Custom¶
- class hoomd.md.force.Custom(aniso=False)¶
Bases:
ForceCustom forces implemented in python.
Derive a custom force class from
Custom, and override theset_forcesmethod to compute forces on particles. Users have direct, zero-copy access to the C++ managed buffers via either thecpu_local_force_arraysorgpu_local_force_arraysproperty. Choose the property that corresponds to the device you wish to alter the data on. In addition to zero-copy access to force buffers, custom forces have access to the local snapshot API via the_state.cpu_local_snapshotor the_state.gpu_local_snapshotproperty.See also
See the documentation in
hoomd.Statefor more information on the local snapshot API.Examples:
class MyCustomForce(hoomd.md.force.Custom): def __init__(self): super().__init__(aniso=True) def set_forces(self, timestep): with self.cpu_local_force_arrays as arrays: arrays.force[:] = -5 arrays.torque[:] = 3 arrays.potential_energy[:] = 27 arrays.virial[:] = np.arange(6)[None, :]
In addition, since data is MPI rank-local, there may be ghost particle data associated with each rank. To access this read-only ghost data, access the property name with either the prefix
ghost_of the suffix_with_ghost.Note
Pass
aniso=Trueto themd.force.Customconstructor if your custom force produces non-zero torques on particles.class MyCustomForce(hoomd.md.force.Custom): def __init__(self): super().__init__() def set_forces(self, timestep): with self.cpu_local_force_arrays as arrays: # access only the ghost particle forces ghost_force_data = arrays.ghost_force # access torque data on this rank and ghost torque data torque_data = arrays.torque_with_ghost
Note
When accessing the local force arrays, always use a context manager.
Note
The shape of the exposed arrays cannot change while in the context manager.
Note
All force data buffers are MPI rank local, so in simulations with MPI, only the data for a single rank is available.
Note
Access to the force buffers is constant (O(1)) time.
{inherited}
Members defined in
Custom: