def pushImagesHDF(self, startingAt=0, detThresh = .9, fitFcn = 'LatGaussFitFR'):
#global seriesName
dataFilename = self.image.seriesName
resultsFilename = genResultFileName(self.image.seriesName)
if os.path.exists(resultsFilename):
di, fn = os.path.split(resultsFilename)
i = 1
stub = os.path.splitext(fn)[0]
while os.path.exists(os.path.join(di, stub + '_%d.h5r' % i)):
i += 1
fdialog = wx.FileDialog(None, 'Analysis file already exists, please select a new filename',
wildcard='H5R files|*.h5r', defaultDir=di, defaultFile=stub + '_%d.h5r' % i, style=wx.SAVE)
succ = fdialog.ShowModal()
if (succ == wx.ID_OK):
resultsFilename = fdialog.GetPath().encode()
else:
raise RuntimeError('Invalid results file - not running')
self.image.seriesName = resultsFilename
self.tq.createQueue('HDFTaskQueue', self.image.seriesName, dataFilename = dataFilename, resultsFilename=resultsFilename, startAt = 'notYet')
mdhQ = MetaDataHandler.QueueMDHandler(self.tq, self.image.seriesName, self.image.mdh)
mdhQ.setEntry('Analysis.DetectionThreshold', detThresh)
mdhQ.setEntry('Analysis.FitModule', fitFcn)
mdhQ.setEntry('Analysis.DataFileID', fileID.genDataSourceID(self.image.dataSource))
evts = self.image.dataSource.getEvents()
if len(evts) > 0:
self.tq.addQueueEvents(self.image.seriesName, evts)
self.tq.releaseTasks(self.image.seriesName, startingAt)
def pushImagesQueue(self,
startingAt=0,
detThresh=.9,
fitFcn='LatGaussFitFR'):
self.image.mdh.setEntry('Analysis.DetectionThreshold', detThresh)
self.image.mdh.setEntry('Analysis.FitModule', fitFcn)
self.image.mdh.setEntry('Analysis.DataFileID',
fileID.genDataSourceID(self.image.dataSource))
self.tq.releaseTasks(self.image.seriesName, startingAt)
def pushImagesDS(self, startingAt=0, detThresh = .9, fitFcn = 'LatGaussFitFR'):
#global seriesName
#dataFilename = self.image.seriesName
resultsFilename = genResultFileName(self.image.seriesName)
while os.path.exists(resultsFilename):
di, fn = os.path.split(resultsFilename)
fdialog = wx.FileDialog(None, 'Analysis file already exists, please select a new filename',
wildcard='H5R files|*.h5r', defaultDir=di, defaultFile=os.path.splitext(fn)[0] + '_1.h5r', style=wx.SAVE)
succ = fdialog.ShowModal()
if (succ == wx.ID_OK):
resultsFilename = fdialog.GetPath().encode()
else:
raise RuntimeError('Invalid results file - not running')
#self.image.seriesName = resultsFilename
debugPrint('Results file = %s' % resultsFilename)
self.tq.createQueue('HDFResultsTaskQueue', resultsFilename, None)
debugPrint('Queue created')
mdhQ = MetaDataHandler.QueueMDHandler(self.tq, resultsFilename, self.image.mdh)
mdhQ.setEntry('Analysis.DetectionThreshold', detThresh)
mdhQ.setEntry('Analysis.FitModule', fitFcn)
mdhQ.setEntry('Analysis.DataFileID', fileID.genDataSourceID(self.image.dataSource))
debugPrint('Metadata transferred to queue')
evts = self.image.dataSource.getEvents()
if len(evts) > 0:
self.tq.addQueueEvents(resultsFilename, evts)
md = MetaDataHandler.NestedClassMDHandler(mdhQ)
mn = self.image.dataSource.moduleName
#if it's a buffered source, go back to underlying source
if mn == 'BufferedDataSource':
mn = self.image.dataSource.dataSource.moduleName
for i in range(startingAt, self.image.dataSource.getNumSlices()):
debugPrint('Posting task %d' %i)
if 'Analysis.BGRange' in md.getEntryNames():
bgi = range(max(i + md.Analysis.BGRange[0],md.EstimatedLaserOnFrameNo), max(i + md.Analysis.BGRange[1],md.EstimatedLaserOnFrameNo))
elif 'Analysis.NumBGFrames' in md.getEntryNames():
bgi = range(max(i - md.Analysis.NumBGFrames, md.EstimatedLaserOnFrameNo), i)
else:
bgi = range(max(i - 10, md.EstimatedLaserOnFrameNo), i)
#task = fitTask(self.queueID, taskNum, self.metaData.Analysis.DetectionThreshold, self.metaData, self.metaData.Analysis.FitModule, 'TQDataSource', bgindices =bgi, SNThreshold = True)
self.tq.postTask(remFitBuf.fitTask(self.image.seriesName,i, detThresh, md, fitFcn, bgindices=bgi, SNThreshold=True, dataSourceModule=mn), queueName=resultsFilename)
self.image.seriesName = resultsFilename
def pushImagesHDF(self,
startingAt=0,
detThresh=.9,
fitFcn='LatGaussFitFR'):
#global seriesName
dataFilename = self.image.seriesName
resultsFilename = genResultFileName(self.image.seriesName)
if os.path.exists(resultsFilename):
di, fn = os.path.split(resultsFilename)
i = 1
stub = os.path.splitext(fn)[0]
while os.path.exists(os.path.join(di, stub + '_%d.h5r' % i)):
i += 1
fdialog = wx.FileDialog(
None,
'Analysis file already exists, please select a new filename',
wildcard='H5R files|*.h5r',
defaultDir=di,
defaultFile=stub + '_%d.h5r' % i,
style=wx.SAVE)
succ = fdialog.ShowModal()
if (succ == wx.ID_OK):
resultsFilename = fdialog.GetPath().encode()
else:
raise RuntimeError('Invalid results file - not running')
self.image.seriesName = resultsFilename
self.tq.createQueue('HDFTaskQueue',
self.image.seriesName,
dataFilename=dataFilename,
resultsFilename=resultsFilename,
startAt='notYet')
mdhQ = MetaDataHandler.QueueMDHandler(self.tq, self.image.seriesName,
self.image.mdh)
mdhQ.setEntry('Analysis.DetectionThreshold', detThresh)
mdhQ.setEntry('Analysis.FitModule', fitFcn)
mdhQ.setEntry('Analysis.DataFileID',
fileID.genDataSourceID(self.image.dataSource))
evts = self.image.dataSource.getEvents()
if len(evts) > 0:
self.tq.addQueueEvents(self.image.seriesName, evts)
self.tq.releaseTasks(self.image.seriesName, startingAt)
def pushImagesQueue(self, startingAt=0, detThresh = .9, fitFcn='LatGaussFitFR'):
self.image.mdh.setEntry('Analysis.DetectionThreshold', detThresh)
self.image.mdh.setEntry('Analysis.FitModule', fitFcn)
self.image.mdh.setEntry('Analysis.DataFileID', fileID.genDataSourceID(self.image.dataSource))
self.tq.releaseTasks(self.image.seriesName, startingAt)
def pushImagesDS(self, startingAt=0, detThresh=.9, fitFcn='LatGaussFitFR'):
#global seriesName
#dataFilename = self.image.seriesName
resultsFilename = genResultFileName(self.image.seriesName)
while os.path.exists(resultsFilename):
di, fn = os.path.split(resultsFilename)
fdialog = wx.FileDialog(
None,
'Analysis file already exists, please select a new filename',
wildcard='H5R files|*.h5r',
defaultDir=di,
defaultFile=os.path.splitext(fn)[0] + '_1.h5r',
style=wx.SAVE)
succ = fdialog.ShowModal()
if (succ == wx.ID_OK):
resultsFilename = fdialog.GetPath().encode()
else:
raise RuntimeError('Invalid results file - not running')
#self.image.seriesName = resultsFilename
debugPrint('Results file = %s' % resultsFilename)
self.tq.createQueue('HDFResultsTaskQueue', resultsFilename, None)
debugPrint('Queue created')
mdhQ = MetaDataHandler.QueueMDHandler(self.tq, resultsFilename,
self.image.mdh)
mdhQ.setEntry('Analysis.DetectionThreshold', detThresh)
mdhQ.setEntry('Analysis.FitModule', fitFcn)
mdhQ.setEntry('Analysis.DataFileID',
fileID.genDataSourceID(self.image.dataSource))
debugPrint('Metadata transferred to queue')
evts = self.image.dataSource.getEvents()
if len(evts) > 0:
self.tq.addQueueEvents(resultsFilename, evts)
md = MetaDataHandler.NestedClassMDHandler(mdhQ)
mn = self.image.dataSource.moduleName
#if it's a buffered source, go back to underlying source
if mn == 'BufferedDataSource':
mn = self.image.dataSource.dataSource.moduleName
for i in range(startingAt, self.image.dataSource.getNumSlices()):
debugPrint('Posting task %d' % i)
if 'Analysis.BGRange' in md.getEntryNames():
bgi = range(
max(i + md.Analysis.BGRange[0],
md.EstimatedLaserOnFrameNo),
max(i + md.Analysis.BGRange[1],
md.EstimatedLaserOnFrameNo))
elif 'Analysis.NumBGFrames' in md.getEntryNames():
bgi = range(
max(i - md.Analysis.NumBGFrames,
md.EstimatedLaserOnFrameNo), i)
else:
bgi = range(max(i - 10, md.EstimatedLaserOnFrameNo), i)
#task = fitTask(self.queueID, taskNum, self.metaData.Analysis.DetectionThreshold, self.metaData, self.metaData.Analysis.FitModule, 'TQDataSource', bgindices =bgi, SNThreshold = True)
self.tq.postTask(remFitBuf.fitTask(self.image.seriesName,
i,
detThresh,
md,
fitFcn,
bgindices=bgi,
SNThreshold=True,
dataSourceModule=mn),
queueName=resultsFilename)
self.image.seriesName = resultsFilename