Num den mismatch #159594626 #92
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slobodan-ilic
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src/cr/cube/crunch_cube.py
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| @@ -147,7 +147,7 @@ def _transform(self, res, include_transforms_for_dims, | |||
| i - dim_offset in include_transforms_for_dims) | |||
| if dim.type == 'multiple_response': | |||
| dim_offset += 1 | |||
| if not transform or dim.type == 'categorical_array': | |||
| if not transform or dim.type in ['categorical_array', 'multiple_response']: | |||
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use a tuple instead of a list.
src/cr/cube/dimension.py
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| @@ -115,8 +115,9 @@ def _elements(self): | |||
| @property | |||
| def inserted_hs_indices(self): | |||
| '''Returns inserted H&S indices for the dimension.''' | |||
| if (self.type == 'categorical_array' or not self.subtotals): | |||
| return [] # For CA subvariables, we don't do H&S insertions | |||
| item_types = ['categorical_array', 'multiple_response'] | |||
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use a tuple instead of a list, or better, move this to a constant in a shared module.
src/cr/cube/measures/index.py
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| result = result[0] | ||
| else: | ||
| if self.prune: | ||
| mask = np.array([slice_.mask for slice_ in result]) |
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could this be an iterator instead of a list comprehension (replace [] with ())
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Says fromiter is only for 1-D. All masks here are 2-D.
src/cr/cube/measures/index.py
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| axis=1, weighted=self.weighted, prune=self.prune | ||
| ) | ||
| return proportions / margin | ||
| result = [] |
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would it be possible to store the result as a numpy array by turning this function into an iterator and then using fromiter?
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Again, don't think so, sorry :|
- MR dimension somehow has an insertion (data from production) - num and den shapes mismatch when calculating proportions - Added utility for showing compressed pruned nd.arrays
slobodan-ilic
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Addressed all the changes that were possible to address without major refactoring @percious |
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