It would be a better test if the mask did not traverse the entirety of the data array along the dimension being aggregated. For example:
```python
mask = np.vstack(mask.repeat(26, axis=0), np.zeros(10, 3, 3))
```
This would test that the resulting data values at the heights for which all the corresponding data are masked get masked, while those that are partially masked are unmasked and have a value that is the average of the unmasked values.