Python write_fet_file示例

示例#1

 def create_multisession_fet_files(self):
     if not os.path.exists(self.clustersDir):
         print 'Creating clusters directory: %s'%(self.clustersDir)
         os.makedirs(self.clustersDir)
     if self.samples is None:
         self.load_all_waveforms()
     self.featureValues = spikesorting.calculate_features(self.samples,self.featureNames)
     spikesorting.write_fet_file(self.fetFilename, self.featureValues)

示例#2

文件： clusterManySessions_v2.py 项目： sjara/jaratoolbox

 def create_multisession_fet_files(self):
     if not os.path.exists(self.clustersDir):
         print 'Creating clusters directory: %s'%(self.clustersDir)
         os.makedirs(self.clustersDir)
     if self.samples is None:
         self.load_waveforms()
     self.featureValues = spikesorting.calculate_features(self.samples,self.featureNames)
     spikesorting.write_fet_file(self.fetFilename, self.featureValues)

示例#3

文件： test006_spikesorting.py 项目： sjara/jaratoolbox

from pylab import *
N_CHANNELS = 4
SAMPLES_PER_SPIKE = 40

dataDir = os.path.join(settings.EPHYS_PATH,'%s/%s/'%(animalName,ephysSession))
tetrodeFile = os.path.join(dataDir,'Tetrode%d.spikes'%tetrode)

dataTT = loadopenephys.DataSpikes(tetrodeFile)
dataTT.timestamps = dataTT.timestamps/0.03  # in microsec
dataTT.samples = dataTT.samples.astype(float)-2**15
dataTT.set_clusters('/tmp/TT2.clu.1')

crep = spikesorting.ClusterReportFromData(dataTT)


'''
dataTT.samples = dataTT.samples.reshape((-1,N_CHANNELS,SAMPLES_PER_SPIKE),order='C')

fetArray = spikesorting.calculate_features(dataTT.samples,['peak','valley'])

spikesorting.write_fet_file('/tmp/TT2.fet.1',fetArray)
'''

'''
plot(dataTT.samples[:10,:].T,'.-')
draw()
show()
'''

'''
~/tmp/klustakwik/KK2/KlustaKwik TT6 1 -Subset 1e5 -MinClusters 6 -MaxClusters 12 -MaxPossibleClusters 12 -UseFeatures 11111111

示例#4

reload(loadopenephys)
from pylab import *
N_CHANNELS = 4
SAMPLES_PER_SPIKE = 40

dataDir = os.path.join(settings.EPHYS_PATH,
                       '%s/%s/' % (animalName, ephysSession))
tetrodeFile = os.path.join(dataDir, 'Tetrode%d.spikes' % tetrode)

dataTT = loadopenephys.DataSpikes(tetrodeFile)
dataTT.timestamps = dataTT.timestamps / 0.03  # in microsec
dataTT.samples = dataTT.samples.astype(float) - 2**15
dataTT.set_clusters('/tmp/TT2.clu.1')

crep = spikesorting.ClusterReportFromData(dataTT)
'''
dataTT.samples = dataTT.samples.reshape((-1,N_CHANNELS,SAMPLES_PER_SPIKE),order='C')

fetArray = spikesorting.calculate_features(dataTT.samples,['peak','valley'])

spikesorting.write_fet_file('/tmp/TT2.fet.1',fetArray)
'''
'''
plot(dataTT.samples[:10,:].T,'.-')
draw()
show()
'''
'''
~/tmp/klustakwik/KK2/KlustaKwik TT6 1 -Subset 1e5 -MinClusters 6 -MaxClusters 12 -MaxPossibleClusters 12 -UseFeatures 11111111

~/tmp/klustakwik/KK2/KlustaKwik TT6 1 -Subset 1e5 -MinClusters 10 -MaxClusters 24 -MaxPossibleClusters 12 -UseFeatures 11111111