def __init__(self, group,flow_target,slab_direction,flow_direction,n_slabs,max_slab=-1,min_slab=-1):
period=1 # This updater has to be applied every timestep
assert (n_slabs > 0 ),"Invalid negative number of slabs."
if min_slab < 0:
min_slab = 0
if max_slab < 0:
max_slab = n_slabs/2
#Cast input to int to avoid mismatch of types in calling the constructor
n_slabs = int(n_slabs)
min_slab = int(min_slab)
max_slab = int(max_slab)
assert (max_slab>-1 and max_slab < n_slabs),"Invalid max_slab in [0,"+str(n_slabs)+")."
assert (min_slab>-1 and min_slab < n_slabs),"Invalid min_slab in [0,"+str(n_slabs)+")."
assert (min_slab != max_slab),"Invalid min/max slabs. Both have the same value."
# initialize the base class
_updater.__init__(self);
self._flow_target = hoomd.variant._setup_variant_input(flow_target);
# create the c++ mirror class
if not hoomd.context.current.device.cpp_exec_conf.isCUDAEnabled():
self.cpp_updater = _md.MuellerPlatheFlow(hoomd.context.current.system_definition, group.cpp_group,flow_target.cpp_variant,slab_direction,flow_direction,n_slabs,min_slab,max_slab);
else:
self.cpp_updater = _md.MuellerPlatheFlowGPU(hoomd.context.current.system_definition, group.cpp_group,flow_target.cpp_variant,slab_direction,flow_direction,n_slabs,min_slab,max_slab);
self.setupUpdater(period);
def _attach(self):
group = self._simulation.state._get_group(self.filter)
sys_def = self._simulation.state._cpp_sys_def
if isinstance(self._simulation.device, hoomd.device.CPU):
self._cpp_obj = _md.MuellerPlatheFlow(
sys_def, self.trigger, group, self.flow_target,
self.slab_direction, self.flow_direction, self.n_slabs,
self.min_slab, self.max_slab, self.flow_epsilon)
else:
self._cpp_obj = _md.MuellerPlatheFlowGPU(
sys_def, self.trigger, group, self.flow_target,
self.slab_direction, self.flow_direction, self.n_slabs,
self.min_slab, self.max_slab, self.flow_epsilon)
super()._attach()
def __init__(self,
group,
flow_target,
slab_direction,
flow_direction,
n_slabs,
max_slab=-1,
min_slab=-1):
hoomd.util.print_status_line()
period = 1 # This updater has to be applied every timestep
assert (n_slabs > 0), "Invalid negative number of slabs."
if min_slab < 0:
min_slab = 0
if max_slab < 0:
max_slab = n_slabs / 2
assert (max_slab > -1 and max_slab < n_slabs
), "Invalid max_slab in [0," + str(n_slabs) + ")."
assert (min_slab > -1 and min_slab < n_slabs
), "Invalid min_slab in [0," + str(n_slabs) + ")."
assert (min_slab !=
max_slab), "Invalid min/max slabs. Both have the same value."
# initialize the base class
_updater.__init__(self)
self._flow_target = hoomd.variant._setup_variant_input(flow_target)
# create the c++ mirror class
if not hoomd.context.exec_conf.isCUDAEnabled():
self.cpp_updater = _md.MuellerPlatheFlow(
hoomd.context.current.system_definition, group.cpp_group,
flow_target.cpp_variant, slab_direction, flow_direction,
n_slabs, min_slab, max_slab)
else:
self.cpp_updater = _md.MuellerPlatheFlowGPU(
hoomd.context.current.system_definition, group.cpp_group,
flow_target.cpp_variant, slab_direction, flow_direction,
n_slabs, min_slab, max_slab)
self.setupUpdater(period)
