ReNunney/tests/test_track1_analysis.py

import sys
from dataclasses import dataclass
from pathlib import Path

ROOT = Path(__file__).resolve().parents[1]
SRC_DIR = ROOT / "src"
if str(SRC_DIR) not in sys.path:
    sys.path.insert(0, str(SRC_DIR))

import renunney.track1_analysis as analysis
import renunney.track1_api as api

from track1_reference import GenerationSummary, Track1Parameters


def test_fit_linear_cost_by_loci_recovers_line():
    rows = [
        analysis.LocusThresholdRow(n=1, threshold_T=12.0, accepted=True),
        analysis.LocusThresholdRow(n=2, threshold_T=14.0, accepted=True),
        analysis.LocusThresholdRow(n=3, threshold_T=16.0, accepted=True),
    ]
    fit = analysis.fit_linear_cost_by_loci(rows)
    assert fit is not None
    assert abs(fit.intercept_c0 - 10.0) < 1e-9
    assert abs(fit.slope_c1 - 2.0) < 1e-9


def test_sweep_number_of_loci_uses_search_results(monkeypatch):
    params = Track1Parameters(K=5000, N0=20, n=1, u=5e-6, R=10.0, T=20)

    class Dummy:
        def __init__(self, threshold_T):
            self.threshold_T = threshold_T

    def fake_search(params, candidate_T_values, runs=20, seed_start=0, cache_path=None, jobs=1):
        return Dummy(threshold_T=10.0 + params.n)

    monkeypatch.setattr(analysis, "search_threshold_over_candidates", fake_search)
    sweep = analysis.sweep_number_of_loci(params, [1, 2, 3], [10, 20, 30], runs=2, seed_start=1, jobs=3)
    assert [row.threshold_T for row in sweep.rows] == [11.0, 12.0, 13.0]
    assert sweep.fit is not None


def test_run_config_loci_regression_mode(monkeypatch):
    @dataclass(frozen=True)
    class DummyFit:
        intercept_c0: float = 5.0
        slope_c1: float = 2.0
        r_squared: float = 1.0
        points_used: int = 3

    class DummySweep:
        rows = [
            analysis.LocusThresholdRow(n=1, threshold_T=7.0, accepted=True),
            analysis.LocusThresholdRow(n=2, threshold_T=9.0, accepted=True),
            analysis.LocusThresholdRow(n=3, threshold_T=11.0, accepted=True),
        ]
        fit = DummyFit()

    monkeypatch.setattr(api, "sweep_number_of_loci", lambda *args, **kwargs: DummySweep())
    config = api.Track1RunConfig(
        mode="loci_regression",
        loci_values=[1, 2, 3],
        t_start=10,
        t_stop=30,
        t_step=10,
        runs=2,
    )
    payload = api.run_config(config)
    assert payload["mode"] == "loci_regression"
    assert payload["loci_values"] == [1, 2, 3]
    assert payload["fit"]["slope_c1"] == 2.0


def test_summarize_tracking_detects_post_initial_nonzero_alleles():
    summaries = [
        GenerationSummary(
            t=-2,
            N=10,
            female_fraction=0.5,
            male_count=5,
            female_count=5,
            fecundity=1.0,
            mean_fitness=1.0,
            mean_expected_female_productivity=1.0,
            target_value=-0.1,
            mean_allele_value=0.0,
            mean_genotype_value=0.0,
            mean_tracking_gap=0.1,
            paper_M=0.05,
            expected_mutations_current_N=0.0001,
            realized_mutation_count=0,
            realized_mutation_rate_per_allele=0.0,
            birth_count=0,
            surviving_offspring_count=0,
            ne_approx=5.0,
            extinct=False,
        ),
        GenerationSummary(
            t=-1,
            N=10,
            female_fraction=0.5,
            male_count=5,
            female_count=5,
            fecundity=1.0,
            mean_fitness=1.0,
            mean_expected_female_productivity=1.0,
            target_value=-0.05,
            mean_allele_value=0.2,
            mean_genotype_value=0.2,
            mean_tracking_gap=0.25,
            paper_M=0.05,
            expected_mutations_current_N=0.0001,
            realized_mutation_count=1,
            realized_mutation_rate_per_allele=0.05,
            birth_count=2,
            surviving_offspring_count=1,
            ne_approx=5.0,
            extinct=False,
        ),
    ]
    tracking = analysis.summarize_tracking(summaries)
    assert tracking.extinction_occurred is False
    assert tracking.first_extinction_t is None
    assert tracking.first_nonzero_allele_t == -1
    assert tracking.last_nonzero_allele_t == -1
    assert tracking.stayed_zero_after_initialization is False


def test_summarize_tracking_detects_extinction_time():
    summaries = [
        GenerationSummary(
            t=0,
            N=10,
            female_fraction=0.5,
            male_count=5,
            female_count=5,
            fecundity=1.0,
            mean_fitness=1.0,
            mean_expected_female_productivity=1.0,
            target_value=0.0,
            mean_allele_value=0.0,
            mean_genotype_value=0.0,
            mean_tracking_gap=0.0,
            paper_M=0.05,
            expected_mutations_current_N=0.0001,
            realized_mutation_count=0,
            realized_mutation_rate_per_allele=0.0,
            birth_count=0,
            surviving_offspring_count=0,
            ne_approx=5.0,
            extinct=False,
        ),
        GenerationSummary(
            t=1,
            N=0,
            female_fraction=0.0,
            male_count=0,
            female_count=0,
            fecundity=0.0,
            mean_fitness=0.0,
            mean_expected_female_productivity=0.0,
            target_value=0.1,
            mean_allele_value=0.0,
            mean_genotype_value=0.0,
            mean_tracking_gap=-0.1,
            paper_M=0.05,
            expected_mutations_current_N=0.0,
            realized_mutation_count=0,
            realized_mutation_rate_per_allele=0.0,
            birth_count=0,
            surviving_offspring_count=0,
            ne_approx=0.0,
            extinct=True,
        ),
    ]
    tracking = analysis.summarize_tracking(summaries)
    assert tracking.extinction_occurred is True
    assert tracking.first_extinction_t == 1