1230 0.0080 0.0372 -0.0003 -0.0002 1.9920 0.1230 0.0090 0.0372 -0.0005 -0.0002
b = fillmissing(a, 'linear')
b = 24x6
1.0e+03 * 1.9920 0.1230 0 0.0372 -0.0022 -0.0002 1.9920 0.1230 0.0010 0.0372 -0.0020 -0.0000 1.9920 0.1230 0.0020 0.0372 -0.0018 0.0002 1.9920 0.1230 0.0030 0.0372 -0.0016 0.0004 1.9920 0.1230 0.0040 0.0372 -0.0014 0.0006 1.9920 0.1230 0.0050 0.0372 -0.0012 0.0008 1.9920 0.1230 0.0060 0.0372 -0.0009 0.0008 1.9920 0.1230 0.0070 0.0372 -0.0010 0.0007 1.9920 0.1230 0.0080 0.0372 -0.0003 -0.0002 1.9920 0.1230 0.0090 0.0372 -0.0005 -0.0002

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