def __init__(self, filename, taskQueue=None):
self.filename = getFullFilename(filename)#convert relative path to full path
#self.data = readTiff.read3DTiff(self.filename)
#use metadata for glob
md = MetaDataHandler.SimpleMDHandler(self.filename)
pattern = md.getEntry('SeriesPattern')
self.files = glob.glob(os.path.join(os.path.split(self.filename)[0], pattern))
self.files.sort()
self.im0 = Image.open(self.files[0])
#self.im.seek(0)
#PIL's endedness support is subtly broken - try to fix it
#NB this is untested for floating point tiffs
self.endedness = 'LE'
if self.im0.ifd.prefix =='MM':
self.endedness = 'BE'
print((self.im0.ifd.prefix))
print((self.endedness))
def __init__(self, filename, taskQueue, chanNum=0):
self.filename = getFullFilename(
filename) #convert relative path to full path
self.chanNum = chanNum
#self.data = readTiff.read3DTiff(self.filename)
#self.im = Image.open(filename)
#self.im.seek(0)
#PIL's endedness support is subtly broken - try to fix it
#NB this is untested for floating point tiffs
#self.endedness = 'LE'
#if self.im.ifd.prefix =='MM':
# self.endedness = 'BE'
#to find the number of images we have to loop over them all
#this is obviously not ideal as PIL loads the image data into memory for each
#slice and this is going to represent a huge performance penalty for large stacks
#should still let them be opened without having all images in memory at once though
#self.numSlices = self.im.tell()
#try:
# while True:
# self.numSlices += 1
# self.im.seek(self.numSlices)
#except EOFError:
# pass
print '> TiffDataSource.py: init from file', self.filename
self.im = tifffile.TIFFfile(self.filename).series[0].pages
def __init__(self, filename, taskQueue, chanNum = 0):
self.filename = getFullFilename(filename)#convert relative path to full path
self.chanNum = chanNum
#self.data = readTiff.read3DTiff(self.filename)
#self.im = Image.open(filename)
#self.im.seek(0)
#PIL's endedness support is subtly broken - try to fix it
#NB this is untested for floating point tiffs
#self.endedness = 'LE'
#if self.im.ifd.prefix =='MM':
# self.endedness = 'BE'
#to find the number of images we have to loop over them all
#this is obviously not ideal as PIL loads the image data into memory for each
#slice and this is going to represent a huge performance penalty for large stacks
#should still let them be opened without having all images in memory at once though
#self.numSlices = self.im.tell()
#try:
# while True:
# self.numSlices += 1
# self.im.seek(self.numSlices)
#except EOFError:
# pass
print '> TiffDataSource.py: init from file', self.filename
self.im = tifffile.TIFFfile(self.filename).series[0].pages
def __init__(self, h5Filename, taskQueue=None):
self.h5Filename = getFullFilename(h5Filename)#convert relative path to full path
self.h5File = tables.openFile(self.h5Filename)
def __init__(self, name, dataFilename = None, resultsFilename=None, onEmpty = doNix, fTaskToPop = popZero, startAt = 'guestimate', frameSize=(-1,-1), complevel=6, complib='zlib'):
if dataFilename is None:
self.dataFilename = genDataFilename(name)
else:
self.dataFilename = dataFilename
if resultsFilename is None:
resultsFilename = genResultFileName(self.dataFilename)
else:
resultsFilename = resultsFilename
ffn = getFullFilename(self.dataFilename)
self.acceptNewTasks = False
self.releaseNewTasks = False
self.postTaskBuffer = []
initialTasks = []
if os.path.exists(ffn): #file already exists - read from it
self.h5DataFile = tables.openFile(ffn, 'r')
#self.metaData = MetaData.genMetaDataFromHDF(self.h5DataFile)
self.dataMDH = MetaDataHandler.NestedClassMDHandler(MetaDataHandler.HDFMDHandler(self.h5DataFile))
#self.dataMDH.mergeEntriesFrom(MetaData.TIRFDefault)
self.imageData = self.h5DataFile.root.ImageData
if startAt == 'guestimate': #calculate a suitable starting value
tLon = self.dataMDH.EstimatedLaserOnFrameNo
if tLon == 0:
startAt = 0
else:
startAt = tLon + 10
if startAt == 'notYet':
initialTasks = []
else:
initialTasks = list(range(startAt, self.h5DataFile.root.ImageData.shape[0]))
self.imNum = len(self.imageData)
self.dataRW = False
else: #make ourselves a new file
self.h5DataFile = tables.openFile(ffn, 'w')
filt = tables.Filters(complevel, complib, shuffle=True)
self.imageData = self.h5DataFile.createEArray(self.h5DataFile.root,
'ImageData',
tables.UInt16Atom(),
(0,)+tuple(frameSize),
filters=filt,
chunkshape=(1,)+tuple(frameSize))
self.events = self.h5DataFile.createTable(self.h5DataFile.root, 'Events', SpoolEvent,filters=filt)
self.imNum=0
self.acceptNewTasks = True
self.dataMDH = MetaDataHandler.HDFMDHandler(self.h5DataFile)
self.dataMDH.mergeEntriesFrom(MetaData.TIRFDefault)
self.dataRW = True
HDFResultsTaskQueue.__init__(self,
name,
resultsFilename,
initialTasks, onEmpty, fTaskToPop)
self.resultsMDH.copyEntriesFrom(self.dataMDH)
self.metaData.copyEntriesFrom(self.resultsMDH)
#copy events to results file
if len (self.h5DataFile.root.Events) > 0:
self.resultsEvents.append(self.h5DataFile.root.Events[:])
self.queueID = name
self.numSlices = self.imageData.shape[0]
#self.dataFileLock = threading.Lock()
self.dataFileLock = tablesLock
#self.getTaskLock = threading.Lock()
self.lastTaskTime = 0
def __init__(self,
name,
dataFilename=None,
resultsFilename=None,
onEmpty=doNix,
fTaskToPop=popZero,
startAt='guestimate',
frameSize=(-1, -1),
complevel=6,
complib='zlib'):
if dataFilename is None:
self.dataFilename = genDataFilename(name)
else:
self.dataFilename = dataFilename
if resultsFilename is None:
resultsFilename = genResultFileName(self.dataFilename)
else:
resultsFilename = resultsFilename
ffn = getFullFilename(self.dataFilename)
self.acceptNewTasks = False
self.releaseNewTasks = False
self.postTaskBuffer = []
initialTasks = []
if os.path.exists(ffn): #file already exists - read from it
self.h5DataFile = tables.openFile(ffn, 'r')
#self.metaData = MetaData.genMetaDataFromHDF(self.h5DataFile)
self.dataMDH = MetaDataHandler.NestedClassMDHandler(
MetaDataHandler.HDFMDHandler(self.h5DataFile))
#self.dataMDH.mergeEntriesFrom(MetaData.TIRFDefault)
self.imageData = self.h5DataFile.root.ImageData
if startAt == 'guestimate': #calculate a suitable starting value
tLon = self.dataMDH.EstimatedLaserOnFrameNo
if tLon == 0:
startAt = 0
else:
startAt = tLon + 10
if startAt == 'notYet':
initialTasks = []
else:
initialTasks = list(
range(startAt, self.h5DataFile.root.ImageData.shape[0]))
self.imNum = len(self.imageData)
self.dataRW = False
else: #make ourselves a new file
self.h5DataFile = tables.openFile(ffn, 'w')
filt = tables.Filters(complevel, complib, shuffle=True)
self.imageData = self.h5DataFile.createEArray(
self.h5DataFile.root,
'ImageData',
tables.UInt16Atom(), (0, ) + tuple(frameSize),
filters=filt,
chunkshape=(1, ) + tuple(frameSize))
self.events = self.h5DataFile.createTable(self.h5DataFile.root,
'Events',
SpoolEvent,
filters=filt)
self.imNum = 0
self.acceptNewTasks = True
self.dataMDH = MetaDataHandler.HDFMDHandler(self.h5DataFile)
self.dataMDH.mergeEntriesFrom(MetaData.TIRFDefault)
self.dataRW = True
HDFResultsTaskQueue.__init__(self, name, resultsFilename, initialTasks,
onEmpty, fTaskToPop)
self.resultsMDH.copyEntriesFrom(self.dataMDH)
self.metaData.copyEntriesFrom(self.resultsMDH)
#copy events to results file
if len(self.h5DataFile.root.Events) > 0:
self.resultsEvents.append(self.h5DataFile.root.Events[:])
self.queueID = name
self.numSlices = self.imageData.shape[0]
#self.dataFileLock = threading.Lock()
self.dataFileLock = tablesLock
#self.getTaskLock = threading.Lock()
self.lastTaskTime = 0
def __init__(self, h5Filename, taskQueue=None):
self.h5Filename = getFullFilename(
h5Filename) #convert relative path to full path
self.h5File = tables.openFile(self.h5Filename)
