Added new features to the ndcube._add_ method #794
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ndcube/ndcube.py
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| # addition | ||
| new_data = self.data + value_data |
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The addition should be done as part of the masked array addition. You've already done this below, you just need to extract the added data from the results as well as the mask.
ndcube/ndcube.py
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| return self._new_instance( | ||
| data=new_data, uncertainty=new_uncertainty, mask=new_mask | ||
| ) |
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Instead of having a separate return here for the NDData case, I think we should build a dictionary of kwargs that we can give self._new_instance, here. So, you can create an empty kwargs dictionary at the start of the method, and add the new data, uncertainty, etc. in the relevant place, e.g.
kwargs["uncertainty"] = new_uncertaintyThen the final line of the method would become
return self._new_instance(**kwargs)There was a problem hiding this comment.
Let me know if this doesn't make sense
Co-authored-by: DanRyanIrish <[email protected]>
Co-authored-by: DanRyanIrish <[email protected]>
…o nddataArithmetic and further modify the _add_ method.
ndcube/ndcube.py
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| if self.uncertainty is not None and value.uncertainty is not None: | ||
| new_uncertainty = self.uncertainty.propagate( | ||
| np.add, value.uncertainty, correlation=0 | ||
| np.add, value.uncertainty, result_data = value.data, correlation=0 |
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The result_data needs to be the result of the operation. So, assuming you moved the addition of the datas using the masked array to before the uncertainty propagation, you could do:
| np.add, value.uncertainty, result_data = value.data, correlation=0 | |
| np.add, value.uncertainty, result_data = kwargs["data"], correlation=0 |
ndcube/ndcube.py
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| # combine mask | ||
| self_ma = np.ma.MaskedArray(self.data, mask=self.mask) | ||
| value_ma = np.ma.MaskedArray(value_data, mask=value.mask) | ||
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| # addition | ||
| result_ma = self_ma + value_ma | ||
| new_mask = result_ma.mask | ||
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| # extract new mask and new data | ||
| kwargs["mask"] = result_ma.mask | ||
| kwargs["data"] = result_ma.data |
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As mentioned in above comment, I think it makes sense to do this before the uncertainty propagation so you can use the kwargs["data"] value in that propagation.
ndcube/ndcube.py
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| kwargs["data"] = result_ma.data | ||
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| # return the new NDCube instance | ||
| return self._new_instance(**kwargs) |
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Move this line to the end of the method and use the kwargs approach when handling the other cases, e.g. Quantity. So, for example, L1082 would become:
kwargs["data"] = self.data + value.to_value(cube_unit)
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A changelog file needs to be added. And your branch needs to be updated with the latest version of main. |
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