def narps():
basedir = '/tmp/data'
assert os.path.exists(basedir)
narps = Narps(basedir)
narps.load_data()
narps.metadata = pandas.read_csv(
os.path.join(narps.dirs.dirs['metadata'], 'all_metadata.csv'))
return (narps)
def narps():
dataurl = os.environ['DATA_URL']
basedir = '/tmp/data'
if not os.path.exists(basedir):
os.mkdir(basedir)
narps = Narps(basedir, dataurl=dataurl)
narps.write_data()
return (narps)
if args.dataurl is not None:
dataurl = args.dataurl
elif 'DATA_URL' in os.environ:
dataurl = os.environ['DATA_URL']
print('reading data URL from environment')
else:
dataurl = None
print('info.json no present - data downloading will be disabled')
# set up simulation if specified
if args.simulate:
print('using simulated data')
# load main class from real analysis
narps_orig = Narps(basedir, overwrite=False)
# create simulated data
# setup main class from original data
narps = Narps(basedir)
narps.load_data()
# Load full metadata and put into narps structure
narps.metadata = pandas.read_csv(
os.path.join(narps.dirs.dirs['metadata'], 'all_metadata.csv'))
basedir = setup_simulated_data(narps, verbose=False)
make_orig_image_sets(narps,
basedir,
verbose=True,
action='store_true',
help='skip creation of overlap/range/std maps')
args = parser.parse_args()
# set up base directory
if args.basedir is not None:
basedir = args.basedir
elif 'NARPS_BASEDIR' in os.environ:
basedir = os.environ['NARPS_BASEDIR']
print("using basedir specified in NARPS_BASEDIR")
else:
basedir = '/data'
print("using default basedir:", basedir)
# setup main class
narps = Narps(basedir)
narps.load_data()
# Load full metadata and put into narps structure
narps.metadata = pandas.read_csv(
os.path.join(narps.dirs.dirs['metadata'], 'all_metadata.csv'))
if not args.test:
if not args.skip_maps:
# create maps showing overlap of thresholded images
mk_overlap_maps(narps)
mk_range_maps(narps)
mk_std_maps(narps)
if args.detailed:
'mean_unthresh_correlation_by_cluster.csv'),
index=False)
return (results_df_wide)
if __name__ == "__main__":
# parse arguments
parser = argparse.ArgumentParser(description='Get similarity summary')
parser.add_argument('-b', '--basedir', help='base directory')
parser.add_argument('-t',
'--test',
action='store_true',
help='use testing mode (no processing)')
args = parser.parse_args()
# set up base directory
if args.basedir is not None:
basedir = args.basedir
elif 'NARPS_BASEDIR' in os.environ:
basedir = os.environ['NARPS_BASEDIR']
print("using basedir specified in NARPS_BASEDIR")
else:
basedir = '/data'
print("using default basedir:", basedir)
narps = Narps(basedir)
if not args.test:
corr_summary = get_similarity_summary(narps)
alldata_df.loc[i, 'package'] = 'Other'
# save data for loading into R
alldata_df.to_csv(
os.path.join(narps.dirs.dirs['metadata'], 'all_metadata.csv'))
if __name__ == "__main__":
# parse arguments
parser = argparse.ArgumentParser(description='Generate NARPS metadata')
parser.add_argument('-b', '--basedir', help='base directory')
args = parser.parse_args()
# set up base directory
if args.basedir is not None:
basedir = args.basedir
elif 'NARPS_BASEDIR' in os.environ:
basedir = os.environ['NARPS_BASEDIR']
print("using basedir specified in NARPS_BASEDIR")
else:
basedir = '/data'
print("using default basedir:", basedir)
overwrite = False
# setup main class
narps = Narps(basedir, overwrite=overwrite)
prepare_metadata(narps)
cut_coords=cut_coords,
axes=ax[i])
plt.savefig(os.path.join(narps.dirs.dirs['figures'], 'consensus_map.pdf'))
plt.close(fig)
if __name__ == "__main__":
# set an environment variable called NARPS_BASEDIR
# with location of base directory
if 'NARPS_BASEDIR' in os.environ:
basedir = os.environ['NARPS_BASEDIR']
else:
basedir = '/data'
# setup main class
narps = Narps(basedir)
narps.load_data()
narps.dirs.dirs['consensus'] = os.path.join(narps.dirs.dirs['output'],
'consensus_analysis')
logfile = os.path.join(narps.dirs.dirs['logs'],
'%s.txt' % sys.argv[0].split('.')[0])
log_to_file(logfile, 'running %s' % sys.argv[0].split('.')[0], flush=True)
if not os.path.exists(narps.dirs.dirs['consensus']):
os.mkdir(narps.dirs.dirs['consensus'])
run_ttests(narps, logfile)
mk_figures(narps, logfile)
# save data to file
metadata_merged.to_csv(
os.path.join(narps.dirs.dirs['figures'],
'MethodsTableMetadataMerged.csv'))
decision_wide.to_csv(
os.path.join(narps.dirs.dirs['figures'], 'DecisionDataWide.csv'))
confidence_wide.to_csv(
os.path.join(narps.dirs.dirs['figures'], 'ConfidenceDataWide.csv'))
if __name__ == "__main__":
# set an environment variable called NARPS_BASEDIR
# with location of base directory
if 'NARPS_BASEDIR' in os.environ:
basedir = os.environ['NARPS_BASEDIR']
else:
basedir = '/tmp/data'
# setup main class
narps = Narps(basedir, dataurl=os.environ['DATA_URL'])
narps.load_data()
logfile = os.path.join(narps.dirs.dirs['logs'],
'MakeSupplementaryFigure1.txt')
log_to_file(logfile, 'running MakeSupplementaryFigure1.py', flush=True)
metadata = get_all_metadata(narps)
mk_supp_figure1(narps, metadata)
def narps(basedir):
narps = Narps(basedir)
narps.write_data()
return (narps)
