codegithubka
diff --git a/‎models/config.py‎
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Lines changed: 2 additions & 2 deletions
diff --git a/‎notebooks/cluster_powerlaw.png‎
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diff --git a/‎notebooks/cluster_powerlaw_check.png‎
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diff --git a/‎notebooks/cluster_size_distributions.png‎
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diff --git a/‎notebooks/cluster_stats_vs_death_rate.png‎
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diff --git a/‎notebooks/phase1.ipynb‎
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diff --git a/‎notebooks/phase1_summary.png‎
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diff --git a/‎notebooks/prey_pop_vs_death_faceted.png‎
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diff --git a/‎notebooks/prey_pop_vs_death_rate.png‎
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diff --git a/‎scripts/experiments.py‎
Lines changed: 13 additions & 10 deletions b/‎scripts/experiments.py‎
Lines changed: 13 additions & 10 deletions
@@ -210,8 +210,8 @@ def estimate_runtime(self, n_cores: int = 32) -> str:
     grid_size=100,
     n_prey_birth=10,
     n_replicates=30,
-    warmup_steps=300,
-    measurement_steps=500,
+    warmup_steps=1000,
+    measurement_steps=1000,
     with_evolution=True,
     evolve_sd=0.10,
     collect_pcf=False,  # Not needed for SOC analysis
 
@@ -218,19 +218,22 @@ def run_single_simulation(
             evolved_stds.append(stats["std"])
 
         # Cluster analysis (at end of measurement)
-        if step == measurement_steps - 1 and prey >= min_count and pred >= (min_count // 4):
-            prey_stats = get_cluster_stats_fast(model.grid, 1)
-            pred_stats = get_cluster_stats_fast(model.grid, 2)
+        if step == measurement_steps - 1:
+            prey_survived = prey_pops[-1] > min_count
+            pred_survived = pred_pops[-1] > (min_count // 4)
 
-            cluster_sizes_prey = prey_stats['sizes'].tolist()
-            cluster_sizes_pred = pred_stats['sizes'].tolist()
+            if prey_survived:
+                prey_stats = get_cluster_stats_fast(model.grid, 1)
+                cluster_sizes_prey = prey_stats['sizes'].tolist()
+                largest_fractions_prey.append(prey_stats['largest_fraction'])
 
-            largest_fractions_prey.append(prey_stats['largest_fraction'])
-            largest_fractions_pred.append(pred_stats['largest_fraction'])
-            # NOTE: Change in largest fraction calculation if needed for critical point location
+            if pred_survived:
+                pred_stats = get_cluster_stats_fast(model.grid, 2)
+                cluster_sizes_pred = pred_stats['sizes'].tolist()
+                largest_fractions_pred.append(pred_stats['largest_fraction'])
 
-            # PCF
-            if compute_pcf:
+            # PCF requires both
+            if compute_pcf and prey_survived and pred_survived:
                 max_dist = min(grid_size / 2, cfg.pcf_max_distance)
                 pcf_data = compute_all_pcfs_fast(model.grid, max_dist, cfg.pcf_n_bins)
                 pcf_samples['prey_prey'].append(pcf_data['prey_prey'])