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fix(utils): find missing-RT rows by the rt column in _rearrange_data - #1450

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lnccbrown:mainfrom
AxelNoun:1449-rearrange-missing-rt-column
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AxelNoun:1449-rearrange-missing-rt-column

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@AxelNoun

@AxelNoun AxelNoun commented Nov 3, 2026 •

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Closes #1449

  • With missing_data=True (with or without deadline), _rearrange_data looked for -999.0 in the first DataFrame column instead of in rt. With another column first (hssm.load_data("cavanagh_theta") starts with participant_id), the missing rows stayed in place and assemble_callables, which scores the first n_missing rows with the missing-data network, scored the wrong rows. The log-density was silently wrong: -576.1 instead of -78.1 on a 40-trial example.
  • Read the rt column by name, and fall back to the first column when there is none (the previous behaviour). The ndarray branch is unchanged.
  • A first column holding -999.0 for another reason (e.g. a covariate) no longer moves rows.
  • A row whose nullable rt is pd.NA no longer falls out of both splits. It stays in the data, and building the model raises an error about the incomplete row.

Tests

  • test_rearrange_data_finds_rt_column_by_name: _rearrange_data with rt second.
  • test_missing_data_loglik_does_not_depend_on_column_order: an HSSM model whose log-density no longer depends on the column order.
  • test_rearrange_data_keeps_rows_with_nullable_na_rt: a pd.NA row stays.
  • All three fail on main and pass with the fix.

Not addressed here: a fixed-vector parameter (v=np.array(...)) is not permuted with the rows, so it is misaligned once missing rows are moved. This already happens on main when rt is first; with this fix it also happens when rt is not first. See #1451.

Other PRs: #1439 also adds a changelog item and regenerates tests/fixtures/ddm_cpn.onnx. The new tests pass on top of that branch. #1448 also adds changelog item 23 and edits a different part of src/hssm/utils.py, with no conflict there. Whichever PR merges later needs its changelog number updated.

Claude helped me with this PR.

Summary by CodeRabbit

  • Bug Fixes
    • Missing reaction-time markers are now identified using the rt column when available, so results are consistent when column order changes.
    • Rows with nullable pd.NA reaction times remain in the data; model construction will still error for these values.
  • Documentation
    • Clarified how missing-value markers are handled in tabular and array data, and documented the model-construction error for nullable reaction times.

_rearrange_data looked for -999.0 in the first DataFrame column instead of
in rt. With another column first, the missing rows stayed in place and
assemble_callables scored the wrong rows with the missing-data network,
silently giving a wrong log-likelihood.

Read the rt column by name and fall back to the first column when there is
none. Add a unit test and a test that the model log-density does not depend
on the column order.

Claude helped me with this change.
@coderabbitai

coderabbitai Bot commented Nov 3, 2026 •

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Explain Change →

No actionable comments were generated in the recent review.

Walkthrough

DataFrame missing-row detection now checks the rt column when present and falls back to the first column otherwise. Nullable pd.NA values remain in the non-missing partition. Tests check row ordering and compare compiled model log-densities across column orders. The changelog documents the change.

Changes: Missing RT detection

Layer / File(s) Summary
RT-based missing-row detection
src/hssm/utils.py, tests/test_missing_and_deadline.py, docs/changelog.md
_rearrange_data now checks the rt column when it exists and otherwise checks the first column. Nullable comparisons are treated as non-missing. Tests cover missing-row ordering, nullable values, and log-density across column orders. The changelog documents the change.

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

Change: Bug fix · Severity of issue fixed: Medium

Suggested reviewers: digicosmos86

Merge Risk: Minimal · up to 86b8d

Missing-RT row detection now uses the rt column regardless of column order, and the nullable-NA edge case is handled and tested. The fixed-vector parameter misalignment is a pre-existing limitation tracked separately in #1451, so merge risk is minimal.

Pre-merge checks: Passed 4

Check name Status Explanation
Description Check Passed Check skipped - CodeRabbit’s high-level summary is enabled.
Title check Passed The title names the main change: _rearrange_data now finds missing-RT rows (-999.0 markers) by the rt column rather than the first column. The changeset matches this. The title follows the conventiona…
Linked Issues check Passed Issue #1449 requires that missing-RT rows (-999.0) be located by the rt column, not the first DataFrame column, so that row reordering and the log-density do not depend on column order when missing_da…
Out of Scope Changes check Passed The changes at the reviewed head address #1449 and the nullable-rt handling described in the PR objectives. The fillna(False) addition is in the same _rearrange_data split logic as the rt-column fix. …
Full details: Title check

Explanation

The title names the main change: _rearrange_data now finds missing-RT rows (-999.0 markers) by the rt column rather than the first column. The changeset matches this. The title follows the conventional commit format and fits the scope of the fix (src/hssm/utils.py, tests, changelog).

Full details: Linked Issues check

Explanation

Issue #1449 requires that missing-RT rows (-999.0) be located by the rt column, not the first DataFrame column, so that row reordering and the log-density do not depend on column order when missing_data=True. The whole-PR diff (merge base 26d82c7 to head 86b8dec) changes only src/hssm/utils.py in _rearrange_data for the DataFrame branch. It selects data["rt"] when an rt column exists and falls back to data.iloc[:, 0] otherwise. The ndarray branch is unchanged. The incremental change since the previous reviewed head (960eb8b) adds (rt == -999.0).fillna(False). This keeps a row whose nullable rt is pd.NA in the non-missing split, so it is no longer dropped from both splits. The core #1449 requirement is met by the code at the reviewed head. The test functions named in the PR description (test_rearrange_data_finds_rt_column_by_name, test_missing_data_loglik_does_not_depend_on_column_order, test_rearrange_data_keeps_rows_with_nullable_na_rt) were not re-read in this pass. The previous assessment covered them, and the test file did not change in the incremental diff. The claim that model construction raises an error for the incomplete pd.NA row was not verified in this pass. That claim is not part of #1449. Fixed-vector parameter misalignment is disclosed as out of scope and tracked in #1451.

Full details: Out of Scope Changes check

Explanation

The changes at the reviewed head address #1449 and the nullable-rt handling described in the PR objectives. The fillna(False) addition is in the same _rearrange_data split logic as the rt-column fix. Its comment states the connection to the row split. The incremental change since the previous head touches only src/hssm/utils.py. The previous assessment found the test and changelog changes tied to the fix. The PR description notes about #1439 and #1448 concern changelog numbering and merge coordination, not code. The fixed-vector parameter limitation is explicitly excluded and not implemented here.

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Actionable comments posted: 2


  • Fix comments: Fix CodeRabbit comments on this PR
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Inline comments:
Review comments at @src/hssm/utils.py:
- Around line 509-510: Update `_rearrange_data` to apply its row permutation to
each row-aligned fixed-vector parameter before building `fixed_vector_params`.
Derive the permutation from original row positions so it remains correct when
`rt` is not the first column, and preserve each vector’s length equal to the row
count.
- Line 510: Update the RT normalization and `missing_indices` construction in
the rearrangement flow so nullable RT values are either normalized before
partitioning or rejected explicitly. Ensure the missing and non-missing
partitions are exhaustive and no row is omitted when `rt` contains `pd.NA`,
while preserving the existing handling of unrelated nullable values in float
`missing_data` inputs.

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Comment thread src/hssm/utils.py Resolved
Comment thread src/hssm/utils.py Resolved
With a nullable dtype, `rt == -999.0` gives `pd.NA` for a `pd.NA` value, and
such a row fell out of both the missing and the non-missing split. Fill the
mask with False, so the row stays and building the model reports it as
incomplete instead of dropping it.

Claude helped me with this change.
Resolve the changelog conflict: main now has items 19 to 22, so the
missing_data entry becomes item 23.

Claude helped me with this change.
The changelog entry moves to item 24 after the entry main added
(lnccbrown#1501). No code conflict.

Claude helped me with this change.

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missing_data: missing-RT rows are only found when rt is the first column, giving a silently wrong likelihood

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