Checkpoint 3

app/main.py

@@ -9,6 +9,7 @@ import os
 import shutil
 import tempfile
 import uuid
+from datetime import datetime
 from pathlib import Path
 
 from fastapi import FastAPI, File, Form, HTTPException, Request, UploadFile
@@ -109,7 +110,6 @@ async def upload_files(
     gender: str = Form(...),
     fat_percentage: float = Form(...),
     focus: str = Form(default="Endurance"),
-    session_id: str = Form(default="default"),
     next_testing_date: str = Form(...),
     report_type: str = Form(default="full"),
     spirometry_pdf: UploadFile = File(...),
@@ -179,6 +179,10 @@ async def upload_files(
         # Prepare patient information
         patient_name = f"{first_name} {last_name}"
         print(f"DEBUG: Received next_testing_date: '{next_testing_date}'")
+
+        # Generate session_id internally using timestamp for unique identification
+        session_id = datetime.now().strftime("%Y%m%d_%H%M%S")
+
         patient_info = {
             "patient_name": patient_name,
             "first_name": first_name,
@@ -290,8 +294,18 @@ async def upload_files(
 @app.get("/preview", response_class=HTMLResponse)
 async def preview(request: Request):
     """Preview generated report"""
+    # Check for required session data
     if not request.session.get("report_path"):
         return RedirectResponse(url="/", status_code=303)
+
+    # Ensure metrics exist in session, initialize if missing
+    if "metrics" not in request.session:
+        request.session["metrics"] = {"pnoe": {}, "spirometry": {}}
+
+    # Ensure patient_info exists
+    if "patient_info" not in request.session:
+        request.session["patient_info"] = {}
+
     return render_template(
         "preview.html", {"request": request, "session": request.session}
     )
@@ -309,8 +323,16 @@ async def serve_graph(filename: str):
 @app.get("/edit", response_class=HTMLResponse)
 async def edit_form(request: Request):
     """Display edit metrics form"""
-    if not request.session.get("metrics"):
+    # Check for required session data
+    if not request.session.get("report_path") or not request.session.get(
+        "patient_info"
+    ):
         return RedirectResponse(url="/", status_code=303)
+
+    # Ensure metrics exist in session, initialize if missing
+    if "metrics" not in request.session:
+        request.session["metrics"] = {"pnoe": {}, "spirometry": {}}
+
     return render_template(
         "edit.html", {"request": request, "session": request.session}
     )
@@ -325,69 +347,117 @@ async def edit_metrics(request: Request):
     # Get form data
     form_data = await request.form()
 
+    # Helper function to safely convert form values to float
+    def safe_float(value):
+        """Convert form value to float, return None if empty or invalid"""
+        if not value or value.strip() == "":
+            return None
+        try:
+            return float(value)
+        except (ValueError, TypeError):
+            return None
+
     # Build metric overrides
     metric_overrides = {"pnoe": {}, "spirometry": {}}
 
-    # Pnoe overrides
-    if form_data.get("vo2_max"):
-        metric_overrides["pnoe"]["vo2_max"] = float(form_data["vo2_max"])
-    if form_data.get("vo2_max_per_kg"):
-        metric_overrides["pnoe"]["vo2_max_per_kg"] = float(form_data["vo2_max_per_kg"])
-    if form_data.get("peak_vt"):
-        metric_overrides["pnoe"]["peak_vt"] = float(form_data["peak_vt"])
-    if form_data.get("peak_vt_hr"):
-        metric_overrides["pnoe"]["peak_vt_hr"] = float(form_data["peak_vt_hr"])
-    if form_data.get("fat_max_value"):
-        metric_overrides["pnoe"]["fat_max_value"] = float(form_data["fat_max_value"])
-    if form_data.get("fat_max_hr"):
-        metric_overrides["pnoe"]["fat_max_hr"] = float(form_data["fat_max_hr"])
+    # Pnoe overrides - only add if value is provided and valid
+    vo2_max_val = safe_float(form_data.get("vo2_max"))
+    if vo2_max_val is not None:
+        metric_overrides["pnoe"]["vo2_max"] = vo2_max_val
 
-    # VT1 and VT2 overrides
-    if (
-        form_data.get("vt1_hr")
-        or form_data.get("vt1_speed")
-        or form_data.get("vt1_time")
-    ):
-        metric_overrides["pnoe"]["vt1"] = {
-            "HeartRate": float(form_data.get("vt1_hr", 0)),
-            "Speed": float(form_data.get("vt1_speed", 0)),
-            "Time": float(form_data.get("vt1_time", 0)),
+    vo2_max_per_kg_val = safe_float(form_data.get("vo2_max_per_kg"))
+    if vo2_max_per_kg_val is not None:
+        metric_overrides["pnoe"]["vo2_max_per_kg"] = vo2_max_per_kg_val
+
+    peak_vt_val = safe_float(form_data.get("peak_vt"))
+    if peak_vt_val is not None:
+        metric_overrides["pnoe"]["peak_vt"] = peak_vt_val
+
+    peak_vt_hr_val = safe_float(form_data.get("peak_vt_hr"))
+    if peak_vt_hr_val is not None:
+        metric_overrides["pnoe"]["peak_vt_hr"] = peak_vt_hr_val
+
+    fat_max_value_val = safe_float(form_data.get("fat_max_value"))
+    if fat_max_value_val is not None:
+        metric_overrides["pnoe"]["fat_max_value"] = fat_max_value_val
+
+    fat_max_hr_val = safe_float(form_data.get("fat_max_hr"))
+    if fat_max_hr_val is not None:
+        metric_overrides["pnoe"]["fat_max_hr"] = fat_max_hr_val
+
+    # VT1 and VT2 overrides - use existing values if not provided
+    existing_metrics = request.session.get("metrics", {})
+    existing_pnoe = existing_metrics.get("pnoe", {})
+    existing_vt1 = existing_pnoe.get("vt1", {})
+    existing_vt2 = existing_pnoe.get("vt2", {})
+
+    vt1_hr_val = safe_float(form_data.get("vt1_hr"))
+    vt1_speed_val = safe_float(form_data.get("vt1_speed"))
+    vt1_time_val = safe_float(form_data.get("vt1_time"))
+
+    if vt1_hr_val is not None or vt1_speed_val is not None or vt1_time_val is not None:
+        vt1_dict = {
+            "HeartRate": vt1_hr_val
+            if vt1_hr_val is not None
+            else existing_vt1.get("HeartRate", 0),
+            "Speed": vt1_speed_val
+            if vt1_speed_val is not None
+            else existing_vt1.get("Speed", 0),
+            "Time": vt1_time_val
+            if vt1_time_val is not None
+            else existing_vt1.get("Time", 0),
         }
+        metric_overrides["pnoe"]["vt1"] = vt1_dict
 
-    if (
-        form_data.get("vt2_hr")
-        or form_data.get("vt2_speed")
-        or form_data.get("vt2_time")
-    ):
-        metric_overrides["pnoe"]["vt2"] = {
-            "HeartRate": float(form_data.get("vt2_hr", 0)),
-            "Speed": float(form_data.get("vt2_speed", 0)),
-            "Time": float(form_data.get("vt2_time", 0)),
+    vt2_hr_val = safe_float(form_data.get("vt2_hr"))
+    vt2_speed_val = safe_float(form_data.get("vt2_speed"))
+    vt2_time_val = safe_float(form_data.get("vt2_time"))
+
+    if vt2_hr_val is not None or vt2_speed_val is not None or vt2_time_val is not None:
+        vt2_dict = {
+            "HeartRate": vt2_hr_val
+            if vt2_hr_val is not None
+            else existing_vt2.get("HeartRate", 0),
+            "Speed": vt2_speed_val
+            if vt2_speed_val is not None
+            else existing_vt2.get("Speed", 0),
+            "Time": vt2_time_val
+            if vt2_time_val is not None
+            else existing_vt2.get("Time", 0),
         }
+        metric_overrides["pnoe"]["vt2"] = vt2_dict
 
-    # Heart rate zones
+    # Heart rate zones - only add if value is provided
     for i in range(1, 6):
         zone_key = f"zone{i}_bpm"
-        if form_data.get(zone_key):
-            metric_overrides["pnoe"][zone_key] = form_data[zone_key]
+        zone_val = form_data.get(zone_key)
+        if zone_val and zone_val.strip():
+            metric_overrides["pnoe"][zone_key] = zone_val.strip()
 
-    # Spirometry overrides
-    if form_data.get("fvc_best"):
-        metric_overrides["spirometry"]["fvc_best"] = float(form_data["fvc_best"])
-    if form_data.get("fvc_pred"):
-        metric_overrides["spirometry"]["fvc_pred"] = float(form_data["fvc_pred"])
-    if form_data.get("fev1_best"):
-        metric_overrides["spirometry"]["fev1_best"] = float(form_data["fev1_best"])
-    if form_data.get("fev1_pred"):
-        metric_overrides["spirometry"]["fev1_pred"] = float(form_data["fev1_pred"])
-    if form_data.get("fev1_fvc_pct_best"):
-        metric_overrides["spirometry"]["fev1_fvc_pct_best"] = float(
-            form_data["fev1_fvc_pct_best"]
-        )
-    if form_data.get("fev1_fvc_pct_pred"):
-        metric_overrides["spirometry"]["fev1_fvc_pct_pred"] = float(
-            form_data["fev1_fvc_pct_pred"]
-        )
+    # Spirometry overrides - only add if value is provided and valid
+    fvc_best_val = safe_float(form_data.get("fvc_best"))
+    if fvc_best_val is not None:
+        metric_overrides["spirometry"]["fvc_best"] = fvc_best_val
+
+    fvc_pred_val = safe_float(form_data.get("fvc_pred"))
+    if fvc_pred_val is not None:
+        metric_overrides["spirometry"]["fvc_pred"] = fvc_pred_val
+
+    fev1_best_val = safe_float(form_data.get("fev1_best"))
+    if fev1_best_val is not None:
+        metric_overrides["spirometry"]["fev1_best"] = fev1_best_val
+
+    fev1_pred_val = safe_float(form_data.get("fev1_pred"))
+    if fev1_pred_val is not None:
+        metric_overrides["spirometry"]["fev1_pred"] = fev1_pred_val
+
+    fev1_fvc_pct_best_val = safe_float(form_data.get("fev1_fvc_pct_best"))
+    if fev1_fvc_pct_best_val is not None:
+        metric_overrides["spirometry"]["fev1_fvc_pct_best"] = fev1_fvc_pct_best_val
+
+    fev1_fvc_pct_pred_val = safe_float(form_data.get("fev1_fvc_pct_pred"))
+    if fev1_fvc_pct_pred_val is not None:
+        metric_overrides["spirometry"]["fev1_fvc_pct_pred"] = fev1_fvc_pct_pred_val
 
     try:
         # Get file paths from session
@@ -468,6 +538,7 @@ async def edit_metrics(request: Request):
             "fat_percentage": patient_info.get("fat_percentage", 0),
             "gender": patient_info.get("gender", "female"),
         }
+        # Calculate fat_mass and lean_mass (extract_patient_info does this when no SECA file)
         context_gen.extract_patient_info(patient_info.get("last_name", ""))
 
         spirometry_overrides = metric_overrides.get("spirometry", {})
@@ -514,7 +585,6 @@ async def generate_report(
     height: str = Form(..., description="Patient height (e.g., 5'4\")"),
     weight: str = Form(..., description="Patient weight (e.g., 123lbs)"),
     focus: str = Form(default="Endurance", description="Training focus"),
-    session_id: str = Form(default="default", description="Session ID"),
     spirometry_pdf: UploadFile = File(..., description="Spirometry PDF file"),
     pnoe_csv: UploadFile = File(..., description="Pnoe CSV file"),
     seca_excel: UploadFile = File(..., description="SECA Excel file"),
@@ -534,7 +604,6 @@ async def generate_report(
         height: Patient height
         weight: Patient weight
         focus: Training focus (default: Endurance)
-        session_id: Session identifier (default: default)
 
     Returns:
         ReportResponse with report path, graphs generated, and analysis data
@@ -571,6 +640,9 @@ async def generate_report(
             with open(seca_path, "wb") as f:
                 shutil.copyfileobj(seca_excel.file, f)
 
+            # Generate session_id internally using timestamp for unique identification
+            session_id = datetime.now().strftime("%Y%m%d_%H%M%S")
+
             # Prepare patient information
             patient_info = {
                 "patient_name": patient_name,

app/report_gen/page_19_20_minimal.html

@@ -471,3 +471,4 @@
 
 
 
+

app/report_gen/page_2.html

@@ -15,7 +15,8 @@
             <!-- Lung Analysis -->
             <div class="flex items-start bg-gray-200 h-24">
                 <div
-                    class="bg-black text-white text-2xl font-bold w-16 h-full flex items-center justify-center mr-8 flex-shrink-0"
+                    class="bg-black text-white text-4xl font-extrabold w-24 h-24 flex items-center justify-center mr-8 flex-shrink-0"
+                    style="border-radius: 0;"
                 >
                     3
                 </div>
@@ -35,7 +36,8 @@
             <!-- Cardio Metrics -->
             <div class="flex items-start bg-gray-200 h-24">
                 <div
-                    class="bg-black text-white text-2xl font-bold w-16 h-full flex items-center justify-center mr-8 flex-shrink-0"
+                    class="bg-black text-white text-4xl font-extrabold w-24 h-24 flex items-center justify-center mr-8 flex-shrink-0"
+                    style="border-radius: 0;"
                 >
                     4
                 </div>
@@ -52,7 +54,8 @@
             <!-- Fuel Utilization -->
             <div class="flex items-start bg-gray-200 h-24">
                 <div
-                    class="bg-black text-white text-2xl font-bold w-16 h-full flex items-center justify-center mr-8 flex-shrink-0"
+                    class="bg-black text-white text-4xl font-extrabold w-24 h-24 flex items-center justify-center mr-8 flex-shrink-0"
+                    style="border-radius: 0;"
                 >
                     5
                 </div>
@@ -66,7 +69,8 @@
             <!-- Local Muscle Activity -->
             <div class="flex items-start bg-gray-200 h-24">
                 <div
-                    class="bg-black text-white text-2xl font-bold w-16 h-full flex items-center justify-center mr-8 flex-shrink-0"
+                    class="bg-black text-white text-4xl font-extrabold w-24 h-24 flex items-center justify-center mr-8 flex-shrink-0"
+                    style="border-radius: 0;"
                 >
                     9
                 </div>
@@ -80,7 +84,8 @@
             <!-- Training Recommendations -->
             <div class="flex items-start bg-gray-200 h-24">
                 <div
-                    class="bg-black text-white text-2xl font-bold w-16 h-full flex items-center justify-center mr-8 flex-shrink-0"
+                    class="bg-black text-white text-4xl font-extrabold w-24 h-24 flex items-center justify-center mr-8 flex-shrink-0"
+                    style="border-radius: 0;"
                 >
                     10
                 </div>
@@ -94,7 +99,8 @@
             <!-- Next Steps -->
             <div class="flex items-start bg-gray-200 h-24">
                 <div
-                    class="bg-black text-white text-2xl font-bold w-16 h-full flex items-center justify-center mr-8 flex-shrink-0"
+                    class="bg-black text-white text-4xl font-extrabold w-24 h-24 flex items-center justify-center mr-8 flex-shrink-0"
+                    style="border-radius: 0;"
                 >
                     12
                 </div>
@@ -111,7 +117,8 @@
             <!-- Glossary -->
             <div class="flex items-start bg-gray-200 h-24">
                 <div
-                    class="bg-black text-white text-2xl font-bold w-16 h-full flex items-center justify-center mr-8 flex-shrink-0"
+                    class="bg-black text-white text-4xl font-extrabold w-24 h-24 flex items-center justify-center mr-8 flex-shrink-0"
+                    style="border-radius: 0;"
                 >
                     13
                 </div>

app/report_gen/page_2_minimal.html

@@ -15,7 +15,8 @@
             <!-- Nutrition Guidelines -->
             <div class="flex items-start bg-gray-200 h-24">
                 <div
-                    class="bg-black text-white text-2xl font-bold w-16 h-full flex items-center justify-center mr-8 flex-shrink-0"
+                    class="bg-black text-white text-4xl font-extrabold w-24 h-24 flex items-center justify-center mr-8 flex-shrink-0"
+                    style="border-radius: 0;"
                 >
                     3
                 </div>
@@ -35,7 +36,8 @@
             <!-- Nutrition Recommendations -->
             <div class="flex items-start bg-gray-200 h-24">
                 <div
-                    class="bg-black text-white text-2xl font-bold w-16 h-full flex items-center justify-center mr-8 flex-shrink-0"
+                    class="bg-black text-white text-4xl font-extrabold w-24 h-24 flex items-center justify-center mr-8 flex-shrink-0"
+                    style="border-radius: 0;"
                 >
                     4
                 </div>
@@ -49,7 +51,8 @@
             <!-- Next Steps -->
             <div class="flex items-start bg-gray-200 h-24">
                 <div
-                    class="bg-black text-white text-2xl font-bold w-16 h-full flex items-center justify-center mr-8 flex-shrink-0"
+                    class="bg-black text-white text-4xl font-extrabold w-24 h-24 flex items-center justify-center mr-8 flex-shrink-0"
+                    style="border-radius: 0;"
                 >
                     5
                 </div>
@@ -66,7 +69,8 @@
             <!-- Glossary -->
             <div class="flex items-start bg-gray-200 h-24">
                 <div
-                    class="bg-black text-white text-2xl font-bold w-16 h-full flex items-center justify-center mr-8 flex-shrink-0"
+                    class="bg-black text-white text-4xl font-extrabold w-24 h-24 flex items-center justify-center mr-8 flex-shrink-0"
+                    style="border-radius: 0;"
                 >
                     6
                 </div>
@@ -82,7 +86,3 @@
         </div>
     </div>
 </div>
-
-
-
-

app/report_gen/page_6.html

@@ -34,7 +34,7 @@
                     <!-- Macro Body (fills to the bottom, cyan or white) -->
                     <div class="flex flex-col items-center py-1 px-2">
                         <div class="font-bold text-sm text-black mb-1">
-                            {{ deficit_calories | default('1725KCals') }}
+                            {{ deficit_calories | default('1725KCals') }} KCals
                         </div>
                         <div class="text-xs text-black leading-tight text-left">
                             <div>{{ deficit_protein | default('120g Protein') }}</div>
@@ -76,7 +76,7 @@
                     {% if i < 5 %}
                         <div class="flex flex-col items-center py-1 px-2">
                             <div class="font-bold text-sm text-black mb-1">
-                                {{ refeed_weekday_calories | default('1615KCals') }}
+                                {{ refeed_weekday_calories | default('1615KCals') }} KCals
                             </div>
                             <div class="text-xs text-black leading-tight text-left">
                                 <div>{{ refeed_weekday_protein | default('120g Protein') }}</div>
@@ -88,7 +88,7 @@
                     {% else %}
                         <div class="flex flex-col items-center py-1 px-2">
                             <div class="font-bold text-black mb-1">
-                                {{ refeed_weekend_calories | default('2000KCals') }}
+                                {{ refeed_weekend_calories | default('2000KCals') }} KCals
                             </div>
                             <div class="text-xs text-black leading-tight text-left">
                                 <div>{{ refeed_weekend_protein | default('120g Protein') }}</div>

app/report_gen/page_7.html

@@ -26,7 +26,7 @@
         <!-- Indications Box -->
         <div class="bg-gray-200 rounded-lg p-4 text-center mb-2">
             <h3 class="font-semibold text-lg mb-2">Indications</h3>
-            <p class="text-gray-700">{{ indication }}</p>
+            <p >{{ indication | default('No Respiratory Capacity Limitation')}}</p>
         </div>
     </div>
 

app/services/context_generator.py

@@ -232,10 +232,15 @@ class ContextGenerator:
                 if zone_key in metric_overrides:
                     metrics[zone_key] = metric_overrides[zone_key]
         else:
-            fat_max_idx = self.pnoe_df["FAT_smoothed"].idxmax()
-            fat_max_row = self.pnoe_df.loc[fat_max_idx]
+            # Use optimal fat burning zone (highest fat:carb ratio) - same as _calculate_zone_metrics
+            # This ensures consistency between zone calculations and zone metrics
+            self.pnoe_df["fat_carb_ratio"] = self.pnoe_df["FAT_smoothed"] / (
+                self.pnoe_df["CHO_smoothed"] + 0.00000001
+            )
+            optimal_fat_idx = self.pnoe_df["fat_carb_ratio"].idxmax()
+            optimal_row = self.pnoe_df.loc[optimal_fat_idx]
             zones = self._calculate_hr_zones(
-                metrics["vt1"], metrics["vt2"], fat_max_row
+                metrics["vt1"], metrics["vt2"], optimal_row
             )
             metrics.update(zones)
 
@@ -280,29 +285,46 @@ class ContextGenerator:
         return vt1, vt2
 
     def _calculate_hr_zones(
-        self, vt1: Optional[Dict], vt2: Optional[Dict], fat_max_row: pd.Series
+        self, vt1: Optional[Dict], vt2: Optional[Dict], optimal_row: pd.Series
     ) -> Dict:
-        """Calculate heart rate zones based on thresholds"""
+        """Calculate heart rate zones based on thresholds
+
+        Uses optimal fat burning zone (highest fat:carb ratio) to match _calculate_zone_metrics.
+        This ensures consistency between zone string calculations and zone metrics table.
+        """
+        import math
+
         zones = {}
         if vt1 and vt2:
-            zone_1_start = fat_max_row["HR(bpm)_smoothed"] - 15
-            zone_2_start = fat_max_row["HR(bpm)_smoothed"]
-            zone_3_start = vt1["HeartRate"]
-            zone_4_start = vt2["HeartRate"] - 10
-            zone_5_start = vt2["HeartRate"] + 10
+            # Use same zone boundary calculation as _calculate_zone_metrics
+            zone_1_start = math.floor(optimal_row["HR(bpm)_smoothed"] - 15)
+            zone_2_start = math.floor(optimal_row["HR(bpm)_smoothed"])
+            zone_3_start = math.floor(vt1["HeartRate"])
+            zone_4_start = math.floor(vt2["HeartRate"] - 10)
+            zone_5_start = math.floor(vt2["HeartRate"])
+            # zone_5_end is calculated for consistency with _calculate_zone_metrics
+            # (not used in string format since zone 5 is open-ended: "+bpm")
+            zone_5_end = math.floor(vt2["HeartRate"] + 10)  # noqa: F841
 
-            zones["zone1_bpm"] = f"{int(zone_1_start)}-{int(zone_2_start)}bpm"
-            zones["zone2_bpm"] = f"{int(zone_2_start)}-{int(vt1['HeartRate'])}bpm"
-            zones["zone3_bpm"] = f"{int(zone_3_start)}-{int(zone_4_start)}bpm"
-            zones["zone4_bpm"] = f"{int(zone_4_start)}-{int(zone_5_start)}bpm"
-            zones["zone5_bpm"] = f"{int(zone_5_start)}+bpm"
+            # Calculate zone ends to match _calculate_zone_metrics exactly
+            zone_1_end = zone_2_start
+            zone_2_end = math.floor(vt1["HeartRate"])
+            zone_3_end = zone_4_start
+            zone_4_end = zone_5_start
+
+            # Format zones to match _calculate_zone_metrics output
+            zones["zone1_bpm"] = f"{int(zone_1_start)}-{int(zone_1_end)}bpm"
+            zones["zone2_bpm"] = f"{int(zone_2_start)}-{int(zone_2_end)}bpm"
+            zones["zone3_bpm"] = f"{int(zone_3_start)}-{int(zone_3_end)}bpm"
+            zones["zone4_bpm"] = f"{int(zone_4_start)}-{int(zone_4_end)}bpm"
+            zones["zone5_bpm"] = f"{int(zone_5_start)}-{int(zone_5_end)}bpm"
         else:
             max_hr = 220 - self.patient_info["age"]
             zones["zone1_bpm"] = f"{int(max_hr * 0.55)}-{int(max_hr * 0.65)}bpm"
             zones["zone2_bpm"] = f"{int(max_hr * 0.65)}-{int(max_hr * 0.75)}bpm"
             zones["zone3_bpm"] = f"{int(max_hr * 0.75)}-{int(max_hr * 0.85)}bpm"
             zones["zone4_bpm"] = f"{int(max_hr * 0.85)}-{int(max_hr * 0.95)}bpm"
-            zones["zone5_bpm"] = f"{int(max_hr * 0.95)}+bpm"
+            zones["zone5_bpm"] = f"{int(max_hr * 0.95)}-{int(max_hr * 1.05)}bpm"
         return zones
 
     def _calculate_vo2_drop_points(self, pnoe_metrics: Dict) -> Dict:
@@ -1180,7 +1202,9 @@ class ContextGenerator:
                 "page_number": 4,
                 "fat_percentage": f"{self.patient_info['fat_percentage']:.1f}",
                 "body_composition_chart": graphs.get("body_composition", ""),
-                "body_fat_chart": graphs.get("body_fat_percent", ""),  # Alias for template
+                "body_fat_chart": graphs.get(
+                    "body_fat_percent", ""
+                ),  # Alias for template
                 "body_fat_percent_chart": graphs.get(
                     "body_fat_percent", ""
                 ),  # Keep for consistency
@@ -1199,29 +1223,29 @@ class ContextGenerator:
                 "weight_loss_rate": rmr_metrics.get("weight_loss_rate", 1.0),
                 "total_calories": rmr_metrics.get("total_calories", 1375),
             }
-            
+
             # For minimal reports, also generate resting heart rate table for page_5
             if report_type == "minimal" and graph_generator:
                 resting_hr_metrics = self._calculate_resting_heart_rate_metrics()
                 rhr_table_info = self._calculate_rhr_table_data(
                     self.patient_info["age"], self.patient_info["gender"]
                 )
-                
+
                 # Get resting heart rate value and determine category
                 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 = [
                     "Age",
                     "Poor",
@@ -1244,7 +1268,7 @@ class ContextGenerator:
                         rhr_table_info["ranges"]["Athlete"],
                     ]
                 ]
-                
+
                 contexts["page_5"]["rhr_table"] = (
                     graph_generator.generate_resting_heart_rate_table(
                         data=rhr_data,
@@ -1265,12 +1289,16 @@ class ContextGenerator:
                 "deficit_carbs": f"{int(rmr_metrics.get('total_calories', 1600) * 0.39 / 4)}g Carbs",
                 "deficit_fat": f"{int(rmr_metrics.get('total_calories', 1600) * 0.39 / 9)}g Fat",
                 "deficit_fiber": "24g Fibre",
-                "refeed_weekday_calories": int(rmr_metrics.get("total_calories", 1600) * 0.85),
+                "refeed_weekday_calories": int(
+                    rmr_metrics.get("total_calories", 1600) * 0.85
+                ),
                 "refeed_weekday_protein": f"{int(rmr_metrics.get('total_calories', 1600) * 0.85 * 0.22 / 4)}g Protein",
                 "refeed_weekday_carbs": f"{int(rmr_metrics.get('total_calories', 1600) * 0.85 * 0.39 / 4)}g Carbs",
                 "refeed_weekday_fat": f"{int(rmr_metrics.get('total_calories', 1600) * 0.85 * 0.39 / 9)}g Fat",
                 "refeed_weekday_fiber": "20g Fibre",
-                "refeed_weekend_calories": int(rmr_metrics.get("total_calories", 1600) * 1.375),
+                "refeed_weekend_calories": int(
+                    rmr_metrics.get("total_calories", 1600) * 1.375
+                ),
                 "refeed_weekend_protein": f"{int(rmr_metrics.get('total_calories', 1600) * 1.375 * 0.22 / 4)}g Protein",
                 "refeed_weekend_carbs": f"{int(rmr_metrics.get('total_calories', 1600) * 1.375 * 0.39 / 4)}g Carbs",
                 "refeed_weekend_fat": f"{int(rmr_metrics.get('total_calories', 1600) * 1.375 * 0.39 / 9)}g Fat",
@@ -1291,12 +1319,12 @@ class ContextGenerator:
 
             # Page 7
             contexts["page_7"] = {
-            "peak_vt": f"{pnoe_metrics['peak_vt']:.2f}",
-            "peak_vt_bpm": f"{int(pnoe_metrics['peak_vt_hr'])}",
-            "fev1_percentage": f"{fev1_percentage:.1f}",
-            "lung_analysis_chart": graphs.get("spirometry_chart", ""),
-            "respiratory_analysis_chart": graphs.get("respiratory", ""),
-        }
+                "peak_vt": f"{pnoe_metrics['peak_vt']:.2f}",
+                "peak_vt_bpm": f"{int(pnoe_metrics['peak_vt_hr'])}",
+                "fev1_percentage": f"{fev1_percentage:.1f}",
+                "lung_analysis_chart": graphs.get("spirometry_chart", ""),
+                "respiratory_analysis_chart": graphs.get("respiratory", ""),
+            }
 
         # Page 8
         contexts["page_8"] = {
@@ -1562,7 +1590,11 @@ class ContextGenerator:
             }
 
         # For minimal reports, create combined context for page_19_20_minimal
-        if report_type == "minimal" and 19 in pages_to_generate and 20 in pages_to_generate:
+        if (
+            report_type == "minimal"
+            and 19 in pages_to_generate
+            and 20 in pages_to_generate
+        ):
             contexts["page_19_20_minimal"] = {
                 "patient_name": self.patient_info["name"],
                 "body_fat_percentage_chart": graphs.get(

app/services/graph_generator.py

@@ -1124,80 +1124,163 @@ class GraphGenerator:
         return self._image_to_base64(chart_path) if save_as_base64 else str(chart_path)
 
     def generate_metabolism_chart(
-        self, rmr_kcal: float, save_as_base64: bool = True
+        self,
+        rmr_kcal: float,
+        weight_kg: float = None,
+        height_cm: float = None,
+        age_years: int = None,
+        sex: str = None,
+        save_as_base64: bool = True,
     ) -> str:
         """
         Generate metabolism chart (Slow vs Fast Metabolism).
+        Matches the notebook implementation with ratio-based scale (0.3 to 1.9).
 
         Args:
-            rmr_kcal: Resting metabolic rate in kcal/day
+            rmr_kcal: Resting metabolic rate in kcal/day (measured RMR)
+            weight_kg: Weight in kg (optional, for calculating ratio)
+            height_cm: Height in cm (optional, for calculating ratio)
+            age_years: Age in years (optional, for calculating ratio)
+            sex: Sex ("male" or "female", optional, for calculating ratio)
             save_as_base64: If True, return base64 string, else return file path
 
         Returns:
             Base64 string or file path
         """
-        from matplotlib.patches import FancyBboxPatch
+        from matplotlib.patches import Rectangle
 
-        fig, ax = plt.subplots(figsize=(10, 2.5))
+        fig, ax = plt.subplots(figsize=(11.5, 2.5))
 
-        # Chart data and positions
-        # Use normalized positions (0-100 scale) for uniform bar length
-        categories = ["Very Slow", "Slow", "Average", "Fast", "Very Fast"]
-        positions = [10, 30, 50, 70, 90]  # Normalized positions on 0-100 scale
+        # Calculate ratio if we have all required parameters
+        ratio = None
+        if all([weight_kg, height_cm, age_years, sex]):
+            # Mifflin-St Jeor equation
+            if sex.lower() == "male":
+                mifflin_rmr = 10 * weight_kg + 6.25 * height_cm - 5 * age_years + 5
+            elif sex.lower() == "female":
+                mifflin_rmr = 10 * weight_kg + 6.25 * height_cm - 5 * age_years - 161
+            else:
+                mifflin_rmr = None
 
-        # Normalize the kcal value to 0-100 scale (assuming range 0-9000 kcal)
-        max_kcal = 9000
-        normalized_value = (rmr_kcal / max_kcal) * 100
-        indicator_pos = normalized_value
-        highlight_end = normalized_value
+            if mifflin_rmr and mifflin_rmr > 0:
+                ratio = rmr_kcal / mifflin_rmr
 
-        # Main Bar (Background) - using 0-100 scale
-        main_bar = FancyBboxPatch(
-            (0, 0.4),
-            100,
-            0.2,
-            boxstyle="round,pad=0,rounding_size=0.1",
-            ec="none",
-            fc="#E0E0E0",
+        # Bar setup - using ratio scale from 0.3 to 1.9 (as in notebook)
+        scale_edges = [0.3, 0.7, 0.9, 1.1, 1.3, 1.5, 1.9]
+        scale_labels = ["Very Slow", "Slow", "Average", "Fast", "Very Fast"]
+        tick_edges = scale_edges[1:-1]  # Remove first and last tick (omit 0.3 and 1.9)
+
+        x_start = scale_edges[0]
+        x_end = scale_edges[-1]
+        # Make the bar THICKER by increasing bar_height and adjusting y_bar
+        bar_height = 0.36
+        y_bar = 0.48
+
+        color_before = "#B2FFC8"
+        color_after = "#ECEDF2"
+        gray_color = "#606060"
+
+        # If we have a ratio, use it; otherwise map rmr_kcal to the scale
+        if ratio is not None:
+            highlight_end = min(max(ratio, x_start), x_end)
+        else:
+            # Fallback: map rmr_kcal to scale (assuming typical range 1000-3000 kcal/day)
+            # Map to 0.3-1.9 scale
+            min_rmr = 1000
+            max_rmr = 3000
+            normalized = (rmr_kcal - min_rmr) / (max_rmr - min_rmr)
+            highlight_end = x_start + normalized * (x_end - x_start)
+            highlight_end = min(max(highlight_end, x_start), x_end)
+
+        # Draw plain rectangle bar (no rounding)
+        ax.add_patch(
+            Rectangle(
+                (x_start, y_bar),
+                x_end - x_start,
+                bar_height,
+                ec="none",
+                fc=color_after,
+                lw=0,
+            )
         )
-        ax.add_patch(main_bar)
 
-        # Highlighted Bar
-        highlight_bar = FancyBboxPatch(
-            (0, 0.4),
-            highlight_end,
-            0.2,
-            boxstyle="round,pad=0,rounding_size=0.1",
-            ec="none",
-            fc="#B2FFC8",
-        )
-        ax.add_patch(highlight_bar)
+        # Highlighted rectangle
+        if highlight_end > x_start:
+            ax.add_patch(
+                Rectangle(
+                    (x_start, y_bar),
+                    highlight_end - x_start,
+                    bar_height,
+                    ec="none",
+                    fc=color_before,
+                    lw=0,
+                )
+            )
 
-        # Text and Labels (show actual kcal value)
+        # kCals label, left-aligned, bold inside green, TEXT COLOR gray
         ax.text(
-            highlight_end / 2,
-            0.5,
-            f"{rmr_kcal:.0f}kCals",
-            ha="center",
+            x_start + 0.07,
+            y_bar + bar_height / 2,
+            f"{int(round(rmr_kcal))}kCals",
+            ha="left",
             va="center",
-            color="#006400",
+            color=gray_color,
+            fontsize=12,
+            weight="bold",
+            bbox=dict(boxstyle="round,pad=0.14", ec="none", fc="#B2FFC8", alpha=1.0),
+        )
+
+        # Triangle marker above highlight end, gray
+        ax.plot(
+            [highlight_end],
+            [y_bar + bar_height + 0.08],
+            marker="v",
+            markersize=14,
+            color=gray_color,
+            clip_on=False,
+        )
+
+        # Draw ticks – omit leftmost/rightmost (thicker and below bar), color gray
+        tick_width = 4.1
+        tick_bottom = y_bar - 0.07  # further below bar
+        tick_top = y_bar  # at the base of bar
+        for edge in tick_edges:
+            ax.plot(
+                [edge, edge],
+                [tick_bottom, tick_top],
+                color=gray_color,
+                lw=tick_width,
+                solid_capstyle="butt",
+                clip_on=False,
+                zorder=2,
+            )
+
+        # Label locations (place directly under each tick), text color gray
+        label_y = tick_bottom - 0.08
+        for label, tick in zip(scale_labels, tick_edges):
+            ax.text(
+                tick,
+                label_y,
+                label,
+                ha="center",
+                va="top",
+                fontsize=11,
+                weight="bold",
+                color=gray_color,
+            )
+
+        # Axis title: bold, with extra gap above the graph
+        ax.text(
+            x_start,
+            y_bar + bar_height + 0.5,
+            "Slow vs Fast Metabolism",
+            ha="left",
+            va="bottom",
             fontsize=14,
             weight="bold",
         )
 
-        # Indicator Triangle
-        ax.plot(indicator_pos, 0.65, "v", markersize=15, color="#606060", clip_on=False)
-
-        # Ticks and Labels
-        for pos, label in zip(positions, categories):
-            ax.text(
-                pos, 0.15, label, ha="center", va="center", fontsize=12, color="#333333"
-            )
-            ax.plot([pos, pos], [0.35, 0.39], color="grey", lw=5)
-
-        # Chart Styling
-        ax.set_title("Slow vs Fast Metabolism", fontsize=18, weight="bold", loc="left")
-        ax.set_xlim(0, 100)  # Normalized scale for uniformity
+        ax.set_xlim(x_start, x_end)
         ax.set_ylim(0, 1)
         ax.axis("off")
 
@@ -1214,6 +1297,7 @@ class GraphGenerator:
     ) -> str:
         """
         Generate fuel source chart (Fats vs Carbs).
+        Matches the notebook implementation with proper tick styling.
 
         Args:
             fat_percentage: Fat percentage at rest
@@ -1224,84 +1308,133 @@ class GraphGenerator:
         """
         from matplotlib.patches import FancyBboxPatch
 
-        fig, ax = plt.subplots(figsize=(10, 2.5))
+        fig, ax = plt.subplots(figsize=(11.5, 2.5))
 
         carb_percentage = 100 - fat_percentage
         optimal_point = 75
 
-        # Main Bars (Fats and Carbs)
-        # Fats bar (yellow)
+        # Let the bars be a bit thicker as well: increase bar height and y
         fats_bar = FancyBboxPatch(
-            (0, 0.4),
+            (0, 0.36),
             fat_percentage,
-            0.2,
+            0.28,
             boxstyle="round,pad=0,rounding_size=0.1",
             ec="none",
             fc="#FEEAAB",
         )
         ax.add_patch(fats_bar)
 
-        # Carbs bar (blue) - starts where the fats bar ends
         carbs_bar = FancyBboxPatch(
-            (fat_percentage, 0.4),
+            (fat_percentage, 0.36),
             carb_percentage,
-            0.2,
+            0.28,
             boxstyle="round,pad=0,rounding_size=0.1",
             ec="none",
             fc="#A7F5FF",
         )
         ax.add_patch(carbs_bar)
 
-        # Text and Labels
+        # Style: match font weight/color/size with other chart
+        label_fontprops = dict(fontsize=12, weight="bold", color="#333333")
+
         ax.text(
             fat_percentage / 2,
             0.5,
-            f"Fats\n{fat_percentage:.1f}%",
+            f"Fats\n{fat_percentage:.0f}%",
             ha="center",
             va="center",
-            color="#333333",
-            fontsize=12,
-            weight="bold",
+            **label_fontprops,
         )
         ax.text(
             fat_percentage + carb_percentage / 2,
             0.5,
-            f"Carbs\n{carb_percentage:.1f}%",
+            f"Carbs\n{100 - fat_percentage:.0f}%",
             ha="center",
             va="center",
-            color="#333333",
-            fontsize=12,
-            weight="bold",
+            **label_fontprops,
         )
 
         # Add 'Optimal' label
-        ax.text(optimal_point, 0.75, "Optimal", ha="center", va="center", fontsize=12)
-
-        # Indicator Triangle
-        ax.plot(
-            fat_percentage, 0.65, "v", markersize=15, color="#606060", clip_on=False
+        ax.text(
+            optimal_point,
+            0.9,
+            "Optimal",
+            ha="center",
+            va="center",
+            fontsize=12,
+            weight="bold",
+            color="#606060",
         )
 
-        # Ticks and Labels
+        # Optimal point line
+        ax.plot([optimal_point, optimal_point], [0.65, 0.8], color="#606060", lw=3)
+
+        # Indicator Triangle
+        ax.plot(fat_percentage, 0.7, "v", markersize=15, color="#606060", clip_on=False)
+
+        # Ticks and Labels - matching notebook implementation
         positions = [0, 25, 50, 75, 100]
+        tick_color = "#606060"
         for pos in positions:
-            ax.text(
-                pos,
-                0.15,
-                str(pos),
-                ha="center",
-                va="center",
-                fontsize=12,
-                color="#333333",
-            )
-            ax.plot([pos, pos], [0.35, 0.39], color="grey", lw=5)
+            # Smallest ticks (first and last) are thicker
+            if pos == 0:
+                ax.text(
+                    pos + 0.5,
+                    0.15,
+                    str(pos),
+                    ha="center",
+                    va="center",
+                    fontsize=12,
+                    color="#333333",
+                    weight="bold",
+                )
+                ax.plot(
+                    [pos, pos],
+                    [0.25, 0.37],
+                    color=tick_color,
+                    lw=14,
+                    solid_capstyle="butt",
+                )
+            elif pos == 100:
+                ax.text(
+                    pos - 0.5,
+                    0.15,
+                    str(pos),
+                    ha="center",
+                    va="center",
+                    fontsize=12,
+                    color="#333333",
+                    weight="bold",
+                )
+                ax.plot(
+                    [pos, pos],
+                    [0.25, 0.37],
+                    color=tick_color,
+                    lw=14,
+                    solid_capstyle="butt",
+                )
+            else:
+                ax.text(
+                    pos,
+                    0.15,
+                    str(pos),
+                    ha="center",
+                    va="center",
+                    fontsize=12,
+                    color="#333333",
+                    weight="bold",
+                )
+                ax.plot(
+                    [pos, pos],
+                    [0.25, 0.37],
+                    color=tick_color,
+                    lw=8,
+                    solid_capstyle="butt",
+                )
 
-        # Add a special tick for the 'Optimal' point
-        ax.plot([optimal_point, optimal_point], [0.6, 0.7], color="black", lw=2)
-
-        # Chart Styling
-        ax.set_title("Fuel Source", fontsize=18, weight="bold", loc="left")
-        ax.set_xlim(0, 100)  # Normalized scale for uniformity
+        # Chart Styling - uniform style for title
+        ax.set_title("Fuel Source", fontsize=14, weight="bold", loc="left", pad=22)
+        ax.set_xlim(0, 100)
         ax.set_ylim(0, 1)
         ax.axis("off")
 

app/services/report_generator.py

@@ -524,9 +524,36 @@ class ReportGeneratorService:
             }
             rmr_metrics = temp_context_gen.calculate_rmr_and_fuel_source()
 
-            # Generate metabolism chart
+            # Convert height to cm if available
+            height_cm = None
+            height_str = patient_info.get("height", "")
+            if height_str:
+                try:
+                    # Try to parse height string (e.g., "5'4"", "165cm", "165")
+                    import re
+                    # Check if it's in feet'inches" format
+                    feet_inches_match = re.match(r"(\d+)'(\d+)\"", height_str)
+                    if feet_inches_match:
+                        feet = int(feet_inches_match.group(1))
+                        inches = int(feet_inches_match.group(2))
+                        height_cm = (feet * 12 + inches) * 2.54
+                    # Check if it ends with cm
+                    elif "cm" in height_str.lower():
+                        height_cm = float(re.sub(r"[^\d.]", "", height_str))
+                    # Otherwise try to parse as number (assume cm)
+                    else:
+                        height_cm = float(re.sub(r"[^\d.]", "", height_str))
+                except (ValueError, AttributeError):
+                    pass
+
+            # Generate metabolism chart with ratio calculation if we have all parameters
             metabolism_chart_b64 = self.graph_generator.generate_metabolism_chart(
-                rmr_metrics["rmr_kcal"], save_as_base64=True
+                rmr_metrics["rmr_kcal"],
+                weight_kg=weight_kg,
+                height_cm=height_cm,
+                age_years=patient_info.get("age", None),
+                sex=gender,
+                save_as_base64=True,
             )
             graphs_dict["metabolism_chart"] = metabolism_chart_b64
 

app/templates/preview.html

@@ -1,24 +1,32 @@
-{% extends "base.html" %}
-
-{% block title %}Report Preview - Report Generator{% endblock %}
-
-{% block content %}
+{% extends "base.html" %} {% block title %}Report Preview - Report Generator{%
+endblock %} {% block content %}
 <div class="px-4 py-6 sm:px-0">
     {% if not session.get('report_path') %}
     <div class="bg-yellow-50 border border-yellow-200 rounded-lg p-4 mb-6">
-        <p class="text-yellow-800">No report found. Please <a href="/" class="underline">upload files</a> first.</p>
+        <p class="text-yellow-800">
+            No report found. Please
+            <a href="/" class="underline">upload files</a> first.
+        </p>
     </div>
     {% else %}
-    
+
     <div class="bg-white shadow rounded-lg mb-6">
         <div class="px-4 py-5 sm:p-6">
             <div class="flex justify-between items-center mb-6">
-                <h2 class="text-2xl font-bold text-gray-900">Generated Report Preview</h2>
+                <h2 class="text-2xl font-bold text-gray-900">
+                    Generated Report Preview
+                </h2>
                 <div class="flex space-x-3">
-                    <a href="/edit" class="inline-flex items-center px-4 py-2 border border-gray-300 shadow-sm text-sm font-medium rounded-md text-gray-700 bg-white hover:bg-gray-50">
+                    <a
+                        href="/edit"
+                        class="inline-flex items-center px-4 py-2 border border-gray-300 shadow-sm text-sm font-medium rounded-md text-gray-700 bg-white hover:bg-gray-50"
+                    >
                         Edit Metrics
                     </a>
-                    <a href="/download-report/{{ session.report_path.split('/')[-1] }}" class="inline-flex items-center px-4 py-2 border border-transparent shadow-sm text-sm font-medium rounded-md text-white bg-indigo-600 hover:bg-indigo-700">
+                    <a
+                        href="/download-report/{{ session.report_path.split('/')[-1] }}"
+                        class="inline-flex items-center px-4 py-2 border border-transparent shadow-sm text-sm font-medium rounded-md text-white bg-indigo-600 hover:bg-indigo-700"
+                    >
                         Download PDF
                     </a>
                 </div>
@@ -26,23 +34,33 @@
 
             <!-- Patient Information -->
             <div class="border-b border-gray-200 pb-6 mb-6">
-                <h3 class="text-lg font-medium text-gray-900 mb-4">Patient Information</h3>
+                <h3 class="text-lg font-medium text-gray-900 mb-4">
+                    Patient Information
+                </h3>
                 <div class="grid grid-cols-2 gap-4 sm:grid-cols-4">
                     <div>
                         <p class="text-sm text-gray-500">Name</p>
-                        <p class="text-base font-medium text-gray-900">{{ session.patient_info['patient_name'] }}</p>
+                        <p class="text-base font-medium text-gray-900">
+                            {{ session.patient_info['patient_name'] }}
+                        </p>
                     </div>
                     <div>
                         <p class="text-sm text-gray-500">Age</p>
-                        <p class="text-base font-medium text-gray-900">{{ session.patient_info['age'] }}</p>
+                        <p class="text-base font-medium text-gray-900">
+                            {{ session.patient_info['age'] }}
+                        </p>
                     </div>
                     <div>
                         <p class="text-sm text-gray-500">Height</p>
-                        <p class="text-base font-medium text-gray-900">{{ session.patient_info['height'] }}</p>
+                        <p class="text-base font-medium text-gray-900">
+                            {{ session.patient_info['height'] }}
+                        </p>
                     </div>
                     <div>
                         <p class="text-sm text-gray-500">Weight</p>
-                        <p class="text-base font-medium text-gray-900">{{ session.patient_info['weight'] }}</p>
+                        <p class="text-base font-medium text-gray-900">
+                            {{ session.patient_info['weight'] }}
+                        </p>
                     </div>
                 </div>
             </div>
@@ -52,56 +70,113 @@
             <div class="space-y-6">
                 <!-- Pnoe Metrics -->
                 <div>
-                    <h3 class="text-lg font-medium text-gray-900 mb-4">Pnoe Metrics</h3>
-                    <div class="grid grid-cols-1 gap-4 sm:grid-cols-2 lg:grid-cols-3">
+                    <h3 class="text-lg font-medium text-gray-900 mb-4">
+                        Pnoe Metrics
+                    </h3>
+                    <div
+                        class="grid grid-cols-1 gap-4 sm:grid-cols-2 lg:grid-cols-3"
+                    >
                         {% if session.metrics.pnoe.get('vo2_max') %}
                         <div class="bg-gray-50 p-4 rounded-lg">
                             <p class="text-sm text-gray-500">VO2 Max</p>
-                            <p class="text-2xl font-bold text-gray-900">{{ "%.2f"|format(session.metrics.pnoe['vo2_max']) }} ml/min</p>
+                            <p class="text-2xl font-bold text-gray-900">
+                                {{
+                                "%.2f"|format(session.metrics.pnoe['vo2_max'])
+                                }} ml/min
+                            </p>
                         </div>
-                        {% endif %}
-                        {% if session.metrics.pnoe.get('vo2_max_per_kg') %}
+                        {% endif %} {% if
+                        session.metrics.pnoe.get('vo2_max_per_kg') %}
                         <div class="bg-gray-50 p-4 rounded-lg">
                             <p class="text-sm text-gray-500">VO2 Max per kg</p>
-                            <p class="text-2xl font-bold text-gray-900">{{ "%.2f"|format(session.metrics.pnoe['vo2_max_per_kg']) }} ml/min/kg</p>
+                            <p class="text-2xl font-bold text-gray-900">
+                                {{
+                                "%.2f"|format(session.metrics.pnoe['vo2_max_per_kg'])
+                                }} ml/min/kg
+                            </p>
                         </div>
-                        {% endif %}
-                        {% if session.metrics.pnoe.get('peak_vt') %}
+                        {% endif %} {% if session.metrics.pnoe.get('peak_vt') %}
                         <div class="bg-gray-50 p-4 rounded-lg">
                             <p class="text-sm text-gray-500">Peak VT</p>
-                            <p class="text-2xl font-bold text-gray-900">{{ "%.2f"|format(session.metrics.pnoe['peak_vt']) }} L</p>
-                            <p class="text-sm text-gray-500 mt-1">HR: {{ "%.0f"|format(session.metrics.pnoe['peak_vt_hr']) }} bpm</p>
+                            <p class="text-2xl font-bold text-gray-900">
+                                {{
+                                "%.2f"|format(session.metrics.pnoe['peak_vt'])
+                                }} L
+                            </p>
+                            <p class="text-sm text-gray-500 mt-1">
+                                HR: {{
+                                "%.0f"|format(session.metrics.pnoe['peak_vt_hr'])
+                                }} bpm
+                            </p>
                         </div>
-                        {% endif %}
-                        {% if session.metrics.pnoe.get('fat_max_value') %}
+                        {% endif %} {% if
+                        session.metrics.pnoe.get('fat_max_value') %}
                         <div class="bg-gray-50 p-4 rounded-lg">
                             <p class="text-sm text-gray-500">Fat Max Value</p>
-                            <p class="text-2xl font-bold text-gray-900">{{ "%.2f"|format(session.metrics.pnoe['fat_max_value']) }} kcal/min</p>
-                            <p class="text-sm text-gray-500 mt-1">HR: {{ "%.0f"|format(session.metrics.pnoe['fat_max_hr']) }} bpm</p>
+                            <p class="text-2xl font-bold text-gray-900">
+                                {{
+                                "%.2f"|format(session.metrics.pnoe['fat_max_value'])
+                                }} kcal/min
+                            </p>
+                            <p class="text-sm text-gray-500 mt-1">
+                                HR: {{
+                                "%.0f"|format(session.metrics.pnoe['fat_max_hr'])
+                                }} bpm
+                            </p>
                         </div>
                         {% endif %}
                     </div>
                 </div>
 
                 <!-- VT1 and VT2 -->
-                {% if session.metrics.pnoe.get('vt1') or session.metrics.pnoe.get('vt2') %}
+                {% if session.metrics.pnoe.get('vt1') or
+                session.metrics.pnoe.get('vt2') %}
                 <div>
-                    <h3 class="text-lg font-medium text-gray-900 mb-4">Ventilatory Thresholds</h3>
+                    <h3 class="text-lg font-medium text-gray-900 mb-4">
+                        Ventilatory Thresholds
+                    </h3>
                     <div class="grid grid-cols-1 gap-4 sm:grid-cols-2">
                         {% if session.metrics.pnoe.get('vt1') %}
                         <div class="bg-blue-50 p-4 rounded-lg">
-                            <p class="text-sm font-medium text-blue-900 mb-2">VT1</p>
-                            <p class="text-sm text-blue-700">Heart Rate: {{ "%.0f"|format(session.metrics.pnoe['vt1']['HeartRate']) }} bpm</p>
-                            <p class="text-sm text-blue-700">Speed: {{ "%.2f"|format(session.metrics.pnoe['vt1']['Speed']) }} mph</p>
-                            <p class="text-sm text-blue-700">Time: {{ "%.0f"|format(session.metrics.pnoe['vt1']['Time']) }} sec</p>
+                            <p class="text-sm font-medium text-blue-900 mb-2">
+                                VT1
+                            </p>
+                            <p class="text-sm text-blue-700">
+                                Heart Rate: {{
+                                "%.0f"|format(session.metrics.pnoe['vt1']['HeartRate'])
+                                }} bpm
+                            </p>
+                            <p class="text-sm text-blue-700">
+                                Speed: {{
+                                "%.2f"|format(session.metrics.pnoe['vt1']['Speed'])
+                                }} mph
+                            </p>
+                            <p class="text-sm text-blue-700">
+                                Time: {{
+                                "%.0f"|format(session.metrics.pnoe['vt1']['Time'])
+                                }} sec
+                            </p>
                         </div>
-                        {% endif %}
-                        {% if session.metrics.pnoe.get('vt2') %}
+                        {% endif %} {% if session.metrics.pnoe.get('vt2') %}
                         <div class="bg-green-50 p-4 rounded-lg">
-                            <p class="text-sm font-medium text-green-900 mb-2">VT2</p>
-                            <p class="text-sm text-green-700">Heart Rate: {{ "%.0f"|format(session.metrics.pnoe['vt2']['HeartRate']) }} bpm</p>
-                            <p class="text-sm text-green-700">Speed: {{ "%.2f"|format(session.metrics.pnoe['vt2']['Speed']) }} mph</p>
-                            <p class="text-sm text-green-700">Time: {{ "%.0f"|format(session.metrics.pnoe['vt2']['Time']) }} sec</p>
+                            <p class="text-sm font-medium text-green-900 mb-2">
+                                VT2
+                            </p>
+                            <p class="text-sm text-green-700">
+                                Heart Rate: {{
+                                "%.0f"|format(session.metrics.pnoe['vt2']['HeartRate'])
+                                }} bpm
+                            </p>
+                            <p class="text-sm text-green-700">
+                                Speed: {{
+                                "%.2f"|format(session.metrics.pnoe['vt2']['Speed'])
+                                }} mph
+                            </p>
+                            <p class="text-sm text-green-700">
+                                Time: {{
+                                "%.0f"|format(session.metrics.pnoe['vt2']['Time'])
+                                }} sec
+                            </p>
                         </div>
                         {% endif %}
                     </div>
@@ -111,17 +186,20 @@
                 <!-- Heart Rate Zones -->
                 {% if session.metrics.pnoe.get('zone1_bpm') %}
                 <div>
-                    <h3 class="text-lg font-medium text-gray-900 mb-4">Heart Rate Zones</h3>
+                    <h3 class="text-lg font-medium text-gray-900 mb-4">
+                        Heart Rate Zones
+                    </h3>
                     <div class="grid grid-cols-1 gap-2 sm:grid-cols-5">
-                        {% for i in range(1, 6) %}
-                        {% set zone_key = "zone" + i|string + "_bpm" %}
-                        {% if session.metrics.pnoe.get(zone_key) %}
+                        {% for i in range(1, 6) %} {% set zone_key = "zone" +
+                        i|string + "_bpm" %} {% if
+                        session.metrics.pnoe.get(zone_key) %}
                         <div class="bg-gray-50 p-3 rounded-lg text-center">
                             <p class="text-xs text-gray-500">Zone {{ i }}</p>
-                            <p class="text-sm font-medium text-gray-900">{{ session.metrics.pnoe[zone_key] }}</p>
+                            <p class="text-sm font-medium text-gray-900">
+                                {{ session.metrics.pnoe[zone_key] }}
+                            </p>
                         </div>
-                        {% endif %}
-                        {% endfor %}
+                        {% endif %} {% endfor %}
                     </div>
                 </div>
                 {% endif %}
@@ -129,27 +207,53 @@
                 <!-- Spirometry Metrics -->
                 {% if session.metrics.spirometry %}
                 <div>
-                    <h3 class="text-lg font-medium text-gray-900 mb-4">Spirometry Metrics</h3>
+                    <h3 class="text-lg font-medium text-gray-900 mb-4">
+                        Spirometry Metrics
+                    </h3>
                     <div class="grid grid-cols-1 gap-4 sm:grid-cols-3">
                         {% if session.metrics.spirometry.get('fvc_best') %}
                         <div class="bg-gray-50 p-4 rounded-lg">
                             <p class="text-sm text-gray-500">FVC Best</p>
-                            <p class="text-2xl font-bold text-gray-900">{{ "%.2f"|format(session.metrics.spirometry['fvc_best']) }} L</p>
-                            <p class="text-sm text-gray-500 mt-1">{{ "%.1f"|format(session.metrics.spirometry['fvc_pred']) }}% predicted</p>
+                            <p class="text-2xl font-bold text-gray-900">
+                                {{
+                                "%.2f"|format(session.metrics.spirometry['fvc_best'])
+                                }} L
+                            </p>
+                            <p class="text-sm text-gray-500 mt-1">
+                                {{
+                                "%.1f"|format(session.metrics.spirometry['fvc_pred'])
+                                }}% predicted
+                            </p>
                         </div>
-                        {% endif %}
-                        {% if session.metrics.spirometry.get('fev1_best') %}
+                        {% endif %} {% if
+                        session.metrics.spirometry.get('fev1_best') %}
                         <div class="bg-gray-50 p-4 rounded-lg">
                             <p class="text-sm text-gray-500">FEV1 Best</p>
-                            <p class="text-2xl font-bold text-gray-900">{{ "%.2f"|format(session.metrics.spirometry['fev1_best']) }} L</p>
-                            <p class="text-sm text-gray-500 mt-1">{{ "%.1f"|format(session.metrics.spirometry['fev1_pred']) }}% predicted</p>
+                            <p class="text-2xl font-bold text-gray-900">
+                                {{
+                                "%.2f"|format(session.metrics.spirometry['fev1_best'])
+                                }} L
+                            </p>
+                            <p class="text-sm text-gray-500 mt-1">
+                                {{
+                                "%.1f"|format(session.metrics.spirometry['fev1_pred'])
+                                }}% predicted
+                            </p>
                         </div>
-                        {% endif %}
-                        {% if session.metrics.spirometry.get('fev1_fvc_pct_best') %}
+                        {% endif %} {% if
+                        session.metrics.spirometry.get('fev1_fvc_pct_best') %}
                         <div class="bg-gray-50 p-4 rounded-lg">
                             <p class="text-sm text-gray-500">FEV1/FVC%</p>
-                            <p class="text-2xl font-bold text-gray-900">{{ "%.2f"|format(session.metrics.spirometry['fev1_fvc_pct_best']) }}%</p>
-                            <p class="text-sm text-gray-500 mt-1">{{ "%.1f"|format(session.metrics.spirometry['fev1_fvc_pct_pred']) }}% predicted</p>
+                            <p class="text-2xl font-bold text-gray-900">
+                                {{
+                                "%.2f"|format(session.metrics.spirometry['fev1_fvc_pct_best'])
+                                }}%
+                            </p>
+                            <p class="text-sm text-gray-500 mt-1">
+                                {{
+                                "%.1f"|format(session.metrics.spirometry['fev1_fvc_pct_pred'])
+                                }}% predicted
+                            </p>
                         </div>
                         {% endif %}
                     </div>
@@ -157,24 +261,8 @@
                 {% endif %}
             </div>
             {% endif %}
-
-            <!-- Graphs Section -->
-            {% if session.graphs_generated %}
-            <div class="mt-8">
-                <h3 class="text-lg font-medium text-gray-900 mb-4">Generated Graphs</h3>
-                <div class="grid grid-cols-1 gap-4 sm:grid-cols-2">
-                    {% for graph in session.graphs_generated %}
-                    <div class="bg-gray-50 p-4 rounded-lg">
-                        <p class="text-sm font-medium text-gray-700 mb-2">{{ graph.name|replace('_', ' ')|title }}</p>
-                        <img src="/graphs/{{ graph.path.split('/')[-1] }}" alt="{{ graph.name }}" class="w-full h-auto rounded">
-                    </div>
-                    {% endfor %}
-                </div>
-            </div>
-            {% endif %}
         </div>
     </div>
     {% endif %}
 </div>
 {% endblock %}
-

app/templates/upload.html

@@ -132,20 +132,6 @@ Generator{% endblock %} {% block content %}
                                 class="mt-1 block w-full rounded-md border-gray-300 shadow-sm focus:border-indigo-500 focus:ring-indigo-500 sm:text-sm px-3 py-2 border"
                             />
                         </div>
-                        <div>
-                            <label
-                                for="session_id"
-                                class="block text-sm font-medium text-gray-700"
-                                >Session ID</label
-                            >
-                            <input
-                                type="text"
-                                name="session_id"
-                                id="session_id"
-                                value="default"
-                                class="mt-1 block w-full rounded-md border-gray-300 shadow-sm focus:border-indigo-500 focus:ring-indigo-500 sm:text-sm px-3 py-2 border"
-                            />
-                        </div>
                         <div>
                             <label
                                 class="block text-sm font-medium text-gray-700 mb-2"

notebooks/analysis.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "id": "b18c1027",
    "metadata": {},
    "outputs": [],
@@ -88,7 +88,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "id": "56a9d655",
    "metadata": {},
    "outputs": [
@@ -104,7 +104,10 @@
    ],
    "source": [
     "import pandas as pd\n",
-    "spirometry_df = pd.read_csv(\"data/spirometry_data.csv\")\n",
+    "import os\n",
+    "\n",
+    "base_dir = os.path.dirname(os.path.abspath('.'))\n",
+    "spirometry_df = pd.read_csv(f\"{base_dir}/data/spirometry_data.csv\")\n",
     "\n",
     "fvc_best = spirometry_df.loc[spirometry_df['Parameters'] == 'FVC', 'Best'].values[0]\n",
     "fvc_pred = spirometry_df.loc[spirometry_df['Parameters'] == 'FVC', '%Pred.'].values[0]\n",
@@ -122,7 +125,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "id": "990f4b4f",
    "metadata": {},
    "outputs": [
@@ -136,7 +139,7 @@
     }
    ],
    "source": [
-    "df = pd.read_csv('data/Pnoe_20250729_1550-Moran_Keirstyn.csv', delimiter=';')\n",
+    "df = pd.read_csv(f'{base_dir}/data/Pnoe_20250729_1550-Moran_Keirstyn.csv', delimiter=';')\n",
     "peak_vt = df['VT(l)'].max()\n",
     "max_vt_row = df.loc[df['VT(l)'].idxmax()]\n",
     "print(f\"Peak VT: {peak_vt}\")\n",
@@ -146,7 +149,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 19,
    "id": "041cbc3d",
    "metadata": {},
    "outputs": [
@@ -154,21 +157,21 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Peak VT: 2.3770000000000002\n",
-      "HR at Peak VT: 171.525\n"
+      "Peak VT: 2.3844444444444446\n",
+      "HR at Peak VT: 172.80555555555554\n"
      ]
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/tmp/ipykernel_69398/4157056299.py:3: FutureWarning: errors='ignore' is deprecated and will raise in a future version. Use to_numeric without passing `errors` and catch exceptions explicitly instead\n",
+      "/tmp/ipykernel_53922/361246798.py:3: FutureWarning: errors='ignore' is deprecated and will raise in a future version. Use to_numeric without passing `errors` and catch exceptions explicitly instead\n",
       "  df = df.apply(pd.to_numeric, errors='ignore')\n"
      ]
     }
    ],
    "source": [
-    "df = pd.read_csv('data/Pnoe_20250729_1550-Moran_Keirstyn.csv', delimiter=';')\n",
+    "df = pd.read_csv(f'{base_dir}/data/Pnoe_20250729_1550-Moran_Keirstyn.csv', delimiter=';')\n",
     "# Convert all columns to numeric where possible, coercing errors to NaN\n",
     "df = df.apply(pd.to_numeric, errors='ignore')\n",
     "df['VO2 Pulse'] = df['VO2(ml/min)'] / df['HR(bpm)']  # VO2 Pulse in mL/beat\n",
@@ -176,7 +179,7 @@
     "df['CHO'] = df['EE(kcal/min)'] * df['CARBS(%)']/100\n",
     "df['FAT'] = df['EE(kcal/min)'] * df['FAT(%)']/100\n",
     "# Smooth key columns using rolling window\n",
-    "window_size = 10\n",
+    "window_size = 9\n",
     "\n",
     "# List of columns to smooth\n",
     "columns_to_smooth = ['VO2(ml/min)', 'VCO2(ml/min)', 'HR(bpm)', 'VT(l)', 'BF(bpm)', 'VE(l/min)', 'VO2 Pulse', 'VO2 Breath', 'CHO', 'FAT']\n",
@@ -195,7 +198,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 20,
    "id": "de7cadd1",
    "metadata": {},
    "outputs": [
@@ -203,7 +206,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Percent FEV: 72.91411042944786\n"
+      "Percent FEV: 73.14246762099523\n"
      ]
     }
    ],
@@ -214,7 +217,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 21,
    "id": "cb972ed3",
    "metadata": {},
    "outputs": [
@@ -311,13 +314,13 @@
        "[1 rows x 147 columns]"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "personal_df = pd.read_excel('data/SECA body comp for all patients.xlsx')\n",
+    "personal_df = pd.read_excel(f'{base_dir}/data/SECA body comp for all patients.xlsx')\n",
     "\n",
     "keirstyn_data = personal_df[personal_df['LastName'].str.contains('Moran', case=False, na=False)]\n",
     "keirstyn_data"
@@ -325,7 +328,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 22,
    "id": "98d9295a",
    "metadata": {},
    "outputs": [
@@ -333,7 +336,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "VO2 Max: 47.906290322580645\n"
+      "VO2 Max: 48.19062126642772\n"
      ]
     }
    ],
@@ -823,7 +826,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "report_generation",
+   "display_name": ".venv",
    "language": "python",
    "name": "python3"
   },
@@ -837,7 +840,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.3"
+   "version": "3.12.6"
   }
  },
  "nbformat": 4,

notebooks/gemini_rer.py

@@ -0,0 +1,249 @@
+import pandas as pd
+
+
+def mifflin_st_jeor(weight_kg, height_cm, age_years, sex):
+    """
+    Compute predicted RMR with Mifflin St Jeor.
+    sex: 'male' or 'female'
+    """
+    base = 10.0 * weight_kg + 6.25 * height_cm - 5.0 * age_years
+    if sex.lower().startswith("m"):
+        return base + 5.0
+    else:
+        return base - 161.0
+
+
+def classify_metabolism(measured_kcal_day, predicted_kcal_day):
+    """
+    Classify metabolic rate relative to prediction.
+    Returns (label, ratio).
+    """
+    ratio = measured_kcal_day / predicted_kcal_day
+
+    if ratio < 0.70:
+        label = "very slow"
+    elif ratio < 0.90:
+        label = "slow"
+    elif ratio <= 1.10:
+        label = "average"
+    elif ratio <= 1.30:
+        label = "fast"
+    else:
+        label = "very fast"
+
+    return label, ratio
+
+
+def find_sampling_window(df):
+    """
+    Derive number of samples that represent about 2 minutes.
+    """
+    dt = df["T(sec)"].diff().median()
+    if dt is None or dt <= 0:
+        raise ValueError("Invalid time step in T(sec)")
+
+    samples = int(round(120.0 / dt))
+    if samples < 1:
+        samples = 1
+    return samples
+
+
+def rolling_stable_window(df, window_samples):
+    """
+    Find the most stable 2-minute window using rolling standard deviation.
+    Returns:
+        means_series, t_start, t_end
+    """
+    cols_mean = [
+        "VO2(ml/min)",
+        "VCO2(ml/min)",
+        "VE(l/min)",
+        "VT(l)",
+        "BF(bpm)",
+        "EE(kcal/min)",
+        "RER",
+        "CARBS(%)",
+        "FAT(%)",
+    ]
+
+    cols_std = [
+        "VO2(ml/min)",
+        "VCO2(ml/min)",
+        "VE(l/min)",
+        "VT(l)",
+        "BF(bpm)",
+    ]
+
+    roll_mean = df[cols_mean].rolling(window_samples, min_periods=window_samples).mean()
+    roll_std = df[cols_std].rolling(window_samples, min_periods=window_samples).std()
+
+    # Sum std devs to get stability score; use skipna=False to preserve NaN for incomplete windows
+    stability_score = roll_std.sum(axis=1, skipna=False)
+
+    # Find index with lowest stability score (dropna to ignore incomplete windows)
+    best_idx = stability_score.dropna().idxmin()
+
+    means_series = roll_mean.loc[best_idx].copy()
+
+    start_idx = max(best_idx - window_samples + 1, 0)
+    end_idx = best_idx
+
+    t_start = float(df["T(sec)"].iloc[start_idx])
+    t_end = float(df["T(sec)"].iloc[end_idx])
+
+    return means_series, t_start, t_end
+
+
+def manual_window_means(df, t_start, t_end):
+    """
+    Compute mean values inside a user-selected time window.
+    """
+    mask = (df["T(sec)"] >= t_start) & (df["T(sec)"] <= t_end)
+    slice_df = df.loc[mask].copy()
+
+    if slice_df.empty:
+        raise ValueError("Manual window has no rows inside T(sec) range")
+
+    cols = [
+        "VO2(ml/min)",
+        "VCO2(ml/min)",
+        "VE(l/min)",
+        "VT(l)",
+        "BF(bpm)",
+        "EE(kcal/min)",
+        "RER",
+        "CARBS(%)",
+        "FAT(%)",
+    ]
+
+    means = slice_df[cols].mean()
+    return means, float(t_start), float(t_end)
+
+
+def load_pnoe_csv(path):
+    """
+    Load and clean a PNOE CSV file.
+    """
+    df = pd.read_csv(path, sep=";")
+
+    numeric_cols = [
+        "T(sec)",
+        "VO2(ml/min)",
+        "VCO2(ml/min)",
+        "RER",
+        "VE(l/min)",
+        "VT(l)",
+        "BF(bpm)",
+        "EE(kcal/min)",
+        "CARBS(%)",
+        "FAT(%)",
+    ]
+
+    for col in numeric_cols:
+        df[col] = pd.to_numeric(df[col], errors="coerce")
+
+    df = df.dropna(subset=["VO2(ml/min)", "EE(kcal/min)"]).reset_index(drop=True)
+    return df
+
+
+def analyze_pnoe_rmr(
+    path,
+    weight_kg,
+    height_cm,
+    age_years,
+    sex,
+    subject_name=None,
+    test_date=None,
+    manual_window=None,
+):
+    """
+    Analyze resting RMR from a PNOE CSV file.
+
+    manual_window:
+        None for automatic stable window
+        or (t_start_sec, t_end_sec) for user-chosen window
+    """
+    df = load_pnoe_csv(path)
+    window_samples = find_sampling_window(df)
+
+    # Automatic stable window
+    auto_means, auto_t_start, auto_t_end = rolling_stable_window(df, window_samples)
+
+    # Manual override if provided
+    manual_means = None
+    manual_t_start = None
+    manual_t_end = None
+
+    if manual_window is not None:
+        t_start_manual, t_end_manual = manual_window
+        manual_means, manual_t_start, manual_t_end = manual_window_means(
+            df, t_start_manual, t_end_manual
+        )
+        chosen_source = "manual"
+        chosen_means = manual_means
+        chosen_t_start = manual_t_start
+        chosen_t_end = manual_t_end
+    else:
+        chosen_source = "auto"
+        chosen_means = auto_means
+        chosen_t_start = auto_t_start
+        chosen_t_end = auto_t_end
+
+    kcal_per_min = float(chosen_means["EE(kcal/min)"])
+    rmr_kcal_day = kcal_per_min * 1440.0
+
+    predicted_kcal_day = mifflin_st_jeor(weight_kg, height_cm, age_years, sex)
+    label, ratio = classify_metabolism(rmr_kcal_day, predicted_kcal_day)
+
+    def pack_metrics(prefix, means, t_start, t_end):
+        if means is None:
+            return {}
+        return {
+            f"{prefix}_window_start_sec": t_start,
+            f"{prefix}_window_end_sec": t_end,
+            f"{prefix}_VO2_L_min": float(means["VO2(ml/min)"]) / 1000.0,
+            f"{prefix}_VCO2_L_min": float(means["VCO2(ml/min)"]) / 1000.0,
+            f"{prefix}_VE_L_min": float(means["VE(l/min)"]),
+            f"{prefix}_VT_L": float(means["VT(l)"]),
+            f"{prefix}_BF_bpm": float(means["BF(bpm)"]),
+            f"{prefix}_RER": float(means["RER"]),
+            f"{prefix}_Fat_percent": float(means["FAT(%)"]),
+            f"{prefix}_Carb_percent": float(means["CARBS(%)"]),
+            f"{prefix}_kcal_per_min": float(means["EE(kcal/min)"]),
+        }
+
+    result = {
+        "subject_name": subject_name,
+        "test_date": test_date,
+        "sex": sex,
+        "weight_kg": weight_kg,
+        "height_cm": height_cm,
+        "age_years": age_years,
+        "chosen_window_source": chosen_source,
+        "chosen_window_start_sec": chosen_t_start,
+        "chosen_window_end_sec": chosen_t_end,
+        "RMR_kcal_day": rmr_kcal_day,
+        "Mifflin_kcal_day": predicted_kcal_day,
+        "Measured_to_Mifflin_ratio": ratio,
+        "Metabolic_classification": label,
+    }
+
+    result.update(pack_metrics("auto", auto_means, auto_t_start, auto_t_end))
+    result.update(pack_metrics("manual", manual_means, manual_t_start, manual_t_end))
+
+    return result
+
+
+result = analyze_pnoe_rmr(
+    path="/home/oluwasanmi/Documents/Work/MKD/report_generation/data/Pnoe_20250729_1550-Moran_Keirstyn.csv",
+    weight_kg=56,
+    height_cm=162,
+    age_years=34,
+    sex="female",
+    subject_name="Cullen Pacas",
+    test_date="2025-11-12",
+    manual_window=None,  # or (t_start_sec, t_end_sec)
+)
+
+for key, value in result.items():
+    print(f"{key}: {value}")