if yCropLists is not None: yCropList = yCropLists[ibaseDir]
else: yCropList = None
correctionBaseDir = correctionBaseDirs[ibaseDir]
for fileIndex in range(len(fusionFileNames)):
if not separateFileMultiView:
fusionFileName = os.path.join(baseDir,fusionFileNames[fileIndex])
# check whether already fused (only checking for registration channel file!
tmpFinalFile = os.path.join(os.path.dirname(fusionFileName),
outFilePattern %(os.path.basename(fusionFileName.split('.')[0]),registrationChannel))
if os.path.exists(tmpFinalFile): continue
# load files
print 'loading file %s...' %fusionFileName
inarray = czifile.imread(fusionFileName)
print 'finished loading'
infoDict = zf.getStackInfoFromCZI(fusionFileName)
else:
fusionFileName = os.path.join(baseDir,fusionFileNames[fileIndex][0])
tmpFinalFile = os.path.join(os.path.dirname(fusionFileName),
outFilePattern %(os.path.basename(fusionFileName.split('.')[0]),registrationChannel))
if os.path.exists(tmpFinalFile): continue
readPaths = [os.path.join(baseDir,fusionFileNames[fileIndex][i]) for i in range(len(fusionFileNames[fileIndex]))]
# load files
print 'loading file %s...' %fusionFileName
inarrays = []
shapes = []
for ifile in range(len(fusionFileNames[fileIndex])):
tmpArray = czifile.imread(readPaths[ifile])
inarrays.append(tmpArray)
__author__ = 'malbert'
import sys
sys.path = [sys.path[0]]+['..']+sys.path[1:]
from dependencies import *
# filePath = prefix+'/data/malbert/data/dbspim/osmo/20151220_p2y12_45dpf_15s_3cells_Subset.czi'
filePath = prefix+'/data/malbert/data/dbspim/20160118_4dpf_myosin/20160118_myosin_pu1_4dpf_30s_2_Subset.czi'
import zeissFusion as zf
info = zf.getStackInfoFromCZI(filePath)
# spacing = n.array([])
times = range(120)
# times = range(1)
bs = []
b = brain.Brain(filePath,
dimc=2,
times=times,
baseDataDir=prefix+'/data/malbert/quantification',
subDir = '20160118_4dpf_myosin',
fileNameFormat='f%06d.h5',
# spacing = n.array([info['spacing'][2]]*3),
spacing = info['spacing'],
# spacing = n.array([0.6,0.6,0.4]),
origin = n.zeros(3)
)
descriptors.RawChannel(b,1,nickname='signal',hierarchy='signal',redo=False,
compression='jls',compressionOption=2)
