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Currently, NDCube does not support arithmetic operations with NDData instances because it does not make sense to combine cubes on different coordinate grids. However, this is not a concern when the NDData instance has a wcs set to None. Therefore, we should support arithmetic operations between NDCube and WCS-less NDData instances. This would serve the cases where users want to NDCube with data with uncertainties and a mask.
Proposed solution
This would need to be explicitly supported in NDCube.__add__ and NDCube.__mul__.
For adding, code needs to be inserted here that checks if not hasattr(value, wcs) or value.wcs is None: and then add then convert the value to the right units ( u.Quantity(value.data, unit=value.unit).to_value(self.unit) ), add the data as masked_arrays, (new_data = np.ma.masked_array(self.data, mask=self.mask) + np.ma.masked_array(value.data, mask=value.mask), and propagate the uncertainties, An example can be seen in NDCube.__pow__ for multipy uncertainty propagation.
A similar structure should work for multiplication somewhere in the codebase around here.
The text was updated successfully, but these errors were encountered:
Describe the feature
Currently,
NDCube
does not support arithmetic operations withNDData
instances because it does not make sense to combine cubes on different coordinate grids. However, this is not a concern when theNDData
instance has awcs
set toNone
. Therefore, we should support arithmetic operations betweenNDCube
and WCS-lessNDData
instances. This would serve the cases where users want toNDCube
with data with uncertainties and a mask.Proposed solution
This would need to be explicitly supported in
NDCube.__add__
andNDCube.__mul__
.For adding, code needs to be inserted here that checks
if not hasattr(value, wcs) or value.wcs is None:
and then add then convert the value to the right units (u.Quantity(value.data, unit=value.unit).to_value(self.unit)
), add the data as masked_arrays, (new_data = np.ma.masked_array(self.data, mask=self.mask) + np.ma.masked_array(value.data, mask=value.mask
), and propagate the uncertainties, An example can be seen inNDCube.__pow__
for multipy uncertainty propagation.A similar structure should work for multiplication somewhere in the codebase around here.
The text was updated successfully, but these errors were encountered: