def testEmptyArchiveAppend(validBidsI, imageMetadata, tmpdir):
# Create in root with no BIDS-I, then append to make non-empty archive
datasetRoot = Path(tmpdir, testEmptyArchiveAppend.__name__)
archive = BidsArchive(datasetRoot)
archive.appendIncremental(validBidsI)
assert not archive.isEmpty()
assert archiveHasMetadata(archive, imageMetadata)
assert appendDataMatches(archive, validBidsI)
assert isValidBidsArchive(datasetRoot)
def testGetEvents(validBidsI, imageMetadata, tmpdir):
archive = BidsArchive(tmpdir)
archive.appendIncremental(validBidsI)
# Get the events from the archive as a pandas data frame
events = archive.getEvents()[0].get_df()
assert events is not None
# Check the required columns are present in the events file data frame
for column in ['onset', 'duration', 'response_time']:
assert column in events.columns
def doRuns(cfg, bidsInterface, subjInterface, webInterface):
"""
Process a run of a bids dataset. The subject and run configuration
values will be supplied by the cfg parameter.
Args:
cfg: configurations parsed from the project toml config file
bidsInterface: client interface to bids data
webInterface: client interface to user web page
Returns: no return value
"""
subject = cfg.subjectName
run = cfg.runNum[0]
entities = {
'subject': subject,
'run': run,
'suffix': 'bold',
'datatype': 'func'
}
webInterface.clearRunPlot(run)
if cfg.writeBidsArchive is True:
# Create a new bids archive from the incrementals
bidsArchivePath = os.path.join(tmpDir,
'bids_archive_' + uuid.uuid4().hex)
print(f'BIDS Archive will be written to {bidsArchivePath}')
newArchive = BidsArchive(bidsArchivePath)
# Initialize the bids stream
streamId = bidsInterface.initOpenNeuroStream(cfg.dsAccessionNumber,
**entities)
numVols = bidsInterface.getNumVolumes(streamId)
for idx in range(numVols):
bidsIncremental = bidsInterface.getIncremental(streamId, idx)
if cfg.writeBidsArchive is True:
newArchive.appendIncremental(bidsIncremental)
imageData = bidsIncremental.imageData
avg_niftiData = numpy.mean(imageData)
print("| average activation value for TR %d is %f" %
(idx, avg_niftiData))
webInterface.plotDataPoint(run, idx, float(avg_niftiData))
