<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def _as_array( self, include_missing=False, get_non_selected=False, weighted=True, include_transforms_for_dims=False, ):
 """Get crunch cube as ndarray. Args include_missing (bool):
 Include rows/cols for missing values. get_non_selected (bool):
 Get non-selected slices for MR vars. weighted (bool):
 Take weighted or unweighted counts. include_transforms_for_dims (list):
 For which dims to include headings & subtotals (H&S) transformations. Returns res (ndarray):
 Tabular representation of crunch cube """

        return self._apply_subtotals(
            self._apply_missings(
                self._measure(weighted).raw_cube_array, include_missing=include_missing
            ),
            include_transforms_for_dims,
        )