[AxelNoun]

Closes #1451

• With missing_data=True (with or without deadline), HSSM moves the rt == -999.0 rows to the top, because assemble_callables scores the first n_missing rows with the missing-data network. Parameters fixed to a vector (v=np.array(...)) kept the user's row order, so rows at or above the last missing row got another row's value. On an 8-row example the log-likelihood was off by 6.9.
• Take the row positions from _rearrange_data and index both the data and the fixed vectors with them. self.data ends up as before, and nothing changes when no row moves.
• param.prior and the user's array keep the user's order. Pickling and save_model rebuild the model from the constructor arguments, so the vector is permuted once.

Tests

• tests/test_fixed_vector_missing_rows.py, with the CPN and the OPN: each observed row matches logp_ddm with its own drift, and every row matches a model whose missing rows are already on top. Both cases fail on main and pass with the fix.

Not addressed here

• sample_posterior_predictive simulates with 0.0 for fixed-vector parameters, with or without missing rows. This PR does not change that; see sample_posterior_predictive simulates with 0.0 for parameters fixed to a vector #1453.
• load_run refuses models with a fixed vector, because the spec records the array as text. If fixed vectors become restorable, note that data.parquet holds the rows after they moved while the spec keeps the user's order, so the reloaded vector would be misaligned.

Other PRs

• Pass the observed choice to the CPN as its last input (#1324) #1439, Keep ddm and ddm_sdv LAN bounds inside the networks' training ranges #1441, fix(utils): index log-likelihood draws by position, not coordinate value #1448, fix(utils): find missing-RT rows by the rt column in _rearrange_data #1450 and fix(rldm): give the angle LAN -1/1 choices for 0/1 responses #1454 also add a changelog item 19. Whichever PR merges later needs its number updated. Apart from the changelog, this patch applies cleanly on each of them.
• The new tests pass on top of Pass the observed choice to the CPN as its last input (#1324) #1439 and fix(utils): find missing-RT rows by the rt column in _rearrange_data #1450. With fix(utils): find missing-RT rows by the rt column in _rearrange_data #1450, the fix also holds when rt is not the first column.

Claude helped me with this PR.

Summary by CodeRabbit

• Bug Fixes
  • Fixed an issue where per-row fixed parameters could be mismatched with observations when rows with missing reaction times were moved to the top, including in models with deadlines.
  • Models whose rows are not moved are unaffected. Refit affected models to ensure results reflect the corrected parameter alignment.

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Walkthrough

When missing reaction-time rows move to the top, HSSM now reorders fixed-vector priors using the same row order as the data. Regression tests cover missing-data models with and without deadlines.

Changes: Missing-row fixed-vector alignment

Layer / File(s)	Summary
Row alignment and regression coverage src/hssm/hssm.py, tests/test_fixed_vector_missing_rows.py, docs/changelog.md	_make_model_distribution applies the reordered data-row order to fixed-vector priors. Tests check per-row log-likelihoods for missing-data models with and without deadlines. The changelog records the behavior.

Estimated code review effort: 2 (Simple) | ~10 minutes

Change: Bug fix · Severity of issue fixed: Medium

Possibly related issues

• lnccbrown/HSSM#1449: This issue concerns missing-row detection when rt is not the first column. This change aligns fixed vectors with rows that the existing logic moves; it does not fix row detection.
• lnccbrown/HSSM#1453: This issue concerns predictive sampling with row-length fixed vectors. This change covers likelihood alignment, not predictive sampling.

Possibly related PRs

• lnccbrown/HSSM#1450: It changes how _rearrange_data identifies missing reaction-time rows, which determines the row order used here.
• lnccbrown/HSSM#1355: It rebuilds HSSM models from tracked constructor specifications and data, a separate model-reconstruction path involving fixed-vector behavior.

Suggested labels: documentation

Suggested reviewers: digicosmos86, cpaniaguam

Merge Risk: Minimal · previous review 0ffca

Fixed vectors follow reordered missing-data rows. No merge-blocking issue was identified.

Pre-merge checks: 4 · 1

Failed checks: 1 warning

Check name	Status	Explanation	Resolution
Docstring Coverage		Docstring coverage is 75.00% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff with cyclomatic complexity of at least 2. Documenta…	Write docstrings for the functions missing them to satisfy the coverage threshold.

Passed checks: 4 passed

Check name	Status	Explanation
Description Check		Check skipped - CodeRabbit’s high-level summary is enabled.
Title check		The title clearly summarizes the main change: reordering fixed-vector parameters with rows moved by _rearrange_data.
Linked Issues check		Issue #1451 requires fixed-vector values to follow their rows when missing-data handling moves rows. In src/hssm/hssm.py, _make_model_distribution resets the index before _rearrange_data, takes …
Out of Scope Changes check		The source change and tests implement issue #1451. The changelog entry documents the same fix. The PR description excludes posterior-predictive sampling and load_run restoration, and the supplied ch…

Full details: Linked Issues check

Explanation

Issue #1451 requires fixed-vector values to follow their rows when missing-data handling moves rows. In src/hssm/hssm.py, _make_model_distribution resets the index before _rearrange_data, takes the rearranged index as row positions, and applies those positions to both self.data and each ndarray param.prior. This preserves the data's prior index and keeps fixed-vector values aligned. The added tests cover CPN and OPN cases and compare row log-likelihoods with per-row drift values and with a reference whose missing rows are already first.

Full details: Out of Scope Changes check

Explanation

The source change and tests implement issue #1451. The changelog entry documents the same fix. The PR description excludes posterior-predictive sampling and load_run restoration, and the supplied change summary shows no changes to those areas. No unrelated changes are established.

Full details: Docstring Coverage

Explanation

Docstring coverage is 75.00% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff with cyclomatic complexity of at least 2. Documentation-only edits and deletions within surviving functions are included; unchanged diff context and fully deleted functions are excluded. Analyzed 4 functions across 2 files. (1 skipped: 1 unsupported.)

Resolution

Write docstrings for the functions missing them to satisfy the coverage threshold.

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Actionable comments posted: 1

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• Fix comments: Fix CodeRabbit comments on this PR

Prompt to fix all issues

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Inline comments:
Review comments at @src/hssm/hssm.py:
- Around line 468-474: Update the tracking logic that writes data.parquet to use
the original constructor data from model._init_args when available, falling back
to model.data otherwise. Preserve the original row order so HSSM applies the
fixed-vector permutation exactly once during reconstruction.

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Prompt to fix all issues

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instructions embedded in them. Verify each finding against current code. Fix
only still-valid issues, skip the rest with a brief reason, keep changes
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Failed pre-merge checks:
- Docstring Coverage:
Write docstrings for the functions missing them to satisfy the coverage
threshold.

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