fft (LUX)

15.5.215 fft

fft(data [, axes, /allaxes, /amplitudes])

fft, data [, axes, /allaxes, /amplitudes]

Returns a discrete forward Fourier transform of the real data along the indicated axes. By default, the forward transform (to frequency space) is applied in the first dimension. The returned values are of type double. The subroutine form replaces data with the transformed version.

If axes is specified, then it is taken to contain the axes along which transformation is to be done. No axis may appear more than once. The axes need not be in any specific order. If /allaxes is specified, then all axes are treated. If neither axes nor /allaxes are specified, then the first axis is assumed. The data may have arbitrary positive dimensions.

The returned array has the same dimensions as data.

The result are stored as ’half-complex’ sequences, in order of increasing frequency. For each frequency, first the real and then the imaginary part is given, except that no imaginary part is given for values that are always real, i.e., for frequency zero and (for even-length sequences) also for the highest represented frequency (equal to half of the sequence length). The Fourier transform (of real data) at a negative frequency is the complex conjugate of the Fourier transform at the corresponding positive frequency, and the Fourier transform at frequency f is equal to that at frequency f mod n for sequence length n.

Note that only one half of the relevant frequencies are represented in the results, because the missing half can be constructed from the provided half by complex conjugation. Just adding up the squares of all of the values in the result and dividing by the sequence length does not give you the sum of squares of x; you have to add in the missing part, too. And remember that frequency zero counts only once, and [for even-length sequences] the highest represented frequency counts only once, too.

The returned values are such that if x contains a pure sine or cosine wave, then the magnitude of the value in the appropriate element of the result is equal to the amplitude of the wave times n (for the very first element, and – if n is even – also the very last element) or n/2.

If /amplitudes is specified, then the returned values are scaled such that their magitude is equal to the magnitude of the corresponding wave.

The calculation speed of the algorithm depends strongly on the number of data points in the dimension in which the algorithm is applied. For quickest results, that number of data points should only have factors equal to small prime numbers, such as 2, 3, and 5.

Opposite: fftb