def agent_obstacle(agents, obstacles, mask):
if is_model(agents, 'circular'):
agent_circular_obstacle(agents, obstacles, mask)
elif is_model(agents, 'three_circle'):
agent_three_circle_obstacle(agents, obstacles, mask)
else:
raise InvalidType
def agents(self, agents):
if is_model(agents, 'circular'):
self.__agents = CircularAgents(agents)
self.agents.addItem(self)
self.agents.setData(agents)
elif is_model(agents, 'three_circle'):
self.__agents = ThreeCircleAgents(agents)
self.agents.addItem(self)
self.agents.setData(agents)
else:
raise FeatureNotImplemented('Wrong agents type: "{}"'.format(
agents))
def agent_agent_block_list(agents, cell_size):
points_indices, cells_count, cells_offset, grid_shape = add_to_cells(
agents['position'], cell_size)
cell_indices = np.arange(len(cells_count))
neigh_cells = neighboring_cells(grid_shape)
if is_model(agents, 'circular'):
agent_agent_circular(agents, cell_indices, neigh_cells, points_indices,
cells_count, cells_offset)
elif is_model(agents, 'three_circle'):
agent_agent_three_circle(agents, cell_indices, neigh_cells,
points_indices, cells_count, cells_offset)
else:
raise InvalidType
def update(self):
agents = self.simulation.agents.array
force = force_fluctuation(agents['mass'], agents['std_rand_force'])
agents['force'] += force
if is_model(agents, 'three_circle'):
torque = torque_fluctuation(agents['inertia_rot'],
agents['std_rand_torque'])
agents['torque'] += torque
def update(self):
agents = self.simulation.agents.array
mask = agents['active']
agents['force'][mask] += force_fluctuation(
agents['mass'][mask], agents['std_rand_force'][mask])
if is_model(agents, 'three_circle'):
agents['torque'][mask] += torque_fluctuation(
agents['inertia_rot'][mask], agents['std_rand_torque'][mask])
def velocity_verlet_integrator_init(agents, dt_min, dt_max):
dt = adaptive_timestep(agents, dt_min, dt_max)
translational_euler(agents, dt)
for agent in agents:
agent['force_prev'][:] = agent['force'][:]
if is_model(agents, 'three_circle'):
rotational_euler(agents, dt)
for agent in agents:
agent['torque_prev'] = agent['torque']
shoulders(agents)
return dt
def velocity_verlet_integrator(agents, dt_min, dt_max):
r"""Velocity verlet integrator algorithm
Translational motion
1.
.. math::
\mathbf{v}_{k+1/2} = \mathbf{v}_{k} + \frac{1}{2} a_{k} \Delta t
2.
.. math::
\mathbf{x}_{k+1} = \mathbf{x}_{k} + \mathbf{v}_{k+1/2} \Delta t
3.
.. math::
a_{k+1} = \mathbf{f}_{k+1} / m
4.
.. math::
\mathbf{v}_{k+1} = \mathbf{v}_{k+1/2} + \frac{1}{2} a_{k+1} \Delta t
.. Todo:: Rotational motion
Args:
agents (Agent):
dt_min (float):
Minimum timestep :math:`\Delta x_{min}` for adaptive integration.
dt_max (float):
Maximum timestep :math:`\Delta x_{max}` for adaptive integration.
Yields:
float: Timestep :math:`\Delta t` that was used for integration.
References
- https://en.wikipedia.org/wiki/Verlet_integration#Velocity_Verlet
"""
dt = adaptive_timestep(agents, dt_min, dt_max)
translational_verlet(agents, dt)
if is_model(agents, 'three_circle'):
rotational_verlet(agents, dt)
shoulders(agents)
return dt
def update(self):
agents = self.simulation.agents.array
force_adjust_agents(agents)
if is_model(agents, 'three_circle'):
torque_adjust_agents(agents)
def update(self):
agents = self.simulation.agents.array
agents['force'] = 0
if is_model(agents, 'three_circle'):
agents['torque'] = 0
def update(self):
if is_model(self.simulation.agents.array, 'three_circle'):
orient_towards_target_direction(self.simulation.agents.array)
def update(self):
agents = self.simulation.agents.array
mask = agents['active']
force_adjust_agents(agents, mask)
if is_model(agents, 'three_circle'):
torque_adjust_agents(agents, mask)
def __init__(self, agents):
super().__init__()
assert is_model(agents, 'three_circle'), \
'Agent should the three_circle model'
def __init__(self, agents):
super().__init__()
assert is_model(agents, 'circular'), 'Agent should be circular model'
