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[ENH] implement methods and test the nimads methods (#921)
* implement methods and test the nimads methods * formatting * show more functionality * remove useless test
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‎examples/01_datasets/05_plot_nimads.py

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Using NIMADS with NiMARE
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========================
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How to use the NeuroImaging Meta-Analysis Data Structure
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`(NIMADS) <https://neurostuff.github.io/NIMADS/>`_ with NiMARE.
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This example demonstrates the key functionality of the NeuroImaging Meta-Analysis Data Structure
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(NIMADS) with NiMARE, including working with StudySets, annotations, coordinates, and metadata.
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"""
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from pprint import pprint
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from requests import request
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from nimare.io import convert_nimads_to_dataset
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from nimare.nimads import Studyset
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###############################################################################
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# Download Data from NeuroStore
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# -----------------------------------------------------------------------------
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return response.json()
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# Download a studyset and its annotation
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nimads_studyset = download_file("https://neurostore.org/api/studysets/Cv2LLUqG76W9?nested=true")
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nimads_annotation = download_file("https://neurostore.org/api/annotations/76PyNqoTNEsE")
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###############################################################################
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# Load Data
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# Create and Explore StudySet
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# -----------------------------------------------------------------------------
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# Load the json files into a NiMADS Studyset object.
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# Load the data into a NiMADS Studyset object and explore its contents
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studyset = Studyset(nimads_studyset, annotations=nimads_annotation)
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# Display basic information about the studyset
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print("\nStudySet Information:")
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print("-" * 50)
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print(f"ID: {studyset.id}")
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print(f"Name: {studyset.name}")
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print(f"Number of studies: {len(studyset.studies)}")
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print(f"Number of annotations: {len(studyset.annotations)}")
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###############################################################################
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# Convert to NiMARE Dataset
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# Explore Studies and Analyses
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# -----------------------------------------------------------------------------
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# Convert the NiMADS Studyset object to a NiMARE Dataset object.
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# Then you can run NiMARE analyses on the Dataset object.
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# Look at the first study and its analyses in detail
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first_study = studyset.studies[0]
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print("\nFirst Study Details:")
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print("-" * 50)
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print(f"Study ID: {first_study.id}")
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print(f"Title: {first_study.name}")
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print(f"Authors: {first_study.authors}")
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print(f"Publication: {first_study.publication}")
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print(f"Number of analyses: {len(first_study.analyses)}")
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# Show details of the first analysis
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first_analysis = first_study.analyses[0]
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print("\nFirst Analysis Details:")
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print("-" * 50)
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print(f"Analysis ID: {first_analysis.id}")
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print(f"Analysis Name: {first_analysis.name}")
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print(f"Number of coordinates: {len(first_analysis.points)}")
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print(f"Number of conditions: {len(first_analysis.conditions)}")
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###############################################################################
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# Working with Coordinates
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# -----------------------------------------------------------------------------
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# Demonstrate coordinate-based queries
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# Example coordinate in MNI space
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example_coord = [-42, -58, -15] # MNI coordinates
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print("\nCoordinate Search Results:")
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print("-" * 50)
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print(f"Searching near coordinate: {example_coord}")
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# Find analyses with coordinates within 10mm
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nearby_analyses = studyset.get_analyses_by_coordinates(example_coord, r=10)
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print(f"\nFound {len(nearby_analyses)} analyses within 10mm")
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# Find 5 closest analyses
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closest_analyses = studyset.get_analyses_by_coordinates(example_coord, n=5)
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print(f"\nClosest 5 analyses: {closest_analyses}")
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nimare_dset = studyset.to_dataset()
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nimare_dset.coordinates.head()
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###############################################################################
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# Directly to NiMARE Dataset
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# Working with Annotations
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# -----------------------------------------------------------------------------
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# Alternatively, you can convert the NiMADS json files directly to a NiMARE Dataset object
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# if you wish to skip using the nimads studyset object directly.
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# Demonstrate how to work with study annotations
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nimare_dset_2 = convert_nimads_to_dataset(nimads_studyset, nimads_annotation)
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nimare_dset_2.coordinates.head()
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print("\nAnnotation Information:")
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print("-" * 50)
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for annotation in studyset.annotations:
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print(f"\nAnnotation ID: {annotation.id}")
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print(f"Annotation Name: {annotation.name}")
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print(f"Number of notes: {len(annotation.notes)}")
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###############################################################################
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# Query Metadata
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# -----------------------------------------------------------------------------
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# Show how to query analyses based on metadata
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# Get all analyses that have a specific metadata field
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metadata_results = studyset.get_analyses_by_metadata("contrast_type")
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print("\nAnalyses with contrast_type metadata:")
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print("-" * 50)
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pprint(metadata_results)
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###############################################################################
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# Convert to NiMARE Dataset
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# -----------------------------------------------------------------------------
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# Convert the NiMADS Studyset to a NiMARE Dataset for further analysis
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nimare_dset = studyset.to_dataset()
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print("\nNiMARE Dataset Information:")
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print("-" * 50)
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print("Coordinates DataFrame Preview:")
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print(nimare_dset.coordinates.head())

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