# fftFreq function Null safety

Array fftFreq(
1. int n,
2. {double d = 1.0,
3. bool realFrequenciesOnly = false}
)

Return the Discrete Fourier Transform sample frequencies. 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, ..., -1` / (dn) if n is even f = `0, 1, ..., (n-1)/2, -(n-1)/2, ..., -1` / (dn) if n is odd

# Parameters

• `n` : int Window length.
• `d` : double, optional Sample spacing (inverse of the sampling rate (1/FS), Fs if called sampling frequency too)). Defaults to 1.
• `realFrequenciesOnly` : bool, optional if true, return only real frequencies of the FFT

# Returns

• f : Array Array of length `n` containing the sample frequencies.
1. "Numpy FFT helper". https://github.com/numpy/numpy/blob/master/numpy/fft/helper.py. Retrieved 2019-07-25.
2. "How to scale the frequency axis after performing fft?". https://www.mathworks.com/matlabcentral/answers/303075-how-to-scale-the-frequency-axis-after-performing-fft. Retrieved 2019-07-25.
3. "Fast Fourier Transform in matplotlib". https://plot.ly/matplotlib/fft/. Retrieved 2019-07-25.
4. "Fourier Transforms (scipy.fftpack)". https://docs.scipy.org/doc/scipy/reference/tutorial/fftpack.html. Retrieved 2019-07-25.

# Examples

``````var signal = Array([-2, 8, 6, 4, 1, 0, 3, 5]);
var fourier = rfft(signal).abs();
var n = signal.length;
var timeStep = 0.1;
var freq = fftFreq(n, d: timeStep);

print(fourier);
print(freq);

/* output:
Array([25.0, 8.632190835805323, 10.04987562112089, 9.56479384901936, 9.0, 9.56479384901936, 10.04987562112089, 8.632190835805325])
Array([0.0, 1.25, 2.5, 3.75, -5.0, -3.75, -2.5, -1.25])
*/
``````