WELL_KNOWN_IDS = Recoder((('9861', 'H0351.2001', '178238387', '157722636'),
('10021', 'H0351.2002', '178238373', '157723301'),
('12876', 'H0351.1009', '178238359', '157722290'),
('15496', 'H0351.1015', '178238266', '162021642'),
('14380', 'H0351.1012', '178238316', '157721937'),
('15697', 'H0351.1016', '178236545', '157682966')),
fields=(
'subj',
'uid',
'url',
't1w',
))
VALID_DONORS = sorted(
WELL_KNOWN_IDS.value_set('subj') | WELL_KNOWN_IDS.value_set('uid'))
def _get_dataset_dir(dataset_name, data_dir=None, verbose=1):
"""
Gets path to `dataset_name`
Parameters
----------
dataset_name : str
The name of the dataset in question
data_dir : str, optional
Path to use as data directory. If not specified, will check for
environmental variables 'ABAGEN_DATA'; if that is not set, will use
'~/abagen-data' instead. Default: None
verbose : int, optional
from nilearn.datasets.utils import _fetch_files, _get_dataset_dir
import pandas as pd
from sklearn.utils import Bunch
from abagen import io
WELL_KNOWN_IDS = Recoder(
(('9861', 'H0351.2001', '178238387', '157722636'),
('10021', 'H0351.2002', '178238373', '157723301'),
('12876', 'H0351.1009', '178238359', '157722290'),
('15496', 'H0351.1015', '178238266', '162021642'),
('14380', 'H0351.1012', '178238316', '157721937'),
('15697', 'H0351.1016', '178236545', '157682966')),
fields=('subj', 'uid', 'url', 't1w',)
)
VALID_DONORS = sorted(WELL_KNOWN_IDS.value_set('subj') |
WELL_KNOWN_IDS.value_set('uid'))
def fetch_microarray(data_dir=None, donors=['9861'], resume=True, verbose=1,
convert=True):
"""
Downloads the Allen Human Brain Atlas microarray expression dataset
Parameters
----------
data_dir : str, optional
Directory where data should be downloaded and unpacked. Default:
current directory
donors : list, optional
List of donors to download; can be either donor number or UID. Can also
