Make unequally spaced data, equally spaced
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Konstantinos Belivanis
il 28 Apr 2015
Commentato: Star Strider
il 1 Mag 2015
Hello all,
I have the hourly temperature history for a long period of time (100k datapoints) for several locations. For easier data manipulation I would like 24 measurements for each day. However the data I have, has sometimes either 2-4 measurements within the same hour or inversely there are some hours without any measurement.
The time spamps are of the format 200001010000 (YEARMODAHRMN). I would like to ask you if you can think or have any script that could do the interpolation between adjacent data so that finally I end up with data points that are equally spaced.
Thank you in advance.
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Star Strider
il 30 Apr 2015
Now that we have the data file, this is one option:
[d,s,r] = xlsread('Austin-Temperatures.xlsx');
d(any(isnan(d),2),:) = []; % Rmeove NaN Rows
ds = num2str(d(:,1), '%11d'); % Convert To Strings
dn = datenum(ds, 'yyyymmddHHMM'); % Date Numbers
dvck = datevec(dn); % Check Conversion
dn_intrp = datenum([dvck(1,1:4) 0 0]):(1/24):datenum([dvck(end,1:4) 0 0]);
T = interp1(dn, d(:,2), dn_intrp', 'linear','extrap');
figure(1)
plot(dn, d(:,2), 'gp', 'MarkerSize',10)
hold on
plot(dn_intrp, T, 'bp', 'MarkerFaceColor','c')
hold off
grid
datetick('x', 'HH:MM')
legend('Original Data', 'Hourly Interpolated Data','Location','N')
The ‘dn_intrp’ assignment creates a vector of hourly ‘date number’ values between the first hour value and the last hour value. It then uses that to interpolate the temperatures in the ‘T’ assignment. I set it to do a linear extrapolation, so here it creates a temperature at 3:00. Delete that if necessary simply by deleting it (the first element) from the ‘dn_intrp’ and ‘T’ vectors.
The plot is simply to illustrate the data the routine produces. It is not necessary for the code.
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Più risposte (1)
pfb
il 28 Apr 2015
Modificato: pfb
il 28 Apr 2015
Perhaps this is obvious, but
datenum(date,'yyyymmddhhMM');
where "date" is a char variable containing your timestamp, converts the date into a number. E.g.
datenum('200001010000','yyyymmddhhMM')
Gives
730486
and
dd=['200001010000';'200101010000']
datenum(dd,'yyyymmddhhMM')
gives
730486
730852
You can go through your timestamps individually, in a loop, or form a Nx12 matrix of chars and feed it to datenum. Either way you end with a Nx1 vector of numbers representing the timestamps, and you'll have a similar vector containing the corresponding temperatures.
At this point, you can form an equally spaced grid using linspace, and use "interp1" to interpolate your data. You'll have to be a bit careful in selecting the correct number of gridpoints, but that should not be hard.
Type "help function" or "doc function" to summon the documentation for the builtin functions.
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