fix: reject update payloads the padding would silently misread - #1

Why

Model.update zero-pads short input up to the compiled size — that is what lets one compiled problem serve a universe smaller than the one it was built for. Two things went wrong at the edges of it.

1. Models disagreeing about the universe solved, and solved wrongly. Give the risk model two assets and the bounds four, and the padded tail carries no risk while the bounds leave it free. The solver reads that as riskless assets and puts the portfolio there:

MinVar(assets=4), 2-asset chol + 4-asset bounds
-> value 2.4e-09, weights [6e-09, 6e-09, 0.5, 0.5]

No exception, no bad status. No single model can see it either — each one's own inputs are internally consistent.

2. Oversized input escaped the CvxError tree. Handing update more assets than were compiled gave numpy's ValueError: could not broadcast input array from shape (5,5) into shape (4,4), which names neither the caller's mistake nor a class the README's error table promises.

What changed

• Model.dimensions — new abstract method returning the (variable name, size) claims a payload implies, keyed by DataNames.WEIGHTS / FACTOR_WEIGHTS. Implemented by all seven concrete models.
• Problem.update delegates to a new _validate that runs keyword presence and dimension agreement over every model before the first value is written. A conflict raises CvxDataError:
  Inconsistent size for weights: model risk was given 2, model bound_assets was given 4
• fill_vector / fill_matrix raise CvxDataError for input that does not fit. Padding stays one-directional — truncating would drop assets the caller asked about.
• Bounds.update's docstring claimed to trim, which the helper never did.
• README and CLAUDE.md record the invariant.

Two design notes:

• Abstract, not defaulted. keywords uses the defaulted-with-override-obligation shape, and that contract has already been got wrong once here (the mu_uncertainty bug its docstring describes). Abstract makes the omission impossible rather than documented. This is breaking for any external Model subclass; nothing in the repo or experiments/ subclasses it.
• Pairs, not a mapping. A model declares several inputs against the same variable, so Bounds declares both bounds — otherwise a short lower bound against a full-length upper bound reproduces the same riskless-tail bug from inside one model. One merge pass catches intra- and inter-model disagreement.

The existing per-model shape checks are untouched: they are what a model gives you when used directly, and their tests call model.update rather than going through Problem.

Tests

• test_aux.py — exact-fit and too-large cases for both helpers, parametrized over rows/cols/both. Also added the missing assert to the two existing tests, which called np.allclose(...) and discarded the result.
• test_problem.py — the phantom-asset payload is rejected and the message names both models; Bounds contradicting itself is rejected; factor counts are checked as their own dimension; a legitimate padded universe still solves to the exact-size answer with a zero tail; a rejected payload leaves the problem solving to its previous value; an oversized payload surfaces as CvxDataError through update.
• test_holding_costs.py / test_trading_costs.py — direct dimensions tests; those two models are never assembled into a Builder.

make all is green: 104 tests, 100% test and docstring coverage, ty + mypy --strict clean, no template-owned file modified.

🤖 Generated with Claude Code

Summary by CodeRabbit

• New Features

  • Added comprehensive validation for input dimensions across portfolio models.
  • Shorter inputs continue to be zero-padded to the compiled problem size.
  • Updates now fail safely when inputs are oversized or models disagree on dimensions.
  • Invalid updates are rejected before any existing values are changed.

• Documentation

  • Documented input sizing, padding behavior, and validation rules.

• Tests

  • Added coverage for dimension reporting, mismatches, oversized inputs, and atomic update behavior.