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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,22 +1,115 @@ | ||
| from polyphy_functions import PolyPhyWindow, PostSimulation, SimulationVisuals, FieldVariables, Agents, TypeAliases, PPVariables, PPData | ||
| from kernels import Kernels | ||
| import argparse | ||
| from numpy.random import default_rng | ||
| import taichi as ti | ||
|
|
||
| class PolyPhy: | ||
| def __init__(self): | ||
| ## Initialize Taichi | ||
| self.parse_args() | ||
| ti.init(arch=ti.cpu) | ||
| self.rng = default_rng() | ||
| self.ppData = PPData() | ||
| self.ppVariables = PPVariables(self.ppData) | ||
| self.batch_mode = False | ||
| self.num_iterations = -1 | ||
| self.parse_values() | ||
| self.agents = Agents(self.rng,self.ppVariables,self.ppData) | ||
| self.fieldVariables = FieldVariables(self.ppVariables,self.ppData) | ||
| self.k = Kernels() | ||
| self.simulationVisuals = SimulationVisuals(self.k,self.ppVariables,self.ppData,self.agents,self.fieldVariables) | ||
|
|
||
| def start_simulation(self): | ||
| PolyPhyWindow(self.k,self.simulationVisuals) | ||
| PolyPhyWindow(self.k,self.simulationVisuals,self.batch_mode,self.num_iterations) | ||
| PostSimulation(self.simulationVisuals) | ||
|
|
||
| def parse_args(self): | ||
| parser = argparse.ArgumentParser(description="PolyPhy") | ||
| parser.add_argument('-b', '--batch-mode', action='store_true', help="Enable batch mode (run simulations in batch mode)") | ||
| parser.add_argument('-n', '--num-iterations', type=int, help="Number of iterations (specify the number of simulation iterations)") | ||
| parser.add_argument('-d', '--sensing-dist', type=float, help="Sensing distance (set the agent's sensing distance in pixels)") | ||
| parser.add_argument('-a', '--sensing-angle', type=float, help="Sensing angle (set the agent's sensing angle in degrees)") | ||
| parser.add_argument('-e', '--sampling-expo', type=float, help="Sampling exponent (adjust the sampling exponent for data collection)") | ||
| parser.add_argument('-s', '--step-size', type=float, help="Step size (define the step size for agent movement)") | ||
| parser.add_argument('-D', '--data-deposit', type=str, help="Data deposit (specify the method for data deposition)") | ||
| parser.add_argument('-A', '--agent-deposit', type=str, help="Agent deposit (specify the method for agent deposition)") | ||
| parser.add_argument('-X', '--deposit-attenuation', type=float, help="Deposit attenuation (adjust the deposit attenuation factor)") | ||
| parser.add_argument('-T', '--trace-attenuation', type=float, help="Trace attenuation (adjust the trace attenuation factor)") | ||
| parser.add_argument('-Z', '--deposit-visualization', type=str, help="Deposit visualization (select the method for deposit visualization)") | ||
| parser.add_argument('-Y', '--trace-visualization', type=str, help="Trace visualization (select the method for trace visualization)") | ||
| parser.add_argument('--distance-distribution', type=str, choices=['constant', 'exponential', 'maxwell-boltzmann'], | ||
| help="Distance distribution (choose the type of distance distribution for agent interactions)") | ||
| parser.add_argument('--directional-distribution', type=str, choices=['discrete', 'cone'], | ||
| help="Directional distribution (choose the type of directional distribution for agent movement)") | ||
| parser.add_argument('--directional-mutation', type=str, choices=['deterministic', 'stochastic'], | ||
| help="Directional mutation (choose the type of directional mutation for agent behavior)") | ||
| parser.add_argument('--deposit-fetching', type=str, choices=['nearest-neighbor', 'noise-perturbed-NN'], | ||
| help="Deposit fetching (select the method for deposit fetching)") | ||
| parser.add_argument('--agent-boundary-handling', type=str, choices=['wrap-around', 're-initialize-center', 're-initialize-randomly'], | ||
| help="Agent boundary handling (specify how agents interact with boundaries)") | ||
|
|
||
| # Parse the command-line arguments | ||
| self.args = parser.parse_args() | ||
|
|
||
| def parse_values(self): | ||
| if self.args.batch_mode: | ||
| self.batch_mode = True | ||
| print("Batch mode enabled!!!") | ||
| if self.args.num_iterations: | ||
| self.num_iterations = int(self.args.num_iterations) | ||
| print(f"Number of iterations: {self.args.num_iterations}") | ||
| else: | ||
| raise AssertionError("Please set number of iterations for batch mode") | ||
| if self.args.num_iterations and not self.args.batch_mode: | ||
| raise AssertionError("Please set to batch mode") | ||
| if self.args.sensing_dist: | ||
| self.ppVariables.setter("sense_distance",self.args.sensing_dist) | ||
| if self.args.sensing_angle: | ||
| self.ppVariables.setter("sense_angle",self.args.sensing_angle) | ||
| if self.args.sampling_expo: | ||
| self.ppVariables.setter("sampling_exponent",self.args.sampling_expo) | ||
| if self.args.step_size: | ||
| self.ppVariables.setter("step_size",self.args.step_size) | ||
| if self.args.data_deposit: | ||
| self.ppVariables.setter("data_deposit",self.args.data_deposit) | ||
| if self.args.agent_deposit: | ||
| self.ppVariables.setter("agent_deposit",self.args.agent_deposit) | ||
| if self.args.deposit_attenuation: | ||
| self.ppVariables.setter("deposit_attenuation",self.args.deposit_attenuation) | ||
| if self.args.trace_attenuation: | ||
| self.ppVariables.setter("trace_attenuation",self.args.trace_attenuation) | ||
| if self.args.deposit_visualization: | ||
| self.ppVariables.setter("deposit_vis",self.args.deposit_visualization) | ||
| if self.args.trace_visualization: | ||
| self.ppVariables.setter("trace_vis",self.args.trace_visualization) | ||
| if self.args.distance_distribution: | ||
| if self.args.distance_distribution == "constant": | ||
| self.ppVariables.setter("distance_sampling_distribution",PPVariables.EnumDistanceSamplingDistribution.CONSTANT) | ||
| elif self.args.distance_distribution == "exponential": | ||
| self.ppVariables.setter("distance_sampling_distribution",PPVariables.EnumDistanceSamplingDistribution.EXPONENTIAL) | ||
| elif self.args.distance_distribution == "maxwell-boltzmann": | ||
| self.ppVariables.setter("distance_sampling_distribution",PPVariables.EnumDistanceSamplingDistribution.MAXWELL_BOLTZMANN) | ||
| if self.args.directional_distribution: | ||
| if self.args.directional_distribution == "discrete": | ||
| self.ppVariables.setter("directional_sampling_distribution",PPVariables.EnumDirectionalSamplingDistribution.DISCRETE) | ||
| elif self.args.directional_distribution == "cone": | ||
| self.ppVariables.setter("directional_sampling_distribution",PPVariables.EnumDirectionalSamplingDistribution.CONE) | ||
| if self.args.directional_mutation: | ||
| if self.args.directional_mutation == "deterministic": | ||
| self.ppVariables.setter("directional_mutation_type",PPVariables.EnumDirectionalMutationType.DETERMINISTIC) | ||
| elif self.args.directional_mutation == "stochastic": | ||
| self.ppVariables.setter("directional_mutation_type",PPVariables.EnumDirectionalMutationType.PROBABILISTIC) | ||
| if self.args.deposit_fetching: | ||
| if self.args.deposit_fetching == "nearest-neighbor": | ||
| self.ppVariables.setter("deposit_fetching_strategy",PPVariables.EnumDepositFetchingStrategy.NN) | ||
| elif self.args.deposit_fetching == "noise-perturbed-NN": | ||
| self.ppVariables.setter("deposit_fetching_strategy",PPVariables.EnumDepositFetchingStrategy.NN_PERTURBED) | ||
| if self.args.agent_boundary_handling: | ||
| if self.args.agent_boundary_handling == "wrap-around": | ||
| self.ppVariables.setter("agent_boundary_handling",PPVariables.EnumAgentBoundaryHandling.WRAP) | ||
| elif self.args.agent_boundary_handling == "re-initialize-center": | ||
| self.ppVariables.setter("agent_boundary_handling",PPVariables.EnumAgentBoundaryHandling.REINIT_CENTER) | ||
| elif self.args.agent_boundary_handling == "re-initialize-randomly": | ||
| self.ppVariables.setter("agent_boundary_handling",PPVariables.EnumAgentBoundaryHandling.REINIT_RANDOMLY) | ||
|
|
||
| PolyPhy().start_simulation() |
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