9.2.7. Testing¶
Testing DataGrabbers.
- pydantic model junifer.testing.datagrabbers.OasisVBMTestingDataGrabber¶
DataGrabber for Oasis VBM testing data.
Wrapper for
nilearn.datasets.fetch_oasis_vbm().Create a new model by parsing and validating input data from keyword arguments.
Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.
self is explicitly positional-only to allow self as a field name.
Show JSON schema
{ "title": "OasisVBMTestingDataGrabber", "description": "DataGrabber for Oasis VBM testing data.\n\nWrapper for :func:`nilearn.datasets.fetch_oasis_vbm`.", "type": "object", "properties": { "types": { "default": [ "VBM_GM" ], "items": { "$ref": "#/$defs/DataType" }, "title": "Types", "type": "array" }, "datadir": { "default": "/tmp/tmp41tyqwjw", "format": "path", "title": "Datadir", "type": "string" } }, "$defs": { "DataType": { "description": "Accepted data type.", "enum": [ "T1w", "T2w", "BOLD", "Warp", "VBM_GM", "VBM_WM", "VBM_CSF", "fALFF", "GCOR", "LCOR", "DWI", "FreeSurfer" ], "title": "DataType", "type": "string" } } }
- Config:
use_enum_values: bool = True
- Fields:
- get_item(subject)¶
Implement indexing support.
- model_post_init(context)¶
Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.
- enum junifer.testing.datagrabbers.PartlyCloudyAgeGroup(value)¶
Age group to fetch.
Adult: fetch adults only (n=33, ages 18-39)Child: fetch children only (n=122, ages 3-12)Both: fetch full sample (n=155)
- Member Type:
Valid values are as follows:
- Adult = <PartlyCloudyAgeGroup.Adult: 'adult'>¶
- Child = <PartlyCloudyAgeGroup.Child: 'child'>¶
- Both = <PartlyCloudyAgeGroup.Both: 'both'>¶
- pydantic model junifer.testing.datagrabbers.PartlyCloudyTestingDataGrabber¶
DataGrabber for Partly Cloudy dataset.
Wrapper for
nilearn.datasets.fetch_development_fmri().- Parameters:
- reduce_confoundsbool, optional
If True, the returned confounds only include 6 motion parameters, mean framewise displacement, signal from white matter, csf, and 6 anatomical compcor parameters. This selection only serves the purpose of having realistic examples. Depending on your research question, other confounds might be more appropriate. If False, returns all fMRIPrep confounds (default True).
- age_group
PartlyCloudyAgeGroup, optional Age group to fetch (default PartlyCloudyAgeGroup.Both).
Create a new model by parsing and validating input data from keyword arguments.
Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.
self is explicitly positional-only to allow self as a field name.
Show JSON schema
{ "title": "PartlyCloudyTestingDataGrabber", "description": "DataGrabber for Partly Cloudy dataset.\n\nWrapper for :func:`nilearn.datasets.fetch_development_fmri`.\n\nParameters\n----------\nreduce_confounds : bool, optional\n If True, the returned confounds only include 6 motion parameters,\n mean framewise displacement, signal from white matter, csf, and\n 6 anatomical compcor parameters. This selection only serves the\n purpose of having realistic examples. Depending on your research\n question, other confounds might be more appropriate.\n If False, returns all :term:`fMRIPrep` confounds (default True).\nage_group : :enum:`.PartlyCloudyAgeGroup`, optional\n Age group to fetch (default PartlyCloudyAgeGroup.Both).", "type": "object", "properties": { "types": { "default": [ "BOLD" ], "items": { "$ref": "#/$defs/DataType" }, "title": "Types", "type": "array" }, "datadir": { "default": "/tmp/tmp5ibdoyq3", "format": "path", "title": "Datadir", "type": "string" }, "reduce_confounds": { "default": true, "title": "Reduce Confounds", "type": "boolean" }, "age_group": { "$ref": "#/$defs/PartlyCloudyAgeGroup", "default": "both" } }, "$defs": { "DataType": { "description": "Accepted data type.", "enum": [ "T1w", "T2w", "BOLD", "Warp", "VBM_GM", "VBM_WM", "VBM_CSF", "fALFF", "GCOR", "LCOR", "DWI", "FreeSurfer" ], "title": "DataType", "type": "string" }, "PartlyCloudyAgeGroup": { "description": "Age group to fetch.\n\n* ``Adult`` : fetch adults only (n=33, ages 18-39)\n* ``Child`` : fetch children only (n=122, ages 3-12)\n* ``Both`` : fetch full sample (n=155)", "enum": [ "adult", "child", "both" ], "title": "PartlyCloudyAgeGroup", "type": "string" } } }
- Config:
use_enum_values: bool = True
- Fields:
- field age_group: PartlyCloudyAgeGroup = PartlyCloudyAgeGroup.Both¶
- pydantic model junifer.testing.datagrabbers.SPMAuditoryTestingDataGrabber¶
DataGrabber for SPM Auditory dataset.
Wrapper for
nilearn.datasets.fetch_spm_auditory().Create a new model by parsing and validating input data from keyword arguments.
Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.
self is explicitly positional-only to allow self as a field name.
Show JSON schema
{ "title": "SPMAuditoryTestingDataGrabber", "description": "DataGrabber for SPM Auditory dataset.\n\nWrapper for :func:`nilearn.datasets.fetch_spm_auditory`.", "type": "object", "properties": { "types": { "default": [ "BOLD", "T1w" ], "items": { "$ref": "#/$defs/DataType" }, "title": "Types", "type": "array" }, "datadir": { "default": "/tmp/tmpf7c8v3r_", "format": "path", "title": "Datadir", "type": "string" } }, "$defs": { "DataType": { "description": "Accepted data type.", "enum": [ "T1w", "T2w", "BOLD", "Warp", "VBM_GM", "VBM_WM", "VBM_CSF", "fALFF", "GCOR", "LCOR", "DWI", "FreeSurfer" ], "title": "DataType", "type": "string" } } }
- Config:
use_enum_values: bool = True
- Fields: