interpolate forest falls precipitation data to a 5 minute time series instead of the original 15 minute in matlab

Assuming you have a time series of precipitation data sampled every 15 minutes, you can use linear interpolation to obtain a 5-minute time series of precipitation data as follows:

main.m
% generate sample precipitation data
t = datetime('now') - hours(24):minutes(15):datetime('now');
precipitation = rand(size(t));

% specify new time axis with 5 minute intervals
t_new = datetime('now') - hours(24):minutes(5):datetime('now');

% interpolate precipitation values
precipitation_new = interp1(t, precipitation, t_new, 'linear');

% plot original and interpolated data
plot(t, precipitation, 'o-', t_new, precipitation_new, '*-');
legend('Original', 'Interpolated');
xlabel('Time');
ylabel('Precipitation');
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In this example, datetime function is used to generate a time series spanning the last 24 hours, sampled every 15 minutes. The interp1 function is used to interpolate the precipitation values to a new time axis with 5 minute intervals, using linear interpolation. Finally, the interpolated precipitation data is plotted along with the original data for comparison.

Note that the result of the interpolation depends on the characteristics of the original data, and different interpolation methods may be more appropriate in some cases.