Various fixes and improvements for v4.0.1 - #276
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ms2_tolerance was removed as an MS2PIPFeatureGenerator kwarg in favor of the top-level tolerance_value/tolerance_mode, but the key was left behind in config defaults, schema, docs, and the sage example.
…e kwarg distribution deeplc_retrain was redundant since it's already scoped under the deeplc feature generator's own config block. Renamed to finetune; the old name is still accepted for backward compatibility but now emits a DeprecationWarning and is mapped onto the new option, with an explicit finetune taking precedence. Also consolidated the near-duplicate predict/finetune kwarg filtering into a single helper, and dropped the unused self._verbose attribute.
…ad code model_dir was a real MS2PIPFeatureGenerator kwarg missing from the config schema, and im2deep's reference_dataset schema default claimed "Meier_unimod.parquet" while the actual default falls through to IM2Deep's own bundled reference dataset. Also removes an unused self._verbose leftover in im2deep.py, mirroring the one already removed from deeplc.py.
README.md had `[ProteomeDiscoverer](#)`, a bare `#` link with no real target. MyST resolves it to an empty cross-reference string, which is harmless locally (just a warning) but crashes sphinx-argparse's xref resolution on ReadTheDocs, failing the whole docs build. De-linked to plain text instead of guessing an unverified vendor URL.
Add entries for v2.0.0 through v3.2.1, compiled from GitHub release notes, so the changelog covers full project history in Keep a Changelog format.
… fix/config-defaults-4.0.1 # Conflicts: # CHANGELOG.md
Drop `==` pins for installer-group packages already constrained by main dependencies (deeplc, im2deep, ms2rescore-rs, psm_utils) -- uv.lock is a single shared resolution, so pinning them twice was redundant and only risked silent drift between the two. Add `--locked` to both installer CI jobs so `uv sync` fails loudly instead of silently re-resolving if pyproject.toml and uv.lock ever fall out of sync. Locked dependency versions can be explicitly upgraded by running `uv sync --all-extras --all-groups --upgrade` Also bump ghaction-chocolatey to v4 in both workflows. Co-authored-by: Copilot <copilot@github.com>
`feature_weights_by_generator()` called `.median()` without `numeric_only=True` on a DataFrame that still had an object-dtype `fold` column from the earlier melt, raising `agg function failed [how->median,dtype->object]`. The exception was caught and only logged as a warning, so the "Feature usage in rescoring model" section silently disappeared from every report generated since the ristretto migration. Add `numeric_only=True`, matching the sibling `feature_weights()` function two lines up.
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Changed
deeplcfeature generator:deeplc_retrainoption renamed tofinetune(redundant naming, already scoped underdeeplc). The old name is still accepted but deprecated, and emits a warning.Fixed
ms2_toleranceoption from the defaultms2pipfeature generator configuration, schema, and example configs. Fragment tolerance is configured centrally via the top-leveltolerance_value/tolerance_modeoptions;MS2PIPFeatureGeneratorno longer acceptsms2_tolerance.model_dir(ms2pipfeature generator) in the configuration schema; it already worked but was missing from the schema.im2deep'sreference_dataset, which incorrectly claimed"Meier_unimod.parquet". The actual default falls through to IM2Deep's own bundled reference dataset.