[ENH] StatsModels: Add invalid_inputs parameter to allow dropping of missing data columns to run nodes#1145
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effigies merged 3 commits intobids-standard:masterfrom Sep 23, 2025
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Version 0.20.0 (September 24, 2025) New feature release in the 0.20.x series. This release finalizes some deprecations that were started in the 0.7 and 0.14 series. In particular, passing indexer arguments to ``BIDSLayout`` and disabling ``absolute_paths`` mode in ``BIDSLayout()`` or ``BIDSLayout.get()`` will now error. To adjust indexing behavior, create an explicit ``BIDSLayoutIndexer()`` and pass ``BIDSLayout(..., indexer=indexer)``. To access relative paths, use the ``BIDSFile.relative_path`` property on ``BIDSLayout.get()`` return values. * FIX: Check for attribute that can be absent before assigning (#1165) * FIX: Accommodate deprecations in the upcoming Pandas 3 release (#1173) * FIX: Repaired convolution issue that arises when onset values are repeated (#1133) * ENH: StatsModels: Add `invalid_inputs` parameter to allow dropping of missing data columns to run nodes (#1145) * ENH: Add missing root-level path patterns (#1169) * ENH: Parse ``seg-`` entities from dseg or probseg files (#1172) * DOC: Update link to derivatives config file (#1132) * MNT: Address warnings produced by pybids and dependencies (#1136) * MNT: Lock test environment, update with dependabot (#1134)
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BIDSStatsModelsNode.run()gracefully drops missing contrasts wheninvalid_contrasts=="drop", but missing data columns in the GLM at the run level (entries ofModel.X) currently always throw an error. As far as I can tell, this makes it impossible to useBIDSStatsModelsNode(and BIDS apps that depend on it, like fitlins) for tasks in which some conditions do not appear in some runs (a use case I happen to have at the moment, which also seems to pop up for others, e.g., here and here). This PR adds aninvalid_inputsparameterBIDSStatsModelsNode.run()andBIDSStatsModelsNodeOutput.__init__()that permits a"drop"value just likeinvalid_contrasts, which warns about missing data columns and then removes them fromvar_names. I've tested this modification withfitlinsand it appears to give the desired enhancement: individual runs estimate all and only the available contrasts (and missing contrasts at downstream nodes are then handled by the existinginvalid_contrastsfeature). I've set the default value ofinvalid_inputsto"error", so that the previous default behavior remains unchanged.