This occurs for numpy functions such as MEAN or COUNT etc acting on vectors:
```Python
>>> import numpy as np
>>> np.array([[2, 3], [3, 4]]).mean(axis=-1)
array([ 2.5,  3.5])
>>> np.array([1, 2, 3, 4]).mean(-1)
2.5
```
As described above, on the collapsing multiple coordinates, this flattenes the numpy array and providedes it to the aggregator which is where this scenario occurs.

Take a look at the additional test "test_analysis.TestMultiCoord.test_multi_coord_no_mdtol"