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mod phase 2 experiment and new shell script for phase 2
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hpc/run_analysis.sh renamed to hpc/run_phase1.sh

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‎hpc/run_phase2.sh‎

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#!/bin/bash
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#SBATCH --job-name=pp_phase2
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#SBATCH --partition=rome
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#SBATCH --nodes=1
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#SBATCH --ntasks=1
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#SBATCH --cpus-per-task=32
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#SBATCH --time=04:00:00
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#SBATCH --mem=16G
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#SBATCH --output=pp_phase2_%j.out
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#SBATCH --error=pp_phase2_%j.err
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# =============================================================================
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# PP Hydra Effect - Phase 2: Self-Organization (SOC Test)
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# =============================================================================
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#
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# PHASE 2: Test if prey_death evolves toward critical point
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# - 6 initial prey_death values × 30 reps = 180 simulations
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# - Longer runs (5000 steps) for evolution to equilibrate
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# - Tracks evolved_prey_death_timeseries
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#
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# SUBMIT: sbatch run_phase2.sh
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# MONITOR: squeue -u $USER
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# CANCEL: scancel <job_id>
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#
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# =============================================================================
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echo "========================================"
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echo "PP Hydra Effect - Phase 2"
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echo "========================================"
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echo "Job ID: $SLURM_JOB_ID"
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echo "Node: $(hostname)"
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echo "CPUs: $SLURM_CPUS_PER_TASK"
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echo "Start: $(date)"
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echo "Working dir: $(pwd)"
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echo "========================================"
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# -----------------------------------------------------------------------------
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# Environment Setup
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# -----------------------------------------------------------------------------
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source ~/snellius_venv/bin/activate
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# Prevent numpy/scipy from spawning extra threads (joblib handles parallelism)
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export OMP_NUM_THREADS=1
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export OPENBLAS_NUM_THREADS=1
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export MKL_NUM_THREADS=1
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export NUMEXPR_NUM_THREADS=1
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# -----------------------------------------------------------------------------
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# Run Phase 2
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# -----------------------------------------------------------------------------
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OUTPUT_DIR="results/phase2_${SLURM_JOB_ID}"
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mkdir -p $OUTPUT_DIR
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echo ""
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echo "Output directory: $OUTPUT_DIR"
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echo ""
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# Dry run first to verify setup
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echo "Dry run check:"
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python3 -u scripts/experiments.py \
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--phase 2 \
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--output $OUTPUT_DIR \
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--cores $SLURM_CPUS_PER_TASK \
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--dry-run
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echo ""
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echo "Starting Phase 2..."
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echo ""
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# Run phase 2
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python3 -u scripts/experiments.py \
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--phase 2 \
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--output $OUTPUT_DIR \
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--cores $SLURM_CPUS_PER_TASK
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# -----------------------------------------------------------------------------
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# Completion
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# -----------------------------------------------------------------------------
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echo ""
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echo "========================================"
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echo "Phase 2 Complete"
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echo "========================================"
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echo "End time: $(date)"
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echo "Results in: $OUTPUT_DIR/"
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echo ""
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echo "Output files:"
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ls -lh $OUTPUT_DIR/
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echo ""
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echo "Next steps:"
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echo " 1. Download phase2_results.jsonl"
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echo " 2. Plot evolved_prey_death_final vs initial prey_death"
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echo " 3. Check if all runs converge to ~0.095-0.105 (critical point)"
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echo " 4. If SOC confirmed, proceed to Phase 3 (finite-size scaling)"
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echo "========================================"

‎models/config.py‎

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"""Central configuration for all experiments."""
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# Grid settings
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grid_size: int = 100 #FIXME: Decide default configuration
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grid_size: int = 1000 #FIXME: Decide default configuration
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densities: Tuple[float, float] = (0.30, 0.15) # (prey, predator) #FIXME: Default densities
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# For FSS experiments: multiple grid sizes
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# Phase 2: Self-organization (evolution toward criticality)
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PHASE2_CONFIG = Config(
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grid_size=100,
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n_prey_birth=10,
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grid_size=1000,
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n_prey_birth=1, # Fixed at cfg.prey_birth (0.2)
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n_replicates=30,
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warmup_steps=1000,
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measurement_steps=1000,
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warmup_steps=1000, # Shorter warmup (evolution starts immediately)
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measurement_steps=3000, # Longer measurement to see convergence
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# Evolution settings
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with_evolution=True,
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evolve_sd=0.10,
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collect_pcf=False, # Not needed for SOC analysis
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evolve_sd=0.01, # Smaller mutation rate for smoother convergence
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evolve_min=0.001,
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evolve_max=0.20, # Allow full range
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collect_pcf=False,
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save_timeseries=True,
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timeseries_subsample=10,
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timeseries_subsample=10, # Track evolution trajectory
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)
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# Phase 3: Finite-size scaling at critical point

‎notebooks/cluster_distributions_critical.png‎

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‎notebooks/phase1.ipynb‎

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‎phase1_18676818/experiments.log‎

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‎phase1_18676818/phase1_config.json‎

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‎phase1_18676818/phase1_metadata.json‎

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‎phase1_18676818/phase1_results.jsonl‎

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