nlcpy.fft.rfftfreq

nlcpy.fft.rfftfreq(n, d=1.0)[ソース]

Returns 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] / (d*n)   if n is even
f = [0, 1, ..., (n-1)/2-1, (n-1)/2] / (d*n)   if n is odd
```

Unlike `fftfreq()` the Nyquist frequency component is considered to be positive.

Parameters
nint

Window length.

dscalar, optional

Sample spacing (inverse of the sampling rate). Defaults to 1.

Returns
fndarray

Array of length `n//2 + 1` containing the sample frequencies.

Examples

```>>> import nlcpy as vp
>>> signal = vp.array([-2, 8, 6, 4, 1, 0, 3, 5, -3, 4], dtype=float)
>>> fourier = vp.fft.rfft(signal)
>>> n = signal.size
>>> sample_rate = 100
>>> freq = vp.fft.fftfreq(n, d=1./sample_rate)
>>> freq
array([  0.,  10.,  20.,  30.,  40., -50., -40., -30., -20., -10.])
>>> freq = vp.fft.rfftfreq(n, d=1./sample_rate)
>>> freq
array([ 0., 10., 20., 30., 40., 50.])
```