CODEWITHSUNDEEP
pythonmatlabpandasgps
eWizardII
eWizardII

Reputation: 1936

Interpolation Function

This is probably a very easy question, but all the sources I have found on interpolation in Matlab are trying to correlate two values, all I wanted to benefit from is if I have data which is collected over an 8 hour period, but the time between data points is varying, how do I adjust it such that the time periods are equal and the data remains consistent?

Or to rephrase from the approach I have been trying: I have GPS lat,lon and Unix time for these points; what I want to do is take the lat and lon at time 1 and time 3 and for the case where I don't know time 2, simply fill it with data from time 1 - is there a functional way to do this? (I know in something like Python Pandas you can use fill) but I'm unsure of how to do this in Matlab.

Upvotes: 2

Views: 769

Answers (5)

dnk8n
dnk8n

Reputation: 715

There is a MATLAB function called interparc.m which will benefit you. It fits a cubic spline through the points and divides the resulting line into equal arc-lengths (depending on the number of points entered by the user)

Upvotes: 2

supyo
supyo

Reputation: 3037

You might try something along the lines of this:

 resampledTime = min(unixTime):resampleInterval:max(unixTime);
 resampledLat = interp1(time,lat,resampledTime);
 resampledLon = interp1(time,lon,resampledTime);

By default, this returns 1-dimensional linear interpolation. For more info, see help interp1

Upvotes: 2

Shai
Shai

Reputation: 114826

I think you are looking for a "zero-order-hold" interpolation a.k.a "nearest neighbor"

Why don't you try interp with method 'nearest'?

Upvotes: 1

BioSP
BioSP

Reputation: 518

What you can do is use interp1 function. This function will fit in deifferent way the numbers for a new X series. For example if you have x=[1 3 5 6 10 12] y=[15 20 17 33 56 89]

This means if you want to fill in for x1=[1 2 3 4 5 6 7 ... 12], you will type y1=interp1(x,y,x1)

Upvotes: 2

TJ1
TJ1

Reputation: 8498

You can look into fitting methods in MATLAB. For example you can look at polyfit or splines. Let's look at polyfit, the way to use it is:

P = polyfit(X,Y,N);

Here X is your time data, and Y is your GPS data measured at time values in X. And N is the order of polynomial. When you calculate P then you can use polyval function as:

Y1 = polyval(P,X1);

Here X1 are uniform time samples for example X1=[1 2 3 4 5 6 7 8] in your case and Y1 will be the estimated data at those times, P is what you calculated using polyfit.

Upvotes: 2

Related Questions