def cluster_session(self, session, tetrode):
ephysSession = self.get_session_name(session)
oneTT = spikesorting.TetrodeToCluster(self.animalName,ephysSession,tetrode)
oneTT.load_waveforms()
oneTT.create_fet_files()
oneT
T.run_clustering()
oneTT.save_report()
def cluster_session(session, tetrode, features=['peak', 'valleyFirstHalf']):
#TODO: the oneTT obj here has dataTT attribute, the cms one does not
oneTT = spikesorting.TetrodeToCluster(session.subject, session.ephys_dir(),
tetrode, features)
oneTT.load_waveforms()
clusterFile = os.path.join(oneTT.clustersDir,
'Tetrode%d.clu.1' % oneTT.tetrode)
if os.path.isfile(clusterFile):
oneTT.dataTT.set_clusters(clusterFile)
else:
oneTT.create_fet_files()
oneTT.run_clustering()
oneTT.save_report()
return oneTT
for experiment in inforec.experiments:
for site in experiment.sites:
for session in site.sessions:
for tetrode in tetrodes:
fullPath = session.full_ephys_path()
fullFn = os.path.join(fullPath,
'Tetrode{}.spikes'.format(tetrode))
#print fullFn
fullBehav = session.full_behav_filename()
#print fullBehav
dataSpikes = loadopenephys.DataSpikes(fullFn)
ephysSession = '{}_{}'.format(session.date, session.timestamp)
features = ['peak', 'valleyFirstHalf']
oneTT = spikesorting.TetrodeToCluster(session.subject,
ephysSession, tetrode,
features)
oneTT.load_waveforms()
clusterFile = os.path.join(oneTT.clustersDir,
'Tetrode%d.clu.1' % oneTT.tetrode)
if os.path.isfile(clusterFile):
oneTT.dataTT.clusters = np.fromfile(clusterFile,
dtype='int32',
sep=' ')[1:]
else:
oneTT.create_fet_files()
oneTT.run_clustering()
oneTT.save_report()
#NOTE:Could create a mini dataframe with the clustering results at this point
'''
Fixing issues with the cluster report.
'''
from jaratoolbox import spikesorting
reload(spikesorting)
CASE = 1
if CASE == 1:
animalName = 'test030'
ephysSession = '2014-06-25_18-33-30_TT6goodGND'
tetrode = 6
oneTT = spikesorting.TetrodeToCluster(animalName, ephysSession, tetrode)
'''
oneTT.create_fet_files()
oneTT.run_clustering()
'''
'''
self.dataTT = loadopenephys.DataSpikes(self.tetrodeFile) #,readWaves=True)
self.nSpikes = self.dataTT.nRecords# FIXME: this is specific to the OpenEphys format
self.dataTT.samples = self.dataTT.samples.astype(float)-2**15# FIXME: this is specific to OpenEphys
self.dataTT.timestamps = self.dataTT.timestamps/self.dataTT.samplingRate
'''
oneTT.save_report()
'''
if timeZero is None:
timeZero = timeStamps[0]
'''
print 'here'
oneTT.create_fet_files()
oneTT.run_clustering()
oneTT.save_report()
ISIviolationsDict[ephysSession][tetrode-1]= oneTT.get_ISI_values() #you can only get the ISI values after running save_report()
except:
print "error with session "+ephysSession
if (ephysSession not in badSessionList):
badSessionList.append(ephysSession)
'''
for indEphys, ephysSession in enumerate(ephysSessionArray):
try:
for tetrode in range(1, (numTetrodes + 1)):
oneTT = spikesorting.TetrodeToCluster(
animalName,
ephysSession,
tetrode,
features=['peak', 'valleyFirstHalf'])
#oneTT.create_fet_files()
#oneTT.run_clustering()
oneTT.save_report('cluster_report_tuning')
except:
badSessions.append(ephysSession)
for session in badSessions:
print session
#oneTT.save_report()
#ISIviolationsDict[ephysSession][tetrode-1]= oneTT.get_ISI_values() #you can only get the ISI values after running save_report()
'''
finalOutputDir = outputDir+'/'+animalName+'_processed'
ISIDict = {}
def test_clustering_single_session(self):
oneTT = spikesorting.TetrodeToCluster('test', 'testdata', 2)
oneTT.load_waveforms()
oneTT.create_fet_files()
oneTT.run_clustering()
oneTT.save_report()
#subject = 'gosi004'
#ephysSession = '2017-02-11_15-46-30'
#ephysSession = '2017-02-11_15-54-13'
subject = 'd1pi015'
ephysSession = '2016-08-07_16-48-07'
srate = 30000.0
'''
inforecFilename = '/data/inforec/gosi004_inforec.py'
inforec = imp.load_source('module.name', inforecFilename)
inforec.experiments[5].sites[0].sessions[0].ephys_dir
'''
ttdata = spikesorting.TetrodeToCluster(subject, ephysSession, tetrode)
ttdata.load_waveforms()
ttdata.set_clusters_from_file()
'''
report = spikesorting.ClusterReportFromData(ttdata.timestamps,
ttdata.samples,
ttdata.clusters,
outputDir=None,
figtitle='title',
showfig=False)
'''
plt.clf()
for cluster in range(1, 7):
#cluster = 2
indsThisCluster = (ttdata.clusters == cluster)