Interpolating missing values according to time vector

Hi!

I want to interpolate the missing values of this vector:

x=[2 6 8 10 NaN NaN NaN NaN 21 59 NaN 12 80];

but, instead of using the intermediate values in each case, I want to interpolate according another vector of "serial times", for example:

time=[738097.24, 738097.253, 738097.261, 738097.4, 738097.53, 738097.69, 738097.81, 738097.8129, 738097.91, 738098.0, 738098.3, 738098.49, 738098.79];

That means, the values between x(4) and x(9) must respect the sequence given in the time vector.

Is there any form to do that automatically?

Thanks!

[dpb]

I have no idea what you mean or expect the result to be???

Answer 1

[Cris LaPierre]

Sure. You just have to separate your knowns and unknowns.

x=[2 6 8 10 NaN NaN NaN NaN 21 59 NaN 12 80]';
time=[738097.24, 738097.253, 738097.261, 738097.4, 738097.53, 738097.69, 738097.81, 738097.8129, 738097.91, 738098.0, 738098.3, 738098.49, 738098.79];
% Create index of known values
indKnown = ~isnan(x);
% interpolate to obtain values of unknown values
x(~indKnown) = interp1(time(indKnown),x(indKnown),time(~indKnown))

x = 13×1

2.0000 6.0000 8.0000 10.0000 12.8039 16.2549 18.8431 18.9057 21.0000 59.0000

[David E.S.]

That's exactly what I want! Thanks!!

Answer 2

[Bob Thompson]

I don't know if there is a single command that would do what you're asking, though others might know of one.

A fairly concise way of finishing the array though is the following:

x(isnan(x)) = interp1(time(~isnan(x)),x(~isnan(x)),time(isnan(x)));

[David E.S.]

Thanks!! I can't accept more than one anwser, but the code is just perfect and fulfills its function!!