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"""Harness-level sanity tests for ``coverage_sdid.py``.

Lives under ``benchmarks/`` rather than ``tests/`` because the targets

here (the private DGP helpers inside ``coverage_sdid.py``) are part of

the MC harness, not the shipped ``diff_diff`` package. CI's isolated-

install job deliberately copies only ``tests/``; running the pytest

collection here would just fail with ``ModuleNotFoundError`` on the

``benchmarks`` import.

Invoke manually when about to regenerate the coverage MC artifact::

pytest benchmarks/python/test_coverage_sdid.py -v

Or from the repo root::

python -m pytest benchmarks/python/test_coverage_sdid.py -v

"""

from __future__ import annotations

from pathlib import Path

import sys

# Make the top-level ``benchmarks.python.coverage_sdid`` import resolvable

# when pytest is invoked from the repo root. The harness itself does a

# similar sys.path insert at module load; this mirror is only needed for

# test collection from this file.

_REPO_ROOT = Path(__file__).resolve().parent.parent.parent

if str(_REPO_ROOT) not in sys.path:

sys.path.insert(0, str(_REPO_ROOT))

from benchmarks.python import coverage_sdid # noqa: E402

def test_stratified_survey_dgp_post_periods_cover_full_post_tail():

"""The ``stratified_survey`` coverage DGP must not drop any post period.

Regression against PR #355 R13 P1: the harness previously hard-

coded ``range(7, 12)`` as ``post_periods`` even though

``generate_survey_did_data`` is 1-indexed and emits periods

1..n_periods, so period 12 was silently included in the pre window.

That contaminated the ``stratified_survey × bootstrap`` calibration

row and every downstream REGISTRY claim that transcribes from the

artifact. The fix derives ``post_periods`` from

``df["period"].max()``; this test fails fast if a future refactor

reintroduces the off-by-one.

"""

df, post_periods = coverage_sdid._stratified_survey_dgp(seed=0)

# Contract: post_periods covers the full tail from cohort onset

# through df["period"].max(), with no gaps (unique + sorted +

# contiguous + maxed at df["period"].max()).

assert len(post_periods) == len(set(post_periods)), (

f"post_periods has duplicates: {post_periods}"

)

assert post_periods == sorted(post_periods), (

f"post_periods not sorted: {post_periods}"

)

gaps = [

(a, b) for a, b in zip(post_periods, post_periods[1:]) if b - a != 1

]

assert not gaps, (

f"post_periods has gaps: {gaps} in {post_periods}"

)

assert post_periods[-1] == int(df["period"].max()), (

f"post_periods max {post_periods[-1]} != df[period].max() "

f"{int(df['period'].max())} — DGP drops the last post period "

"(off-by-one on 1-indexed generate_survey_did_data)."

)

# Strong form: cohort onset is 7, n_periods=12 → [7,8,9,10,11,12].

assert post_periods == [7, 8, 9, 10, 11, 12], (

f"post_periods={post_periods} must equal [7,8,9,10,11,12] for "

"the documented 6-pre/6-post survey DGP; any other slice "

"changes the calibration interpretation in REGISTRY."

)