Normalize times for performance table times

Author: uriahf

src/rtichoke/performance_table.py

@@ -100,14 +100,21 @@ def create_performance_table_times(
     Numerical results come from ``prepare_performance_data_times()``. The table
     keeps time horizon and censoring/competing-event heuristics visible so that
     multiple requested evaluation scenarios are not collapsed in presentation.
-    Integer horizon values are normalized to floats to match the time-dependent
-    performance pipeline's join-key schema.
+    Observed times and fixed horizons are normalized to floats to match the
+    time-dependent performance pipeline's join-key schema.
     """
     normalized_horizons = [float(horizon) for horizon in fixed_time_horizons]
+    if isinstance(times, dict):
+        normalized_times = {
+            key: np.asarray(value, dtype=float) for key, value in times.items()
+        }
+    else:
+        normalized_times = np.asarray(times, dtype=float)
+
     performance_data = prepare_performance_data_times(
         probs=probs,
         reals=reals,
-        times=times,
+        times=normalized_times,
         fixed_time_horizons=normalized_horizons,
         heuristics_sets=heuristics_sets,
         by=by,