fft(x, y, dir) : Computes the one-dimensional discrete Fourier transform using an in-place complex-to-complex FFT algorithm. Note: The transform also produces a mirror copy of the frequency components, which correspond to the signal's negative frequencies.
x: float array, real part of the data, array size must be a power of 2
y: float array, imaginary part of the data, array size must be the same as x; for real-valued input, y must be an array of zeros
dir: string, options = , defines the direction of the transform: forward" (time-to-frequency) or inverse (frequency-to-time)
Returns: x, y: tuple (float array, float array), real and imaginary parts of the transformed data (original x and y are changed on output)
fftPower(x, y) : Helper function that computes the power of each frequency component (in other words, Fourier amplitudes squared).
x: float array, real part of the Fourier amplitudes
y: float array, imaginary part of the Fourier amplitudes
Returns: power: float array of the same length as x and y, Fourier amplitudes squared
fftFreq(N) : Helper function that returns the FFT sample frequencies defined in cycles per timeframe unit. For example, if the timeframe is 5m, the frequencies are in cycles/(5 minutes).
N: int, window length (number of points in the transformed dataset)
Returns: freq : float array of N, contains the sample frequencies (with zero at the start).
A word of caution: always be aware of the risks and do not interpret data produced by the script or contained in the preview chart as trading advice.
In true TradingView spirit, the author has published this Pine code as an open-source library so that other Pine programmers from our community can reuse it. Cheers to the author! You may use this library privately or in other open-source publications, but reuse of this code in a publication is governed by House Rules.
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