def __init__(self, id, p_move, states, transitions, durations, current_state, home_cell_id, current_state_duration=0, been_infected=0):
self.id = id
self.p_move = p_move
self.states = states
self.transitions = transitions
self.durations = durations
self.current_state = current_state
self.home_cell_id = home_cell_id
self.current_state_duration = current_state_duration # how long the agent has been in this state
self.been_infected = been_infected
self.least_state = get_least_severe_state(states)
def __init__(self, id, p_move, transitions, states, durations,
current_state, home_cell_id):
""" An agent can move from cell to cell and get infected by another
agent being simoultaneously in the same cell.
:param id: id of the agent
:type id: Integer (int)
:param p_move: Probability for an agent to move if a move is made in the <Map> where it is
:type p_move: float between 0 and 1
:param transitions: Markovian transition matrix between the `states`
:type transitions: numpy array of shape (#states, #states) with rows summing up to 1
:param states: states in which an agent can be
:type states: list of <State>
:param durations: durations of the states if the agent move to them
:type durations: iterable of length #states containing strictly positive integers
:param current_state: state of the agent at its initialization
:type current_state: <State>
:param home_cell_id: if of the home cell of the agent
:type home_cell_id: int
"""
self.id = id
self.p_move = p_move
self.transitions = transitions
self.states = states
self.durations = durations
self.current_state = current_state
self.home_cell_id = home_cell_id
self.current_cell_id = home_cell_id
# Define dicts for `states`
self.name2state = {state.get_name(): state for state in states}
self.name2index = {
state.get_name(): i
for i, state in enumerate(states)
}
self.index2state = {i: state for i, state in enumerate(states)}
self.state_names = {state.get_name() for state in states}
# Define variables for `current_state`
self.n_states = len(states)
self.current_state_age = 0
self.current_state_index = self.name2index.get(
current_state.get_name())
self.least_severe_state = get_least_severe_state(states)
"""
Test1: contagions
Simulation with 2 agents in the same cell who can be in 2 distinct states: 'healthy' or 'sick'.
Those agents have distinct durations `durations_1` and `durations_2` attached to those states.
After one step, agent 1 gets sick. He contaminates agent 2. Then both get healthy again after different durations
"""
state0 = State(id=0, name='healthy', contagiousity=0, sensitivity=1, severity=0)
state1 = State(id=1, name='sick', contagiousity=1, sensitivity=0, severity=0.5)
transitions = array([[1, 0], [1, 0]])
states = [state0, state1]
least_severe_state = get_least_severe_state([state0, state1])
validated = 'OK' if least_severe_state.get_id() == state1.get_id() else 'Failed'
print(f'Check for least_severe_state: {validated}')
durations_1 = (-1, 3) # 1st state duration: undefinite, 2nd state duration: 3 timesteps (days)
durations_2 = (-1, 2) # 1st state duration: undefinite, 2nd state duration: 2 timesteps (days)
p_move_1 = 0.3
p_move_2 = 0.5
ind_1 = Agent(id=1, p_move=p_move_1, transitions=transitions, states=states, durations=durations_1, current_state=state0, home_cell_id=1)
ind_2 = Agent(id=2, p_move=p_move_2, transitions=transitions, states=states, durations=durations_2, current_state=state0, home_cell_id=1)
position_1 = (1, 1)
attractivity_1 = 0.5
cell_1 = Cell(id=1, position=position_1, attractivity=attractivity_1, unsafety=1, agents=[ind_1, ind_2])