@@ -73,7 +73,7 @@ class Config:
7373 grid_sizes : Tuple [int , ...] = (100 , 200 , 500 , 1000 )
7474
7575 # Default/fixed parameters
76- prey_birth : float = 0.20
76+ prey_birth : float = 0.80
7777 prey_death : float = 0.05
7878 predator_birth : float = 0.2 # FIXME: Default predator death rate
7979 predator_death : float = 0.1 # FIXME: Default predator death rate
@@ -84,9 +84,9 @@ class Config:
8484
8585 # Prey parameter sweep (Phase 1)
8686 prey_birth_range : Tuple [float , float ] = (0.10 , 0.35 )
87- prey_death_range : Tuple [float , float ] = (0.001 , 0.10 )
87+ prey_death_range : Tuple [float , float ] = (0.0 , 0.20 )
8888 n_prey_birth : int = 15 # FIXME: Decide number of grid points along prey axes
89- n_prey_death : int = 15
89+ n_prey_death : int = 20
9090
9191 # Predator parameter sweep (Phase 4 sensitivity)
9292 predator_birth_values : Tuple [float , ...] = (0.15 , 0.20 , 0.25 , 0.30 ) #FIXME: Bogus values for now
@@ -100,7 +100,7 @@ class Config:
100100
101101 # Simulation steps
102102 warmup_steps : int = 300 # FIXME: Steps to run before measuring
103- measurement_steps : int = 300 # FIXME: Decide measurement steps
103+ measurement_steps : int = 500 # FIXME: Decide measurement steps
104104
105105 # Evo
106106 with_evolution : bool = False
@@ -191,17 +191,18 @@ def estimate_runtime(self, n_cores: int = 32) -> str:
191191
192192# Phase 1: Parameter sweep to find critical point
193193PHASE1_CONFIG = Config (
194- grid_size = 1000 ,
194+ grid_size = 100 ,
195195 n_prey_birth = 15 ,
196196 n_prey_death = 15 ,
197197 prey_birth_range = (0.10 , 0.35 ),
198- prey_death_range = (0.001 , 0.10 ),
199- n_replicates = 20 ,
198+ prey_death_range = (0.0 , 0.20 ),
199+ n_replicates = 30 ,
200200 warmup_steps = 300 ,
201- measurement_steps = 1000 ,
201+ measurement_steps = 500 ,
202202 collect_pcf = True ,
203203 pcf_sample_rate = 0.2 ,
204204 save_timeseries = False ,
205+ directed_hunting = False ,
205206)
206207
207208# Phase 2: Self-organization (evolution toward criticality)
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