pygmi.raster.fft

A set of FFT routines.

Functions

fftprep(data)	FFT preparation.
fft_getkxy(fftmod, xdim, ydim)	Get KX and KY.
nextpow2(n)	Next power of 2.
calculate_raps(dat)	Calculate the Radially Averaged Power Spectrum (RAPS) of a 2D dataset.

Module Contents

pygmi.raster.fft.fftprep(data)

FFT preparation.

This routine pads using minimum curvature gridding.

Parameters:

data (pygmi.raster.datatypes.Data) – Input dataset.

Returns:

• zfin (ndarray.) – Output prepared data.

• datamedian (float) – Median of data.

Return type:

tuple[pygmi.raster.datatypes.Data, float]

pygmi.raster.fft.fft_getkxy(fftmod, xdim, ydim)

Get KX and KY.

Parameters:

• fftmod (numpy.typing.NDArray) – FFT data.

• xdim (float) – Cell x dimension.

• ydim (float) – Cell y dimension.

Returns:

• KX (ndarray) – X sample frequencies.

• KY (ndarray) – Y sample frequencies.

Return type:

tuple[numpy.typing.NDArray, numpy.typing.NDArray]

pygmi.raster.fft.nextpow2(n)

Next power of 2.

Parameters:

n (float | numpy.typing.NDArray) – Current value.

Returns:

Output next power of 2.

Return type:

float or numpy array

pygmi.raster.fft.calculate_raps(dat)

Calculate the Radially Averaged Power Spectrum (RAPS) of a 2D dataset.

Parameters:

dat (pygmi.raster.datatypes.Data) – Input dataset.

Returns:

• k (ndarray) – The 1D array of radial wavenumbers.

• raps (ndarray) – The 1D array of radially averaged power spectrum values.

Return type:

tuple[numpy.typing.NDArray, numpy.typing.NDArray, numpy.typing.NDArray, tuple]