Problem with FFT in PYTHON

1. What are the disadvantages of FFT?
2. How accurate is FFT?
3. Which is better FFT or DFT?
4. What does FFT do in Python?

What are the disadvantages of FFT?

A disadvantage associated with the FFT is the restricted range of waveform data that can be transformed and the need to apply a window weighting function (to be defined) to the waveform to compensate for spectral leakage (also to be defined). An alternative to the FFT is the discrete Fourier transform (DFT).

How accurate is FFT?

Discrete Fourier transforms computed through the FFT are far more accurate than slow transforms, and convolutions computed via FFT are far more accurate than the direct results. However, these results depend critically on the accuracy of the FFT software employed, which should generally be considered suspect.

Which is better FFT or DFT?

FFT algorithms are faster ways of doing DFT. It is a family of algorithms and not a single algorithm. How it becomes faster can be explained based on the heart of the algorithm: Divide And Conquer.

What does FFT do in Python?

The fast Fourier transform (FFT) is an algorithm for computing the discrete Fourier transform (DFT), whereas the DFT is the transform itself. Another distinction that you'll see made in the scipy. fft library is between different types of input. fft() accepts complex-valued input, and rfft() accepts real-valued input.