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| from __future__ import division | |
| import numpy as np | |
| def periodogram_fft(x, fs=1.0, window=None, nfft=256): | |
| """ | |
| Calculate a PSD estimate using FFT | |
| :param x: 1-d iterable of values | |
| :param fs: Sampling frequency | |
| :param window: Window | |
| :param nfft: Number of DFT points | |
| :return: PSD estimate | |
| :rtype : ndarray | |
| """ | |
| if window is None: | |
| window = [] | |
| x = np.asarray(x) | |
| x_size = np.shape(x) | |
| x_len = x_size[0] | |
| if len(x_size) > 1: | |
| if x_size[0] == 1: | |
| x_len = x_size[1] | |
| if x_len > nfft: | |
| overlap = x_len % nfft | |
| if overlap: | |
| x = np.append(x, np.zeros((1, nfft-overlap))) | |
| x = np.sum(np.reshape(x, (-1, nfft)), axis=0) | |
| n = x_len | |
| if len(window): | |
| n = sum(x*x for x in window) | |
| Pxx = np.abs(np.fft.fft(x, nfft)) ** 2/n | |
| Pxx /= fs | |
| Pxx[1:nfft/2] += Pxx[-1:nfft/2:-1] | |
| return Pxx[0:nfft/2+1] |
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