def setupOutputs(self):
self._disconnectInternals()
# we need a new cache
cache = OpCompressedCache(parent=self)
cache.name = self.name + "WrappedCache"
# connect cache outputs
self.CleanBlocks.connect(cache.CleanBlocks)
self.OutputHdf5.connect(cache.OutputHdf5)
self._op2.Input.connect(cache.Output)
# connect cache inputs
cache.InputHdf5.connect(self.InputHdf5)
cache.Input.connect(self._op1.Output)
# set the cache block shape
tagged_shape = self._op1.Output.meta.getTaggedShape()
tagged_shape['t'] = 1
tagged_shape['c'] = 1
cacheshape = map(lambda k: tagged_shape[k], 'xyzct')
if _labeling_impl == "lazy":
#HACK hardcoded block shape
blockshape = numpy.minimum(cacheshape, 256)
else:
# use full spatial volume if not lazy
blockshape = cacheshape
cache.BlockShape.setValue(tuple(blockshape))
self._cache = cache
def setupOutputs(self):
self._disconnectInternals()
# we need a new cache
cache = OpCompressedCache(parent=self)
cache.name = self.name + "WrappedCache"
# connect cache outputs
self.CleanBlocks.connect(cache.CleanBlocks)
self.OutputHdf5.connect(cache.OutputHdf5)
self._op2.Input.connect(cache.Output)
# connect cache inputs
cache.InputHdf5.connect(self.InputHdf5)
cache.Input.connect(self._op1.Output)
# set the cache block shape
tagged_shape = self._op1.Output.meta.getTaggedShape()
tagged_shape['t'] = 1
tagged_shape['c'] = 1
cacheshape = map(lambda k: tagged_shape[k], 'xyzct')
if _labeling_impl == "lazy":
#HACK hardcoded block shape
blockshape = numpy.minimum(cacheshape, 256)
else:
# use full spatial volume if not lazy
blockshape = cacheshape
cache.BlockShape.setValue(tuple(blockshape))
self._cache = cache
def setupOutputs(self):
self._disconnectInternals()
# we need a new cache
cache = OpCompressedCache(parent=self)
cache.name = self.name + "WrappedCache"
# connect cache outputs
self.CleanBlocks.connect(cache.CleanBlocks)
self.OutputHdf5.connect(cache.OutputHdf5)
self._op2.Input.connect(cache.Output)
# connect cache inputs
cache.InputHdf5.connect(self.InputHdf5)
cache.Input.connect(self._op1.Output)
# set the cache block shape
tagged_shape = self._op1.Output.meta.getTaggedShape()
tagged_shape['t'] = 1
tagged_shape['c'] = 1
blockshape = map(lambda k: tagged_shape[k], 'xyzct')
cache.BlockShape.setValue(tuple(blockshape))
self._cache = cache
