Description Usage Arguments Value
View source: R/interpolationFFT.R
There are two ways to interpolate data from a given spectrum.
Frist, one can do zero padding to cover n
new data points. Or, secound
the complex amplitude with the associated frequency is taken and evaluated
at given points xout
. Doing that for all frequencies and amplitudes
will give the interpolation. The result is compared to linear approximation
for didactic reasons.
1 | interpolate.fft(y, x = NULL, n = NULL, xout = NULL)
|
y |
numeric data vector to be interpolated |
x |
numeric data vector with reference points |
n |
number of new points |
xout |
a vector new points |
A list with a x
and y
component is returned. The e99
value evaluates the error of the interpolation with respect to linear approximation
with the approx()
function.
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