def setModel(modName, md):
global IntXVals, IntYVals, IntZVals, interpModel, interpModelName, dx, dy, dz
if not modName == interpModelName:
mf = open(getFullExistingFilename(modName), 'rb')
mod, voxelsize = cPickle.load(mf)
mf.close()
interpModelName = modName
if not voxelsize.x == md.voxelsize.x:
raise RuntimeError("PSF and Image voxel sizes don't match")
IntXVals = 1e3*voxelsize.x*scipy.mgrid[-(mod.shape[0]/2.):(mod.shape[0]/2.)]
IntYVals = 1e3*voxelsize.y*scipy.mgrid[-(mod.shape[1]/2.):(mod.shape[1]/2.)]
IntZVals = 1e3*voxelsize.z*scipy.mgrid[-(mod.shape[2]/2.):(mod.shape[2]/2.)]
dx = voxelsize.x*1e3
dy = voxelsize.y*1e3
dz = voxelsize.z*1e3
interpModel = mod
interpModel = interpModel/interpModel.max() #normalise to 1
twist.twistCal(interpModel, IntXVals, IntYVals, IntZVals)
def preparePSF(md, PSSize):
global PSFFileName, cachedPSF, cachedOTF2, cachedOTFH, autocorr
PSFFilename = md.PSFFile
if (not (PSFFileName == PSFFilename)) or (not (cachedPSF.shape == PSSize)):
try:
ps, vox = md.taskQueue.getQueueData(md.dataSourceID, 'PSF')
except:
fid = open(getFullExistingFilename(PSFFilename), 'rb')
ps, vox = pickle.load(fid)
fid.close()
ps = ps.max(2)
ps = ps - ps.min()
#ps = ps*(ps > 0)
ps = ps*scipy.signal.hanning(ps.shape[0])[:,None]*scipy.signal.hanning(ps.shape[1])[None,:]
ps = ps/ps.sum()
PSFFileName = PSFFilename
pw = (numpy.array(PSSize) - ps.shape)/2.
pw1 = numpy.floor(pw)
pw2 = numpy.ceil(pw)
cachedPSF = pad.with_constant(ps, ((pw2[0], pw1[0]), (pw2[1], pw1[1])), (0,))
cachedOTFH = ifftn(cachedPSF)*cachedPSF.size
cachedOTF2 = cachedOTFH*fftn(cachedPSF)
def setModel(modName, md):
global IntXVals, IntYVals, IntZVals, interpModel, dx, dy, dz
mf = open(getFullExistingFilename(modName), 'rb')
mod, voxelsize = pickle.load(mf)
mf.close()
mod = resizePSF(mod, interpModel.shape)
#if not voxelsize.x == md.voxelsize.x:
# raise RuntimeError("PSF and Image voxel sizes don't match")
IntXVals = 1e3*voxelsize.x*mgrid[-(mod.shape[0]/2.):(mod.shape[0]/2.)]
IntYVals = 1e3*voxelsize.y*mgrid[-(mod.shape[1]/2.):(mod.shape[1]/2.)]
IntZVals = 1e3*voxelsize.z*mgrid[-(mod.shape[2]/2.):(mod.shape[2]/2.)]
dx = voxelsize.x*1e3
dy = voxelsize.y*1e3
dz = voxelsize.z*1e3
#interpModel = mod
#interpModel = np.maximum(mod/mod.max(), 0) #normalise to 1
interpModel = np.maximum(mod/mod[:,:,len(IntZVals)/2].sum(), 0) #normalise to 1 and clip
def setModel(modName, md):
global IntXVals, IntYVals, IntZVals, interpModel, interpModelF, interpModelName, dx, dy, dz, kx, ky, kz
if not modName == interpModelName:
mf = open(getFullExistingFilename(modName), 'rb')
mod, voxelsize = cPickle.load(mf)
mf.close()
interpModelName = modName
if not voxelsize.x == md.voxelsize.x:
raise RuntimeError("PSF and Image voxel sizes don't match")
IntXVals = 1e3*voxelsize.x*mgrid[-(mod.shape[0]/2.):(mod.shape[0]/2.)]
IntYVals = 1e3*voxelsize.y*mgrid[-(mod.shape[1]/2.):(mod.shape[1]/2.)]
IntZVals = 1e3*voxelsize.z*mgrid[-(mod.shape[2]/2.):(mod.shape[2]/2.)]
dx = voxelsize.x*1e3
dy = voxelsize.y*1e3
dz = voxelsize.z*1e3
interpModel = mod
interpModel = interpModel/interpModel.max() #normalise to 1
interpModelF = numpy.fft.fftn(interpModel)
kx,ky,kz = numpy.mgrid[:interpModel.shape[0],:interpModel.shape[1],:interpModel.shape[2]]
kx = numpy.fft.fftshift(kx - interpModel.shape[0]/2.)/interpModel.shape[0]
ky = numpy.fft.fftshift(ky - interpModel.shape[1]/2.)/interpModel.shape[1]
kz = numpy.fft.fftshift(kz - interpModel.shape[2]/2.)/interpModel.shape[2]
def preparePSF(md, PSSize):
global PSFFileName, cachedPSF, cachedOTF2, cachedOTFH, autocorr
PSFFilename = md.PSFFile
if (not (PSFFileName == PSFFilename)) or (not (cachedPSF.shape == PSSize)):
try:
ps, vox = md.taskQueue.getQueueData(md.dataSourceID, 'PSF')
except:
fid = open(getFullExistingFilename(PSFFilename), 'rb')
ps, vox = pickle.load(fid)
fid.close()
ps = ps.max(2)
ps = ps - ps.min()
#ps = ps*(ps > 0)
ps = ps * scipy.signal.hanning(
ps.shape[0])[:, None] * scipy.signal.hanning(ps.shape[1])[None, :]
ps = ps / ps.sum()
PSFFileName = PSFFilename
pw = (numpy.array(PSSize) - ps.shape) / 2.
pw1 = numpy.floor(pw)
pw2 = numpy.ceil(pw)
cachedPSF = pad.with_constant(ps, ((pw2[0], pw1[0]), (pw2[1], pw1[1])),
(0, ))
cachedOTFH = ifftn(cachedPSF) * cachedPSF.size
cachedOTF2 = cachedOTFH * fftn(cachedPSF)
def setModel(modName, md):
global IntXVals, IntYVals, IntZVals, interpModel, interpModelName, dx, dy, dz
if not modName == interpModelName:
mf = open(getFullExistingFilename(modName), 'rb')
mod, voxelsize = cPickle.load(mf)
mf.close()
interpModelName = modName
#if not voxelsize.x == md.voxelsize.x:
# raise RuntimeError("PSF and Image voxel sizes don't match")
IntXVals = 1e3 * voxelsize.x * mgrid[-(mod.shape[0] / 2.):
(mod.shape[0] / 2.)]
IntYVals = 1e3 * voxelsize.y * mgrid[-(mod.shape[1] / 2.):
(mod.shape[1] / 2.)]
IntZVals = 1e3 * voxelsize.z * mgrid[-(mod.shape[2] / 2.):
(mod.shape[2] / 2.)]
dx = voxelsize.x * 1e3
dy = voxelsize.y * 1e3
dz = voxelsize.z * 1e3
interpModel = mod
interpModel = interpModel / interpModel.max() #normalise to 1
#do the spline filtering here rather than in interpolation
interpModel = ndimage.spline_filter(interpModel)
twist.twistCal(interpModel, IntXVals, IntYVals, IntZVals)
def setModelFromMetadata(self, md):
'''load the model from file - returns True if the model changed, False if
an existing model was reused'''
#global IntXVals, IntYVals, IntZVals, interpModel, interpModelName, dx, dy, dz
modName = md.PSFFile
if not modName == self.interpModelName:
#special case for theoretical models
if modName.startswith('ZMODEL:'):
params = eval(modName[7:])
mod, voxelsize = self.genTheoreticalModelZernike(md, **params)
else:
#try and get psf from task queue
#if not md.taskQueue == None:
try:
mod, voxelsize = md.taskQueue.getQueueData(
md.dataSourceID, 'PSF')
except:
mf = open(getFullExistingFilename(modName), 'rb')
mod, voxelsize = load(mf)
mf.close()
self.setModel(modName, mod, voxelsize)
#print 'model changed'
return True #model changed
else:
return False #model not changed
def preparePSF(md, axis):
global PSFFileName, lobeSeparation
PSFFilename = md.PSFFile
if (not (PSFFileName == PSFFilename)):
try:
ps, vox = md.taskQueue.getQueueData(md.dataSourceID, 'PSF')
except:
fid = open(getFullExistingFilename(PSFFilename), 'rb')
ps, vox = pickle.load(fid)
fid.close()
ps = ps.max(2)
ps = ps - ps.min()
ps = ps / ps.max()
PSFFileName = PSFFilename
if axis == 'x':
I = ps.max(1)
else:
I = ps.max(0)
sepr = I[(I.size / 2):].argmax()
sepl = I[(I.size / 2)::-1].argmax()
print((sepr, sepl))
lobeSeparation = sepr + sepl
def preparePSF(md, axis):
global PSFFileName, lobeSeparation
PSFFilename = md.PSFFile
if (not (PSFFileName == PSFFilename)):
try:
ps, vox = md.taskQueue.getQueueData(md.dataSourceID, 'PSF')
except:
fid = open(getFullExistingFilename(PSFFilename), 'rb')
ps, vox = pickle.load(fid)
fid.close()
ps = ps.max(2)
ps = ps - ps.min()
ps = ps /ps.max()
PSFFileName = PSFFilename
if axis == 'x':
I = ps.max(1)
else:
I = ps.max(0)
sepr = I[(I.size/2):].argmax()
sepl = I[(I.size/2)::-1].argmax()
print((sepr, sepl))
lobeSeparation = sepr + sepl
def setModelFromMetadata(self, md):
'''load the model from file - returns True if the model changed, False if
an existing model was reused'''
#global IntXVals, IntYVals, IntZVals, interpModel, interpModelName, dx, dy, dz
modName = md.PSFFile
if not modName == self.interpModelName:
#special case for theoretical models
if modName.startswith('ZMODEL:'):
params = eval(modName[7:])
mod, voxelsize = self.genTheoreticalModelZernike(md, **params)
else:
#try and get psf from task queue
#if not md.taskQueue == None:
try:
mod, voxelsize = md.taskQueue.getQueueData(md.dataSourceID, 'PSF')
except:
mf = open(getFullExistingFilename(modName), 'rb')
mod, voxelsize = load(mf)
mf.close()
self.setModel(modName, mod, voxelsize)
#print 'model changed'
return True #model changed
else:
return False #model not changed
def _fetchMap(self, md, mapName):
'''retrive a map, with a given name. First try and get it from the Queue,
then try finding it locally'''
try:
varmap = md.taskQueue.getQueueData(md.dataSourceID, 'MAP', mapName)
except:
fn = getFullExistingFilename(mapName)
varmap = ImageStack(filename=fn).data[:,:,0].squeeze() #this should handle .tif, .h5, and a few others
return varmap
def _fetchMap(self, md, mapName):
'''retrive a map, with a given name. First try and get it from the Queue,
then try finding it locally'''
try:
varmap = md.taskQueue.getQueueData(md.dataSourceID, 'MAP', mapName)
except:
fn = getFullExistingFilename(mapName)
varmap = ImageStack(filename=fn).data[:,:,0].squeeze() #this should handle .tif, .h5, and a few others
return varmap
def preparePSF(md, PSSize):
global PSFFileName, PSFSize, FTW
PSFFilename = md.PSFFile
if (not (PSFFileName == PSFFilename)) or (not (PSFSize == PSSize)):
try:
ps, vox = md.taskQueue.getQueueData(md.dataSourceID, 'PSF')
except:
fid = open(getFullExistingFilename(PSFFilename), 'rb')
ps, vox = pickle.load(fid)
fid.close()
FTW = fftwWeiner(ps, vox, PSSize)
PSFFileName = PSFFilename
PSFSize = PSSize
def preparePSF(md, PSSize):
global PSFFileName, PSFSize, FTW
PSFFilename = md.PSFFile
if (not (PSFFileName == PSFFilename)) or (not (PSFSize == PSSize)):
try:
ps, vox = md.taskQueue.getQueueData(md.dataSourceID, 'PSF')
except:
fid = open(getFullExistingFilename(PSFFilename), 'rb')
ps, vox = pickle.load(fid)
fid.close()
FTW = fftwWeiner(ps,vox, PSSize)
PSFFileName = PSFFilename
PSFSize = PSSize
def getQueueData(self, fieldName, *args):
'''Get data, defined by fieldName and potntially additional arguments, ascociated with queue'''
if fieldName == 'ImageShape':
with self.dataFileLock.rlock:
res = self.h5DataFile.root.ImageData.shape[1:]
return res
elif fieldName == 'ImageData':
sliceNum, = args
with self.dataFileLock.rlock:
res = self.h5DataFile.root.ImageData[sliceNum, :,:]
return res
elif fieldName == 'NumSlices':
#self.dataFileLock.acquire()
#res = self.h5DataFile.root.ImageData.shape[0]
#self.dataFileLock.release()
#print res, self.numSlices
#return res
return self.numSlices
elif fieldName == 'Events':
with self.dataFileLock.rlock:
res = self.h5DataFile.root.Events[:]
return res
elif fieldName == 'PSF':
from PYME.ParallelTasks.relativeFiles import getFullExistingFilename
res = None
#self.dataFileLock.acquire()
#try:
#res = self.h5DataFile.root.PSFData[:]
#finally:
# self.dataFileLock.release()
#try:
modName = self.resultsMDH.getEntry('PSFFile')
mf = open(getFullExistingFilename(modName), 'rb')
res = np.load(mf)
mf.close()
#except:
#pass
return res
else:
return HDFResultsTaskQueue.getQueueData(self, fieldName, *args)
def getQueueData(self, fieldName, *args):
'''Get data, defined by fieldName and potntially additional arguments, ascociated with queue'''
if fieldName == 'ImageShape':
with self.dataFileLock.rlock:
res = self.h5DataFile.root.ImageData.shape[1:]
return res
elif fieldName == 'ImageData':
sliceNum, = args
with self.dataFileLock.rlock:
res = self.h5DataFile.root.ImageData[sliceNum, :, :]
return res
elif fieldName == 'NumSlices':
#self.dataFileLock.acquire()
#res = self.h5DataFile.root.ImageData.shape[0]
#self.dataFileLock.release()
#print res, self.numSlices
#return res
return self.numSlices
elif fieldName == 'Events':
with self.dataFileLock.rlock:
res = self.h5DataFile.root.Events[:]
return res
elif fieldName == 'PSF':
from PYME.ParallelTasks.relativeFiles import getFullExistingFilename
res = None
#self.dataFileLock.acquire()
#try:
#res = self.h5DataFile.root.PSFData[:]
#finally:
# self.dataFileLock.release()
#try:
modName = self.resultsMDH.getEntry('PSFFile')
mf = open(getFullExistingFilename(modName), 'rb')
res = np.load(mf)
mf.close()
#except:
#pass
return res
else:
return HDFResultsTaskQueue.getQueueData(self, fieldName, *args)
def setModelFromFile(self, modName, md=None):
'''load the model from file - returns True if the model changed, False if
an existing model was reused'''
#global IntXVals, IntYVals, IntZVals, interpModel, interpModelName, dx, dy, dz
if not modName == self.interpModelName:
#special case for theoretical models
if modName.startswith('ZMODEL:'):
#print modName[7:]
params = eval(modName[7:])
mod, voxelsize = self.genTheoreticalModelZernike(md, **params)
else:
mf = open(getFullExistingFilename(modName), 'rb')
mod, voxelsize = load(mf)
mf.close()
self.setModel(modName, mod, voxelsize)
#print 'model changed'
return True #model changed
else:
return False #model not changed
def getQueueData(self, fieldName, *args):
'''Get data, defined by fieldName and potntially additional arguments, ascociated with queue'''
if fieldName == 'FitResults':
startingAt, = args
with self.fileResultsLock.rlock:
if self.h5ResultsFile.__contains__('/FitResults'):
res = self.h5ResultsFile.root.FitResults[startingAt:]
else:
res = []
return res
elif fieldName == 'MAP':
mapName, = args
from PYME.ParallelTasks.relativeFiles import getFullExistingFilename
from PYME.DSView.image import ImageStack
fn = getFullExistingFilename(mapName)
varmap = ImageStack(filename=fn).data[:,:,0].squeeze() #this should handle .tif, .h5, and a few others
return varmap
else:
return None
def setModelFromFile(self, modName, md=None):
'''load the model from file - returns True if the model changed, False if
an existing model was reused'''
#global IntXVals, IntYVals, IntZVals, interpModel, interpModelName, dx, dy, dz
if not modName == self.interpModelName:
#special case for theoretical models
if modName.startswith('ZMODEL:'):
#print modName[7:]
params = eval(modName[7:])
mod, voxelsize = self.genTheoreticalModelZernike(md, **params)
else:
mf = open(getFullExistingFilename(modName), 'rb')
mod, voxelsize = load(mf)
mf.close()
self.setModel(modName, mod, voxelsize)
#print 'model changed'
return True #model changed
else:
return False #model not changed
def getQueueData(self, fieldName, *args):
'''Get data, defined by fieldName and potntially additional arguments, ascociated with queue'''
if fieldName == 'FitResults':
startingAt, = args
with self.fileResultsLock.rlock:
if self.h5ResultsFile.__contains__('/FitResults'):
res = self.h5ResultsFile.root.FitResults[startingAt:]
else:
res = []
return res
elif fieldName == 'MAP':
mapName, = args
from PYME.ParallelTasks.relativeFiles import getFullExistingFilename
from PYME.DSView.image import ImageStack
fn = getFullExistingFilename(mapName)
varmap = ImageStack(filename=fn).data[:, :, 0].squeeze(
) #this should handle .tif, .h5, and a few others
return varmap
else:
return None