add scalarfields on grid
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parent
808dc6f78c
commit
1952198fad
30
agent.py
30
agent.py
@ -13,43 +13,57 @@ from mesa.space import Coordinate
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class RandomWalkerAnt(Agent):
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class RandomWalkerAnt(Agent):
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def __init__(self, unique_id, model, do_follow_chemical_A=True,
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def __init__(self, unique_id, model, do_follow_chemical_A=True,
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energy_0=1, chemical_drop_rate_0=1, sensitvity_0=1, alpha=0.5)-> None:
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energy_0=1, chemical_drop_rate_0=1, sensitvity_0=1, alpha=0.5) -> None:
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super().__init__(unique_id=unique_id, model=model)
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super().__init__(unique_id=unique_id, model=model)
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self._next_pos : None | Coordinate = None
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self._next_pos : None | Coordinate = None
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self.prev_pos = None
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self.prev_pos : None | Coordinate = None
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self.do_follow_chemical_A : bool = True # False -> follow_chemical_B = True
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self.do_follow_chemical_A : bool = True # False -> follow_chemical_B = True
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self.energy : float = energy_0
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self.energy : float = energy_0
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self.sensitvity : float = sensitvity_0
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self.sensitvity : float = sensitvity_0
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self.chemical_drop_rate : float = chemical_drop_rate_0 #TODO: check whether needs to be separated into A and B
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self.chemical_drop_rate : float = chemical_drop_rate_0 #TODO: check whether needs to be separated into A and B
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self.alpha = alpha
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self.alpha = alpha
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def sensitvity_to_concentration(self, prop : float) -> float:
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# TODO
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return prop
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def step(self):
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def step(self):
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# Calculate where next ant location should be and store in _next_pos
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# TODO
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pass
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def drop_chemicals(self):
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# drop chemicals (depending on current state) on concentration field
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# TODO
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# use self.model.grid.add_to_field(key, value, pos) to not interfere with other ants
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pass
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pass
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def advance(self) -> None:
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def advance(self) -> None:
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self.drop_chemicals()
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self.pos = self._next_pos
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self.pos = self._next_pos
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@property
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@property
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def front_neighbors(self):
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def front_neighbors(self):
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if self.prev_pos is not None:
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if self.prev_pos is not None:
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assert(self.pos is not None)
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x, y = self.pos
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x, y = self.pos
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x_prev, y_prev = self.prev_pos
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x_prev, y_prev = self.prev_pos
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dx, dy = x - x_prev, y - y_prev
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dx, dy = x - x_prev, y - y_prev
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front = [
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front = np.array([
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(x, y + dy),
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(x, y + dy),
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(x + dx, y),
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(x + dx, y + dy),
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(x + dx, y + dy),
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]
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(x + dx, y),
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])
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return front #TODO: verify (do we need to sperate into even/odd?)
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return front #TODO: verify (do we need to sperate into even/odd?)
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else:
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else:
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# TODO: return all neighbors or raise Exception?
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# TODO: return all neighbors or raise Exception?
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pass
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pass
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"""
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"""
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This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, version 3.
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This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, version 3.
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1
main.py
1
main.py
@ -32,6 +32,7 @@ def main():
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agent.do_follow_chemical_A = False
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agent.do_follow_chemical_A = False
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agent.prev_pos = (9,10)
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agent.prev_pos = (9,10)
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print(agent.front_neighbors)
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print(agent.front_neighbors)
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print(agent.pos, agent.unique_id, agent.do_follow_chemical_A)
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print(agent.pos, agent.unique_id, agent.do_follow_chemical_A)
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30
model.py
30
model.py
@ -11,25 +11,37 @@ License: AGPL 3 (see end of file)
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import numpy as np
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import numpy as np
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from mesa.model import Model
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from mesa.model import Model
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from mesa.space import Coordinate, HexGrid, Iterable
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from mesa.space import Coordinate, HexGrid, Iterable
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from multihex import MultiHexGrid
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from multihex import MultiHexGrid, MultiHexGridScalarFields
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from mesa.time import SimultaneousActivation
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from mesa.time import SimultaneousActivation
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from mesa.datacollection import DataCollector
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from mesa.datacollection import DataCollector
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from agent import RandomWalkerAnt
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from agent import RandomWalkerAnt
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from agent import Pheromone
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class ActiveWalkerModel(Model):
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class ActiveWalkerModel(Model):
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# TODO: separate food and source into new agents?
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# TODO: pheromone concentrations as well as agents?
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def __init__(self, width : int, height : int , num_max_agents : int,
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def __init__(self, width : int, height : int , num_max_agents : int,
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num_initial_roamers : int,
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num_initial_roamers : int,
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nest_position : Coordinate,
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nest_position : Coordinate,
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max_steps:int=1000) -> None:
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max_steps:int=1000) -> None:
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super().__init__()
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super().__init__()
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fields={"A" : True, # key : also have _next prop (for no interference in step)
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"B": True,
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"nests": False,
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"food" : False,
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}
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self.schedule = SimultaneousActivation(self)
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self.schedule = SimultaneousActivation(self)
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self.grid = MultiHexGrid(width=width, height=height, torus=True) # TODO: replace with MultiHexGrid
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self.grid = MultiHexGridScalarFields(width=width, height=height, torus=True, fields=fields)
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self._unique_id_counter : int = -1 # only touch via get_unique_id() or get_unique_ids(num_ids)
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self._unique_id_counter = -1
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self.max_steps = max_steps
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self.max_steps = max_steps
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self.nest_position : Coordinate = nest_position
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self.nest_position : Coordinate = nest_position
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self.num_max_agents = num_max_agents
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self.num_max_agents = num_max_agents
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self.decay_rates = {"A" :1,
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"B": 1,
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}
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for agent_id in self.get_unique_ids(num_initial_roamers):
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for agent_id in self.get_unique_ids(num_initial_roamers):
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agent = RandomWalkerAnt(unique_id=agent_id, model=self, do_follow_chemical_A=True)
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agent = RandomWalkerAnt(unique_id=agent_id, model=self, do_follow_chemical_A=True)
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self.schedule.add(agent)
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self.schedule.add(agent)
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@ -41,8 +53,18 @@ class ActiveWalkerModel(Model):
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)
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)
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self.datacollector.collect(self) # keep at end of __init___
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self.datacollector.collect(self) # keep at end of __init___
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def step(self):
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def step(self):
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self.schedule.step()
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self.schedule.step() # step() and advance() all agents
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# apply decay rate on pheromone levels
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for key in ("A", "B"):
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field = self.grid.fields[key]
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self.grid.fields[key] = field - self.decay_rates[key]*field
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self.grid.step() # actually apply deposits on fields
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self.datacollector.collect(self)
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self.datacollector.collect(self)
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if self.schedule.steps >= self.max_steps:
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if self.schedule.steps >= self.max_steps:
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27
multihex.py
27
multihex.py
@ -12,6 +12,7 @@ License: AGPL 3 (see end of file)
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from mesa.space import HexGrid
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from mesa.space import HexGrid
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from mesa.agent import Agent
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from mesa.agent import Agent
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import numpy as np
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import numpy as np
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import numpy.typing as npt
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from mesa.space import Coordinate, accept_tuple_argument
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from mesa.space import Coordinate, accept_tuple_argument
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import itertools
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import itertools
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from typing import (
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from typing import (
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@ -91,6 +92,32 @@ class MultiHexGrid(HexGrid):
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)
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)
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class MultiHexGridScalarFields(MultiHexGrid):
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def __init__(self, fields: dict[str, bool], width : int, height : int, torus : bool, scalar_initial_value : float=0) -> None:
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super().__init__(width=width, height=height, torus=torus)
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self._field_props = fields
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self.fields : dict[str, npt.NDArray[np.float_]] = {}
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for key, is_step_field in fields.items():
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self.fields[key] = np.ones((width, height)).astype(float) * scalar_initial_value
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if is_step_field:
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self.fields[f"_next_{key}"] = np.zeros((width, height)).astype(float)
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def reset_field(self, key : str) -> None:
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self.fields[key] = np.zeros((self.width, self.height))
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def add_to_field(self, field_key : str, value : float, pos : Coordinate) -> None:
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if self._field_props[field_key]:
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self.fields[f"_next_{field_key}"][pos] += value
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else:
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self.fields[field_key][pos] += value
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def step(self) -> None:
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for key, is_step_field in self._field_props.items():
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if is_step_field:
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self.fields[key] += self.fields[f"_next_{key}"]
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self.reset_field(f"_next_{key}")
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"""
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"""
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This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, version 3.
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This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, version 3.
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