Silence the benign all-NaN-imputer warning at source (tau_projected before the curve exists); message-targeted so real warnings stay visible

batteryswap_example/models_cv.py

@@ -30,6 +30,15 @@ import warnings
 import numpy as np
 import pandas as pd
 
+# Benign and expected: tau_projected (and occasionally other physics columns)
+# is all-NaN at the earliest origins, before the master curve exists; the
+# imputer skips the column, which has been the accepted behavior since the
+# feature was added (phase 6). One fit per origin per fold prints it, so an
+# all48oof run emits it ~290 times - silence THIS message only, so real
+# warnings stay visible.
+warnings.filterwarnings(
+    'ignore', message='Skipping features without any observed values')
+
 from sklearn.impute import SimpleImputer
 from sklearn.preprocessing import StandardScaler
 from sklearn.pipeline import make_pipeline