# Get all dois from collections using the NeuroVault API
from pyneurovault.api import get_collections, export_collections_tsv
# This will return a pandas data frame
collections = get_collections()
# Take a look at the fields
collections.columns
# Export collections tsv
export_collections_tsv("/home/vanessa/Desktop/dois.tsv",collections)
# Retrieve the "DOI" column, remove null values
dois = collections["DOI"][collections["DOI"].isnull()==False]
# Export them to a tab separated file
dois.to_csv("/home/vanessa/Desktop/dois.tsv",sep="\t",index=None)
# Or turn into a list for something else
dois.tolist()
# Get a collection
collection = api.get_collections(pks=457)
# collection.collection_id is 457
# Get all images
images = api.get_images()
# Get all images meta data for a collection
images = api.get_images(collection_pks=457)
# Remove images that are thresholded
images = api.filter(df=images,column_name="is_thresholded",field_value=False)
# Not in MNI
images = api.filter(df=images,column_name="not_mni",field_value=False)
# Just fMRI bold
images = api.filter(df=images,column_name="modality",field_value="fMRI-BOLD")
# Download images, collections, or both
api.export_images_tsv("/home/vanessa/Desktop/images.tsv",images)
api.export_collections_tsv("/home/vanessa/Desktop/collections.tsv",collection)
# Download all images to file, resample to target
outfolder = "/home/vanessa/Desktop"
standard = "/usr/share/fsl/data/standard/MNI152_T1_2mm_brain.nii.gz"
api.download_images(dest_dir = outfolder,images_df=images,target=standard)
# If you don't want to resample
api.download_images(dest_dir = outfolder,images_df=images,resample=False)
