Good progress

app/services/context_generator.py

@@ -707,10 +707,40 @@ class ContextGenerator:
                 formatted_ranges[category] = f"{min_val}-{max_val}bpm"
 
         return {
-            "age_range": f"{age_range} ({gender[0].upper()})",
+            "age_range": age_range,
             "ranges": formatted_ranges,
+            "raw_ranges": ranges,  # Keep raw ranges for category determination
         }
 
+    def _determine_rhr_category(self, rhr: float, age: int, gender: str) -> str:
+        """Determine resting heart rate category based on value, age, and gender (matching notebook logic)"""
+        rhr_table_info = self._calculate_rhr_table_data(age, gender)
+        ranges = rhr_table_info["raw_ranges"]
+
+        # Check Poor category first (open-ended at top)
+        min_val, max_val = ranges["Poor"]
+        if max_val is None and rhr >= min_val:
+            return "Poor"
+
+        # Check other categories from Below Average down to Athlete
+        # For RHR, lower is better, so we check from highest to lowest
+        for category in [
+            "Below Average",
+            "Average",
+            "Above Average",
+            "Good",
+            "Excellent",
+            "Athlete",
+        ]:
+            min_val, max_val = ranges[category]
+            # Check if value falls in this range (inclusive of min, exclusive of max)
+            if min_val <= rhr < max_val:
+                return category
+
+        # If value is below all ranges (below Athlete minimum), return Athlete
+        # This handles the case where rhr < min of Athlete
+        return "Athlete"
+
     def _calculate_zone_metrics(self, pnoe_metrics: Dict) -> Dict:
         """Calculate detailed metrics for each heart rate zone based on actual data"""
         import math
@@ -1294,14 +1324,24 @@ class ContextGenerator:
                 self.patient_info["age"], self.patient_info["gender"]
             )
 
-            gender_label = (
-                "Age (F)"
-                if self.patient_info["gender"].lower().startswith("f")
-                else "Age (M)"
+            # Get resting heart rate value and determine category
+            # Extract numeric value from "53bpm" format (resting_hr_metrics already calculated above)
+            rhr_value_str = resting_hr_metrics.get("resting_heart_rate", "0bpm")
+            rhr_value = float(rhr_value_str.replace("bpm", "").strip())
+
+            category = self._determine_rhr_category(
+                rhr_value,
+                self.patient_info["age"],
+                self.patient_info["gender"],
             )
 
+            gender_label = (
+                "F" if self.patient_info["gender"].lower().startswith("f") else "M"
+            )
+            age_range_label = f"{rhr_table_info['age_range']} ({gender_label})"
+
             rhr_columns = [
-                gender_label,
+                "Age",
                 "Poor",
                 "Below Average",
                 "Average",
@@ -1312,7 +1352,7 @@ class ContextGenerator:
             ]
             rhr_data = [
                 [
-                    rhr_table_info["age_range"],
+                    age_range_label,
                     rhr_table_info["ranges"]["Poor"],
                     rhr_table_info["ranges"]["Below Average"],
                     rhr_table_info["ranges"]["Average"],
@@ -1322,13 +1362,13 @@ class ContextGenerator:
                     rhr_table_info["ranges"]["Athlete"],
                 ]
             ]
-            rhr_colors = [["#b2ebf2"] + ["#f5f5f5"] * 7]
 
             contexts["page_11"]["rhr_table"] = (
                 graph_generator.generate_resting_heart_rate_table(
                     data=rhr_data,
                     columns=rhr_columns,
-                    cell_colors=rhr_colors,
+                    rhr_value=rhr_value,
+                    category=category,
                     save_as_base64=True,
                 )
             )