Fix longitudinal functional template#331
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Templates for different takss _could_ be different resolutions. This refactors the resampling such that a template is generated per task for the longitudinal workflow.
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- Update stale docstring - Use "ents['task']" instead of filtering for - Address de-duping via assertion of grid for unique file paths - Fix resampling order for mask
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- Removed check for uniqueness of bold dataframe - Update stale docstring: `bold_ref` -> `bold_files` - Wrap task with `bids_safe_label` when calling `tpl.save` - Compare affines using `np.allclose` due to floating point precision - Use a BoldKey NamedTuple as key to unique bold files
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Generate a longitudinal template with bold resolution after the initial creation from anatomical data. This will be used as the reference image in downstream longitudinal functional processing.
This makes use of the first bold image found to extract the resolution. Another possibility is to resample it to a fixed resolution (potentially user provided), but this can be a downstream feature and will not be included in this PR.
Closes #330