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In classification.py implement the ps_selection function with two flavors: NAD and NMAD.
classification.py
NAD
NMAD
point_selection
def _nmad(self, chunk_azimuth=500, chunk_range=500): """ Estimate the NMAD for a xarray dataset. """ # Time dimension order t_order = list(self._obj.dims.keys()).index("time") # Rechunk to make temporal operation more efficient amplitude = self._obj.amplitude.chunk( {"azimuth": chunk_azimuth, "range": chunk_range, "time": -1} ) median_amplitude = amplitude.median(axis=t_order) mad = (np.abs(amplitude - median_amplitude)).median(dim="time") nmad = mad / (median_amplitude + np.finfo(amplitude.dtype).eps) return nmad
The text was updated successfully, but these errors were encountered:
rogerkuou
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In
classification.py
implement the ps_selection function with two flavors:NAD
andNMAD
.NAD
function from sarxarray implementation to here.NMAD
implementation by Wiestke, which is attached below.point_selection
function in sarxarrayThe text was updated successfully, but these errors were encountered: