def macm_workflow(ns_data_dir, output_dir, prefix, mask_fn):
# download neurosynth dataset if necessary
dataset_file = op.join(ns_data_dir, 'neurosynth_dataset.pkl.gz')
if not op.isfile(dataset_file):
if not op.isdir(ns_data_dir):
os.mkdir(ns_data_dir)
download(ns_data_dir, unpack=True)
###############################################################################
# Convert Neurosynth database to NiMARE dataset file
# --------------------------------------------------
dset = convert_neurosynth_to_dataset(
op.join(ns_data_dir, 'database.txt'),
op.join(ns_data_dir, 'features.txt'))
dset.save(dataset_file)
dset = Dataset.load(dataset_file)
mask_ids = dset.get_studies_by_mask(mask_fn)
maskdset = dset.slice(mask_ids)
nonmask_ids = sorted(list(set(dset.ids) - set(mask_ids)))
nonmaskdset = dset.slice(nonmask_ids)
ale = ALE(kernel__fwhm=15)
ale.fit(maskdset)
corr = FWECorrector(method='permutation',
n_iters=10,
n_cores=-1,
voxel_thresh=0.001)
cres = corr.transform(ale.results)
cres.save_maps(output_dir=output_dir, prefix=prefix)
def neurosynth_download(ns_data_dir):
dataset_file = op.join(ns_data_dir, "neurosynth_dataset.pkl.gz")
os.makedirs(ns_data_dir, exist_ok=True)
download(ns_data_dir, unpack=True)
###############################################################################
# Convert Neurosynth database to NiMARE dataset file
# --------------------------------------------------
dset = convert_neurosynth_to_dataset(op.join(ns_data_dir, "database.txt"),
op.join(ns_data_dir, "features.txt"))
dset.save(dataset_file)
def _getdata():
"""Downloads data from neurosynth and returns it as a Dataset.
Also pickles the dataset for future use."""
LOG.warning("Downloading and processing Neurosynth database")
os.makedirs("data", exist_ok=True)
from neurosynth.base.dataset import download
download(path="data", unpack=True)
data = Dataset("data/database.txt")
data.add_features("data/features.txt")
data.save("data/dataset.pkl")
return data
def neurosynth_download(ns_data_dir=None):
if ns_data_dir is None:
raise Exception('A valid directory is required for downloading Neurosynth data!')
dataset_file = op.join(ns_data_dir, 'neurosynth_dataset.pkl.gz')
if not op.isdir(ns_data_dir):
os.mkdir(ns_data_dir)
download(ns_data_dir, unpack=True)
###############################################################################
# Convert Neurosynth database to NiMARE dataset file
# --------------------------------------------------
dset = convert_neurosynth_to_dataset(
op.join(ns_data_dir, 'database.txt'),
op.join(ns_data_dir, 'features.txt'))
dset.save(dataset_file)
def fetch_neurosynth_dataset(data_dir, return_pkl=True):
"""Downloads the Neurosynth dataset
Parameters
----------
data_dir : str
Directory in which to download the dataset.
return_pkl : bool
If true, creates and returns the .pkl file. Otherwise returns
the dataset and features files.
Returns
-------
tuple, str
If save_pkl is false, returns a tuple containing the path to the
database.txt and the features.txt file. Otherwise returns the path
to the .pkl file.
"""
if not os.path.isdir(data_dir):
os.mkdir(data_dir)
dataset_file = os.path.join(data_dir, "database.txt")
if not os.path.isfile(dataset_file):
logging.info("Downloading the Neurosynth dataset.")
download(data_dir, unpack=True)
feature_file = os.path.join(data_dir, "features.txt")
if return_pkl:
pkl_file = os.path.join(data_dir, "dataset.pkl")
if not os.path.isfile(pkl_file):
logging.info(
"Converting Neurosynth data to a .pkl file. This may take a while."
)
dataset = Dataset(dataset_file, feature_file)
dataset.save(pkl_file)
return pkl_file
return (dataset_file, feature_file)
# --------------------------------
import os
from neurosynth.base.dataset import download
import nimare
###############################################################################
# Download Neurosynth
# --------------------------------
out_dir = os.path.abspath('../example_data/')
if not os.path.isdir(out_dir):
os.mkdir(out_dir)
if not os.path.isfile(os.path.join(out_dir, 'database.txt')):
download(out_dir, unpack=True)
###############################################################################
# Convert Neurosynth database to NiMARE dataset file
# --------------------------------------------------
dset = nimare.io.convert_neurosynth_to_dataset(
os.path.join(out_dir, 'database.txt'),
os.path.join(out_dir, 'features.txt'))
dset.save(os.path.join(out_dir, 'neurosynth_dataset.pkl.gz'))
###############################################################################
# Add article abstracts to dataset
# --------------------------------
dset = nimare.extract.download_abstracts(dset, '*****@*****.**')
dset.save(os.path.join(out_dir, 'neurosynth_nimare_with_abstracts.pkl.gz'))
"""
Download Neurosynth dataset and add abstracts.
"""
import os
from neurosynth.base.dataset import download
import nimare
# Download Neurosynth
if not os.path.isfile('resources/database.txt'):
download('resources/', unpack=True)
# Convert Neurosynth database files to NiMARE Dataset
dset = nimare.io.convert_neurosynth_to_dataset('resources/database.txt',
'resources/features.txt')
# Add article abstracts to Dataset and save to file
dset = nimare.extract.download_abstracts(dset, '*****@*****.**')
dset.save('resources/neurosynth_with_abstracts.pkl.gz')