AFQ.definitions.mapping
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Module Contents#
Classes#
Use an existing FNIRT map. Expects a warp file |
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Does not perform any transformations from MNI to subject where |
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Calculate a Syn registration for each subject/session |
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Calculate a SLR registration for each subject/session |
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Calculate an affine registration for each subject/session |
- class AFQ.definitions.mapping.FnirtMap(warp_path=None, space_path=None, warp_suffix=None, space_suffix=None, warp_filters={}, space_filters={})[source]#
Bases:
AFQ.definitions.utils.Definition
Use an existing FNIRT map. Expects a warp file and an image file for each subject / session; image file is used as src space for warp.
- Parameters
- warp_pathstr, optional
path to file to get warp from. Use this or warp_suffix. Default: None
- space_pathstr, optional
path to file to get warp from. Use this or space_suffix. Default: None
- warp_suffixstr, optional
suffix to pass to bids_layout.get() to identify the warp file. Default: None
- space_suffixstr, optional
suffix to pass to bids_layout.get() to identify the space file. Default: None
- warp_filtersstr, optional
Additional filters to pass to bids_layout.get() to identify the warp file. Default: {}
- space_filtersstr, optional
Additional filters to pass to bids_layout.get() to identify the space file. Default: {}
Notes
If you have an existing mapping calculated using Fnirt, you can pass bids filters to
AFQ.definitions.mapping.FnirtMap
and pyAFQ will find and use that mapping.Examples
- fnirt_map = FnirtMap(
warp_suffix=”warp”, space_suffix=”MNI”, warp_filters={“scope”: “TBSS”}, space_filters={“scope”: “TBSS”})
api.GroupAFQ(mapping=fnirt_map)
- class AFQ.definitions.mapping.IdentityMap[source]#
Bases:
AFQ.definitions.utils.Definition
Does not perform any transformations from MNI to subject where pyAFQ normally would.
Examples
my_example_mapping = IdentityMap() api.GroupAFQ(mapping=my_example_mapping)
- class AFQ.definitions.mapping.SynMap(use_prealign=True, affine_kwargs={}, syn_kwargs={})[source]#
Bases:
GeneratedMapMixin
,AFQ.definitions.utils.Definition
Calculate a Syn registration for each subject/session using reg_subject and reg_template.
- Parameters
- use_prealignbool
Whether to perform a linear pre-registration. Default: True
- affine_kwargsdictionary, optional
Parameters to pass to affine_registration in dipy.align, which does the linear pre-alignment. Only used if use_prealign is True. Default: {}
- syn_kwargsdictionary, optional
Parameters to pass to syn_registration in dipy.align, which does the SyN alignment. Default: {}
Notes
The default mapping class is to use Symmetric Diffeomorphic Image Registration (SyN). This is done with an optional linear pre-alignment by default. The parameters of the pre-alginment can be specified when initializing the SynMap.
Examples
api.GroupAFQ(mapping=SynMap())
- class AFQ.definitions.mapping.SlrMap(slr_kwargs={})[source]#
Bases:
GeneratedMapMixin
,AFQ.definitions.utils.Definition
Calculate a SLR registration for each subject/session using reg_subject and reg_template.
- Parameters
- slr_kwargsdictionary, optional
Parameters to pass to whole_brain_slr in dipy, which does the SLR alignment. Default: {}
Notes
Use this class to tell pyAFQ to use Streamline-based Linear Registration (SLR) for registration. Note that the reg_template and reg_subject parameters passed to
AFQ.api.group.GroupAFQ
should be streamlines when using this registration.Examples
api.GroupAFQ(mapping=SlrMap())
- class AFQ.definitions.mapping.AffMap(affine_kwargs={})[source]#
Bases:
GeneratedMapMixin
,AFQ.definitions.utils.Definition
Calculate an affine registration for each subject/session using reg_subject and reg_template.
- Parameters
- affine_kwargsdictionary, optional
Parameters to pass to affine_registration in dipy.align, which does the linear pre-alignment. Default: {}
Notes
This will only perform a linear alignment for registration.
Examples
api.GroupAFQ(mapping=AffMap())