Merge pull request #45 from biosustain/fix_sphinx_docs

📝 Fix documentation

Author: enryH

docs/tutorial/analysis.ipynb

@@ -107,7 +107,7 @@
     "    N,\n",
     "    model_family=\"all\",  # Include mechanistic, phenomenological, and non-parametric\n",
     "    phase_boundary_method=\"tangent\",  # tangent or threshold\n",
-    "    spline_s=0.2,\n",
+    "    spline=0.2,\n",
     "    window_points=7,\n",
     ")\n",
     "\n",
@@ -245,7 +245,7 @@
     "    N,\n",
     "    model_family=\"all\",  # Include mechanistic, phenomenological, and non-parametric\n",
     "    phase_boundary_method=\"tangent\",  # tangent or threshold\n",
-    "    spline_s=0.2,\n",
+    "    spline=0.2,\n",
     "    window_points=7,\n",
     ")\n",
     "\n",
@@ -325,7 +325,7 @@
    "source": [
     "# Phase boundary comparison on spline fit\n",
     "fit_spline = gc.non_parametric.fit_non_parametric(\n",
-    "    t, N, method=\"spline\", spline_s=0.2, window_points=7\n",
+    "    t, N, method=\"spline\", spline=0.2, window_points=7\n",
     ")\n",
     "\n",
     "phase_boundary_rows = []\n",

docs/tutorial/plotting.ipynb

@@ -6,12 +6,16 @@
 All methods operate in linear OD space (not log-transformed).
 """
 
+from logging import getLogger
+
 import numpy as np
 from scipy.interpolate import make_smoothing_spline
 from scipy.stats import theilslopes
 
 from .inference import bad_fit_stats
 
+logger = getLogger(__name__)
+
 # Default settings for the auto-spline (sigma-based smoothing + OD weights).
 _SPLINE_SMOOTH_MULT = 5.0
 _SPLINE_GCV_WEIGHT_FLOOR_Q = 0.15
@@ -27,7 +31,7 @@
 # -----------------------------------------------------------------------------
 
 
-def fit_sliding_window(t, N, window_points=15, step=None, n_fits=None):
+def fit_sliding_window(t, N, window_points=15, step=None, n_fits=None, **kwargs):
     """
     Calculate maximum specific growth rate using the sliding window method.
 
@@ -54,6 +58,8 @@ def fit_sliding_window(t, N, window_points=15, step=None, n_fits=None):
         Returns None if calculation fails.
 
     """
+    if kwargs:
+        logger.warning("fit_sliding_window received unused kwargs: %s", kwargs)
     if len(t) < window_points or np.ptp(t) <= 0:
         return None