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tests/test_logistic.py

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+import numpy as np
+
+import growthcurves as gc
+
+
+def logistic_growth(t, baseline, N0, K, mu, lag):
+    """Logistic growth model with smooth transition through lag phase"""
+    # Standard logistic formula centered at lag time
+    # This creates a smooth S-curve with inflection point at t = lag + (K - N0) / N0
+    factor = (K - N0) / N0
+    growth = K / (1 + factor * np.exp(-mu * (t - lag)))
+    return baseline + growth, lag + np.log(factor) / mu
+
+
+def test_fit_parametric():
+    np.random.seed(42)
+    expected = {
+        "params": {
+            "mu": 0.1499259523503361,
+            "K": 0.4499768424238933,
+            "N0": 0.0006250371640236538,
+            "y0": 0.05000966836757205,
+            "fit_t_min": 0.0,
+            "fit_t_max": 87.8,
+        },
+        "model_type": "mech_logistic",
+    }
+    expected = expected["params"]
+    # Test that the function returns expected values for known parameters
+    n_points = 440
+    measurement_interval_minutes = 12
+    t = np.array([(measurement_interval_minutes * n) / 60 for n in range(n_points)])
+    K = 0.45
+    mu = 0.15
+    N0 = 0.05
+    baseline = N0
+    lag = 30.0
+    N, _ = logistic_growth(t, baseline=baseline, N0=N0, K=K, mu=mu, lag=lag)
+    actual = gc.parametric.fit_parametric(t, N, method="mech_logistic")
+    actual = actual["params"]
+    for k, v in expected.items():
+        assert k in actual, f"Parameter {k} not found in actual output"
+        assert np.isclose(actual[k], v), f"Parameter {k} does not match expected value"