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<!doctype html>
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<title>experiments API documentation</title>
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<h2>Contents</h2>
<ul>
<li><a href="#predator-prey-hydra-effect-experiments">Predator-Prey Hydra Effect Experiments</a></li>
</ul>
<h2>API Documentation</h2>
<ul class="memberlist">
<li>
<a class="function" href="#generate_unique_seed">generate_unique_seed</a>
</li>
<li>
<a class="function" href="#count_populations">count_populations</a>
</li>
<li>
<a class="function" href="#get_evolved_stats">get_evolved_stats</a>
</li>
<li>
<a class="function" href="#average_pcfs">average_pcfs</a>
</li>
<li>
<a class="function" href="#save_results_jsonl">save_results_jsonl</a>
</li>
<li>
<a class="function" href="#save_results_npz">save_results_npz</a>
</li>
<li>
<a class="function" href="#load_results_jsonl">load_results_jsonl</a>
</li>
<li>
<a class="function" href="#run_single_simulation">run_single_simulation</a>
</li>
<li>
<a class="function" href="#run_phase1">run_phase1</a>
</li>
<li>
<a class="function" href="#run_phase2">run_phase2</a>
</li>
<li>
<a class="function" href="#run_phase3">run_phase3</a>
</li>
<li>
<a class="function" href="#run_phase4">run_phase4</a>
</li>
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<a class="function" href="#run_phase5">run_phase5</a>
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<section class="module-info">
<h1 class="modulename">
experiments </h1>
<div class="docstring"><h1 id="predator-prey-hydra-effect-experiments">Predator-Prey Hydra Effect Experiments</h1>
<p>HPC-ready experiment runner for investigating the Hydra effect in
predator-prey cellular automata.</p>
<h6 id="experimental-phases">Experimental Phases</h6>
<ul>
<li><strong>Phase 1</strong>: Parameter sweep to find critical point (bifurcation + cluster analysis)</li>
<li><strong>Phase 2</strong>: Self-organization analysis (evolution toward criticality)</li>
<li><strong>Phase 3</strong>: Finite-size scaling at critical point</li>
<li><strong>Phase 4</strong>: Sensitivity analysis across parameter regimes</li>
<li><strong>Phase 5</strong>: Model extensions (directed hunting comparison)</li>
</ul>
<h6 id="functions">Functions</h6>
<div class="pdoc-code codehilite">
<pre><span></span><code><span class="n">run_single_simulation</span> <span class="c1"># Execute one simulation run and collect metrics.</span>
<span class="n">run_phase1</span><span class="p">,</span> <span class="n">run_phase2</span><span class="p">,</span> <span class="n">run_phase3</span><span class="p">,</span> <span class="n">run_phase4</span><span class="p">,</span> <span class="n">run_phase5</span> <span class="c1"># Phase-specific experiment runners.</span>
</code></pre>
</div>
<h6 id="utilities">Utilities</h6>
<div class="pdoc-code codehilite">
<pre><span></span><code><span class="n">generate_unique_seed</span> <span class="c1"># Deterministic seed generation from parameters.</span>
<span class="n">count_populations</span> <span class="c1"># Count species populations on grid.</span>
<span class="n">get_evolved_stats</span> <span class="c1"># Statistics for evolved parameters.</span>
<span class="n">average_pcfs</span> <span class="c1"># Average multiple PCF measurements.</span>
<span class="n">save_results_jsonl</span><span class="p">,</span> <span class="n">load_results_jsonl</span><span class="p">,</span> <span class="n">save_results_npz</span> <span class="c1"># I/O functions for experiment results.</span>
</code></pre>
</div>
<h6 id="command-line-usage">Command Line Usage</h6>
<div class="pdoc-code codehilite">
<pre><span></span><code>python<span class="w"> </span>experiments.py<span class="w"> </span>--phase<span class="w"> </span><span class="m">1</span><span class="w"> </span><span class="c1"># Run phase 1</span>
python<span class="w"> </span>experiments.py<span class="w"> </span>--phase<span class="w"> </span><span class="m">1</span><span class="w"> </span>--dry-run<span class="w"> </span><span class="c1"># Estimate runtime</span>
python<span class="w"> </span>experiments.py<span class="w"> </span>--phase<span class="w"> </span>all<span class="w"> </span><span class="c1"># Run all phases</span>
python<span class="w"> </span>experiments.py<span class="w"> </span>--phase<span class="w"> </span><span class="m">1</span><span class="w"> </span>--output<span class="w"> </span>results/<span class="w"> </span><span class="c1"># Custom output</span>
</code></pre>
</div>
<h6 id="programmatic-usage">Programmatic Usage</h6>
<div class="pdoc-code codehilite">
<pre><span></span><code><span class="kn">from</span><span class="w"> </span><span class="nn">experiments</span><span class="w"> </span><span class="kn">import</span> <span class="n">run_single_simulation</span><span class="p">,</span> <span class="n">run_phase1</span>
<span class="kn">from</span><span class="w"> </span><span class="nn"><a href="models/config.html">models.config</a></span><span class="w"> </span><span class="kn">import</span> <span class="n">PHASE1_CONFIG</span>
<span class="c1"># Single simulation</span>
<span class="n">result</span> <span class="o">=</span> <span class="n">run_single_simulation</span><span class="p">(</span>
<span class="n">prey_birth</span><span class="o">=</span><span class="mf">0.2</span><span class="p">,</span>
<span class="n">prey_death</span><span class="o">=</span><span class="mf">0.05</span><span class="p">,</span>
<span class="n">predator_birth</span><span class="o">=</span><span class="mf">0.8</span><span class="p">,</span>
<span class="n">predator_death</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span>
<span class="n">grid_size</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span>
<span class="n">seed</span><span class="o">=</span><span class="mi">42</span><span class="p">,</span>
<span class="n">cfg</span><span class="o">=</span><span class="n">PHASE1_CONFIG</span><span class="p">,</span>
<span class="p">)</span>
<span class="c1"># Full phase (writes to output directory)</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">logging</span>
<span class="n">results</span> <span class="o">=</span> <span class="n">run_phase1</span><span class="p">(</span><span class="n">PHASE1_CONFIG</span><span class="p">,</span> <span class="n">Path</span><span class="p">(</span><span class="s2">"results/"</span><span class="p">),</span> <span class="n">logging</span><span class="o">.</span><span class="n">getLogger</span><span class="p">())</span>
</code></pre>
</div>
</div>
<input id="mod-experiments-view-source" class="view-source-toggle-state" type="checkbox" aria-hidden="true" tabindex="-1">
<label class="view-source-button" for="mod-experiments-view-source"><span>View Source</span></label>
<div class="pdoc-code codehilite"><pre><span></span><span id="L-1"><a href="#L-1"><span class="linenos"> 1</span></a><span class="ch">#!/usr/bin/env python3</span>
</span><span id="L-2"><a href="#L-2"><span class="linenos"> 2</span></a><span class="sd">"""</span>
</span><span id="L-3"><a href="#L-3"><span class="linenos"> 3</span></a><span class="sd">Predator-Prey Hydra Effect Experiments</span>
</span><span id="L-4"><a href="#L-4"><span class="linenos"> 4</span></a><span class="sd">======================================</span>
</span><span id="L-5"><a href="#L-5"><span class="linenos"> 5</span></a>
</span><span id="L-6"><a href="#L-6"><span class="linenos"> 6</span></a><span class="sd">HPC-ready experiment runner for investigating the Hydra effect in</span>
</span><span id="L-7"><a href="#L-7"><span class="linenos"> 7</span></a><span class="sd">predator-prey cellular automata.</span>
</span><span id="L-8"><a href="#L-8"><span class="linenos"> 8</span></a>
</span><span id="L-9"><a href="#L-9"><span class="linenos"> 9</span></a><span class="sd">Experimental Phases</span>
</span><span id="L-10"><a href="#L-10"><span class="linenos"> 10</span></a><span class="sd">-------------------</span>
</span><span id="L-11"><a href="#L-11"><span class="linenos"> 11</span></a><span class="sd">- **Phase 1**: Parameter sweep to find critical point (bifurcation + cluster analysis)</span>
</span><span id="L-12"><a href="#L-12"><span class="linenos"> 12</span></a><span class="sd">- **Phase 2**: Self-organization analysis (evolution toward criticality)</span>
</span><span id="L-13"><a href="#L-13"><span class="linenos"> 13</span></a><span class="sd">- **Phase 3**: Finite-size scaling at critical point</span>
</span><span id="L-14"><a href="#L-14"><span class="linenos"> 14</span></a><span class="sd">- **Phase 4**: Sensitivity analysis across parameter regimes</span>
</span><span id="L-15"><a href="#L-15"><span class="linenos"> 15</span></a><span class="sd">- **Phase 5**: Model extensions (directed hunting comparison)</span>
</span><span id="L-16"><a href="#L-16"><span class="linenos"> 16</span></a>
</span><span id="L-17"><a href="#L-17"><span class="linenos"> 17</span></a><span class="sd">Functions</span>
</span><span id="L-18"><a href="#L-18"><span class="linenos"> 18</span></a><span class="sd">---------</span>
</span><span id="L-19"><a href="#L-19"><span class="linenos"> 19</span></a><span class="sd">```python</span>
</span><span id="L-20"><a href="#L-20"><span class="linenos"> 20</span></a><span class="sd">run_single_simulation # Execute one simulation run and collect metrics.</span>
</span><span id="L-21"><a href="#L-21"><span class="linenos"> 21</span></a><span class="sd">run_phase1, run_phase2, run_phase3, run_phase4, run_phase5 # Phase-specific experiment runners.</span>
</span><span id="L-22"><a href="#L-22"><span class="linenos"> 22</span></a><span class="sd">```</span>
</span><span id="L-23"><a href="#L-23"><span class="linenos"> 23</span></a>
</span><span id="L-24"><a href="#L-24"><span class="linenos"> 24</span></a><span class="sd">Utilities</span>
</span><span id="L-25"><a href="#L-25"><span class="linenos"> 25</span></a><span class="sd">---------</span>
</span><span id="L-26"><a href="#L-26"><span class="linenos"> 26</span></a><span class="sd">```python</span>
</span><span id="L-27"><a href="#L-27"><span class="linenos"> 27</span></a><span class="sd">generate_unique_seed # Deterministic seed generation from parameters.</span>
</span><span id="L-28"><a href="#L-28"><span class="linenos"> 28</span></a><span class="sd">count_populations # Count species populations on grid.</span>
</span><span id="L-29"><a href="#L-29"><span class="linenos"> 29</span></a><span class="sd">get_evolved_stats # Statistics for evolved parameters.</span>
</span><span id="L-30"><a href="#L-30"><span class="linenos"> 30</span></a><span class="sd">average_pcfs # Average multiple PCF measurements.</span>
</span><span id="L-31"><a href="#L-31"><span class="linenos"> 31</span></a><span class="sd">save_results_jsonl, load_results_jsonl, save_results_npz # I/O functions for experiment results.</span>
</span><span id="L-32"><a href="#L-32"><span class="linenos"> 32</span></a><span class="sd">```</span>
</span><span id="L-33"><a href="#L-33"><span class="linenos"> 33</span></a>
</span><span id="L-34"><a href="#L-34"><span class="linenos"> 34</span></a><span class="sd">Command Line Usage</span>
</span><span id="L-35"><a href="#L-35"><span class="linenos"> 35</span></a><span class="sd">------------------</span>
</span><span id="L-36"><a href="#L-36"><span class="linenos"> 36</span></a><span class="sd">```bash</span>
</span><span id="L-37"><a href="#L-37"><span class="linenos"> 37</span></a><span class="sd">python experiments.py --phase 1 # Run phase 1</span>
</span><span id="L-38"><a href="#L-38"><span class="linenos"> 38</span></a><span class="sd">python experiments.py --phase 1 --dry-run # Estimate runtime</span>
</span><span id="L-39"><a href="#L-39"><span class="linenos"> 39</span></a><span class="sd">python experiments.py --phase all # Run all phases</span>
</span><span id="L-40"><a href="#L-40"><span class="linenos"> 40</span></a><span class="sd">python experiments.py --phase 1 --output results/ # Custom output</span>
</span><span id="L-41"><a href="#L-41"><span class="linenos"> 41</span></a><span class="sd">```</span>
</span><span id="L-42"><a href="#L-42"><span class="linenos"> 42</span></a>
</span><span id="L-43"><a href="#L-43"><span class="linenos"> 43</span></a><span class="sd">Programmatic Usage</span>
</span><span id="L-44"><a href="#L-44"><span class="linenos"> 44</span></a><span class="sd">------------------</span>
</span><span id="L-45"><a href="#L-45"><span class="linenos"> 45</span></a><span class="sd">```python</span>
</span><span id="L-46"><a href="#L-46"><span class="linenos"> 46</span></a><span class="sd">from experiments import run_single_simulation, run_phase1</span>
</span><span id="L-47"><a href="#L-47"><span class="linenos"> 47</span></a><span class="sd">from models.config import PHASE1_CONFIG</span>
</span><span id="L-48"><a href="#L-48"><span class="linenos"> 48</span></a>
</span><span id="L-49"><a href="#L-49"><span class="linenos"> 49</span></a><span class="sd"># Single simulation</span>
</span><span id="L-50"><a href="#L-50"><span class="linenos"> 50</span></a><span class="sd">result = run_single_simulation(</span>
</span><span id="L-51"><a href="#L-51"><span class="linenos"> 51</span></a><span class="sd"> prey_birth=0.2,</span>
</span><span id="L-52"><a href="#L-52"><span class="linenos"> 52</span></a><span class="sd"> prey_death=0.05,</span>
</span><span id="L-53"><a href="#L-53"><span class="linenos"> 53</span></a><span class="sd"> predator_birth=0.8,</span>
</span><span id="L-54"><a href="#L-54"><span class="linenos"> 54</span></a><span class="sd"> predator_death=0.1,</span>
</span><span id="L-55"><a href="#L-55"><span class="linenos"> 55</span></a><span class="sd"> grid_size=100,</span>
</span><span id="L-56"><a href="#L-56"><span class="linenos"> 56</span></a><span class="sd"> seed=42,</span>
</span><span id="L-57"><a href="#L-57"><span class="linenos"> 57</span></a><span class="sd"> cfg=PHASE1_CONFIG,</span>
</span><span id="L-58"><a href="#L-58"><span class="linenos"> 58</span></a><span class="sd">)</span>
</span><span id="L-59"><a href="#L-59"><span class="linenos"> 59</span></a>
</span><span id="L-60"><a href="#L-60"><span class="linenos"> 60</span></a><span class="sd"># Full phase (writes to output directory)</span>
</span><span id="L-61"><a href="#L-61"><span class="linenos"> 61</span></a><span class="sd">import logging</span>
</span><span id="L-62"><a href="#L-62"><span class="linenos"> 62</span></a><span class="sd">results = run_phase1(PHASE1_CONFIG, Path("results/"), logging.getLogger())</span>
</span><span id="L-63"><a href="#L-63"><span class="linenos"> 63</span></a><span class="sd">```</span>
</span><span id="L-64"><a href="#L-64"><span class="linenos"> 64</span></a><span class="sd">"""</span>
</span><span id="L-65"><a href="#L-65"><span class="linenos"> 65</span></a>
</span><span id="L-66"><a href="#L-66"><span class="linenos"> 66</span></a><span class="kn">import</span><span class="w"> </span><span class="nn">argparse</span>
</span><span id="L-67"><a href="#L-67"><span class="linenos"> 67</span></a><span class="kn">import</span><span class="w"> </span><span class="nn">hashlib</span>
</span><span id="L-68"><a href="#L-68"><span class="linenos"> 68</span></a><span class="kn">import</span><span class="w"> </span><span class="nn">json</span>
</span><span id="L-69"><a href="#L-69"><span class="linenos"> 69</span></a><span class="kn">import</span><span class="w"> </span><span class="nn">logging</span>
</span><span id="L-70"><a href="#L-70"><span class="linenos"> 70</span></a><span class="kn">import</span><span class="w"> </span><span class="nn">os</span>
</span><span id="L-71"><a href="#L-71"><span class="linenos"> 71</span></a><span class="kn">import</span><span class="w"> </span><span class="nn">sys</span>
</span><span id="L-72"><a href="#L-72"><span class="linenos"> 72</span></a><span class="kn">import</span><span class="w"> </span><span class="nn">time</span>
</span><span id="L-73"><a href="#L-73"><span class="linenos"> 73</span></a><span class="kn">from</span><span class="w"> </span><span class="nn">dataclasses</span><span class="w"> </span><span class="kn">import</span> <span class="n">asdict</span>
</span><span id="L-74"><a href="#L-74"><span class="linenos"> 74</span></a><span class="kn">from</span><span class="w"> </span><span class="nn">pathlib</span><span class="w"> </span><span class="kn">import</span> <span class="n">Path</span>
</span><span id="L-75"><a href="#L-75"><span class="linenos"> 75</span></a><span class="kn">from</span><span class="w"> </span><span class="nn">typing</span><span class="w"> </span><span class="kn">import</span> <span class="n">Dict</span><span class="p">,</span> <span class="n">List</span><span class="p">,</span> <span class="n">Tuple</span><span class="p">,</span> <span class="n">Optional</span>
</span><span id="L-76"><a href="#L-76"><span class="linenos"> 76</span></a><span class="kn">import</span><span class="w"> </span><span class="nn">warnings</span>
</span><span id="L-77"><a href="#L-77"><span class="linenos"> 77</span></a>
</span><span id="L-78"><a href="#L-78"><span class="linenos"> 78</span></a><span class="kn">import</span><span class="w"> </span><span class="nn">numpy</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">np</span>
</span><span id="L-79"><a href="#L-79"><span class="linenos"> 79</span></a><span class="kn">from</span><span class="w"> </span><span class="nn">tqdm</span><span class="w"> </span><span class="kn">import</span> <span class="n">tqdm</span>
</span><span id="L-80"><a href="#L-80"><span class="linenos"> 80</span></a>
</span><span id="L-81"><a href="#L-81"><span class="linenos"> 81</span></a><span class="n">warnings</span><span class="o">.</span><span class="n">filterwarnings</span><span class="p">(</span><span class="s2">"ignore"</span><span class="p">)</span>
</span><span id="L-82"><a href="#L-82"><span class="linenos"> 82</span></a>
</span><span id="L-83"><a href="#L-83"><span class="linenos"> 83</span></a><span class="c1"># Project imports</span>
</span><span id="L-84"><a href="#L-84"><span class="linenos"> 84</span></a><span class="n">project_root</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="n">Path</span><span class="p">(</span><span class="vm">__file__</span><span class="p">)</span><span class="o">.</span><span class="n">parent</span><span class="o">.</span><span class="n">parent</span><span class="p">)</span>
</span><span id="L-85"><a href="#L-85"><span class="linenos"> 85</span></a><span class="k">if</span> <span class="n">project_root</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">sys</span><span class="o">.</span><span class="n">path</span><span class="p">:</span>
</span><span id="L-86"><a href="#L-86"><span class="linenos"> 86</span></a> <span class="n">sys</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">insert</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">project_root</span><span class="p">)</span>
</span><span id="L-87"><a href="#L-87"><span class="linenos"> 87</span></a>
</span><span id="L-88"><a href="#L-88"><span class="linenos"> 88</span></a><span class="kn">from</span><span class="w"> </span><span class="nn">models.config</span><span class="w"> </span><span class="kn">import</span> <span class="n">Config</span><span class="p">,</span> <span class="n">get_phase_config</span><span class="p">,</span> <span class="n">PHASE_CONFIGS</span>
</span><span id="L-89"><a href="#L-89"><span class="linenos"> 89</span></a>
</span><span id="L-90"><a href="#L-90"><span class="linenos"> 90</span></a><span class="c1"># Numba imports</span>
</span><span id="L-91"><a href="#L-91"><span class="linenos"> 91</span></a><span class="k">try</span><span class="p">:</span>
</span><span id="L-92"><a href="#L-92"><span class="linenos"> 92</span></a> <span class="kn">from</span><span class="w"> </span><span class="nn">models.numba_optimized</span><span class="w"> </span><span class="kn">import</span> <span class="p">(</span>
</span><span id="L-93"><a href="#L-93"><span class="linenos"> 93</span></a> <span class="n">compute_all_pcfs_fast</span><span class="p">,</span>
</span><span id="L-94"><a href="#L-94"><span class="linenos"> 94</span></a> <span class="n">get_cluster_stats_fast</span><span class="p">,</span>
</span><span id="L-95"><a href="#L-95"><span class="linenos"> 95</span></a> <span class="n">warmup_numba_kernels</span><span class="p">,</span>
</span><span id="L-96"><a href="#L-96"><span class="linenos"> 96</span></a> <span class="n">set_numba_seed</span><span class="p">,</span>
</span><span id="L-97"><a href="#L-97"><span class="linenos"> 97</span></a> <span class="n">NUMBA_AVAILABLE</span><span class="p">,</span>
</span><span id="L-98"><a href="#L-98"><span class="linenos"> 98</span></a> <span class="p">)</span>
</span><span id="L-99"><a href="#L-99"><span class="linenos"> 99</span></a>
</span><span id="L-100"><a href="#L-100"><span class="linenos"> 100</span></a> <span class="n">USE_NUMBA</span> <span class="o">=</span> <span class="n">NUMBA_AVAILABLE</span>
</span><span id="L-101"><a href="#L-101"><span class="linenos"> 101</span></a><span class="k">except</span> <span class="ne">ImportError</span><span class="p">:</span>
</span><span id="L-102"><a href="#L-102"><span class="linenos"> 102</span></a> <span class="n">USE_NUMBA</span> <span class="o">=</span> <span class="kc">False</span>
</span><span id="L-103"><a href="#L-103"><span class="linenos"> 103</span></a>
</span><span id="L-104"><a href="#L-104"><span class="linenos"> 104</span></a> <span class="k">def</span><span class="w"> </span><span class="nf">warmup_numba_kernels</span><span class="p">(</span><span class="n">size</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
</span><span id="L-105"><a href="#L-105"><span class="linenos"> 105</span></a> <span class="k">pass</span>
</span><span id="L-106"><a href="#L-106"><span class="linenos"> 106</span></a>
</span><span id="L-107"><a href="#L-107"><span class="linenos"> 107</span></a> <span class="k">def</span><span class="w"> </span><span class="nf">set_numba_seed</span><span class="p">(</span><span class="n">seed</span><span class="p">):</span>
</span><span id="L-108"><a href="#L-108"><span class="linenos"> 108</span></a> <span class="k">pass</span>
</span><span id="L-109"><a href="#L-109"><span class="linenos"> 109</span></a>
</span><span id="L-110"><a href="#L-110"><span class="linenos"> 110</span></a>
</span><span id="L-111"><a href="#L-111"><span class="linenos"> 111</span></a><span class="c1"># =============================================================================</span>
</span><span id="L-112"><a href="#L-112"><span class="linenos"> 112</span></a><span class="c1"># Utility Functions</span>
</span><span id="L-113"><a href="#L-113"><span class="linenos"> 113</span></a><span class="c1"># =============================================================================</span>
</span><span id="L-114"><a href="#L-114"><span class="linenos"> 114</span></a>
</span><span id="L-115"><a href="#L-115"><span class="linenos"> 115</span></a>
</span><span id="L-116"><a href="#L-116"><span class="linenos"> 116</span></a><span class="k">def</span><span class="w"> </span><span class="nf">generate_unique_seed</span><span class="p">(</span><span class="n">params</span><span class="p">:</span> <span class="nb">dict</span><span class="p">,</span> <span class="n">rep</span><span class="p">:</span> <span class="nb">int</span><span class="p">)</span> <span class="o">-></span> <span class="nb">int</span><span class="p">:</span>
</span><span id="L-117"><a href="#L-117"><span class="linenos"> 117</span></a><span class="w"> </span><span class="sd">"""</span>
</span><span id="L-118"><a href="#L-118"><span class="linenos"> 118</span></a><span class="sd"> Create a deterministic seed from a dictionary of parameters and a repetition index.</span>
</span><span id="L-119"><a href="#L-119"><span class="linenos"> 119</span></a>
</span><span id="L-120"><a href="#L-120"><span class="linenos"> 120</span></a><span class="sd"> This function serializes the input dictionary into a sorted JSON string,</span>
</span><span id="L-121"><a href="#L-121"><span class="linenos"> 121</span></a><span class="sd"> appends the repetition count, and hashes the resulting string using SHA-256.</span>
</span><span id="L-122"><a href="#L-122"><span class="linenos"> 122</span></a><span class="sd"> The first 8 characters of the hex digest are then converted to an integer</span>
</span><span id="L-123"><a href="#L-123"><span class="linenos"> 123</span></a><span class="sd"> to provide a stable, unique seed for random number generators.</span>
</span><span id="L-124"><a href="#L-124"><span class="linenos"> 124</span></a>
</span><span id="L-125"><a href="#L-125"><span class="linenos"> 125</span></a><span class="sd"> Parameters</span>
</span><span id="L-126"><a href="#L-126"><span class="linenos"> 126</span></a><span class="sd"> ----------</span>
</span><span id="L-127"><a href="#L-127"><span class="linenos"> 127</span></a><span class="sd"> params : dict</span>
</span><span id="L-128"><a href="#L-128"><span class="linenos"> 128</span></a><span class="sd"> A dictionary of configuration parameters. Keys are sorted to ensure</span>
</span><span id="L-129"><a href="#L-129"><span class="linenos"> 129</span></a><span class="sd"> determinism regardless of insertion order.</span>
</span><span id="L-130"><a href="#L-130"><span class="linenos"> 130</span></a><span class="sd"> rep : int</span>
</span><span id="L-131"><a href="#L-131"><span class="linenos"> 131</span></a><span class="sd"> The repetition or iteration index, used to ensure different seeds</span>
</span><span id="L-132"><a href="#L-132"><span class="linenos"> 132</span></a><span class="sd"> are generated for the same parameter set across multiple runs.</span>
</span><span id="L-133"><a href="#L-133"><span class="linenos"> 133</span></a>
</span><span id="L-134"><a href="#L-134"><span class="linenos"> 134</span></a><span class="sd"> Returns</span>
</span><span id="L-135"><a href="#L-135"><span class="linenos"> 135</span></a><span class="sd"> -------</span>
</span><span id="L-136"><a href="#L-136"><span class="linenos"> 136</span></a><span class="sd"> int</span>
</span><span id="L-137"><a href="#L-137"><span class="linenos"> 137</span></a><span class="sd"> A unique integer seed derived from the input parameters.</span>
</span><span id="L-138"><a href="#L-138"><span class="linenos"> 138</span></a>
</span><span id="L-139"><a href="#L-139"><span class="linenos"> 139</span></a><span class="sd"> Examples</span>
</span><span id="L-140"><a href="#L-140"><span class="linenos"> 140</span></a><span class="sd"> --------</span>
</span><span id="L-141"><a href="#L-141"><span class="linenos"> 141</span></a><span class="sd"> >>> params = {'learning_rate': 0.01, 'batch_size': 32}</span>
</span><span id="L-142"><a href="#L-142"><span class="linenos"> 142</span></a><span class="sd"> >>> generate_unique_seed(params, 1)</span>
</span><span id="L-143"><a href="#L-143"><span class="linenos"> 143</span></a><span class="sd"> 3432571217</span>
</span><span id="L-144"><a href="#L-144"><span class="linenos"> 144</span></a><span class="sd"> >>> generate_unique_seed(params, 2)</span>
</span><span id="L-145"><a href="#L-145"><span class="linenos"> 145</span></a><span class="sd"> 3960013583</span>
</span><span id="L-146"><a href="#L-146"><span class="linenos"> 146</span></a><span class="sd"> """</span>
</span><span id="L-147"><a href="#L-147"><span class="linenos"> 147</span></a> <span class="n">identifier</span> <span class="o">=</span> <span class="n">json</span><span class="o">.</span><span class="n">dumps</span><span class="p">(</span><span class="n">params</span><span class="p">,</span> <span class="n">sort_keys</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> <span class="o">+</span> <span class="sa">f</span><span class="s2">"_</span><span class="si">{</span><span class="n">rep</span><span class="si">}</span><span class="s2">"</span>
</span><span id="L-148"><a href="#L-148"><span class="linenos"> 148</span></a> <span class="k">return</span> <span class="nb">int</span><span class="p">(</span><span class="n">hashlib</span><span class="o">.</span><span class="n">sha256</span><span class="p">(</span><span class="n">identifier</span><span class="o">.</span><span class="n">encode</span><span class="p">())</span><span class="o">.</span><span class="n">hexdigest</span><span class="p">()[:</span><span class="mi">8</span><span class="p">],</span> <span class="mi">16</span><span class="p">)</span>
</span><span id="L-149"><a href="#L-149"><span class="linenos"> 149</span></a>
</span><span id="L-150"><a href="#L-150"><span class="linenos"> 150</span></a>
</span><span id="L-151"><a href="#L-151"><span class="linenos"> 151</span></a><span class="k">def</span><span class="w"> </span><span class="nf">count_populations</span><span class="p">(</span><span class="n">grid</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">)</span> <span class="o">-></span> <span class="n">Tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="nb">int</span><span class="p">,</span> <span class="nb">int</span><span class="p">]:</span>
</span><span id="L-152"><a href="#L-152"><span class="linenos"> 152</span></a><span class="w"> </span><span class="sd">"""</span>
</span><span id="L-153"><a href="#L-153"><span class="linenos"> 153</span></a><span class="sd"> Count the number of empty, prey, and predator cells in the simulation grid.</span>
</span><span id="L-154"><a href="#L-154"><span class="linenos"> 154</span></a>
</span><span id="L-155"><a href="#L-155"><span class="linenos"> 155</span></a><span class="sd"> Parameters</span>
</span><span id="L-156"><a href="#L-156"><span class="linenos"> 156</span></a><span class="sd"> ----------</span>
</span><span id="L-157"><a href="#L-157"><span class="linenos"> 157</span></a><span class="sd"> grid : np.ndarray</span>
</span><span id="L-158"><a href="#L-158"><span class="linenos"> 158</span></a><span class="sd"> A 2D NumPy array representing the simulation environment, where:</span>
</span><span id="L-159"><a href="#L-159"><span class="linenos"> 159</span></a><span class="sd"> - 0: Empty cell</span>
</span><span id="L-160"><a href="#L-160"><span class="linenos"> 160</span></a><span class="sd"> - 1: Prey</span>
</span><span id="L-161"><a href="#L-161"><span class="linenos"> 161</span></a><span class="sd"> - 2: Predator</span>
</span><span id="L-162"><a href="#L-162"><span class="linenos"> 162</span></a>
</span><span id="L-163"><a href="#L-163"><span class="linenos"> 163</span></a><span class="sd"> Returns</span>
</span><span id="L-164"><a href="#L-164"><span class="linenos"> 164</span></a><span class="sd"> -------</span>
</span><span id="L-165"><a href="#L-165"><span class="linenos"> 165</span></a><span class="sd"> empty_count : int</span>
</span><span id="L-166"><a href="#L-166"><span class="linenos"> 166</span></a><span class="sd"> Total number of cells with a value of 0.</span>
</span><span id="L-167"><a href="#L-167"><span class="linenos"> 167</span></a><span class="sd"> prey_count : int</span>
</span><span id="L-168"><a href="#L-168"><span class="linenos"> 168</span></a><span class="sd"> Total number of cells with a value of 1.</span>
</span><span id="L-169"><a href="#L-169"><span class="linenos"> 169</span></a><span class="sd"> predator_count : int</span>
</span><span id="L-170"><a href="#L-170"><span class="linenos"> 170</span></a><span class="sd"> Total number of cells with a value of 2.</span>
</span><span id="L-171"><a href="#L-171"><span class="linenos"> 171</span></a>
</span><span id="L-172"><a href="#L-172"><span class="linenos"> 172</span></a><span class="sd"> Examples</span>
</span><span id="L-173"><a href="#L-173"><span class="linenos"> 173</span></a><span class="sd"> --------</span>
</span><span id="L-174"><a href="#L-174"><span class="linenos"> 174</span></a><span class="sd"> >>> grid = np.array([[0, 1], [2, 1]])</span>
</span><span id="L-175"><a href="#L-175"><span class="linenos"> 175</span></a><span class="sd"> >>> count_populations(grid)</span>
</span><span id="L-176"><a href="#L-176"><span class="linenos"> 176</span></a><span class="sd"> (1, 2, 1)</span>
</span><span id="L-177"><a href="#L-177"><span class="linenos"> 177</span></a><span class="sd"> """</span>
</span><span id="L-178"><a href="#L-178"><span class="linenos"> 178</span></a> <span class="k">return</span> <span class="nb">int</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">grid</span> <span class="o">==</span> <span class="mi">0</span><span class="p">)),</span> <span class="nb">int</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">grid</span> <span class="o">==</span> <span class="mi">1</span><span class="p">)),</span> <span class="nb">int</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">grid</span> <span class="o">==</span> <span class="mi">2</span><span class="p">))</span>
</span><span id="L-179"><a href="#L-179"><span class="linenos"> 179</span></a>
</span><span id="L-180"><a href="#L-180"><span class="linenos"> 180</span></a>
</span><span id="L-181"><a href="#L-181"><span class="linenos"> 181</span></a><span class="k">def</span><span class="w"> </span><span class="nf">get_evolved_stats</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">param</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-></span> <span class="n">Dict</span><span class="p">:</span>
</span><span id="L-182"><a href="#L-182"><span class="linenos"> 182</span></a><span class="w"> </span><span class="sd">"""</span>
</span><span id="L-183"><a href="#L-183"><span class="linenos"> 183</span></a><span class="sd"> Get statistics of an evolved parameter from the model.</span>
</span><span id="L-184"><a href="#L-184"><span class="linenos"> 184</span></a>
</span><span id="L-185"><a href="#L-185"><span class="linenos"> 185</span></a><span class="sd"> This function retrieves parameter values from the model's internal storage,</span>
</span><span id="L-186"><a href="#L-186"><span class="linenos"> 186</span></a><span class="sd"> filters out NaN values, and calculates basic descriptive statistics.</span>
</span><span id="L-187"><a href="#L-187"><span class="linenos"> 187</span></a>
</span><span id="L-188"><a href="#L-188"><span class="linenos"> 188</span></a><span class="sd"> Parameters</span>
</span><span id="L-189"><a href="#L-189"><span class="linenos"> 189</span></a><span class="sd"> ----------</span>
</span><span id="L-190"><a href="#L-190"><span class="linenos"> 190</span></a><span class="sd"> model : object</span>
</span><span id="L-191"><a href="#L-191"><span class="linenos"> 191</span></a><span class="sd"> The simulation model instance containing a `cell_params` attribute</span>
</span><span id="L-192"><a href="#L-192"><span class="linenos"> 192</span></a><span class="sd"> with a `.get()` method.</span>
</span><span id="L-193"><a href="#L-193"><span class="linenos"> 193</span></a><span class="sd"> param : str</span>
</span><span id="L-194"><a href="#L-194"><span class="linenos"> 194</span></a><span class="sd"> The name of the parameter to calculate statistics for.</span>
</span><span id="L-195"><a href="#L-195"><span class="linenos"> 195</span></a>
</span><span id="L-196"><a href="#L-196"><span class="linenos"> 196</span></a><span class="sd"> Returns</span>
</span><span id="L-197"><a href="#L-197"><span class="linenos"> 197</span></a><span class="sd"> -------</span>
</span><span id="L-198"><a href="#L-198"><span class="linenos"> 198</span></a><span class="sd"> stats : dict</span>
</span><span id="L-199"><a href="#L-199"><span class="linenos"> 199</span></a><span class="sd"> A dictionary containing the following keys:</span>
</span><span id="L-200"><a href="#L-200"><span class="linenos"> 200</span></a><span class="sd"> - 'mean': Arithmetic mean of valid values.</span>
</span><span id="L-201"><a href="#L-201"><span class="linenos"> 201</span></a><span class="sd"> - 'std': Standard deviation of valid values.</span>
</span><span id="L-202"><a href="#L-202"><span class="linenos"> 202</span></a><span class="sd"> - 'min': Minimum valid value.</span>
</span><span id="L-203"><a href="#L-203"><span class="linenos"> 203</span></a><span class="sd"> - 'max': Maximum valid value.</span>
</span><span id="L-204"><a href="#L-204"><span class="linenos"> 204</span></a><span class="sd"> - 'n': Count of non-NaN values.</span>
</span><span id="L-205"><a href="#L-205"><span class="linenos"> 205</span></a><span class="sd"> If no valid data is found, all stats return NaN and n returns 0.</span>
</span><span id="L-206"><a href="#L-206"><span class="linenos"> 206</span></a>
</span><span id="L-207"><a href="#L-207"><span class="linenos"> 207</span></a><span class="sd"> Examples</span>
</span><span id="L-208"><a href="#L-208"><span class="linenos"> 208</span></a><span class="sd"> --------</span>
</span><span id="L-209"><a href="#L-209"><span class="linenos"> 209</span></a><span class="sd"> >>> stats = get_evolved_stats(my_model, "speed")</span>
</span><span id="L-210"><a href="#L-210"><span class="linenos"> 210</span></a><span class="sd"> >>> print(stats['mean'])</span>
</span><span id="L-211"><a href="#L-211"><span class="linenos"> 211</span></a><span class="sd"> 1.25</span>
</span><span id="L-212"><a href="#L-212"><span class="linenos"> 212</span></a><span class="sd"> """</span>
</span><span id="L-213"><a href="#L-213"><span class="linenos"> 213</span></a> <span class="n">arr</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">cell_params</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">param</span><span class="p">)</span>
</span><span id="L-214"><a href="#L-214"><span class="linenos"> 214</span></a> <span class="k">if</span> <span class="n">arr</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
</span><span id="L-215"><a href="#L-215"><span class="linenos"> 215</span></a> <span class="k">return</span> <span class="p">{</span><span class="s2">"mean"</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span><span class="p">,</span> <span class="s2">"std"</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span><span class="p">,</span> <span class="s2">"min"</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span><span class="p">,</span> <span class="s2">"max"</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span><span class="p">,</span> <span class="s2">"n"</span><span class="p">:</span> <span class="mi">0</span><span class="p">}</span>
</span><span id="L-216"><a href="#L-216"><span class="linenos"> 216</span></a> <span class="n">valid</span> <span class="o">=</span> <span class="n">arr</span><span class="p">[</span><span class="o">~</span><span class="n">np</span><span class="o">.</span><span class="n">isnan</span><span class="p">(</span><span class="n">arr</span><span class="p">)]</span>
</span><span id="L-217"><a href="#L-217"><span class="linenos"> 217</span></a> <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">valid</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
</span><span id="L-218"><a href="#L-218"><span class="linenos"> 218</span></a> <span class="k">return</span> <span class="p">{</span><span class="s2">"mean"</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span><span class="p">,</span> <span class="s2">"std"</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span><span class="p">,</span> <span class="s2">"min"</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span><span class="p">,</span> <span class="s2">"max"</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span><span class="p">,</span> <span class="s2">"n"</span><span class="p">:</span> <span class="mi">0</span><span class="p">}</span>
</span><span id="L-219"><a href="#L-219"><span class="linenos"> 219</span></a> <span class="k">return</span> <span class="p">{</span>
</span><span id="L-220"><a href="#L-220"><span class="linenos"> 220</span></a> <span class="s2">"mean"</span><span class="p">:</span> <span class="nb">float</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">valid</span><span class="p">)),</span>
</span><span id="L-221"><a href="#L-221"><span class="linenos"> 221</span></a> <span class="s2">"std"</span><span class="p">:</span> <span class="nb">float</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">std</span><span class="p">(</span><span class="n">valid</span><span class="p">)),</span>
</span><span id="L-222"><a href="#L-222"><span class="linenos"> 222</span></a> <span class="s2">"min"</span><span class="p">:</span> <span class="nb">float</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">min</span><span class="p">(</span><span class="n">valid</span><span class="p">)),</span>
</span><span id="L-223"><a href="#L-223"><span class="linenos"> 223</span></a> <span class="s2">"max"</span><span class="p">:</span> <span class="nb">float</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">max</span><span class="p">(</span><span class="n">valid</span><span class="p">)),</span>
</span><span id="L-224"><a href="#L-224"><span class="linenos"> 224</span></a> <span class="s2">"n"</span><span class="p">:</span> <span class="nb">len</span><span class="p">(</span><span class="n">valid</span><span class="p">),</span>
</span><span id="L-225"><a href="#L-225"><span class="linenos"> 225</span></a> <span class="p">}</span>
</span><span id="L-226"><a href="#L-226"><span class="linenos"> 226</span></a>
</span><span id="L-227"><a href="#L-227"><span class="linenos"> 227</span></a>
</span><span id="L-228"><a href="#L-228"><span class="linenos"> 228</span></a><span class="k">def</span><span class="w"> </span><span class="nf">average_pcfs</span><span class="p">(</span>
</span><span id="L-229"><a href="#L-229"><span class="linenos"> 229</span></a> <span class="n">pcf_list</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="n">Tuple</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="nb">int</span><span class="p">]],</span>
</span><span id="L-230"><a href="#L-230"><span class="linenos"> 230</span></a><span class="p">)</span> <span class="o">-></span> <span class="n">Tuple</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">]:</span>
</span><span id="L-231"><a href="#L-231"><span class="linenos"> 231</span></a><span class="w"> </span><span class="sd">"""</span>
</span><span id="L-232"><a href="#L-232"><span class="linenos"> 232</span></a><span class="sd"> Average multiple Pair Correlation Function (PCF) measurements and calculate standard error.</span>
</span><span id="L-233"><a href="#L-233"><span class="linenos"> 233</span></a>
</span><span id="L-234"><a href="#L-234"><span class="linenos"> 234</span></a><span class="sd"> Parameters</span>
</span><span id="L-235"><a href="#L-235"><span class="linenos"> 235</span></a><span class="sd"> ----------</span>
</span><span id="L-236"><a href="#L-236"><span class="linenos"> 236</span></a><span class="sd"> pcf_list : list of tuple</span>
</span><span id="L-237"><a href="#L-237"><span class="linenos"> 237</span></a><span class="sd"> A list where each element is a tuple containing:</span>
</span><span id="L-238"><a href="#L-238"><span class="linenos"> 238</span></a><span class="sd"> - distances (np.ndarray): The radial distances (r).</span>
</span><span id="L-239"><a href="#L-239"><span class="linenos"> 239</span></a><span class="sd"> - pcf_values (np.ndarray): The correlation values g(r).</span>
</span><span id="L-240"><a href="#L-240"><span class="linenos"> 240</span></a><span class="sd"> - count (int): Metadata or weight (not used in current calculation).</span>
</span><span id="L-241"><a href="#L-241"><span class="linenos"> 241</span></a>
</span><span id="L-242"><a href="#L-242"><span class="linenos"> 242</span></a><span class="sd"> Returns</span>
</span><span id="L-243"><a href="#L-243"><span class="linenos"> 243</span></a><span class="sd"> -------</span>
</span><span id="L-244"><a href="#L-244"><span class="linenos"> 244</span></a><span class="sd"> distances : np.ndarray</span>
</span><span id="L-245"><a href="#L-245"><span class="linenos"> 245</span></a><span class="sd"> The radial distances from the first entry in the list.</span>
</span><span id="L-246"><a href="#L-246"><span class="linenos"> 246</span></a><span class="sd"> pcf_mean : np.ndarray</span>
</span><span id="L-247"><a href="#L-247"><span class="linenos"> 247</span></a><span class="sd"> The element-wise mean of the PCF values across all measurements.</span>
</span><span id="L-248"><a href="#L-248"><span class="linenos"> 248</span></a><span class="sd"> pcf_se : np.ndarray</span>
</span><span id="L-249"><a href="#L-249"><span class="linenos"> 249</span></a><span class="sd"> The standard error of the mean for the PCF values.</span>
</span><span id="L-250"><a href="#L-250"><span class="linenos"> 250</span></a>
</span><span id="L-251"><a href="#L-251"><span class="linenos"> 251</span></a><span class="sd"> Examples</span>
</span><span id="L-252"><a href="#L-252"><span class="linenos"> 252</span></a><span class="sd"> --------</span>
</span><span id="L-253"><a href="#L-253"><span class="linenos"> 253</span></a><span class="sd"> >>> data = [(np.array([0, 1]), np.array([1.0, 2.0]), 10),</span>
</span><span id="L-254"><a href="#L-254"><span class="linenos"> 254</span></a><span class="sd"> ... (np.array([0, 1]), np.array([1.2, 1.8]), 12)]</span>
</span><span id="L-255"><a href="#L-255"><span class="linenos"> 255</span></a><span class="sd"> >>> dist, mean, se = average_pcfs(data)</span>
</span><span id="L-256"><a href="#L-256"><span class="linenos"> 256</span></a><span class="sd"> >>> mean</span>
</span><span id="L-257"><a href="#L-257"><span class="linenos"> 257</span></a><span class="sd"> array([1.1, 1.9])</span>
</span><span id="L-258"><a href="#L-258"><span class="linenos"> 258</span></a><span class="sd"> """</span>
</span><span id="L-259"><a href="#L-259"><span class="linenos"> 259</span></a> <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">pcf_list</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
</span><span id="L-260"><a href="#L-260"><span class="linenos"> 260</span></a> <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([]),</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([]),</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([])</span>
</span><span id="L-261"><a href="#L-261"><span class="linenos"> 261</span></a>
</span><span id="L-262"><a href="#L-262"><span class="linenos"> 262</span></a> <span class="n">distances</span> <span class="o">=</span> <span class="n">pcf_list</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
</span><span id="L-263"><a href="#L-263"><span class="linenos"> 263</span></a> <span class="n">pcfs</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">p</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">pcf_list</span><span class="p">])</span>
</span><span id="L-264"><a href="#L-264"><span class="linenos"> 264</span></a>
</span><span id="L-265"><a href="#L-265"><span class="linenos"> 265</span></a> <span class="n">pcf_mean</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">pcfs</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
</span><span id="L-266"><a href="#L-266"><span class="linenos"> 266</span></a> <span class="n">pcf_se</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">std</span><span class="p">(</span><span class="n">pcfs</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span> <span class="o">/</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">pcfs</span><span class="p">))</span>
</span><span id="L-267"><a href="#L-267"><span class="linenos"> 267</span></a>
</span><span id="L-268"><a href="#L-268"><span class="linenos"> 268</span></a> <span class="k">return</span> <span class="n">distances</span><span class="p">,</span> <span class="n">pcf_mean</span><span class="p">,</span> <span class="n">pcf_se</span>
</span><span id="L-269"><a href="#L-269"><span class="linenos"> 269</span></a>
</span><span id="L-270"><a href="#L-270"><span class="linenos"> 270</span></a>
</span><span id="L-271"><a href="#L-271"><span class="linenos"> 271</span></a><span class="k">def</span><span class="w"> </span><span class="nf">save_results_jsonl</span><span class="p">(</span><span class="n">results</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="n">Dict</span><span class="p">],</span> <span class="n">output_path</span><span class="p">:</span> <span class="n">Path</span><span class="p">):</span>
</span><span id="L-272"><a href="#L-272"><span class="linenos"> 272</span></a><span class="w"> </span><span class="sd">"""</span>
</span><span id="L-273"><a href="#L-273"><span class="linenos"> 273</span></a><span class="sd"> Save a list of dictionaries to a file in JSON Lines (JSONL) format.</span>
</span><span id="L-274"><a href="#L-274"><span class="linenos"> 274</span></a>
</span><span id="L-275"><a href="#L-275"><span class="linenos"> 275</span></a><span class="sd"> Each dictionary in the list is serialized into a single JSON string and</span>
</span><span id="L-276"><a href="#L-276"><span class="linenos"> 276</span></a><span class="sd"> written as a new line. Non-serializable objects are converted to strings</span>
</span><span id="L-277"><a href="#L-277"><span class="linenos"> 277</span></a><span class="sd"> using the default string representation.</span>
</span><span id="L-278"><a href="#L-278"><span class="linenos"> 278</span></a>
</span><span id="L-279"><a href="#L-279"><span class="linenos"> 279</span></a><span class="sd"> Parameters</span>
</span><span id="L-280"><a href="#L-280"><span class="linenos"> 280</span></a><span class="sd"> ----------</span>
</span><span id="L-281"><a href="#L-281"><span class="linenos"> 281</span></a><span class="sd"> results : list of dict</span>
</span><span id="L-282"><a href="#L-282"><span class="linenos"> 282</span></a><span class="sd"> The collection of result dictionaries to be saved.</span>
</span><span id="L-283"><a href="#L-283"><span class="linenos"> 283</span></a><span class="sd"> output_path : Path</span>
</span><span id="L-284"><a href="#L-284"><span class="linenos"> 284</span></a><span class="sd"> The file system path (pathlib.Path) where the JSONL file will be created.</span>
</span><span id="L-285"><a href="#L-285"><span class="linenos"> 285</span></a>
</span><span id="L-286"><a href="#L-286"><span class="linenos"> 286</span></a><span class="sd"> Returns</span>
</span><span id="L-287"><a href="#L-287"><span class="linenos"> 287</span></a><span class="sd"> -------</span>
</span><span id="L-288"><a href="#L-288"><span class="linenos"> 288</span></a><span class="sd"> None</span>
</span><span id="L-289"><a href="#L-289"><span class="linenos"> 289</span></a>
</span><span id="L-290"><a href="#L-290"><span class="linenos"> 290</span></a><span class="sd"> Notes</span>
</span><span id="L-291"><a href="#L-291"><span class="linenos"> 291</span></a><span class="sd"> -----</span>
</span><span id="L-292"><a href="#L-292"><span class="linenos"> 292</span></a><span class="sd"> The file is opened in 'w' (write) mode, which will overwrite any existing</span>
</span><span id="L-293"><a href="#L-293"><span class="linenos"> 293</span></a><span class="sd"> content at the specified path.</span>
</span><span id="L-294"><a href="#L-294"><span class="linenos"> 294</span></a>
</span><span id="L-295"><a href="#L-295"><span class="linenos"> 295</span></a><span class="sd"> Examples</span>
</span><span id="L-296"><a href="#L-296"><span class="linenos"> 296</span></a><span class="sd"> --------</span>
</span><span id="L-297"><a href="#L-297"><span class="linenos"> 297</span></a><span class="sd"> >>> data = [{"id": 1, "score": 0.95}, {"id": 2, "score": 0.88}]</span>
</span><span id="L-298"><a href="#L-298"><span class="linenos"> 298</span></a><span class="sd"> >>> save_results_jsonl(data, Path("results.jsonl"))</span>
</span><span id="L-299"><a href="#L-299"><span class="linenos"> 299</span></a><span class="sd"> """</span>
</span><span id="L-300"><a href="#L-300"><span class="linenos"> 300</span></a> <span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">output_path</span><span class="p">,</span> <span class="s2">"w"</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="s2">"utf-8"</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
</span><span id="L-301"><a href="#L-301"><span class="linenos"> 301</span></a> <span class="k">for</span> <span class="n">result</span> <span class="ow">in</span> <span class="n">results</span><span class="p">:</span>
</span><span id="L-302"><a href="#L-302"><span class="linenos"> 302</span></a> <span class="n">f</span><span class="o">.</span><span class="n">write</span><span class="p">(</span><span class="n">json</span><span class="o">.</span><span class="n">dumps</span><span class="p">(</span><span class="n">result</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="nb">str</span><span class="p">)</span> <span class="o">+</span> <span class="s2">"</span><span class="se">\n</span><span class="s2">"</span><span class="p">)</span>
</span><span id="L-303"><a href="#L-303"><span class="linenos"> 303</span></a>
</span><span id="L-304"><a href="#L-304"><span class="linenos"> 304</span></a>
</span><span id="L-305"><a href="#L-305"><span class="linenos"> 305</span></a><span class="k">def</span><span class="w"> </span><span class="nf">save_results_npz</span><span class="p">(</span><span class="n">results</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="n">Dict</span><span class="p">],</span> <span class="n">output_path</span><span class="p">:</span> <span class="n">Path</span><span class="p">):</span>
</span><span id="L-306"><a href="#L-306"><span class="linenos"> 306</span></a><span class="w"> </span><span class="sd">"""</span>
</span><span id="L-307"><a href="#L-307"><span class="linenos"> 307</span></a><span class="sd"> Save simulation results to a compressed NumPy (.npz) binary file.</span>
</span><span id="L-308"><a href="#L-308"><span class="linenos"> 308</span></a>
</span><span id="L-309"><a href="#L-309"><span class="linenos"> 309</span></a><span class="sd"> This function flattens a list of result dictionaries into a single</span>
</span><span id="L-310"><a href="#L-310"><span class="linenos"> 310</span></a><span class="sd"> dictionary of NumPy arrays, prefixing keys with the run index to</span>
</span><span id="L-311"><a href="#L-311"><span class="linenos"> 311</span></a><span class="sd"> maintain data separation. The resulting file is compressed to</span>
</span><span id="L-312"><a href="#L-312"><span class="linenos"> 312</span></a><span class="sd"> reduce storage space.</span>
</span><span id="L-313"><a href="#L-313"><span class="linenos"> 313</span></a>
</span><span id="L-314"><a href="#L-314"><span class="linenos"> 314</span></a><span class="sd"> Parameters</span>
</span><span id="L-315"><a href="#L-315"><span class="linenos"> 315</span></a><span class="sd"> ----------</span>
</span><span id="L-316"><a href="#L-316"><span class="linenos"> 316</span></a><span class="sd"> results : list of dict</span>
</span><span id="L-317"><a href="#L-317"><span class="linenos"> 317</span></a><span class="sd"> A list where each dictionary contains key-value pairs of</span>
</span><span id="L-318"><a href="#L-318"><span class="linenos"> 318</span></a><span class="sd"> simulation data (e.g., arrays, lists, or scalars).</span>
</span><span id="L-319"><a href="#L-319"><span class="linenos"> 319</span></a><span class="sd"> output_path : Path</span>
</span><span id="L-320"><a href="#L-320"><span class="linenos"> 320</span></a><span class="sd"> The file system path (pathlib.Path) where the compressed</span>
</span><span id="L-321"><a href="#L-321"><span class="linenos"> 321</span></a><span class="sd"> NPZ file will be saved.</span>
</span><span id="L-322"><a href="#L-322"><span class="linenos"> 322</span></a>
</span><span id="L-323"><a href="#L-323"><span class="linenos"> 323</span></a><span class="sd"> Returns</span>
</span><span id="L-324"><a href="#L-324"><span class="linenos"> 324</span></a><span class="sd"> -------</span>
</span><span id="L-325"><a href="#L-325"><span class="linenos"> 325</span></a><span class="sd"> None</span>
</span><span id="L-326"><a href="#L-326"><span class="linenos"> 326</span></a>
</span><span id="L-327"><a href="#L-327"><span class="linenos"> 327</span></a><span class="sd"> Notes</span>
</span><span id="L-328"><a href="#L-328"><span class="linenos"> 328</span></a><span class="sd"> -----</span>
</span><span id="L-329"><a href="#L-329"><span class="linenos"> 329</span></a><span class="sd"> The keys in the saved file follow the format 'run_{index}_{original_key}'.</span>
</span><span id="L-330"><a href="#L-330"><span class="linenos"> 330</span></a><span class="sd"> Values are automatically converted to NumPy arrays if they are not</span>
</span><span id="L-331"><a href="#L-331"><span class="linenos"> 331</span></a><span class="sd"> already.</span>
</span><span id="L-332"><a href="#L-332"><span class="linenos"> 332</span></a>
</span><span id="L-333"><a href="#L-333"><span class="linenos"> 333</span></a><span class="sd"> Examples</span>
</span><span id="L-334"><a href="#L-334"><span class="linenos"> 334</span></a><span class="sd"> --------</span>
</span><span id="L-335"><a href="#L-335"><span class="linenos"> 335</span></a><span class="sd"> >>> results = [{"energy": [1, 2]}, {"energy": [3, 4]}]</span>
</span><span id="L-336"><a href="#L-336"><span class="linenos"> 336</span></a><span class="sd"> >>> save_results_npz(results, Path("output.npz"))</span>
</span><span id="L-337"><a href="#L-337"><span class="linenos"> 337</span></a><span class="sd"> """</span>
</span><span id="L-338"><a href="#L-338"><span class="linenos"> 338</span></a> <span class="n">data</span> <span class="o">=</span> <span class="p">{}</span>
</span><span id="L-339"><a href="#L-339"><span class="linenos"> 339</span></a> <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">res</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">results</span><span class="p">):</span>
</span><span id="L-340"><a href="#L-340"><span class="linenos"> 340</span></a> <span class="k">for</span> <span class="n">key</span><span class="p">,</span> <span class="n">val</span> <span class="ow">in</span> <span class="n">res</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
</span><span id="L-341"><a href="#L-341"><span class="linenos"> 341</span></a> <span class="n">data</span><span class="p">[</span><span class="sa">f</span><span class="s2">"run_</span><span class="si">{</span><span class="n">i</span><span class="si">}</span><span class="s2">_</span><span class="si">{</span><span class="n">key</span><span class="si">}</span><span class="s2">"</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">val</span><span class="p">)</span>
</span><span id="L-342"><a href="#L-342"><span class="linenos"> 342</span></a> <span class="n">np</span><span class="o">.</span><span class="n">savez_compressed</span><span class="p">(</span><span class="n">output_path</span><span class="p">,</span> <span class="o">**</span><span class="n">data</span><span class="p">)</span>
</span><span id="L-343"><a href="#L-343"><span class="linenos"> 343</span></a>
</span><span id="L-344"><a href="#L-344"><span class="linenos"> 344</span></a>
</span><span id="L-345"><a href="#L-345"><span class="linenos"> 345</span></a><span class="k">def</span><span class="w"> </span><span class="nf">load_results_jsonl</span><span class="p">(</span><span class="n">input_path</span><span class="p">:</span> <span class="n">Path</span><span class="p">)</span> <span class="o">-></span> <span class="n">List</span><span class="p">[</span><span class="n">Dict</span><span class="p">]:</span>
</span><span id="L-346"><a href="#L-346"><span class="linenos"> 346</span></a><span class="w"> </span><span class="sd">"""</span>
</span><span id="L-347"><a href="#L-347"><span class="linenos"> 347</span></a><span class="sd"> Load simulation results from a JSON Lines (JSONL) formatted file.</span>
</span><span id="L-348"><a href="#L-348"><span class="linenos"> 348</span></a>
</span><span id="L-349"><a href="#L-349"><span class="linenos"> 349</span></a><span class="sd"> This function reads a file line-by-line, parsing each line as an</span>
</span><span id="L-350"><a href="#L-350"><span class="linenos"> 350</span></a><span class="sd"> independent JSON object and aggregating them into a list of dictionaries.</span>
</span><span id="L-351"><a href="#L-351"><span class="linenos"> 351</span></a>
</span><span id="L-352"><a href="#L-352"><span class="linenos"> 352</span></a><span class="sd"> Parameters</span>
</span><span id="L-353"><a href="#L-353"><span class="linenos"> 353</span></a><span class="sd"> ----------</span>
</span><span id="L-354"><a href="#L-354"><span class="linenos"> 354</span></a><span class="sd"> input_path : Path</span>
</span><span id="L-355"><a href="#L-355"><span class="linenos"> 355</span></a><span class="sd"> The file system path (pathlib.Path) to the JSONL file.</span>
</span><span id="L-356"><a href="#L-356"><span class="linenos"> 356</span></a>
</span><span id="L-357"><a href="#L-357"><span class="linenos"> 357</span></a><span class="sd"> Returns</span>
</span><span id="L-358"><a href="#L-358"><span class="linenos"> 358</span></a><span class="sd"> -------</span>
</span><span id="L-359"><a href="#L-359"><span class="linenos"> 359</span></a><span class="sd"> results : list of dict</span>
</span><span id="L-360"><a href="#L-360"><span class="linenos"> 360</span></a><span class="sd"> A list of dictionaries reconstructed from the file content.</span>
</span><span id="L-361"><a href="#L-361"><span class="linenos"> 361</span></a>
</span><span id="L-362"><a href="#L-362"><span class="linenos"> 362</span></a><span class="sd"> Raises</span>
</span><span id="L-363"><a href="#L-363"><span class="linenos"> 363</span></a><span class="sd"> ------</span>
</span><span id="L-364"><a href="#L-364"><span class="linenos"> 364</span></a><span class="sd"> FileNotFoundError</span>
</span><span id="L-365"><a href="#L-365"><span class="linenos"> 365</span></a><span class="sd"> If the specified input path does not exist.</span>
</span><span id="L-366"><a href="#L-366"><span class="linenos"> 366</span></a><span class="sd"> json.JSONDecodeError</span>
</span><span id="L-367"><a href="#L-367"><span class="linenos"> 367</span></a><span class="sd"> If a line in the file is not valid JSON.</span>
</span><span id="L-368"><a href="#L-368"><span class="linenos"> 368</span></a>
</span><span id="L-369"><a href="#L-369"><span class="linenos"> 369</span></a><span class="sd"> Examples</span>
</span><span id="L-370"><a href="#L-370"><span class="linenos"> 370</span></a><span class="sd"> --------</span>
</span><span id="L-371"><a href="#L-371"><span class="linenos"> 371</span></a><span class="sd"> >>> data = load_results_jsonl(Path("results.jsonl"))</span>
</span><span id="L-372"><a href="#L-372"><span class="linenos"> 372</span></a><span class="sd"> >>> len(data)</span>
</span><span id="L-373"><a href="#L-373"><span class="linenos"> 373</span></a><span class="sd"> 2</span>
</span><span id="L-374"><a href="#L-374"><span class="linenos"> 374</span></a><span class="sd"> """</span>
</span><span id="L-375"><a href="#L-375"><span class="linenos"> 375</span></a> <span class="n">results</span> <span class="o">=</span> <span class="p">[]</span>
</span><span id="L-376"><a href="#L-376"><span class="linenos"> 376</span></a> <span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">input_path</span><span class="p">,</span> <span class="s2">"r"</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="s2">"utf-8"</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
</span><span id="L-377"><a href="#L-377"><span class="linenos"> 377</span></a> <span class="k">for</span> <span class="n">line</span> <span class="ow">in</span> <span class="n">f</span><span class="p">:</span>
</span><span id="L-378"><a href="#L-378"><span class="linenos"> 378</span></a> <span class="n">results</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">json</span><span class="o">.</span><span class="n">loads</span><span class="p">(</span><span class="n">line</span><span class="o">.</span><span class="n">strip</span><span class="p">()))</span>
</span><span id="L-379"><a href="#L-379"><span class="linenos"> 379</span></a> <span class="k">return</span> <span class="n">results</span>
</span><span id="L-380"><a href="#L-380"><span class="linenos"> 380</span></a>
</span><span id="L-381"><a href="#L-381"><span class="linenos"> 381</span></a>
</span><span id="L-382"><a href="#L-382"><span class="linenos"> 382</span></a><span class="c1"># =============================================================================</span>
</span><span id="L-383"><a href="#L-383"><span class="linenos"> 383</span></a><span class="c1"># Simulation Functionality</span>
</span><span id="L-384"><a href="#L-384"><span class="linenos"> 384</span></a><span class="c1"># =============================================================================</span>
</span><span id="L-385"><a href="#L-385"><span class="linenos"> 385</span></a>
</span><span id="L-386"><a href="#L-386"><span class="linenos"> 386</span></a>
</span><span id="L-387"><a href="#L-387"><span class="linenos"> 387</span></a><span class="k">def</span><span class="w"> </span><span class="nf">run_single_simulation</span><span class="p">(</span>
</span><span id="L-388"><a href="#L-388"><span class="linenos"> 388</span></a> <span class="n">prey_birth</span><span class="p">:</span> <span class="nb">float</span><span class="p">,</span>
</span><span id="L-389"><a href="#L-389"><span class="linenos"> 389</span></a> <span class="n">prey_death</span><span class="p">:</span> <span class="nb">float</span><span class="p">,</span>
</span><span id="L-390"><a href="#L-390"><span class="linenos"> 390</span></a> <span class="n">predator_birth</span><span class="p">:</span> <span class="nb">float</span><span class="p">,</span>
</span><span id="L-391"><a href="#L-391"><span class="linenos"> 391</span></a> <span class="n">predator_death</span><span class="p">:</span> <span class="nb">float</span><span class="p">,</span>
</span><span id="L-392"><a href="#L-392"><span class="linenos"> 392</span></a> <span class="n">grid_size</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
</span><span id="L-393"><a href="#L-393"><span class="linenos"> 393</span></a> <span class="n">seed</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
</span><span id="L-394"><a href="#L-394"><span class="linenos"> 394</span></a> <span class="n">cfg</span><span class="p">:</span> <span class="n">Config</span><span class="p">,</span>
</span><span id="L-395"><a href="#L-395"><span class="linenos"> 395</span></a> <span class="n">with_evolution</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
</span><span id="L-396"><a href="#L-396"><span class="linenos"> 396</span></a> <span class="n">compute_pcf</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
</span><span id="L-397"><a href="#L-397"><span class="linenos"> 397</span></a><span class="p">)</span> <span class="o">-></span> <span class="n">Dict</span><span class="p">:</span>
</span><span id="L-398"><a href="#L-398"><span class="linenos"> 398</span></a><span class="w"> </span><span class="sd">"""</span>
</span><span id="L-399"><a href="#L-399"><span class="linenos"> 399</span></a><span class="sd"> Run a single Predator-Prey (PP) simulation and collect comprehensive metrics.</span>
</span><span id="L-400"><a href="#L-400"><span class="linenos"> 400</span></a>
</span><span id="L-401"><a href="#L-401"><span class="linenos"> 401</span></a><span class="sd"> This function initializes a Cellular Automata model, executes a warmup phase</span>
</span><span id="L-402"><a href="#L-402"><span class="linenos"> 402</span></a><span class="sd"> to reach steady state, and then performs a measurement phase to track</span>
</span><span id="L-403"><a href="#L-403"><span class="linenos"> 403</span></a><span class="sd"> population dynamics, spatial clustering, and evolutionary changes.</span>
</span><span id="L-404"><a href="#L-404"><span class="linenos"> 404</span></a>
</span><span id="L-405"><a href="#L-405"><span class="linenos"> 405</span></a><span class="sd"> Parameters</span>
</span><span id="L-406"><a href="#L-406"><span class="linenos"> 406</span></a><span class="sd"> ----------</span>
</span><span id="L-407"><a href="#L-407"><span class="linenos"> 407</span></a><span class="sd"> prey_birth : float</span>
</span><span id="L-408"><a href="#L-408"><span class="linenos"> 408</span></a><span class="sd"> The probability or rate of prey reproduction.</span>
</span><span id="L-409"><a href="#L-409"><span class="linenos"> 409</span></a><span class="sd"> prey_death : float</span>
</span><span id="L-410"><a href="#L-410"><span class="linenos"> 410</span></a><span class="sd"> The base probability or rate of prey mortality.</span>
</span><span id="L-411"><a href="#L-411"><span class="linenos"> 411</span></a><span class="sd"> predator_birth : float</span>
</span><span id="L-412"><a href="#L-412"><span class="linenos"> 412</span></a><span class="sd"> The probability or rate of predator reproduction upon consuming prey.</span>
</span><span id="L-413"><a href="#L-413"><span class="linenos"> 413</span></a><span class="sd"> predator_death : float</span>
</span><span id="L-414"><a href="#L-414"><span class="linenos"> 414</span></a><span class="sd"> The probability or rate of predator mortality.</span>
</span><span id="L-415"><a href="#L-415"><span class="linenos"> 415</span></a><span class="sd"> grid_size : int</span>
</span><span id="L-416"><a href="#L-416"><span class="linenos"> 416</span></a><span class="sd"> The side length of the square simulation grid.</span>
</span><span id="L-417"><a href="#L-417"><span class="linenos"> 417</span></a><span class="sd"> seed : int</span>
</span><span id="L-418"><a href="#L-418"><span class="linenos"> 418</span></a><span class="sd"> Random seed for ensuring reproducibility of the simulation run.</span>
</span><span id="L-419"><a href="#L-419"><span class="linenos"> 419</span></a><span class="sd"> cfg : Config</span>
</span><span id="L-420"><a href="#L-420"><span class="linenos"> 420</span></a><span class="sd"> A configuration object containing simulation hyperparameters (densities,</span>
</span><span id="L-421"><a href="#L-421"><span class="linenos"> 421</span></a><span class="sd"> sampling rates, timing, etc.).</span>
</span><span id="L-422"><a href="#L-422"><span class="linenos"> 422</span></a><span class="sd"> with_evolution : bool, optional</span>
</span><span id="L-423"><a href="#L-423"><span class="linenos"> 423</span></a><span class="sd"> If True, enables the evolution of the 'prey_death' parameter within</span>
</span><span id="L-424"><a href="#L-424"><span class="linenos"> 424</span></a><span class="sd"> the model (default is False).</span>
</span><span id="L-425"><a href="#L-425"><span class="linenos"> 425</span></a><span class="sd"> compute_pcf : bool, optional</span>
</span><span id="L-426"><a href="#L-426"><span class="linenos"> 426</span></a><span class="sd"> Explicit toggle for Pair Correlation Function calculation. If None,</span>
</span><span id="L-427"><a href="#L-427"><span class="linenos"> 427</span></a><span class="sd"> it is determined by `cfg.pcf_sample_rate` (default is None).</span>
</span><span id="L-428"><a href="#L-428"><span class="linenos"> 428</span></a>
</span><span id="L-429"><a href="#L-429"><span class="linenos"> 429</span></a><span class="sd"> Returns</span>
</span><span id="L-430"><a href="#L-430"><span class="linenos"> 430</span></a><span class="sd"> -------</span>
</span><span id="L-431"><a href="#L-431"><span class="linenos"> 431</span></a><span class="sd"> result : dict</span>
</span><span id="L-432"><a href="#L-432"><span class="linenos"> 432</span></a><span class="sd"> A dictionary containing simulation results including:</span>
</span><span id="L-433"><a href="#L-433"><span class="linenos"> 433</span></a><span class="sd"> - Input parameters and survival flags.</span>
</span><span id="L-434"><a href="#L-434"><span class="linenos"> 434</span></a><span class="sd"> - Population mean and standard deviation for both species.</span>
</span><span id="L-435"><a href="#L-435"><span class="linenos"> 435</span></a><span class="sd"> - Cluster statistics (number of clusters, sizes, largest fractions).</span>
</span><span id="L-436"><a href="#L-436"><span class="linenos"> 436</span></a><span class="sd"> - Evolutionary statistics (mean, std, min, max, and final values).</span>
</span><span id="L-437"><a href="#L-437"><span class="linenos"> 437</span></a><span class="sd"> - PCF data and spatial indices (segregation and clustering).</span>
</span><span id="L-438"><a href="#L-438"><span class="linenos"> 438</span></a><span class="sd"> - Optional time series for populations and evolved parameters.</span>
</span><span id="L-439"><a href="#L-439"><span class="linenos"> 439</span></a>
</span><span id="L-440"><a href="#L-440"><span class="linenos"> 440</span></a><span class="sd"> Notes</span>
</span><span id="L-441"><a href="#L-441"><span class="linenos"> 441</span></a><span class="sd"> -----</span>
</span><span id="L-442"><a href="#L-442"><span class="linenos"> 442</span></a><span class="sd"> The function relies on several external utilities: `count_populations`,</span>
</span><span id="L-443"><a href="#L-443"><span class="linenos"> 443</span></a><span class="sd"> `get_evolved_stats`, `get_cluster_stats_fast`, `compute_all_pcfs_fast`,</span>
</span><span id="L-444"><a href="#L-444"><span class="linenos"> 444</span></a><span class="sd"> and `average_pcfs`.</span>
</span><span id="L-445"><a href="#L-445"><span class="linenos"> 445</span></a><span class="sd"> """</span>
</span><span id="L-446"><a href="#L-446"><span class="linenos"> 446</span></a>
</span><span id="L-447"><a href="#L-447"><span class="linenos"> 447</span></a> <span class="kn">from</span><span class="w"> </span><span class="nn">models.CA</span><span class="w"> </span><span class="kn">import</span> <span class="n">PP</span>
</span><span id="L-448"><a href="#L-448"><span class="linenos"> 448</span></a>
</span><span id="L-449"><a href="#L-449"><span class="linenos"> 449</span></a> <span class="k">if</span> <span class="n">USE_NUMBA</span><span class="p">:</span>
</span><span id="L-450"><a href="#L-450"><span class="linenos"> 450</span></a> <span class="n">set_numba_seed</span><span class="p">(</span><span class="n">seed</span><span class="p">)</span>
</span><span id="L-451"><a href="#L-451"><span class="linenos"> 451</span></a>
</span><span id="L-452"><a href="#L-452"><span class="linenos"> 452</span></a> <span class="k">if</span> <span class="n">compute_pcf</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
</span><span id="L-453"><a href="#L-453"><span class="linenos"> 453</span></a> <span class="n">compute_pcf</span> <span class="o">=</span> <span class="n">cfg</span><span class="o">.</span><span class="n">collect_pcf</span> <span class="ow">and</span> <span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">random</span><span class="p">()</span> <span class="o"><</span> <span class="n">cfg</span><span class="o">.</span><span class="n">pcf_sample_rate</span><span class="p">)</span>
</span><span id="L-454"><a href="#L-454"><span class="linenos"> 454</span></a>
</span><span id="L-455"><a href="#L-455"><span class="linenos"> 455</span></a> <span class="c1"># Initialize model</span>
</span><span id="L-456"><a href="#L-456"><span class="linenos"> 456</span></a> <span class="n">model</span> <span class="o">=</span> <span class="n">PP</span><span class="p">(</span>
</span><span id="L-457"><a href="#L-457"><span class="linenos"> 457</span></a> <span class="n">rows</span><span class="o">=</span><span class="n">grid_size</span><span class="p">,</span>
</span><span id="L-458"><a href="#L-458"><span class="linenos"> 458</span></a> <span class="n">cols</span><span class="o">=</span><span class="n">grid_size</span><span class="p">,</span>
</span><span id="L-459"><a href="#L-459"><span class="linenos"> 459</span></a> <span class="n">densities</span><span class="o">=</span><span class="n">cfg</span><span class="o">.</span><span class="n">densities</span><span class="p">,</span>
</span><span id="L-460"><a href="#L-460"><span class="linenos"> 460</span></a> <span class="n">neighborhood</span><span class="o">=</span><span class="s2">"moore"</span><span class="p">,</span> <span class="c1"># NOTE: Default neighborhood</span>
</span><span id="L-461"><a href="#L-461"><span class="linenos"> 461</span></a> <span class="n">params</span><span class="o">=</span><span class="p">{</span>
</span><span id="L-462"><a href="#L-462"><span class="linenos"> 462</span></a> <span class="s2">"prey_birth"</span><span class="p">:</span> <span class="n">prey_birth</span><span class="p">,</span>
</span><span id="L-463"><a href="#L-463"><span class="linenos"> 463</span></a> <span class="s2">"prey_death"</span><span class="p">:</span> <span class="n">prey_death</span><span class="p">,</span>
</span><span id="L-464"><a href="#L-464"><span class="linenos"> 464</span></a> <span class="s2">"predator_death"</span><span class="p">:</span> <span class="n">predator_death</span><span class="p">,</span>
</span><span id="L-465"><a href="#L-465"><span class="linenos"> 465</span></a> <span class="s2">"predator_birth"</span><span class="p">:</span> <span class="n">predator_birth</span><span class="p">,</span>
</span><span id="L-466"><a href="#L-466"><span class="linenos"> 466</span></a> <span class="p">},</span>
</span><span id="L-467"><a href="#L-467"><span class="linenos"> 467</span></a> <span class="n">seed</span><span class="o">=</span><span class="n">seed</span><span class="p">,</span>
</span><span id="L-468"><a href="#L-468"><span class="linenos"> 468</span></a> <span class="n">directed_hunting</span><span class="o">=</span><span class="n">cfg</span><span class="o">.</span><span class="n">directed_hunting</span><span class="p">,</span>
</span><span id="L-469"><a href="#L-469"><span class="linenos"> 469</span></a> <span class="p">)</span>
</span><span id="L-470"><a href="#L-470"><span class="linenos"> 470</span></a>
</span><span id="L-471"><a href="#L-471"><span class="linenos"> 471</span></a> <span class="k">if</span> <span class="n">with_evolution</span><span class="p">:</span>
</span><span id="L-472"><a href="#L-472"><span class="linenos"> 472</span></a> <span class="n">model</span><span class="o">.</span><span class="n">evolve</span><span class="p">(</span>
</span><span id="L-473"><a href="#L-473"><span class="linenos"> 473</span></a> <span class="s2">"prey_death"</span><span class="p">,</span>
</span><span id="L-474"><a href="#L-474"><span class="linenos"> 474</span></a> <span class="n">sd</span><span class="o">=</span><span class="n">cfg</span><span class="o">.</span><span class="n">evolve_sd</span><span class="p">,</span>
</span><span id="L-475"><a href="#L-475"><span class="linenos"> 475</span></a> <span class="n">min_val</span><span class="o">=</span><span class="n">cfg</span><span class="o">.</span><span class="n">evolve_min</span><span class="p">,</span>
</span><span id="L-476"><a href="#L-476"><span class="linenos"> 476</span></a> <span class="n">max_val</span><span class="o">=</span><span class="n">cfg</span><span class="o">.</span><span class="n">evolve_max</span><span class="p">,</span>
</span><span id="L-477"><a href="#L-477"><span class="linenos"> 477</span></a> <span class="p">)</span>
</span><span id="L-478"><a href="#L-478"><span class="linenos"> 478</span></a>
</span><span id="L-479"><a href="#L-479"><span class="linenos"> 479</span></a> <span class="c1"># Scale timing with grid size</span>
</span><span id="L-480"><a href="#L-480"><span class="linenos"> 480</span></a> <span class="n">warmup_steps</span> <span class="o">=</span> <span class="n">cfg</span><span class="o">.</span><span class="n">get_warmup_steps</span><span class="p">(</span><span class="n">grid_size</span><span class="p">)</span>
</span><span id="L-481"><a href="#L-481"><span class="linenos"> 481</span></a> <span class="n">measurement_steps</span> <span class="o">=</span> <span class="n">cfg</span><span class="o">.</span><span class="n">get_measurement_steps</span><span class="p">(</span><span class="n">grid_size</span><span class="p">)</span>
</span><span id="L-482"><a href="#L-482"><span class="linenos"> 482</span></a>
</span><span id="L-483"><a href="#L-483"><span class="linenos"> 483</span></a> <span class="c1"># Warmup phase</span>
</span><span id="L-484"><a href="#L-484"><span class="linenos"> 484</span></a> <span class="k">for</span> <span class="n">_</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">warmup_steps</span><span class="p">):</span>
</span><span id="L-485"><a href="#L-485"><span class="linenos"> 485</span></a> <span class="n">model</span><span class="o">.</span><span class="n">update</span><span class="p">()</span>
</span><span id="L-486"><a href="#L-486"><span class="linenos"> 486</span></a>
</span><span id="L-487"><a href="#L-487"><span class="linenos"> 487</span></a> <span class="c1"># Measurement phase: start collecting our mertics</span>
</span><span id="L-488"><a href="#L-488"><span class="linenos"> 488</span></a> <span class="n">prey_pops</span><span class="p">,</span> <span class="n">pred_pops</span> <span class="o">=</span> <span class="p">[],</span> <span class="p">[]</span> <span class="c1"># Prey populations and predator populations</span>
</span><span id="L-489"><a href="#L-489"><span class="linenos"> 489</span></a> <span class="n">evolved_means</span><span class="p">,</span> <span class="n">evolved_stds</span> <span class="o">=</span> <span class="p">[],</span> <span class="p">[]</span> <span class="c1"># Evolution stats over time</span>
</span><span id="L-490"><a href="#L-490"><span class="linenos"> 490</span></a> <span class="n">cluster_sizes_prey</span><span class="p">,</span> <span class="n">cluster_sizes_pred</span> <span class="o">=</span> <span class="p">[],</span> <span class="p">[]</span> <span class="c1"># Cluster sizes</span>
</span><span id="L-491"><a href="#L-491"><span class="linenos"> 491</span></a> <span class="n">largest_fractions_prey</span><span class="p">,</span> <span class="n">largest_fractions_pred</span> <span class="o">=</span> <span class="p">(</span>
</span><span id="L-492"><a href="#L-492"><span class="linenos"> 492</span></a> <span class="p">[],</span>
</span><span id="L-493"><a href="#L-493"><span class="linenos"> 493</span></a> <span class="p">[],</span>
</span><span id="L-494"><a href="#L-494"><span class="linenos"> 494</span></a> <span class="p">)</span> <span class="c1"># Largest cluster fractions = size of largest cluster / total population</span>
</span><span id="L-495"><a href="#L-495"><span class="linenos"> 495</span></a> <span class="n">pcf_samples</span> <span class="o">=</span> <span class="p">{</span><span class="s2">"prey_prey"</span><span class="p">:</span> <span class="p">[],</span> <span class="s2">"pred_pred"</span><span class="p">:</span> <span class="p">[],</span> <span class="s2">"prey_pred"</span><span class="p">:</span> <span class="p">[]}</span>
</span><span id="L-496"><a href="#L-496"><span class="linenos"> 496</span></a>
</span><span id="L-497"><a href="#L-497"><span class="linenos"> 497</span></a> <span class="c1"># Determine minimum count for analysis</span>
</span><span id="L-498"><a href="#L-498"><span class="linenos"> 498</span></a> <span class="n">min_count</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">cfg</span><span class="o">.</span><span class="n">min_density_for_analysis</span> <span class="o">*</span> <span class="p">(</span><span class="n">grid_size</span><span class="o">**</span><span class="mi">2</span><span class="p">))</span>
</span><span id="L-499"><a href="#L-499"><span class="linenos"> 499</span></a>
</span><span id="L-500"><a href="#L-500"><span class="linenos"> 500</span></a> <span class="k">for</span> <span class="n">step</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">measurement_steps</span><span class="p">):</span>
</span><span id="L-501"><a href="#L-501"><span class="linenos"> 501</span></a> <span class="n">model</span><span class="o">.</span><span class="n">update</span><span class="p">()</span>
</span><span id="L-502"><a href="#L-502"><span class="linenos"> 502</span></a>
</span><span id="L-503"><a href="#L-503"><span class="linenos"> 503</span></a> <span class="n">_</span><span class="p">,</span> <span class="n">prey</span><span class="p">,</span> <span class="n">pred</span> <span class="o">=</span> <span class="n">count_populations</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">grid</span><span class="p">)</span>
</span><span id="L-504"><a href="#L-504"><span class="linenos"> 504</span></a> <span class="n">prey_pops</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">prey</span><span class="p">)</span>
</span><span id="L-505"><a href="#L-505"><span class="linenos"> 505</span></a> <span class="n">pred_pops</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">pred</span><span class="p">)</span>
</span><span id="L-506"><a href="#L-506"><span class="linenos"> 506</span></a>
</span><span id="L-507"><a href="#L-507"><span class="linenos"> 507</span></a> <span class="c1"># Track evolution</span>
</span><span id="L-508"><a href="#L-508"><span class="linenos"> 508</span></a> <span class="k">if</span> <span class="n">with_evolution</span><span class="p">:</span>
</span><span id="L-509"><a href="#L-509"><span class="linenos"> 509</span></a> <span class="n">stats</span> <span class="o">=</span> <span class="n">get_evolved_stats</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="s2">"prey_death"</span><span class="p">)</span>
</span><span id="L-510"><a href="#L-510"><span class="linenos"> 510</span></a> <span class="n">evolved_means</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">stats</span><span class="p">[</span><span class="s2">"mean"</span><span class="p">])</span>
</span><span id="L-511"><a href="#L-511"><span class="linenos"> 511</span></a> <span class="n">evolved_stds</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">stats</span><span class="p">[</span><span class="s2">"std"</span><span class="p">])</span>
</span><span id="L-512"><a href="#L-512"><span class="linenos"> 512</span></a>
</span><span id="L-513"><a href="#L-513"><span class="linenos"> 513</span></a> <span class="c1"># Cluster analysis (at end of measurement)</span>
</span><span id="L-514"><a href="#L-514"><span class="linenos"> 514</span></a> <span class="k">if</span> <span class="n">step</span> <span class="o">==</span> <span class="n">measurement_steps</span> <span class="o">-</span> <span class="mi">1</span><span class="p">:</span>
</span><span id="L-515"><a href="#L-515"><span class="linenos"> 515</span></a> <span class="n">prey_survived</span> <span class="o">=</span> <span class="n">prey_pops</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="o">></span> <span class="n">min_count</span>
</span><span id="L-516"><a href="#L-516"><span class="linenos"> 516</span></a> <span class="n">pred_survived</span> <span class="o">=</span> <span class="n">pred_pops</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="o">></span> <span class="p">(</span><span class="n">min_count</span> <span class="o">//</span> <span class="mi">4</span><span class="p">)</span>
</span><span id="L-517"><a href="#L-517"><span class="linenos"> 517</span></a>
</span><span id="L-518"><a href="#L-518"><span class="linenos"> 518</span></a> <span class="k">if</span> <span class="n">prey_survived</span><span class="p">:</span>
</span><span id="L-519"><a href="#L-519"><span class="linenos"> 519</span></a> <span class="n">prey_stats</span> <span class="o">=</span> <span class="n">get_cluster_stats_fast</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">grid</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
</span><span id="L-520"><a href="#L-520"><span class="linenos"> 520</span></a> <span class="n">cluster_sizes_prey</span> <span class="o">=</span> <span class="n">prey_stats</span><span class="p">[</span><span class="s2">"sizes"</span><span class="p">]</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
</span><span id="L-521"><a href="#L-521"><span class="linenos"> 521</span></a> <span class="n">largest_fractions_prey</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">prey_stats</span><span class="p">[</span><span class="s2">"largest_fraction"</span><span class="p">])</span>
</span><span id="L-522"><a href="#L-522"><span class="linenos"> 522</span></a>
</span><span id="L-523"><a href="#L-523"><span class="linenos"> 523</span></a> <span class="k">if</span> <span class="n">pred_survived</span><span class="p">:</span>
</span><span id="L-524"><a href="#L-524"><span class="linenos"> 524</span></a> <span class="n">pred_stats</span> <span class="o">=</span> <span class="n">get_cluster_stats_fast</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">grid</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span>
</span><span id="L-525"><a href="#L-525"><span class="linenos"> 525</span></a> <span class="n">cluster_sizes_pred</span> <span class="o">=</span> <span class="n">pred_stats</span><span class="p">[</span><span class="s2">"sizes"</span><span class="p">]</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
</span><span id="L-526"><a href="#L-526"><span class="linenos"> 526</span></a> <span class="n">largest_fractions_pred</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">pred_stats</span><span class="p">[</span><span class="s2">"largest_fraction"</span><span class="p">])</span>
</span><span id="L-527"><a href="#L-527"><span class="linenos"> 527</span></a>
</span><span id="L-528"><a href="#L-528"><span class="linenos"> 528</span></a> <span class="c1"># PCF requires both</span>
</span><span id="L-529"><a href="#L-529"><span class="linenos"> 529</span></a> <span class="k">if</span> <span class="n">compute_pcf</span> <span class="ow">and</span> <span class="n">prey_survived</span> <span class="ow">and</span> <span class="n">pred_survived</span><span class="p">:</span>
</span><span id="L-530"><a href="#L-530"><span class="linenos"> 530</span></a> <span class="n">max_dist</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="n">grid_size</span> <span class="o">/</span> <span class="mi">2</span><span class="p">,</span> <span class="n">cfg</span><span class="o">.</span><span class="n">pcf_max_distance</span><span class="p">)</span>
</span><span id="L-531"><a href="#L-531"><span class="linenos"> 531</span></a> <span class="n">pcf_data</span> <span class="o">=</span> <span class="n">compute_all_pcfs_fast</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">grid</span><span class="p">,</span> <span class="n">max_dist</span><span class="p">,</span> <span class="n">cfg</span><span class="o">.</span><span class="n">pcf_n_bins</span><span class="p">)</span>
</span><span id="L-532"><a href="#L-532"><span class="linenos"> 532</span></a> <span class="n">pcf_samples</span><span class="p">[</span><span class="s2">"prey_prey"</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">pcf_data</span><span class="p">[</span><span class="s2">"prey_prey"</span><span class="p">])</span>
</span><span id="L-533"><a href="#L-533"><span class="linenos"> 533</span></a> <span class="n">pcf_samples</span><span class="p">[</span><span class="s2">"pred_pred"</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">pcf_data</span><span class="p">[</span><span class="s2">"pred_pred"</span><span class="p">])</span>
</span><span id="L-534"><a href="#L-534"><span class="linenos"> 534</span></a> <span class="n">pcf_samples</span><span class="p">[</span><span class="s2">"prey_pred"</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">pcf_data</span><span class="p">[</span><span class="s2">"prey_pred"</span><span class="p">])</span>
</span><span id="L-535"><a href="#L-535"><span class="linenos"> 535</span></a>
</span><span id="L-536"><a href="#L-536"><span class="linenos"> 536</span></a> <span class="c1"># Compile results</span>
</span><span id="L-537"><a href="#L-537"><span class="linenos"> 537</span></a> <span class="n">result</span> <span class="o">=</span> <span class="p">{</span>
</span><span id="L-538"><a href="#L-538"><span class="linenos"> 538</span></a> <span class="c1"># Parameters</span>
</span><span id="L-539"><a href="#L-539"><span class="linenos"> 539</span></a> <span class="s2">"prey_birth"</span><span class="p">:</span> <span class="n">prey_birth</span><span class="p">,</span>
</span><span id="L-540"><a href="#L-540"><span class="linenos"> 540</span></a> <span class="s2">"prey_death"</span><span class="p">:</span> <span class="n">prey_death</span><span class="p">,</span>
</span><span id="L-541"><a href="#L-541"><span class="linenos"> 541</span></a> <span class="s2">"predator_birth"</span><span class="p">:</span> <span class="n">predator_birth</span><span class="p">,</span>
</span><span id="L-542"><a href="#L-542"><span class="linenos"> 542</span></a> <span class="s2">"predator_death"</span><span class="p">:</span> <span class="n">predator_death</span><span class="p">,</span>
</span><span id="L-543"><a href="#L-543"><span class="linenos"> 543</span></a> <span class="s2">"grid_size"</span><span class="p">:</span> <span class="n">grid_size</span><span class="p">,</span>
</span><span id="L-544"><a href="#L-544"><span class="linenos"> 544</span></a> <span class="s2">"with_evolution"</span><span class="p">:</span> <span class="n">with_evolution</span><span class="p">,</span>
</span><span id="L-545"><a href="#L-545"><span class="linenos"> 545</span></a> <span class="s2">"seed"</span><span class="p">:</span> <span class="n">seed</span><span class="p">,</span>
</span><span id="L-546"><a href="#L-546"><span class="linenos"> 546</span></a> <span class="c1"># Population dynamics</span>
</span><span id="L-547"><a href="#L-547"><span class="linenos"> 547</span></a> <span class="s2">"prey_mean"</span><span class="p">:</span> <span class="nb">float</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">prey_pops</span><span class="p">)),</span>
</span><span id="L-548"><a href="#L-548"><span class="linenos"> 548</span></a> <span class="s2">"prey_std"</span><span class="p">:</span> <span class="nb">float</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">std</span><span class="p">(</span><span class="n">prey_pops</span><span class="p">)),</span>
</span><span id="L-549"><a href="#L-549"><span class="linenos"> 549</span></a> <span class="s2">"pred_mean"</span><span class="p">:</span> <span class="nb">float</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">pred_pops</span><span class="p">)),</span>
</span><span id="L-550"><a href="#L-550"><span class="linenos"> 550</span></a> <span class="s2">"pred_std"</span><span class="p">:</span> <span class="nb">float</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">std</span><span class="p">(</span><span class="n">pred_pops</span><span class="p">)),</span>
</span><span id="L-551"><a href="#L-551"><span class="linenos"> 551</span></a> <span class="s2">"prey_survived"</span><span class="p">:</span> <span class="n">prey_pops</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="o">></span> <span class="n">min_count</span><span class="p">,</span>
</span><span id="L-552"><a href="#L-552"><span class="linenos"> 552</span></a> <span class="s2">"pred_survived"</span><span class="p">:</span> <span class="n">pred_pops</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="o">></span> <span class="p">(</span><span class="n">min_count</span> <span class="o">//</span> <span class="mi">4</span><span class="p">),</span>
</span><span id="L-553"><a href="#L-553"><span class="linenos"> 553</span></a> <span class="c1"># Cluster statistics</span>
</span><span id="L-554"><a href="#L-554"><span class="linenos"> 554</span></a> <span class="s2">"prey_n_clusters"</span><span class="p">:</span> <span class="nb">len</span><span class="p">(</span><span class="n">cluster_sizes_prey</span><span class="p">),</span>
</span><span id="L-555"><a href="#L-555"><span class="linenos"> 555</span></a> <span class="s2">"pred_n_clusters"</span><span class="p">:</span> <span class="nb">len</span><span class="p">(</span><span class="n">cluster_sizes_pred</span><span class="p">),</span>
</span><span id="L-556"><a href="#L-556"><span class="linenos"> 556</span></a> <span class="s2">"prey_cluster_sizes"</span><span class="p">:</span> <span class="n">cluster_sizes_prey</span><span class="p">,</span>
</span><span id="L-557"><a href="#L-557"><span class="linenos"> 557</span></a> <span class="s2">"pred_cluster_sizes"</span><span class="p">:</span> <span class="n">cluster_sizes_pred</span><span class="p">,</span>
</span><span id="L-558"><a href="#L-558"><span class="linenos"> 558</span></a> <span class="c1"># Order parameters</span>
</span><span id="L-559"><a href="#L-559"><span class="linenos"> 559</span></a> <span class="s2">"prey_largest_fraction"</span><span class="p">:</span> <span class="p">(</span>
</span><span id="L-560"><a href="#L-560"><span class="linenos"> 560</span></a> <span class="nb">float</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">largest_fractions_prey</span><span class="p">))</span> <span class="k">if</span> <span class="n">largest_fractions_prey</span> <span class="k">else</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span>
</span><span id="L-561"><a href="#L-561"><span class="linenos"> 561</span></a> <span class="p">),</span>
</span><span id="L-562"><a href="#L-562"><span class="linenos"> 562</span></a> <span class="s2">"pred_largest_fraction"</span><span class="p">:</span> <span class="p">(</span>
</span><span id="L-563"><a href="#L-563"><span class="linenos"> 563</span></a> <span class="nb">float</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">largest_fractions_pred</span><span class="p">))</span> <span class="k">if</span> <span class="n">largest_fractions_pred</span> <span class="k">else</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span>
</span><span id="L-564"><a href="#L-564"><span class="linenos"> 564</span></a> <span class="p">),</span>
</span><span id="L-565"><a href="#L-565"><span class="linenos"> 565</span></a> <span class="p">}</span>
</span><span id="L-566"><a href="#L-566"><span class="linenos"> 566</span></a>
</span><span id="L-567"><a href="#L-567"><span class="linenos"> 567</span></a> <span class="c1"># Time series (if requested)</span>
</span><span id="L-568"><a href="#L-568"><span class="linenos"> 568</span></a> <span class="k">if</span> <span class="n">cfg</span><span class="o">.</span><span class="n">save_timeseries</span><span class="p">:</span>
</span><span id="L-569"><a href="#L-569"><span class="linenos"> 569</span></a> <span class="n">subsample</span> <span class="o">=</span> <span class="n">cfg</span><span class="o">.</span><span class="n">timeseries_subsample</span>
</span><span id="L-570"><a href="#L-570"><span class="linenos"> 570</span></a> <span class="n">result</span><span class="p">[</span><span class="s2">"prey_timeseries"</span><span class="p">]</span> <span class="o">=</span> <span class="n">prey_pops</span><span class="p">[</span>
</span><span id="L-571"><a href="#L-571"><span class="linenos"> 571</span></a> <span class="p">::</span><span class="n">subsample</span>
</span><span id="L-572"><a href="#L-572"><span class="linenos"> 572</span></a> <span class="p">]</span> <span class="c1"># NOTE: Sample temporal data every 'subsample' steps</span>
</span><span id="L-573"><a href="#L-573"><span class="linenos"> 573</span></a> <span class="n">result</span><span class="p">[</span><span class="s2">"pred_timeseries"</span><span class="p">]</span> <span class="o">=</span> <span class="n">pred_pops</span><span class="p">[::</span><span class="n">subsample</span><span class="p">]</span>
</span><span id="L-574"><a href="#L-574"><span class="linenos"> 574</span></a>
</span><span id="L-575"><a href="#L-575"><span class="linenos"> 575</span></a> <span class="c1"># Evolution statistics</span>
</span><span id="L-576"><a href="#L-576"><span class="linenos"> 576</span></a> <span class="k">if</span> <span class="n">with_evolution</span> <span class="ow">and</span> <span class="n">evolved_means</span><span class="p">:</span>
</span><span id="L-577"><a href="#L-577"><span class="linenos"> 577</span></a> <span class="n">valid_means</span> <span class="o">=</span> <span class="p">[</span><span class="n">v</span> <span class="k">for</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">evolved_means</span> <span class="k">if</span> <span class="ow">not</span> <span class="n">np</span><span class="o">.</span><span class="n">isnan</span><span class="p">(</span><span class="n">v</span><span class="p">)]</span>
</span><span id="L-578"><a href="#L-578"><span class="linenos"> 578</span></a> <span class="n">result</span><span class="p">[</span><span class="s2">"evolved_prey_death_mean"</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
</span><span id="L-579"><a href="#L-579"><span class="linenos"> 579</span></a> <span class="nb">float</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">valid_means</span><span class="p">))</span> <span class="k">if</span> <span class="n">valid_means</span> <span class="k">else</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span>
</span><span id="L-580"><a href="#L-580"><span class="linenos"> 580</span></a> <span class="p">)</span>
</span><span id="L-581"><a href="#L-581"><span class="linenos"> 581</span></a> <span class="n">result</span><span class="p">[</span><span class="s2">"evolved_prey_death_std"</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
</span><span id="L-582"><a href="#L-582"><span class="linenos"> 582</span></a> <span class="nb">float</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">([</span><span class="n">v</span> <span class="k">for</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">evolved_stds</span> <span class="k">if</span> <span class="ow">not</span> <span class="n">np</span><span class="o">.</span><span class="n">isnan</span><span class="p">(</span><span class="n">v</span><span class="p">)]))</span>
</span><span id="L-583"><a href="#L-583"><span class="linenos"> 583</span></a> <span class="k">if</span> <span class="n">evolved_stds</span>
</span><span id="L-584"><a href="#L-584"><span class="linenos"> 584</span></a> <span class="k">else</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span>
</span><span id="L-585"><a href="#L-585"><span class="linenos"> 585</span></a> <span class="p">)</span>
</span><span id="L-586"><a href="#L-586"><span class="linenos"> 586</span></a> <span class="n">result</span><span class="p">[</span><span class="s2">"evolved_prey_death_final"</span><span class="p">]</span> <span class="o">=</span> <span class="n">valid_means</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="k">if</span> <span class="n">valid_means</span> <span class="k">else</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span>
</span><span id="L-587"><a href="#L-587"><span class="linenos"> 587</span></a> <span class="n">result</span><span class="p">[</span><span class="s2">"evolved_prey_death_min"</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
</span><span id="L-588"><a href="#L-588"><span class="linenos"> 588</span></a> <span class="nb">float</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">min</span><span class="p">(</span><span class="n">valid_means</span><span class="p">))</span> <span class="k">if</span> <span class="n">valid_means</span> <span class="k">else</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span>
</span><span id="L-589"><a href="#L-589"><span class="linenos"> 589</span></a> <span class="p">)</span>
</span><span id="L-590"><a href="#L-590"><span class="linenos"> 590</span></a> <span class="n">result</span><span class="p">[</span><span class="s2">"evolved_prey_death_max"</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
</span><span id="L-591"><a href="#L-591"><span class="linenos"> 591</span></a> <span class="nb">float</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">max</span><span class="p">(</span><span class="n">valid_means</span><span class="p">))</span> <span class="k">if</span> <span class="n">valid_means</span> <span class="k">else</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span>
</span><span id="L-592"><a href="#L-592"><span class="linenos"> 592</span></a> <span class="p">)</span>
</span><span id="L-593"><a href="#L-593"><span class="linenos"> 593</span></a> <span class="n">result</span><span class="p">[</span><span class="s2">"evolve_sd"</span><span class="p">]</span> <span class="o">=</span> <span class="n">cfg</span><span class="o">.</span><span class="n">evolve_sd</span>
</span><span id="L-594"><a href="#L-594"><span class="linenos"> 594</span></a>
</span><span id="L-595"><a href="#L-595"><span class="linenos"> 595</span></a> <span class="k">if</span> <span class="n">cfg</span><span class="o">.</span><span class="n">save_timeseries</span><span class="p">:</span>
</span><span id="L-596"><a href="#L-596"><span class="linenos"> 596</span></a> <span class="n">result</span><span class="p">[</span><span class="s2">"evolved_prey_death_timeseries"</span><span class="p">]</span> <span class="o">=</span> <span class="n">evolved_means</span><span class="p">[</span>
</span><span id="L-597"><a href="#L-597"><span class="linenos"> 597</span></a> <span class="p">::</span> <span class="n">cfg</span><span class="o">.</span><span class="n">timeseries_subsample</span>
</span><span id="L-598"><a href="#L-598"><span class="linenos"> 598</span></a> <span class="p">]</span>
</span><span id="L-599"><a href="#L-599"><span class="linenos"> 599</span></a>
</span><span id="L-600"><a href="#L-600"><span class="linenos"> 600</span></a> <span class="c1"># PCF statistics</span>
</span><span id="L-601"><a href="#L-601"><span class="linenos"> 601</span></a> <span class="k">if</span> <span class="n">pcf_samples</span><span class="p">[</span><span class="s2">"prey_prey"</span><span class="p">]:</span>
</span><span id="L-602"><a href="#L-602"><span class="linenos"> 602</span></a> <span class="n">dist</span><span class="p">,</span> <span class="n">pcf_rr</span><span class="p">,</span> <span class="n">_</span> <span class="o">=</span> <span class="n">average_pcfs</span><span class="p">(</span><span class="n">pcf_samples</span><span class="p">[</span><span class="s2">"prey_prey"</span><span class="p">])</span>
</span><span id="L-603"><a href="#L-603"><span class="linenos"> 603</span></a> <span class="n">_</span><span class="p">,</span> <span class="n">pcf_cc</span><span class="p">,</span> <span class="n">_</span> <span class="o">=</span> <span class="n">average_pcfs</span><span class="p">(</span><span class="n">pcf_samples</span><span class="p">[</span><span class="s2">"pred_pred"</span><span class="p">])</span>
</span><span id="L-604"><a href="#L-604"><span class="linenos"> 604</span></a> <span class="n">_</span><span class="p">,</span> <span class="n">pcf_cr</span><span class="p">,</span> <span class="n">_</span> <span class="o">=</span> <span class="n">average_pcfs</span><span class="p">(</span><span class="n">pcf_samples</span><span class="p">[</span><span class="s2">"prey_pred"</span><span class="p">])</span>
</span><span id="L-605"><a href="#L-605"><span class="linenos"> 605</span></a>
</span><span id="L-606"><a href="#L-606"><span class="linenos"> 606</span></a> <span class="n">result</span><span class="p">[</span><span class="s2">"pcf_distances"</span><span class="p">]</span> <span class="o">=</span> <span class="n">dist</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
</span><span id="L-607"><a href="#L-607"><span class="linenos"> 607</span></a> <span class="n">result</span><span class="p">[</span><span class="s2">"pcf_prey_prey"</span><span class="p">]</span> <span class="o">=</span> <span class="n">pcf_rr</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
</span><span id="L-608"><a href="#L-608"><span class="linenos"> 608</span></a> <span class="n">result</span><span class="p">[</span><span class="s2">"pcf_pred_pred"</span><span class="p">]</span> <span class="o">=</span> <span class="n">pcf_cc</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
</span><span id="L-609"><a href="#L-609"><span class="linenos"> 609</span></a> <span class="n">result</span><span class="p">[</span><span class="s2">"pcf_prey_pred"</span><span class="p">]</span> <span class="o">=</span> <span class="n">pcf_cr</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
</span><span id="L-610"><a href="#L-610"><span class="linenos"> 610</span></a>
</span><span id="L-611"><a href="#L-611"><span class="linenos"> 611</span></a> <span class="c1"># Short-range indices</span>
</span><span id="L-612"><a href="#L-612"><span class="linenos"> 612</span></a> <span class="n">short_mask</span> <span class="o">=</span> <span class="n">dist</span> <span class="o"><</span> <span class="mf">3.0</span>
</span><span id="L-613"><a href="#L-613"><span class="linenos"> 613</span></a> <span class="k">if</span> <span class="n">np</span><span class="o">.</span><span class="n">any</span><span class="p">(</span><span class="n">short_mask</span><span class="p">):</span>
</span><span id="L-614"><a href="#L-614"><span class="linenos"> 614</span></a> <span class="n">result</span><span class="p">[</span><span class="s2">"segregation_index"</span><span class="p">]</span> <span class="o">=</span> <span class="nb">float</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">pcf_cr</span><span class="p">[</span><span class="n">short_mask</span><span class="p">]))</span>
</span><span id="L-615"><a href="#L-615"><span class="linenos"> 615</span></a> <span class="n">result</span><span class="p">[</span><span class="s2">"prey_clustering_index"</span><span class="p">]</span> <span class="o">=</span> <span class="nb">float</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">pcf_rr</span><span class="p">[</span><span class="n">short_mask</span><span class="p">]))</span>
</span><span id="L-616"><a href="#L-616"><span class="linenos"> 616</span></a> <span class="n">result</span><span class="p">[</span><span class="s2">"pred_clustering_index"</span><span class="p">]</span> <span class="o">=</span> <span class="nb">float</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">pcf_cc</span><span class="p">[</span><span class="n">short_mask</span><span class="p">]))</span>
</span><span id="L-617"><a href="#L-617"><span class="linenos"> 617</span></a>
</span><span id="L-618"><a href="#L-618"><span class="linenos"> 618</span></a> <span class="k">return</span> <span class="n">result</span>
</span><span id="L-619"><a href="#L-619"><span class="linenos"> 619</span></a>
</span><span id="L-620"><a href="#L-620"><span class="linenos"> 620</span></a>
</span><span id="L-621"><a href="#L-621"><span class="linenos"> 621</span></a><span class="c1"># =============================================================================</span>
</span><span id="L-622"><a href="#L-622"><span class="linenos"> 622</span></a><span class="c1"># Experiment Phases</span>
</span><span id="L-623"><a href="#L-623"><span class="linenos"> 623</span></a><span class="c1"># =============================================================================</span>
</span><span id="L-624"><a href="#L-624"><span class="linenos"> 624</span></a>
</span><span id="L-625"><a href="#L-625"><span class="linenos"> 625</span></a>
</span><span id="L-626"><a href="#L-626"><span class="linenos"> 626</span></a><span class="k">def</span><span class="w"> </span><span class="nf">run_phase1</span><span class="p">(</span><span class="n">cfg</span><span class="p">:</span> <span class="n">Config</span><span class="p">,</span> <span class="n">output_dir</span><span class="p">:</span> <span class="n">Path</span><span class="p">,</span> <span class="n">logger</span><span class="p">:</span> <span class="n">logging</span><span class="o">.</span><span class="n">Logger</span><span class="p">)</span> <span class="o">-></span> <span class="n">List</span><span class="p">[</span><span class="n">Dict</span><span class="p">]:</span>
</span><span id="L-627"><a href="#L-627"><span class="linenos"> 627</span></a><span class="w"> </span><span class="sd">"""</span>
</span><span id="L-628"><a href="#L-628"><span class="linenos"> 628</span></a><span class="sd"> Execute Phase 1 of the simulation: a parameter sweep to identify critical points.</span>
</span><span id="L-629"><a href="#L-629"><span class="linenos"> 629</span></a>
</span><span id="L-630"><a href="#L-630"><span class="linenos"> 630</span></a><span class="sd"> This function performs a 1D sweep across varying prey mortality rates while</span>
</span><span id="L-631"><a href="#L-631"><span class="linenos"> 631</span></a><span class="sd"> keeping other parameters fixed. It utilizes parallel execution via joblib</span>
</span><span id="L-632"><a href="#L-632"><span class="linenos"> 632</span></a><span class="sd"> and saves results incrementally to a JSONL file to ensure data integrity</span>
</span><span id="L-633"><a href="#L-633"><span class="linenos"> 633</span></a><span class="sd"> during long-running batches.</span>
</span><span id="L-634"><a href="#L-634"><span class="linenos"> 634</span></a>
</span><span id="L-635"><a href="#L-635"><span class="linenos"> 635</span></a><span class="sd"> Parameters</span>
</span><span id="L-636"><a href="#L-636"><span class="linenos"> 636</span></a><span class="sd"> ----------</span>
</span><span id="L-637"><a href="#L-637"><span class="linenos"> 637</span></a><span class="sd"> cfg : Config</span>
</span><span id="L-638"><a href="#L-638"><span class="linenos"> 638</span></a><span class="sd"> Configuration object containing simulation hyperparameters, sweep</span>
</span><span id="L-639"><a href="#L-639"><span class="linenos"> 639</span></a><span class="sd"> ranges, and execution settings (n_jobs, grid_size, etc.).</span>
</span><span id="L-640"><a href="#L-640"><span class="linenos"> 640</span></a><span class="sd"> output_dir : Path</span>
</span><span id="L-641"><a href="#L-641"><span class="linenos"> 641</span></a><span class="sd"> Directory where result files (JSONL) and metadata (JSON) will be stored.</span>
</span><span id="L-642"><a href="#L-642"><span class="linenos"> 642</span></a><span class="sd"> logger : logging.Logger</span>
</span><span id="L-643"><a href="#L-643"><span class="linenos"> 643</span></a><span class="sd"> Logger instance for tracking simulation progress and recording</span>
</span><span id="L-644"><a href="#L-644"><span class="linenos"> 644</span></a><span class="sd"> operational metadata.</span>
</span><span id="L-645"><a href="#L-645"><span class="linenos"> 645</span></a>
</span><span id="L-646"><a href="#L-646"><span class="linenos"> 646</span></a><span class="sd"> Returns</span>
</span><span id="L-647"><a href="#L-647"><span class="linenos"> 647</span></a><span class="sd"> -------</span>
</span><span id="L-648"><a href="#L-648"><span class="linenos"> 648</span></a><span class="sd"> all_results : list of dict</span>
</span><span id="L-649"><a href="#L-649"><span class="linenos"> 649</span></a><span class="sd"> A list of dictionaries containing the metrics collected from every</span>
</span><span id="L-650"><a href="#L-650"><span class="linenos"> 650</span></a><span class="sd"> individual simulation run in the sweep.</span>
</span><span id="L-651"><a href="#L-651"><span class="linenos"> 651</span></a>
</span><span id="L-652"><a href="#L-652"><span class="linenos"> 652</span></a><span class="sd"> Notes</span>
</span><span id="L-653"><a href="#L-653"><span class="linenos"> 653</span></a><span class="sd"> -----</span>
</span><span id="L-654"><a href="#L-654"><span class="linenos"> 654</span></a><span class="sd"> The function performs the following steps:</span>
</span><span id="L-655"><a href="#L-655"><span class="linenos"> 655</span></a><span class="sd"> 1. Pre-warms Numba kernels for performance.</span>
</span><span id="L-656"><a href="#L-656"><span class="linenos"> 656</span></a><span class="sd"> 2. Generates a deterministic set of simulation jobs using unique seeds.</span>
</span><span id="L-657"><a href="#L-657"><span class="linenos"> 657</span></a><span class="sd"> 3. Executes simulations in parallel using a generator for memory efficiency.</span>
</span><span id="L-658"><a href="#L-658"><span class="linenos"> 658</span></a><span class="sd"> 4. Records metadata including a timestamp and a serialized snapshot of</span>
</span><span id="L-659"><a href="#L-659"><span class="linenos"> 659</span></a><span class="sd"> the configuration.</span>
</span><span id="L-660"><a href="#L-660"><span class="linenos"> 660</span></a><span class="sd"> """</span>
</span><span id="L-661"><a href="#L-661"><span class="linenos"> 661</span></a> <span class="kn">from</span><span class="w"> </span><span class="nn">joblib</span><span class="w"> </span><span class="kn">import</span> <span class="n">Parallel</span><span class="p">,</span> <span class="n">delayed</span>
</span><span id="L-662"><a href="#L-662"><span class="linenos"> 662</span></a>
</span><span id="L-663"><a href="#L-663"><span class="linenos"> 663</span></a> <span class="n">warmup_numba_kernels</span><span class="p">(</span><span class="n">cfg</span><span class="o">.</span><span class="n">grid_size</span><span class="p">,</span> <span class="n">directed_hunting</span><span class="o">=</span><span class="n">cfg</span><span class="o">.</span><span class="n">directed_hunting</span><span class="p">)</span>
</span><span id="L-664"><a href="#L-664"><span class="linenos"> 664</span></a>
</span><span id="L-665"><a href="#L-665"><span class="linenos"> 665</span></a> <span class="n">prey_deaths</span> <span class="o">=</span> <span class="n">cfg</span><span class="o">.</span><span class="n">get_prey_deaths</span><span class="p">()</span>
</span><span id="L-666"><a href="#L-666"><span class="linenos"> 666</span></a>
</span><span id="L-667"><a href="#L-667"><span class="linenos"> 667</span></a> <span class="c1"># Build job list</span>
</span><span id="L-668"><a href="#L-668"><span class="linenos"> 668</span></a> <span class="n">jobs</span> <span class="o">=</span> <span class="p">[]</span>
</span><span id="L-669"><a href="#L-669"><span class="linenos"> 669</span></a> <span class="c1"># Sweep through prey_death only (prey_birth is fixed)</span>
</span><span id="L-670"><a href="#L-670"><span class="linenos"> 670</span></a> <span class="k">for</span> <span class="n">pd</span> <span class="ow">in</span> <span class="n">prey_deaths</span><span class="p">:</span>
</span><span id="L-671"><a href="#L-671"><span class="linenos"> 671</span></a> <span class="k">for</span> <span class="n">rep</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">cfg</span><span class="o">.</span><span class="n">n_replicates</span><span class="p">):</span>
</span><span id="L-672"><a href="#L-672"><span class="linenos"> 672</span></a> <span class="n">params</span> <span class="o">=</span> <span class="p">{</span><span class="s2">"pd"</span><span class="p">:</span> <span class="n">pd</span><span class="p">}</span>
</span><span id="L-673"><a href="#L-673"><span class="linenos"> 673</span></a>
</span><span id="L-674"><a href="#L-674"><span class="linenos"> 674</span></a> <span class="n">seed</span> <span class="o">=</span> <span class="n">generate_unique_seed</span><span class="p">(</span><span class="n">params</span><span class="p">,</span> <span class="n">rep</span><span class="p">)</span>
</span><span id="L-675"><a href="#L-675"><span class="linenos"> 675</span></a> <span class="n">jobs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span>
</span><span id="L-676"><a href="#L-676"><span class="linenos"> 676</span></a> <span class="p">(</span>
</span><span id="L-677"><a href="#L-677"><span class="linenos"> 677</span></a> <span class="n">cfg</span><span class="o">.</span><span class="n">prey_birth</span><span class="p">,</span>
</span><span id="L-678"><a href="#L-678"><span class="linenos"> 678</span></a> <span class="n">pd</span><span class="p">,</span>
</span><span id="L-679"><a href="#L-679"><span class="linenos"> 679</span></a> <span class="n">cfg</span><span class="o">.</span><span class="n">predator_birth</span><span class="p">,</span>
</span><span id="L-680"><a href="#L-680"><span class="linenos"> 680</span></a> <span class="n">cfg</span><span class="o">.</span><span class="n">predator_death</span><span class="p">,</span>
</span><span id="L-681"><a href="#L-681"><span class="linenos"> 681</span></a> <span class="n">cfg</span><span class="o">.</span><span class="n">grid_size</span><span class="p">,</span>
</span><span id="L-682"><a href="#L-682"><span class="linenos"> 682</span></a> <span class="n">seed</span><span class="p">,</span>
</span><span id="L-683"><a href="#L-683"><span class="linenos"> 683</span></a> <span class="n">cfg</span><span class="p">,</span>
</span><span id="L-684"><a href="#L-684"><span class="linenos"> 684</span></a> <span class="kc">False</span><span class="p">,</span>
</span><span id="L-685"><a href="#L-685"><span class="linenos"> 685</span></a> <span class="p">)</span>
</span><span id="L-686"><a href="#L-686"><span class="linenos"> 686</span></a> <span class="p">)</span>
</span><span id="L-687"><a href="#L-687"><span class="linenos"> 687</span></a>
</span><span id="L-688"><a href="#L-688"><span class="linenos"> 688</span></a> <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Phase 1: </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">jobs</span><span class="p">)</span><span class="si">:</span><span class="s2">,</span><span class="si">}</span><span class="s2"> simulations"</span><span class="p">)</span>
</span><span id="L-689"><a href="#L-689"><span class="linenos"> 689</span></a> <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span>
</span><span id="L-690"><a href="#L-690"><span class="linenos"> 690</span></a> <span class="sa">f</span><span class="s2">" Grid: </span><span class="si">{</span><span class="n">cfg</span><span class="o">.</span><span class="n">n_prey_death</span><span class="si">}</span><span class="s2"> prey_death values × </span><span class="si">{</span><span class="n">cfg</span><span class="o">.</span><span class="n">n_replicates</span><span class="si">}</span><span class="s2"> reps (prey_birth=</span><span class="si">{</span><span class="n">cfg</span><span class="o">.</span><span class="n">prey_birth</span><span class="si">}</span><span class="s2">)"</span>
</span><span id="L-691"><a href="#L-691"><span class="linenos"> 691</span></a> <span class="p">)</span>
</span><span id="L-692"><a href="#L-692"><span class="linenos"> 692</span></a> <span class="c1"># Run with incremental saving</span>
</span><span id="L-693"><a href="#L-693"><span class="linenos"> 693</span></a> <span class="n">output_jsonl</span> <span class="o">=</span> <span class="n">output_dir</span> <span class="o">/</span> <span class="s2">"phase1_results.jsonl"</span>
</span><span id="L-694"><a href="#L-694"><span class="linenos"> 694</span></a> <span class="n">all_results</span> <span class="o">=</span> <span class="p">[]</span>
</span><span id="L-695"><a href="#L-695"><span class="linenos"> 695</span></a>
</span><span id="L-696"><a href="#L-696"><span class="linenos"> 696</span></a> <span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">output_jsonl</span><span class="p">,</span> <span class="s2">"w"</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="s2">"utf-8"</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
</span><span id="L-697"><a href="#L-697"><span class="linenos"> 697</span></a> <span class="n">executor</span> <span class="o">=</span> <span class="n">Parallel</span><span class="p">(</span><span class="n">n_jobs</span><span class="o">=</span><span class="n">cfg</span><span class="o">.</span><span class="n">n_jobs</span><span class="p">,</span> <span class="n">return_as</span><span class="o">=</span><span class="s2">"generator"</span><span class="p">)</span>
</span><span id="L-698"><a href="#L-698"><span class="linenos"> 698</span></a> <span class="n">tasks</span> <span class="o">=</span> <span class="p">(</span><span class="n">delayed</span><span class="p">(</span><span class="n">run_single_simulation</span><span class="p">)(</span><span class="o">*</span><span class="n">job</span><span class="p">)</span> <span class="k">for</span> <span class="n">job</span> <span class="ow">in</span> <span class="n">jobs</span><span class="p">)</span>
</span><span id="L-699"><a href="#L-699"><span class="linenos"> 699</span></a>
</span><span id="L-700"><a href="#L-700"><span class="linenos"> 700</span></a> <span class="k">for</span> <span class="n">result</span> <span class="ow">in</span> <span class="n">tqdm</span><span class="p">(</span><span class="n">executor</span><span class="p">(</span><span class="n">tasks</span><span class="p">),</span> <span class="n">total</span><span class="o">=</span><span class="nb">len</span><span class="p">(</span><span class="n">jobs</span><span class="p">),</span> <span class="n">desc</span><span class="o">=</span><span class="s2">"Phase 1"</span><span class="p">):</span>
</span><span id="L-701"><a href="#L-701"><span class="linenos"> 701</span></a> <span class="n">f</span><span class="o">.</span><span class="n">write</span><span class="p">(</span><span class="n">json</span><span class="o">.</span><span class="n">dumps</span><span class="p">(</span><span class="n">result</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="nb">str</span><span class="p">)</span> <span class="o">+</span> <span class="s2">"</span><span class="se">\n</span><span class="s2">"</span><span class="p">)</span>
</span><span id="L-702"><a href="#L-702"><span class="linenos"> 702</span></a> <span class="n">f</span><span class="o">.</span><span class="n">flush</span><span class="p">()</span>
</span><span id="L-703"><a href="#L-703"><span class="linenos"> 703</span></a> <span class="n">all_results</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">result</span><span class="p">)</span>
</span><span id="L-704"><a href="#L-704"><span class="linenos"> 704</span></a>
</span><span id="L-705"><a href="#L-705"><span class="linenos"> 705</span></a> <span class="c1"># Save metadata</span>
</span><span id="L-706"><a href="#L-706"><span class="linenos"> 706</span></a> <span class="n">meta</span> <span class="o">=</span> <span class="p">{</span>
</span><span id="L-707"><a href="#L-707"><span class="linenos"> 707</span></a> <span class="s2">"phase"</span><span class="p">:</span> <span class="mi">1</span><span class="p">,</span>
</span><span id="L-708"><a href="#L-708"><span class="linenos"> 708</span></a> <span class="s2">"description"</span><span class="p">:</span> <span class="s2">"Parameter sweep for critical point"</span><span class="p">,</span>
</span><span id="L-709"><a href="#L-709"><span class="linenos"> 709</span></a> <span class="s2">"n_sims"</span><span class="p">:</span> <span class="nb">len</span><span class="p">(</span><span class="n">all_results</span><span class="p">),</span>
</span><span id="L-710"><a href="#L-710"><span class="linenos"> 710</span></a> <span class="s2">"timestamp"</span><span class="p">:</span> <span class="n">time</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s2">"%Y-%m-</span><span class="si">%d</span><span class="s2"> %H:%M:%S"</span><span class="p">),</span>
</span><span id="L-711"><a href="#L-711"><span class="linenos"> 711</span></a> <span class="s2">"config"</span><span class="p">:</span> <span class="n">asdict</span><span class="p">(</span><span class="n">cfg</span><span class="p">),</span>
</span><span id="L-712"><a href="#L-712"><span class="linenos"> 712</span></a> <span class="p">}</span>
</span><span id="L-713"><a href="#L-713"><span class="linenos"> 713</span></a> <span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">output_dir</span> <span class="o">/</span> <span class="s2">"phase1_metadata.json"</span><span class="p">,</span> <span class="s2">"w"</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
</span><span id="L-714"><a href="#L-714"><span class="linenos"> 714</span></a> <span class="n">json</span><span class="o">.</span><span class="n">dump</span><span class="p">(</span><span class="n">meta</span><span class="p">,</span> <span class="n">f</span><span class="p">,</span> <span class="n">indent</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="nb">str</span><span class="p">)</span>
</span><span id="L-715"><a href="#L-715"><span class="linenos"> 715</span></a>
</span><span id="L-716"><a href="#L-716"><span class="linenos"> 716</span></a> <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Phase 1 complete. Results: </span><span class="si">{</span><span class="n">output_jsonl</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
</span><span id="L-717"><a href="#L-717"><span class="linenos"> 717</span></a> <span class="k">return</span> <span class="n">all_results</span>
</span><span id="L-718"><a href="#L-718"><span class="linenos"> 718</span></a>
</span><span id="L-719"><a href="#L-719"><span class="linenos"> 719</span></a>
</span><span id="L-720"><a href="#L-720"><span class="linenos"> 720</span></a><span class="k">def</span><span class="w"> </span><span class="nf">run_phase2</span><span class="p">(</span><span class="n">cfg</span><span class="p">:</span> <span class="n">Config</span><span class="p">,</span> <span class="n">output_dir</span><span class="p">:</span> <span class="n">Path</span><span class="p">,</span> <span class="n">logger</span><span class="p">:</span> <span class="n">logging</span><span class="o">.</span><span class="n">Logger</span><span class="p">)</span> <span class="o">-></span> <span class="n">List</span><span class="p">[</span><span class="n">Dict</span><span class="p">]:</span>
</span><span id="L-721"><a href="#L-721"><span class="linenos"> 721</span></a><span class="w"> </span><span class="sd">"""</span>
</span><span id="L-722"><a href="#L-722"><span class="linenos"> 722</span></a><span class="sd"> Execute Phase 2 of the simulation: self-organization and criticality analysis.</span>
</span><span id="L-723"><a href="#L-723"><span class="linenos"> 723</span></a>
</span><span id="L-724"><a href="#L-724"><span class="linenos"> 724</span></a><span class="sd"> This phase tests the Self-Organized Criticality (SOC) hypothesis by</span>
</span><span id="L-725"><a href="#L-725"><span class="linenos"> 725</span></a><span class="sd"> initializing simulations at different points in the parameter space and</span>
</span><span id="L-726"><a href="#L-726"><span class="linenos"> 726</span></a><span class="sd"> observing whether evolutionary pressure drives the system toward a</span>
</span><span id="L-727"><a href="#L-727"><span class="linenos"> 727</span></a><span class="sd"> common critical point, regardless of initial prey mortality rates.</span>
</span><span id="L-728"><a href="#L-728"><span class="linenos"> 728</span></a>
</span><span id="L-729"><a href="#L-729"><span class="linenos"> 729</span></a><span class="sd"> Parameters</span>
</span><span id="L-730"><a href="#L-730"><span class="linenos"> 730</span></a><span class="sd"> ----------</span>
</span><span id="L-731"><a href="#L-731"><span class="linenos"> 731</span></a><span class="sd"> cfg : Config</span>
</span><span id="L-732"><a href="#L-732"><span class="linenos"> 732</span></a><span class="sd"> Configuration object containing simulation hyperparameters, evolution</span>
</span><span id="L-733"><a href="#L-733"><span class="linenos"> 733</span></a><span class="sd"> settings, and execution constraints.</span>
</span><span id="L-734"><a href="#L-734"><span class="linenos"> 734</span></a><span class="sd"> output_dir : Path</span>
</span><span id="L-735"><a href="#L-735"><span class="linenos"> 735</span></a><span class="sd"> Directory where result files (JSONL) and metadata (JSON) will be stored.</span>
</span><span id="L-736"><a href="#L-736"><span class="linenos"> 736</span></a><span class="sd"> logger : logging.Logger</span>
</span><span id="L-737"><a href="#L-737"><span class="linenos"> 737</span></a><span class="sd"> Logger instance for tracking progress and evolutionary convergence.</span>
</span><span id="L-738"><a href="#L-738"><span class="linenos"> 738</span></a>
</span><span id="L-739"><a href="#L-739"><span class="linenos"> 739</span></a><span class="sd"> Returns</span>
</span><span id="L-740"><a href="#L-740"><span class="linenos"> 740</span></a><span class="sd"> -------</span>
</span><span id="L-741"><a href="#L-741"><span class="linenos"> 741</span></a><span class="sd"> all_results : list of dict</span>
</span><span id="L-742"><a href="#L-742"><span class="linenos"> 742</span></a><span class="sd"> A list of dictionaries containing metrics from the evolutionary</span>
</span><span id="L-743"><a href="#L-743"><span class="linenos"> 743</span></a><span class="sd"> simulation runs.</span>
</span><span id="L-744"><a href="#L-744"><span class="linenos"> 744</span></a>
</span><span id="L-745"><a href="#L-745"><span class="linenos"> 745</span></a><span class="sd"> Notes</span>
</span><span id="L-746"><a href="#L-746"><span class="linenos"> 746</span></a><span class="sd"> -----</span>
</span><span id="L-747"><a href="#L-747"><span class="linenos"> 747</span></a><span class="sd"> The function captures:</span>
</span><span id="L-748"><a href="#L-748"><span class="linenos"> 748</span></a><span class="sd"> 1. Convergence of 'prey_death' across multiple replicates.</span>
</span><span id="L-749"><a href="#L-749"><span class="linenos"> 749</span></a><span class="sd"> 2. Final steady-state population distributions.</span>
</span><span id="L-750"><a href="#L-750"><span class="linenos"> 750</span></a><span class="sd"> 3. Incremental saving of results to prevent data loss.</span>
</span><span id="L-751"><a href="#L-751"><span class="linenos"> 751</span></a><span class="sd"> """</span>
</span><span id="L-752"><a href="#L-752"><span class="linenos"> 752</span></a> <span class="kn">from</span><span class="w"> </span><span class="nn">joblib</span><span class="w"> </span><span class="kn">import</span> <span class="n">Parallel</span><span class="p">,</span> <span class="n">delayed</span>
</span><span id="L-753"><a href="#L-753"><span class="linenos"> 753</span></a>
</span><span id="L-754"><a href="#L-754"><span class="linenos"> 754</span></a> <span class="n">warmup_numba_kernels</span><span class="p">(</span><span class="n">cfg</span><span class="o">.</span><span class="n">grid_size</span><span class="p">,</span> <span class="n">directed_hunting</span><span class="o">=</span><span class="n">cfg</span><span class="o">.</span><span class="n">directed_hunting</span><span class="p">)</span>
</span><span id="L-755"><a href="#L-755"><span class="linenos"> 755</span></a>
</span><span id="L-756"><a href="#L-756"><span class="linenos"> 756</span></a> <span class="c1"># Test at multiple prey_birth values</span>
</span><span id="L-757"><a href="#L-757"><span class="linenos"> 757</span></a> <span class="n">pb</span> <span class="o">=</span> <span class="mf">0.2</span>
</span><span id="L-758"><a href="#L-758"><span class="linenos"> 758</span></a> <span class="c1"># Vary intial prey_death</span>
</span><span id="L-759"><a href="#L-759"><span class="linenos"> 759</span></a> <span class="n">initial_prey_deaths</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span>
</span><span id="L-760"><a href="#L-760"><span class="linenos"> 760</span></a> <span class="n">cfg</span><span class="o">.</span><span class="n">prey_death_range</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">cfg</span><span class="o">.</span><span class="n">prey_death_range</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">cfg</span><span class="o">.</span><span class="n">n_prey_death</span>
</span><span id="L-761"><a href="#L-761"><span class="linenos"> 761</span></a> <span class="p">)</span>
</span><span id="L-762"><a href="#L-762"><span class="linenos"> 762</span></a>
</span><span id="L-763"><a href="#L-763"><span class="linenos"> 763</span></a> <span class="n">jobs</span> <span class="o">=</span> <span class="p">[]</span>
</span><span id="L-764"><a href="#L-764"><span class="linenos"> 764</span></a> <span class="k">for</span> <span class="n">initial_pd</span> <span class="ow">in</span> <span class="n">initial_prey_deaths</span><span class="p">:</span>
</span><span id="L-765"><a href="#L-765"><span class="linenos"> 765</span></a> <span class="k">for</span> <span class="n">rep</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">cfg</span><span class="o">.</span><span class="n">n_replicates</span><span class="p">):</span>
</span><span id="L-766"><a href="#L-766"><span class="linenos"> 766</span></a> <span class="n">params</span> <span class="o">=</span> <span class="p">{</span><span class="s2">"pb"</span><span class="p">:</span> <span class="n">pb</span><span class="p">,</span> <span class="s2">"initial_pd"</span><span class="p">:</span> <span class="n">initial_pd</span><span class="p">,</span> <span class="s2">"phase"</span><span class="p">:</span> <span class="mi">2</span><span class="p">}</span>
</span><span id="L-767"><a href="#L-767"><span class="linenos"> 767</span></a> <span class="n">seed</span> <span class="o">=</span> <span class="n">generate_unique_seed</span><span class="p">(</span><span class="n">params</span><span class="p">,</span> <span class="n">rep</span><span class="p">)</span>
</span><span id="L-768"><a href="#L-768"><span class="linenos"> 768</span></a> <span class="n">jobs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span>
</span><span id="L-769"><a href="#L-769"><span class="linenos"> 769</span></a> <span class="p">(</span>
</span><span id="L-770"><a href="#L-770"><span class="linenos"> 770</span></a> <span class="n">pb</span><span class="p">,</span>
</span><span id="L-771"><a href="#L-771"><span class="linenos"> 771</span></a> <span class="n">initial_pd</span><span class="p">,</span>
</span><span id="L-772"><a href="#L-772"><span class="linenos"> 772</span></a> <span class="n">cfg</span><span class="o">.</span><span class="n">predator_birth</span><span class="p">,</span>
</span><span id="L-773"><a href="#L-773"><span class="linenos"> 773</span></a> <span class="n">cfg</span><span class="o">.</span><span class="n">predator_death</span><span class="p">,</span>
</span><span id="L-774"><a href="#L-774"><span class="linenos"> 774</span></a> <span class="n">cfg</span><span class="o">.</span><span class="n">grid_size</span><span class="p">,</span>
</span><span id="L-775"><a href="#L-775"><span class="linenos"> 775</span></a> <span class="n">seed</span><span class="p">,</span>
</span><span id="L-776"><a href="#L-776"><span class="linenos"> 776</span></a> <span class="n">cfg</span><span class="p">,</span>
</span><span id="L-777"><a href="#L-777"><span class="linenos"> 777</span></a> <span class="kc">True</span><span class="p">,</span>
</span><span id="L-778"><a href="#L-778"><span class="linenos"> 778</span></a> <span class="p">)</span>
</span><span id="L-779"><a href="#L-779"><span class="linenos"> 779</span></a> <span class="p">)</span>
</span><span id="L-780"><a href="#L-780"><span class="linenos"> 780</span></a>
</span><span id="L-781"><a href="#L-781"><span class="linenos"> 781</span></a> <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Phase 2: </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">jobs</span><span class="p">)</span><span class="si">:</span><span class="s2">,</span><span class="si">}</span><span class="s2"> simulations"</span><span class="p">)</span>
</span><span id="L-782"><a href="#L-782"><span class="linenos"> 782</span></a> <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s2">" prey_birth value: </span><span class="si">{</span><span class="n">pb</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
</span><span id="L-783"><a href="#L-783"><span class="linenos"> 783</span></a> <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s2">" initial prey_death values: </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">initial_prey_deaths</span><span class="p">)</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
</span><span id="L-784"><a href="#L-784"><span class="linenos"> 784</span></a> <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s2">" Replicates: </span><span class="si">{</span><span class="n">cfg</span><span class="o">.</span><span class="n">n_replicates</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
</span><span id="L-785"><a href="#L-785"><span class="linenos"> 785</span></a>
</span><span id="L-786"><a href="#L-786"><span class="linenos"> 786</span></a> <span class="n">output_jsonl</span> <span class="o">=</span> <span class="n">output_dir</span> <span class="o">/</span> <span class="s2">"phase2_results.jsonl"</span>
</span><span id="L-787"><a href="#L-787"><span class="linenos"> 787</span></a> <span class="n">all_results</span> <span class="o">=</span> <span class="p">[]</span>
</span><span id="L-788"><a href="#L-788"><span class="linenos"> 788</span></a>
</span><span id="L-789"><a href="#L-789"><span class="linenos"> 789</span></a> <span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">output_jsonl</span><span class="p">,</span> <span class="s2">"w"</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="s2">"utf-8"</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
</span><span id="L-790"><a href="#L-790"><span class="linenos"> 790</span></a> <span class="n">executor</span> <span class="o">=</span> <span class="n">Parallel</span><span class="p">(</span><span class="n">n_jobs</span><span class="o">=</span><span class="n">cfg</span><span class="o">.</span><span class="n">n_jobs</span><span class="p">,</span> <span class="n">return_as</span><span class="o">=</span><span class="s2">"generator"</span><span class="p">)</span>
</span><span id="L-791"><a href="#L-791"><span class="linenos"> 791</span></a> <span class="n">tasks</span> <span class="o">=</span> <span class="p">(</span><span class="n">delayed</span><span class="p">(</span><span class="n">run_single_simulation</span><span class="p">)(</span><span class="o">*</span><span class="n">job</span><span class="p">)</span> <span class="k">for</span> <span class="n">job</span> <span class="ow">in</span> <span class="n">jobs</span><span class="p">)</span>
</span><span id="L-792"><a href="#L-792"><span class="linenos"> 792</span></a>
</span><span id="L-793"><a href="#L-793"><span class="linenos"> 793</span></a> <span class="k">for</span> <span class="n">result</span> <span class="ow">in</span> <span class="n">tqdm</span><span class="p">(</span><span class="n">executor</span><span class="p">(</span><span class="n">tasks</span><span class="p">),</span> <span class="n">total</span><span class="o">=</span><span class="nb">len</span><span class="p">(</span><span class="n">jobs</span><span class="p">),</span> <span class="n">desc</span><span class="o">=</span><span class="s2">"Phase 2"</span><span class="p">):</span>
</span><span id="L-794"><a href="#L-794"><span class="linenos"> 794</span></a> <span class="n">f</span><span class="o">.</span><span class="n">write</span><span class="p">(</span><span class="n">json</span><span class="o">.</span><span class="n">dumps</span><span class="p">(</span><span class="n">result</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="nb">str</span><span class="p">)</span> <span class="o">+</span> <span class="s2">"</span><span class="se">\n</span><span class="s2">"</span><span class="p">)</span>
</span><span id="L-795"><a href="#L-795"><span class="linenos"> 795</span></a> <span class="n">f</span><span class="o">.</span><span class="n">flush</span><span class="p">()</span>
</span><span id="L-796"><a href="#L-796"><span class="linenos"> 796</span></a> <span class="n">all_results</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">result</span><span class="p">)</span>
</span><span id="L-797"><a href="#L-797"><span class="linenos"> 797</span></a>
</span><span id="L-798"><a href="#L-798"><span class="linenos"> 798</span></a> <span class="n">meta</span> <span class="o">=</span> <span class="p">{</span>
</span><span id="L-799"><a href="#L-799"><span class="linenos"> 799</span></a> <span class="s2">"phase"</span><span class="p">:</span> <span class="mi">2</span><span class="p">,</span>
</span><span id="L-800"><a href="#L-800"><span class="linenos"> 800</span></a> <span class="s2">"description"</span><span class="p">:</span> <span class="s2">"Self-organization toward criticality"</span><span class="p">,</span>
</span><span id="L-801"><a href="#L-801"><span class="linenos"> 801</span></a> <span class="s2">"n_sims"</span><span class="p">:</span> <span class="nb">len</span><span class="p">(</span><span class="n">all_results</span><span class="p">),</span>
</span><span id="L-802"><a href="#L-802"><span class="linenos"> 802</span></a> <span class="s2">"initial_prey_deaths"</span><span class="p">:</span> <span class="n">initial_prey_deaths</span><span class="o">.</span><span class="n">tolist</span><span class="p">(),</span>
</span><span id="L-803"><a href="#L-803"><span class="linenos"> 803</span></a> <span class="s2">"timestamp"</span><span class="p">:</span> <span class="n">time</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s2">"%Y-%m-</span><span class="si">%d</span><span class="s2"> %H:%M:%S"</span><span class="p">),</span>
</span><span id="L-804"><a href="#L-804"><span class="linenos"> 804</span></a> <span class="p">}</span>
</span><span id="L-805"><a href="#L-805"><span class="linenos"> 805</span></a> <span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">output_dir</span> <span class="o">/</span> <span class="s2">"phase2_metadata.json"</span><span class="p">,</span> <span class="s2">"w"</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
</span><span id="L-806"><a href="#L-806"><span class="linenos"> 806</span></a> <span class="n">json</span><span class="o">.</span><span class="n">dump</span><span class="p">(</span><span class="n">meta</span><span class="p">,</span> <span class="n">f</span><span class="p">,</span> <span class="n">indent</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="nb">str</span><span class="p">)</span>
</span><span id="L-807"><a href="#L-807"><span class="linenos"> 807</span></a>
</span><span id="L-808"><a href="#L-808"><span class="linenos"> 808</span></a> <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Phase 2 complete. Results: </span><span class="si">{</span><span class="n">output_jsonl</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
</span><span id="L-809"><a href="#L-809"><span class="linenos"> 809</span></a> <span class="k">return</span> <span class="n">all_results</span>
</span><span id="L-810"><a href="#L-810"><span class="linenos"> 810</span></a>
</span><span id="L-811"><a href="#L-811"><span class="linenos"> 811</span></a>
</span><span id="L-812"><a href="#L-812"><span class="linenos"> 812</span></a><span class="k">def</span><span class="w"> </span><span class="nf">run_phase3</span><span class="p">(</span><span class="n">cfg</span><span class="p">:</span> <span class="n">Config</span><span class="p">,</span> <span class="n">output_dir</span><span class="p">:</span> <span class="n">Path</span><span class="p">,</span> <span class="n">logger</span><span class="p">:</span> <span class="n">logging</span><span class="o">.</span><span class="n">Logger</span><span class="p">)</span> <span class="o">-></span> <span class="n">List</span><span class="p">[</span><span class="n">Dict</span><span class="p">]:</span>
</span><span id="L-813"><a href="#L-813"><span class="linenos"> 813</span></a><span class="w"> </span><span class="sd">"""</span>
</span><span id="L-814"><a href="#L-814"><span class="linenos"> 814</span></a><span class="sd"> Phase 3: Finite-size scaling at critical point.</span>
</span><span id="L-815"><a href="#L-815"><span class="linenos"> 815</span></a>
</span><span id="L-816"><a href="#L-816"><span class="linenos"> 816</span></a><span class="sd"> - Multiple grid sizes at (critical_prey_birth, critical_prey_death)</span>
</span><span id="L-817"><a href="#L-817"><span class="linenos"> 817</span></a><span class="sd"> - Analyze cluster size cutoffs vs L</span>
</span><span id="L-818"><a href="#L-818"><span class="linenos"> 818</span></a><span class="sd"> """</span>
</span><span id="L-819"><a href="#L-819"><span class="linenos"> 819</span></a> <span class="kn">from</span><span class="w"> </span><span class="nn">joblib</span><span class="w"> </span><span class="kn">import</span> <span class="n">Parallel</span><span class="p">,</span> <span class="n">delayed</span>
</span><span id="L-820"><a href="#L-820"><span class="linenos"> 820</span></a>
</span><span id="L-821"><a href="#L-821"><span class="linenos"> 821</span></a> <span class="c1"># NOTE: Tuned to critical points from phase 1</span>
</span><span id="L-822"><a href="#L-822"><span class="linenos"> 822</span></a> <span class="n">pb</span> <span class="o">=</span> <span class="n">cfg</span><span class="o">.</span><span class="n">critical_prey_birth</span>
</span><span id="L-823"><a href="#L-823"><span class="linenos"> 823</span></a> <span class="n">pd</span> <span class="o">=</span> <span class="n">cfg</span><span class="o">.</span><span class="n">critical_prey_death</span>
</span><span id="L-824"><a href="#L-824"><span class="linenos"> 824</span></a>
</span><span id="L-825"><a href="#L-825"><span class="linenos"> 825</span></a> <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Phase 3: FSS at critical point (pb=</span><span class="si">{</span><span class="n">pb</span><span class="si">}</span><span class="s2">, pd=</span><span class="si">{</span><span class="n">pd</span><span class="si">}</span><span class="s2">)"</span><span class="p">)</span>
</span><span id="L-826"><a href="#L-826"><span class="linenos"> 826</span></a>
</span><span id="L-827"><a href="#L-827"><span class="linenos"> 827</span></a> <span class="k">for</span> <span class="n">L</span> <span class="ow">in</span> <span class="n">cfg</span><span class="o">.</span><span class="n">grid_sizes</span><span class="p">:</span>
</span><span id="L-828"><a href="#L-828"><span class="linenos"> 828</span></a> <span class="n">warmup_numba_kernels</span><span class="p">(</span><span class="n">L</span><span class="p">,</span> <span class="n">directed_hunting</span><span class="o">=</span><span class="n">cfg</span><span class="o">.</span><span class="n">directed_hunting</span><span class="p">)</span>
</span><span id="L-829"><a href="#L-829"><span class="linenos"> 829</span></a>
</span><span id="L-830"><a href="#L-830"><span class="linenos"> 830</span></a> <span class="n">jobs</span> <span class="o">=</span> <span class="p">[]</span>
</span><span id="L-831"><a href="#L-831"><span class="linenos"> 831</span></a> <span class="k">for</span> <span class="n">L</span> <span class="ow">in</span> <span class="n">cfg</span><span class="o">.</span><span class="n">grid_sizes</span><span class="p">:</span> <span class="c1"># Sweep through grid sizes</span>