credit.verification.standard

Attributes

logger

Functions

average_zonal_spectrum(da, grid[, norm])	takes the average of all spectra in da
zonal_spectrum(da, grid[, norm])	Returns the zonal energy spectrum of a dataarray with dimensions
average_div_rot_spectrum(ds, grid[, wave_spec, norm])	takes the average of all divergence and rotational spectra in da
div_rot_spectrum(ds, grid[, norm])	Returns the spectrum of the divergent and rotational components of a flow

Module Contents

credit.verification.standard.logger

credit.verification.standard.average_zonal_spectrum(da, grid, norm='ortho')

takes the average of all spectra in da

input: Torch Tensor with dim (…, wavenumber) output: numpy array with dim (wavenumber)

credit.verification.standard.zonal_spectrum(da, grid, norm='ortho')

Returns the zonal energy spectrum of a dataarray with dimensions

input: DataArray with backing array with dim (…, lat, lon) output: Torch Tensor with dim (…, nlat // 2 + 1)

credit.verification.standard.average_div_rot_spectrum(ds, grid, wave_spec='n', norm='ortho')

takes the average of all divergence and rotational spectra in da

input: Torch Tensor with dim (…, n, m), total_wavenum x … output: numpy array with dim (wavenumber)

credit.verification.standard.div_rot_spectrum(ds, grid, norm='ortho')

Returns the spectrum of the divergent and rotational components of a flow

input: Dataset with variables U,V each with backing array with dim (…, lat, lon) output: Torch Tensor with dim (…, nlat // 2 + 1)