uwacan.spectral.fft

fft(time_data, nfft=None)

Compute the fft of a time signal.

This computes the single-sided fft of the input data, intended to go from real time data to frequency data. The output array has nfft//2+1 frequency bins. No scaling is applied to the output, i.e., it has the same normalization as numpy.fft.rfft.

Parameters:

time_data_core.TimeData or xr.DataArray or numpy.ndarray

The input time-domain data to compute the spectrum for. The data can be one of the following:

• TimeData: Wrapped time data from uwacan.

• xarray.DataArray: An xarray DataArray with a ‘time’ dimension.

• numpy.ndarray: A NumPy array containing time-series data. The fft will be over the last axis.

nfftint, optional

The number of bins to use for the fft. Defaults to the length of the time signal.

Returns:

_core.FrequencyData or xr.DataArray or numpy.ndarray

The computed single-sided fft of the input data. The return type matches the input type:

• If time_data is a TimeData, returns a FrequencyData object.

• If time_data is an xarray.DataArray, returns an xarray.DataArray with a ‘frequency’ dimension.

• If time_data is a numpy.ndarray, returns a NumPy array containing the fft data.