Here is containment `C[i, j]` for a range of chunk sizes from 1 to 12 for computing `groupby("time.month")` of a monthly mean dataset.

The images only show 12 time steps.

These are colored so that light yellow is `C=0`, and dark purple is `C=1`.

`C[i,j] = 1` when the chunks occupied by group `i` perfectly overlaps with those occupied by group `j` (so the diagonal elements

are always 1).

The title on each image is `(chunk size, sparsity)`.

When the chunksize _is_ a divisor of the period 12, `C` is a [block diagonal](https://en.wikipedia.org/wiki/Block_matrix) matrix.

When the chunksize _is not_ a divisor of the period 12, `C` is much less sparse in comparison.


Given the above `C`, flox will choose `"cohorts"` for chunk sizes (1, 2, 3, 4, 6, 12), and `"map-reduce"` for the rest.