Run an analysis query over the annotation's studyset and write its result into the notes: column (boolean) is true for each analysis the query selects and false for every other, and each of feature_columns (string) carries that analysis's feature, or null where its record says nothing. The annotation's metadata.analysis_queries.<column> keeps the selection frozen: the canonical query, the selected analysis ids, the normalizers and fits (mapping_tools) their features came from, and when.
| Name | Type | Description | Notes |
|---|---|---|---|
| query | AnalysisQuery | ||
| column | str | [optional] [default to 'included'] | |
| feature_columns | List[str] | [optional] |
from neurostore_sdk.models.annotation_pipeline_extension_analysis_query import AnnotationPipelineExtensionAnalysisQuery
# TODO update the JSON string below
json = "{}"
# create an instance of AnnotationPipelineExtensionAnalysisQuery from a JSON string
annotation_pipeline_extension_analysis_query_instance = AnnotationPipelineExtensionAnalysisQuery.from_json(json)
# print the JSON string representation of the object
print(AnnotationPipelineExtensionAnalysisQuery.to_json())
# convert the object into a dict
annotation_pipeline_extension_analysis_query_dict = annotation_pipeline_extension_analysis_query_instance.to_dict()
# create an instance of AnnotationPipelineExtensionAnalysisQuery from a dict
annotation_pipeline_extension_analysis_query_from_dict = AnnotationPipelineExtensionAnalysisQuery.from_dict(annotation_pipeline_extension_analysis_query_dict)