Reduce and rank over a population with no persons

[MaxGhenis]

What this fixes

With no persons in a simulation, GroupPopulation.all, max and min raise:

ValueError: zero-size array to reduction operation maximum which has no identity

reduce fills each group with its neutral element, but it first took numpy.max of the persons' positions to size its loop, and that array is empty. members_position (numpy.max(members_entity_id)) and Population.get_rank (numpy.max(positions)) have the same problem. All three now size their loop as 0 when there are no persons, so it runs zero times. They use a length check rather than numpy.max(..., initial=-1), which would raise for an unsigned index array. get_rank reshapes its value matrix to (count, 0) so it stays two-dimensional. sum and nb_persons already returned 0 for this case.

The independent review found that an empty membership given as [], or built by build_default_simulation(count=0) (np.array(range(0))), is float64. NumPy indexes only with integers, so ranks and projections over no persons still raised. The members_entity_id setter now stores an empty membership as an integer array, and build_default_simulation uses np.arange(count), which is integer even for 0.

The audit verifier's witness was one household and no persons. With this PR, all returns [True], any [False], max [-inf], min [inf], sum [0], nb_persons [0], and get_rank returns an empty array.

Invariants

For any number of groups (1 to 6) and any assignment of 0 to 30 persons to them (so groups may be empty and there may be no persons at all), given as an integer array or a plain list:

• sum, nb_persons, any, all, max and min equal a plain-Python oracle, with 0, False, True, -inf and inf for a group with no members;
• get_rank gives each person the position of their value among their group's values, ties going to the person listed first.

Tests

• New test_group_population_empty.py: the witness for every reduction, get_rank with no persons, a plain [] membership, and a default simulation of no one (rank, nth person, project, projector max, all).
• New test_group_population_reductions_property.py: one Hypothesis property, 300 examples.

Before the fix, on master's policyengine_core/populations:

test_group_population_empty.py:               2 failed   (ValueError: zero-size array to reduction operation maximum which has no identity)
test_group_population_reductions_property.py: 1 failed   (minimal: one group, no persons)

Round 2 (after the independent review), the new tests on the first head eca6a621:

test_group_population_empty.py:                 2 failed, 2 passed (plain [] and count=0 cases)
test_group_population_reductions_property.py:   1 failed   (minimal: one group, no persons, given as a list)

After:

test_group_population_empty.py:                 4 passed
test_group_population_reductions_property.py:   1 passed
test_simulation_builder.py:                    35 passed
test_entities.py:                              23 passed
test_dump_restore.py:                           1 passed
test_bincount_minlength.py:                     2 passed
test_projectors.py:                             6 passed

Ruff format and ruff check pass. I ran these files one at a time and left the full suite to CI, because the shared host is saturated.

Impact

No country output can change. For any non-empty population the length check takes the same numpy.max(x) + 1 as before, and the reshape is a no-op when the matrix already has rows. Only populations with zero persons behave differently, and those used to raise. np.arange(count) gives the same integer values as np.array(range(count)) for every positive count. No microsimulation runs with zero persons, so no A/B run is needed.

axiom: n/a: engine fix in population reductions, no policy change

Other audit findings, handled elsewhere

The 2026-10-06 invariants audit of master 757147c7 also confirmed defects that this PR leaves alone, because other work owns them:

• Stock ADD changing later plain reads: draft Cache ADD and DIVIDE results only where a plain read returns them #571.
• Year deletion leaving monthly fast-cache entries: draft Drop every contained period from the fast cache when deleting or setting a period #566.
• Disk deletion of contained periods, and disk branch-name parsing and prefix collisions: draft Delete the periods within a deleted period from disk storage #565 (it inherits Keep branch period reads, dumps, and disk deletion consistent #552).
• Clone aliases bound to the parent: fixed by Bind a clone's calc and df to the clone, and give it its own system's entities #586.
• Serialization and subsample input provenance: Restore inputs as inputs, evict the fast cache on holder writes, reject non-numeric uprating and defined_for #576 and Rebuild a subsampled simulation from its inputs, not its calculated values #573.
• Restored entity counts: Fix restore_simulation entity counts #548.
• A monthly input leaving a cached annual sum stale (set_input for one period leaves the variable's cached sum or twelfth over an overlapping period in place #579): tracked separately.

Branch staleness after set_input and raw-file restore are documented behaviour, not defects.

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