numpy.fft.rfftfreq — NumPy v1.13 Manual (original) (raw)
numpy.fft. rfftfreq(n, d=1.0)[source]¶
Return the Discrete Fourier Transform sample frequencies (for usage with rfft, irfft).
The returned float array f contains the frequency bin centers in cycles per unit of the sample spacing (with zero at the start). For instance, if the sample spacing is in seconds, then the frequency unit is cycles/second.
Given a window length n and a sample spacing d:
f = [0, 1, ..., n/2-1, n/2] / (dn) if n is even f = [0, 1, ..., (n-1)/2-1, (n-1)/2] / (dn) if n is odd
Unlike fftfreq (but like scipy.fftpack.rfftfreq) the Nyquist frequency component is considered to be positive.
| Parameters: | n : int Window length. d : scalar, optional Sample spacing (inverse of the sampling rate). Defaults to 1. |
|---|---|
| Returns: | f : ndarray Array of length n//2 + 1 containing the sample frequencies. |
Examples
signal = np.array([-2, 8, 6, 4, 1, 0, 3, 5, -3, 4], dtype=float) fourier = np.fft.rfft(signal) n = signal.size sample_rate = 100 freq = np.fft.fftfreq(n, d=1./sample_rate) freq array([ 0., 10., 20., 30., 40., -50., -40., -30., -20., -10.]) freq = np.fft.rfftfreq(n, d=1./sample_rate) freq array([ 0., 10., 20., 30., 40., 50.])