def __init__(self, conn_sock, client_address, server):
self.server = server
self.client_address = client_address
self.buffer = ""
self.is_writable = False
self.init = False
self.data = "" # data deals with string based data (non numpy data)
self.ntype = "" # ntype deals with numpy stringified arrays sent remotely - store type (not data)
self.nflag = False # nflag related to numpy data recv (buffer not enough large to get it in one turn) - set a reset point for data
self.isPartial = False
self.nVols = 0
self.ldata = ""
self.pvol = []
self.isarray = False
self.result = False
self.issent = False
self.params = nrrd.nrrd()
self.nimage = nrrd.nrrd()
self.roiA = nrrd.nrrd()
self.roiB = nrrd.nrrd()
self.wm = nrrd.nrrd()
self.ten = nrrd.nrrd()
self.res = numpy.empty(0)
asyncore.dispatcher.__init__(self, conn_sock)
logger.debug("created handler; waiting for loop")
def __init__(self, conn_sock, client_address, server):
self.server = server
self.client_address = client_address
self.buffer = ""
self.is_writable = False
self.init = False
self.data = "" # data deals with string based data (non numpy data)
self.ntype = "" # ntype deals with numpy stringified arrays sent remotely - store type (not data)
self.nflag = False # nflag related to numpy data recv (buffer not enough large to get it in one turn) - set a reset point for data
self.isPartial = False
self.nVols = 0
self.ldata = ""
self.pvol = []
self.isarray = False
self.result = False
self.issent = False
self.params = nrrd.nrrd()
self.nimage = nrrd.nrrd()
self.roiA = nrrd.nrrd()
self.roiB = nrrd.nrrd()
self.wm = nrrd.nrrd()
self.ten = nrrd.nrrd()
self.res = numpy.empty(0)
asyncore.dispatcher.__init__(self, conn_sock)
logger.debug("created handler; waiting for loop")
def get(self, id):
"""get and return the image from slicer with the given id
"""
# create a socket
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
s.connect((self.host, self.port))
s.send('get ' + str(id) + ' \n') # send
nimage = nrrd.nrrd()
fp = s.makefile()
line = string.strip(fp.readline())
name = string.strip(fp.readline())
nimage.set('name', name)
name = string.split(name)
scalar_type = string.strip(fp.readline())
nimage.set('scalar_type', scalar_type)
scalar_type = string.split(scalar_type)
dimensions = string.strip(fp.readline())
nimage.set('dimensions', dimensions)
dimensions = string.split(dimensions)
space_origin = string.strip(fp.readline())
nimage.set('space_origin', space_origin)
space_origin = string.split(space_origin)
space_directions = string.strip(fp.readline())
nimage.set('space_directions', space_directions)
space_directions = string.split(space_directions)
dtype = vtk_types[int(scalar_type[1])]
size = numpy_sizes[dtype]
size = size * int(dimensions[3]) * int(dimensions[2]) * int(
dimensions[1])
data = s.recv(size)
while len(data) != size:
data += s.recv(size)
im = numpy.fromstring(data, dtype)
im = im.reshape(int(dimensions[3]), int(dimensions[2]),
int(dimensions[1]))
s.close()
nimage.setImage(im)
return nimage
def get(self, id):
"""get and return the image from slicer with the given id
"""
# create a socket
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
s.connect( (self.host, self.port) )
s.send('get ' + str(id) + ' \n') # send
nimage = nrrd.nrrd()
fp = s.makefile();
line = string.strip(fp.readline())
name = string.strip(fp.readline())
nimage.set('name', name)
name = string.split(name)
scalar_type = string.strip(fp.readline())
nimage.set('scalar_type', scalar_type)
scalar_type = string.split(scalar_type)
dimensions = string.strip(fp.readline())
nimage.set('dimensions', dimensions)
dimensions = string.split(dimensions)
space_origin = string.strip(fp.readline())
nimage.set('space_origin', space_origin)
space_origin = string.split(space_origin)
space_directions = string.strip(fp.readline())
nimage.set('space_directions', space_directions)
space_directions = string.split(space_directions)
dtype = vtk_types [ int(scalar_type[1]) ]
size = numpy_sizes [ dtype ]
size = size * int(dimensions[3]) * int(dimensions[2]) * int(dimensions[1])
data = s.recv(size)
while len(data) != size:
data += s.recv(size)
im = numpy.fromstring (data, dtype)
im = im.reshape( int(dimensions[3]), int(dimensions[2]), int(dimensions[1]) )
s.close()
nimage.setImage(im)
return nimage
def handle_read(self):
# handle incomings
if self.nimage.hasKey('size') and not self.result:
self.isarray = True
size = self.nimage.get('size')
dims = self.nimage.get('dimensions')
nvols = int(dims[3])
sizePerVol = size / nvols
if not self.nflag:
self.data = ""
self.nflag = True
self.ldata += self.recv(sizePerVol)
if len(self.ldata) == sizePerVol:
self.isPartial = True
self.data += self.ldata
self.pvol.append(self.ldata)
self.nVols += 1
self.ldata = ""
# get DWI and run pipeline
if self.nVols == nvols:
logger.debug("volume acquired!")
self.set_data(self.data)
self.pvol = []
self.isPartial = False
self.nVols = 0
self.data = ""
logger.info("pipeline launchned")
self.res = self.pipeline(self.nimage.getImage())
logger.debug(
"result shape : %s:%s:%s" %
(self.res.shape[0], self.res.shape[1], self.res.shape[2]))
logger.debug("result type : %s" % self.res.dtype)
logger.info("pipeline completed")
self.data = 'FACK'
self.result = True
logger.debug("ready for sending!")
else:
if not self.result:
self.isarray = False
self.data = self.recv(SIZE)
if not self.init: # first get parameters of the pipeline
self.set_params(self.data)
elif self.data: # second get data associated to the vector image
self.set_data(self.data)
else:
logger.error("command unknown")
else: # special case for returning to client (Slicer) - currently SlicerDaemon used
if not self.issent:
self.data = self.recv(SIZE)
cmd = string.strip(self.data)
cmd = string.split(cmd)
if len(cmd) != 1:
logger.info("command awaited!")
else:
logger.info("command : %s" % cmd[0])
if cmd[0] == 'get':
logger.info("send back data!")
self.data = self.res.tostring() # 'PACK'
self.issent = True
else:
logger.error("command unknown")
else:
logger.info("closing!")
self.result = False
# determine response
if self.data and not self.isarray and not self.result:
self.buffer += 'ACK'
self.is_writable = True
self.data = ""
elif (self.data or self.ldata) and self.isarray and not self.result:
logger.debug("acquiring array")
if self.isPartial:
self.buffer += 'ACK'
self.is_writable = True
self.isPartial = False
elif self.data and self.result:
self.buffer = self.data
self.is_writable = True
# reset
if self.issent:
self.data = "" # set previously
self.ntype = ""
self.init = False
self.isarray = False
self.nflag = False
self.params = nrrd.nrrd()
self.nimage = nrrd.nrrd()
self.roiA = nrrd.nrrd()
self.roiB = nrrd.nrrd()
self.wm = nrrd.nrrd()
self.res = numpy.empty(0)
self.issent = False
logger.debug("data size : %s" % len(self.buffer))
logger.info("ready to handle write!")
else:
logger.info("got null data")
def main (\
inputSHost = 'localhost',\
inputSPort = 18943,\
inputPar0 = "",\
inputVol0 = "",\
inputVol1 = "",\
inputVol2 = "",\
inputVol3 = ""
):
if not inputPar0:
return
if not inputVol0:
return
host = inputSHost
port = inputSPort
parName = inputPar0
dwiName = inputVol0
roiAName = ""
roiBName = ""
wmName = ""
if inputVol1:
roiAName = inputVol1
if inputVol2:
roiBName = inputVol2
if inputVol3:
wmName = inputVol3
#if inputVol4:
# ten = scene.GetNodeByID(inputVol4)
# tenName = ten.GetName()
paramsN = nrrd.nrrd()
dwiN = nrrd.nrrd()
roiAN = nrrd.nrrd()
roiBN = nrrd.nrrd()
wmN = nrrd.nrrd()
paramsN.set('location', os.getcwd())
dwiN = recvVolume(dwiName, 'dwi')
paramsN.set('dwi', dwiName)
if roiAName:
roiAN = recvVolume(roiAName, 'roi')
paramsN.set('roiA', roiAName)
if roiBName:
roiBN = recvVolume(roiBName, 'roi')
paramsN.set('roiB', roiBName)
if wmName:
wmN = recvVolume(wmName, 'wm')
paramsN.set('wm', wmName)
#if tenName:
# s.send('tensor ' + str(tenName) + '\n')
# ack = s.recv(SIZE)
print "Params loaded from : %s" % str(parName)
params = numpy.fromfile(parName, 'float')
paramsN.set('pipeline', 'STOCHASTIC')
print "Pipeline?? : %s" % str(paramsN.get('pipeline'))
# smoothing
paramsN.set('smoothEnabled', int(params[0]))
stdD = numpy.array([params[1], params[2], params[3]], 'float')
paramsN.set('stdDev', stdD)
# brain
paramsN.set('wmEnabled', int(params[4]))
paramsN.set('infWMThres', params[5])
paramsN.set('supWMThres', params[6])
# tensor
paramsN.set('tensEnabled', int(params[7]))
bLine = 0
paramsN.set('bLine', params[8])
paramsN.set('faEnabled', int(params[9]))
paramsN.set('traceEnabled', int(params[10]))
paramsN.set('modeEnabled', int(params[11]))
# stochastic tracto
paramsN.set('stEnabled', int(params[12]))
paramsN.set('totalTracts', params[13])
paramsN.set('maxLength', params[14])
paramsN.set('stepSize', params[15])
paramsN.set('spaceEnabled', int(params[16]))
paramsN.set('stopEnabled', int(params[17]))
paramsN.set('fa', params[18])
# connectivity
paramsN.set('cmEnabled', int(params[19]))
probMode = int(params[20])
if probMode == 0:
probMode = 'binary'
elif probMode == 1:
probMode = 'cumulative'
elif probMode == 2:
probMode = 'weighted'
paramsN.set('probMode', probMode)
paramsN.set('lengthEnabled', int(params[21]))
lengthClass = int(params[22])
if lengthClass == 0:
lengthClass = 'dThird'
elif lengthClass == 1:
lengthClass = 'mThird'
elif lengthClass == 2:
lengthClass = 'uThird'
paramsN.set('lengthClass', lengthClass)
pipeline(host, port, paramsN, dwiN, roiAN, roiBN, wmN)
inputPar0 = ""
inputVol0 = ""
inputVol1 = ""
inputVol2 = ""
inputVol3 = ""
return
def recvVolume(volName, type, isDti=False):
volN = nrrd.nrrd()
print "Load data from : %s" % str(volName)
# load auxiliary files
rootName = os.path.join(os.path.dirname(volName), os.path.basename(volName).split('.' + os.path.basename(volName).split('.')[-1])[0])
# take dimensions of the image
print "Load dims from : %s" % str(rootName + '.dims')
dims = numpy.fromfile(rootName + '.dims', 'uint16')
print "Dims of data : %s" % str(dims)
if len(dims) == 5:
dtype = vtk_types [ int(dims[4]) ]
data = numpy.fromfile(volName, dtype)
data = data.reshape(dims[0], dims[1], dims[2], dims[3])
elif len(dims) == 3:
dtype = vtk_types [ int(dims[2]) ]
data = numpy.fromfile(volName, dtype)
data = data.reshape(dims[0], dims[1])
elif len(dims) == 4:
dtype = vtk_types [ int(dims[3]) ]
data = numpy.fromfile(volName, dtype)
data = data.reshape(dims[0], dims[1], dims[2])
# should return if dims is different
shape = data.shape
dtype = data.dtype
print "Data shape : %s" % str(shape)
print "Data type : %s" % str(dtype)
# set data into the nrrd object
volN.setImage(data)
volN.set('name', volName)
volN.set('fullname', volName)
volN.set('type', dtype)
volN.set('dimensions', shape)
org = numpy.fromfile(rootName + '.org', 'float')
volN.set('origin', org)
spa = numpy.fromfile(rootName + '.spa', 'float')
volN.set('spacing', spa)
I2R = numpy.fromfile(rootName + '.ijk', 'float')
I2R = I2R.reshape(4,4)
volN.set('ijk2ras', I2R)
R2I = numpy.fromfile(rootName + '.ras', 'float')
R2I = R2I.reshape(4,4)
volN.set('ras2ijk', R2I)
isDwi = False
if len(shape)==4:
isDwi = True
I2RD = numpy.fromfile(rootName + '.ijkd', 'float')
I2RD = I2RD.reshape(4,4)
volN.set('ijk2rasd', I2RD)
G = numpy.fromfile(rootName + '.grad', 'float')
G = G.astype('float')
volN.set('grads', G)
b = numpy.fromfile(rootName + '.bval', 'float')
b = b.astype('float')
volN.set('bval', b)
M2R = numpy.fromfile(rootName + '.mu', 'float')
M2R = M2R.reshape(4,4)
volN.set('mu', M2R)
return volN
def get(self, id):
"""get and return the image from slicer with the given id
"""
# create a socket
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
s.connect( (self.host, self.port) )
s.send('get ' + str(id) + ' \n') # send
nimage = nrrd.nrrd()
fp = s.makefile();
line = string.strip(fp.readline())
name = string.strip(fp.readline())
nimage.set('name', name)
name = string.split(name)
logger.debug( "Name : %s" % name)
scalar_type = string.strip(fp.readline())
nimage.set('scalar_type', scalar_type)
scalar_type = string.split(scalar_type)
logger.debug( "Type : %s" % scalar_type)
dimensions = string.strip(fp.readline())
nimage.set('dimensions', dimensions)
dimensions = string.split(dimensions)
if len(dimensions)==4:
logger.debug( "Dimensions : %s:%s:%s" % (dimensions[1], dimensions[2], dimensions[3]))
if len (dimensions)==5:
logger.debug( "Dimensions : %s:%s:%s:%s" % (dimensions[1], dimensions[2], dimensions[3], dimensions[4]))
space_origin = string.strip(fp.readline())
nimage.set('space_origin', space_origin)
space_origin = string.split(space_origin)
space_directions = string.strip(fp.readline())
nimage.set('space_directions', space_directions)
space_directions = string.split(space_directions)
kinds = string.strip(fp.readline())
nimage.set('kinds', kinds)
kinds = string.split(kinds)
isDti = False
if kinds[1] =='3D-masked-symmetric-matrix':
mu = string.strip(fp.readline())
nimage.set('measurement_frame', mu)
mu = string.split(mu)
isDti = True
isDwi = False
if kinds[1] =='vector':
mu = string.strip(fp.readline())
nimage.set('measurement_frame', mu)
mu = string.split(mu)
isDwi = True
dtype = vtk_types [ int(scalar_type[1]) ]
size = numpy_sizes [ dtype ]
if isDti:
size = size * int(dimensions[1]) * int(dimensions[4]) * int(dimensions[3]) * int(dimensions[2])
elif isDwi:
size = size * int(dimensions[4]) * int(dimensions[3]) * int(dimensions[2]) * int(dimensions[1])
else:
size = size * int(dimensions[3]) * int(dimensions[2]) * int(dimensions[1])
data = s.recv(size)
while len(data) != size:
data += s.recv(size)
im = numpy.fromstring (data, dtype)
if isDti:
im = im.reshape( int(dimensions[1]), int(dimensions[4]) * int(dimensions[3]) * int(dimensions[2]) )
elif isDwi:
im = im.reshape( int(dimensions[4]), int(dimensions[3]), int(dimensions[2]) , int(dimensions[1]) )
else:
im = im.reshape( int(dimensions[3]), int(dimensions[2]), int(dimensions[1]) )
s.close()
nimage.setImage(im)
return nimage
def main (\
inputPar0 = "",\
inputVol0 = "",\
inputVol1 = "",\
inputVol2 = "",\
inputVol3 = ""
):
if not inputPar0:
return
if not inputVol0:
return
parName = inputPar0
dwiName = inputVol0
roiAName = ""
roiBName = ""
wmName = ""
if inputVol1:
roiAName = inputVol1
if inputVol2:
roiBName = inputVol2
if inputVol3:
wmName = inputVol3
#if inputVol4:
# ten = scene.GetNodeByID(inputVol4)
# tenName = ten.GetName()
paramsN = nrrd.nrrd()
dwiN = nrrd.nrrd()
roiAN = nrrd.nrrd()
roiBN = nrrd.nrrd()
wmN = nrrd.nrrd()
paramsN.set('location', os.getcwd())
dwiN = recvVolume(dwiName, 'dwi')
paramsN.set('dwi', dwiName)
if roiAName:
roiAN = recvVolume(roiAName, 'roi')
paramsN.set('roiA', roiAName)
if roiBName:
roiBN = recvVolume(roiBName, 'roi')
paramsN.set('roiB', roiBName)
if wmName:
wmN = recvVolume(wmName, 'wm')
paramsN.set('wm', wmName)
#if tenName:
# s.send('tensor ' + str(tenName) + '\n')
# ack = s.recv(SIZE)
print "Params loaded from : %s" % str(parName)
params = numpy.fromfile(parName, 'float')
paramsN.set('pipeline', 'STOCHASTIC')
print "Pipeline?? : %s" % str(paramsN.get('pipeline'))
# smoothing
paramsN.set('smoothEnabled', int(params[0]))
stdD = numpy.array([params[1], params[2], params[3]], 'float')
paramsN.set('stdDev', stdD)
# brain
paramsN.set('wmEnabled', int(params[4]))
paramsN.set('infWMThres', params[5])
paramsN.set('supWMThres', params[6])
# tensor
paramsN.set('tensEnabled', int(params[7]))
bLine = 0
paramsN.set('bLine', params[8])
paramsN.set('faEnabled', int(params[9]))
paramsN.set('traceEnabled', int(params[10]))
paramsN.set('modeEnabled', int(params[11]))
# stochastic tracto
paramsN.set('stEnabled', int(params[12]))
paramsN.set('totalTracts', params[13])
paramsN.set('maxLength', params[14])
paramsN.set('stepSize', params[15])
paramsN.set('spaceEnabled', int(params[16]))
paramsN.set('stopEnabled', int(params[17]))
paramsN.set('fa', params[18])
# connectivity
paramsN.set('cmEnabled', int(params[19]))
probMode = int(params[20])
if probMode == 0:
probMode = 'binary'
elif probMode == 1:
probMode = 'cumulative'
elif probMode == 2:
probMode = 'weighted'
paramsN.set('probMode', probMode)
paramsN.set('lengthEnabled', int(params[21]))
lengthClass = int(params[22])
if lengthClass == 0:
lengthClass = 'dThird'
elif lengthClass == 1:
lengthClass = 'mThird'
elif lengthClass == 2:
lengthClass = 'uThird'
paramsN.set('lengthClass', lengthClass)
pipeline(paramsN, dwiN, roiAN, roiBN, wmN)
inputPar0 = ""
inputVol0 = ""
inputVol1 = ""
inputVol2 = ""
inputVol3 = ""
return
def recvVolume(volName, type, isDti=False):
volN = nrrd.nrrd()
print "Load data from : %s" % str(volName)
# load auxiliary files
rootName = os.path.join(os.path.dirname(volName), os.path.basename(volName).split('.' + os.path.basename(volName).split('.')[-1])[0])
# take dimensions of the image
print "Load dims from : %s" % str(rootName + '.dims')
dims = numpy.fromfile(rootName + '.dims', 'uint16')
print "Dims of data : %s" % str(dims)
if len(dims) == 5:
dtype = vtk_types [ int(dims[4]) ]
data = numpy.fromfile(volName, dtype)
data = data.reshape(dims[0], dims[1], dims[2], dims[3])
elif len(dims) == 3:
dtype = vtk_types [ int(dims[2]) ]
data = numpy.fromfile(volName, dtype)
data = data.reshape(dims[0], dims[1])
elif len(dims) == 4:
dtype = vtk_types [ int(dims[3]) ]
data = numpy.fromfile(volName, dtype)
data = data.reshape(dims[0], dims[1], dims[2])
# should return if dims is different
shape = data.shape
dtype = data.dtype
print "Data shape : %s" % str(shape)
print "Data type : %s" % str(dtype)
# set data into the nrrd object
volN.setImage(data)
volN.set('name', volName)
volN.set('fullname', volName)
volN.set('type', dtype)
volN.set('dimensions', shape)
org = numpy.fromfile(rootName + '.org', 'float')
volN.set('origin', org)
spa = numpy.fromfile(rootName + '.spa', 'float')
volN.set('spacing', spa)
I2R = numpy.fromfile(rootName + '.ijk', 'float')
I2R = I2R.reshape(4,4)
volN.set('ijk2ras', I2R)
R2I = numpy.fromfile(rootName + '.ras', 'float')
R2I = R2I.reshape(4,4)
volN.set('ras2ijk', R2I)
isDwi = False
if len(shape)==4:
isDwi = True
I2RD = numpy.fromfile(rootName + '.ijkd', 'float')
I2RD = I2RD.reshape(4,4)
volN.set('ijk2rasd', I2RD)
G = numpy.fromfile(rootName + '.grad', 'float')
G = G.astype('float')
volN.set('grads', G)
b = numpy.fromfile(rootName + '.bval', 'float')
b = b.astype('float')
volN.set('bval', b)
M2R = numpy.fromfile(rootName + '.mu', 'float')
M2R = M2R.reshape(4,4)
volN.set('mu', M2R)
return volN
def get(self, id):
"""get and return the image from slicer with the given id
"""
# create a socket
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
s.connect((self.host, self.port))
s.send('get ' + str(id) + ' \n') # send
nimage = nrrd.nrrd()
fp = s.makefile()
line = string.strip(fp.readline())
name = string.strip(fp.readline())
nimage.set('name', name)
name = string.split(name)
logger.debug("Name : %s" % name)
scalar_type = string.strip(fp.readline())
nimage.set('scalar_type', scalar_type)
scalar_type = string.split(scalar_type)
logger.debug("Type : %s" % scalar_type)
dimensions = string.strip(fp.readline())
nimage.set('dimensions', dimensions)
dimensions = string.split(dimensions)
if len(dimensions) == 4:
logger.debug("Dimensions : %s:%s:%s" %
(dimensions[1], dimensions[2], dimensions[3]))
if len(dimensions) == 5:
logger.debug(
"Dimensions : %s:%s:%s:%s" %
(dimensions[1], dimensions[2], dimensions[3], dimensions[4]))
space_origin = string.strip(fp.readline())
nimage.set('space_origin', space_origin)
space_origin = string.split(space_origin)
space_directions = string.strip(fp.readline())
nimage.set('space_directions', space_directions)
space_directions = string.split(space_directions)
kinds = string.strip(fp.readline())
nimage.set('kinds', kinds)
kinds = string.split(kinds)
isDti = False
if kinds[1] == '3D-masked-symmetric-matrix':
mu = string.strip(fp.readline())
nimage.set('measurement_frame', mu)
mu = string.split(mu)
isDti = True
isDwi = False
if kinds[1] == 'vector':
mu = string.strip(fp.readline())
nimage.set('measurement_frame', mu)
mu = string.split(mu)
isDwi = True
dtype = vtk_types[int(scalar_type[1])]
size = numpy_sizes[dtype]
if isDti:
size = size * int(dimensions[1]) * int(dimensions[4]) * int(
dimensions[3]) * int(dimensions[2])
elif isDwi:
size = size * int(dimensions[4]) * int(dimensions[3]) * int(
dimensions[2]) * int(dimensions[1])
else:
size = size * int(dimensions[3]) * int(dimensions[2]) * int(
dimensions[1])
data = s.recv(size)
while len(data) != size:
data += s.recv(size)
im = numpy.fromstring(data, dtype)
if isDti:
im = im.reshape(
int(dimensions[1]),
int(dimensions[4]) * int(dimensions[3]) * int(dimensions[2]))
elif isDwi:
im = im.reshape(int(dimensions[4]), int(dimensions[3]),
int(dimensions[2]), int(dimensions[1]))
else:
im = im.reshape(int(dimensions[3]), int(dimensions[2]),
int(dimensions[1]))
s.close()
nimage.setImage(im)
return nimage
def handle_read(self):
# handle incomings
if self.nimage.hasKey('size') and not self.result:
self.isarray = True
size = self.nimage.get('size')
dims = self.nimage.get('dimensions')
nvols = int(dims[3])
sizePerVol = size/nvols
if not self.nflag:
self.data = ""
self.nflag = True
self.ldata += self.recv(sizePerVol)
if len(self.ldata)==sizePerVol:
self.isPartial = True
self.data += self.ldata
self.pvol.append(self.ldata)
self.nVols +=1
self.ldata = ""
# get DWI and run pipeline
if self.nVols==nvols:
logger.debug("volume acquired!")
self.set_data(self.data)
self.pvol = []
self.isPartial = False
self.nVols = 0
self.data = ""
logger.info("pipeline launchned")
self.res = self.pipeline(self.nimage.getImage())
logger.debug("result shape : %s:%s:%s" % (self.res.shape[0] , self.res.shape[1] , self.res.shape[2] ))
logger.debug("result type : %s" % self.res.dtype)
logger.info("pipeline completed")
self.data = 'FACK'
self.result = True
logger.debug("ready for sending!")
else:
if not self.result:
self.isarray = False
self.data = self.recv(SIZE)
if not self.init: # first get parameters of the pipeline
self.set_params(self.data)
elif self.data: # second get data associated to the vector image
self.set_data(self.data)
else:
logger.error("command unknown")
else: # special case for returning to client (Slicer) - currently SlicerDaemon used
if not self.issent:
self.data = self.recv(SIZE)
cmd = string.strip(self.data)
cmd = string.split(cmd)
if len(cmd)!=1:
logger.info("command awaited!")
else:
logger.info("command : %s" % cmd[0])
if cmd[0]=='get':
logger.info("send back data!")
self.data = self.res.tostring() # 'PACK'
self.issent = True
else:
logger.error("command unknown")
else:
logger.info("closing!")
self.result = False
# determine response
if self.data and not self.isarray and not self.result:
self.buffer += 'ACK'
self.is_writable = True
self.data = ""
elif (self.data or self.ldata) and self.isarray and not self.result:
logger.debug("acquiring array")
if self.isPartial:
self.buffer += 'ACK'
self.is_writable = True
self.isPartial = False
elif self.data and self.result:
self.buffer = self.data
self.is_writable = True
# reset
if self.issent:
self.data = "" # set previously
self.ntype = ""
self.init = False
self.isarray = False
self.nflag = False
self.params = nrrd.nrrd()
self.nimage = nrrd.nrrd()
self.roiA = nrrd.nrrd()
self.roiB = nrrd.nrrd()
self.wm = nrrd.nrrd()
self.res = numpy.empty(0)
self.issent = False
logger.debug("data size : %s" %len(self.buffer))
logger.info("ready to handle write!")
else:
logger.info("got null data")
