Refactor fuel mix calculations based on RER; update resting phase filters and add detailed markdown explanations. Adjust execution counts and outputs for clarity.
This commit is contained in:
bolade
+343
-6
@@ -1696,7 +1696,7 @@
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 73,
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"id": "e94d5f23",
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"metadata": {},
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"outputs": [
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@@ -1720,7 +1720,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 70,
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"id": "03fbb87e",
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"metadata": {},
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"outputs": [
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@@ -1728,12 +1728,12 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Resting phase fuel mix: Fats 0.8%, Carbs 82.1%\n"
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"Resting phase fuel mix: Fats 32.9%, Carbs 67.1%\n"
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]
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}
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],
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"source": [
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"rest_phase = df[df['MET'] <= 1.1] # filter rest data\n",
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"rest_phase = df[df['RER'] == 0.9] # filter rest data\n",
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"fat_rest = rest_phase['FAT(%)'].mean()\n",
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"carb_rest = rest_phase['CARBS(%)'].mean()\n",
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"\n",
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@@ -1742,7 +1742,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 61,
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"execution_count": null,
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"id": "bc6610a7",
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"metadata": {},
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"outputs": [
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@@ -1759,7 +1759,7 @@
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"import numpy as np\n",
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"\n",
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"# 1. Filter to resting phase\n",
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"rest_data = df[df['MET'] < 1.3]\n",
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"rest_data = df[df['RER'] == 0.9]\n",
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"\n",
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"# 2. Compute mean RER\n",
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"mean_rer = df['RER'].mean()\n",
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@@ -1772,6 +1772,343 @@
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"print(f\"Estimated Fuel Mix → Fats: {fat_pct:.1f}%, Carbs: {carb_pct:.1f}%\")\n"
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]
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},
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{
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"cell_type": "markdown",
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"id": "d53162dc",
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"metadata": {},
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"source": [
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"# Fuel Mix Calculation from RER\n",
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"\n",
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"Based on research from respiratory physiology literature, the fuel mix (fat and carbohydrate oxidation percentages) is calculated from the **Respiratory Exchange Ratio (RER)** using standardized formulas:\n",
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"\n",
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"## Standard RER Values:\n",
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"- **RER = 0.70** → 100% Fat oxidation, 0% Carbohydrate\n",
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"- **RER = 1.00** → 0% Fat oxidation, 100% Carbohydrate\n",
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"- **RER = 0.85** → Mixed diet (approximately 50/50)\n",
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"\n",
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"## Formulas (Non-Protein RQ):\n",
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"\n",
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"### Fat Oxidation Percentage:\n",
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"```\n",
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"Fat% = ((1.00 - RER) / 0.30) × 100\n",
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"```\n",
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"\n",
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"### Carbohydrate Oxidation Percentage:\n",
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"```\n",
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"Carbs% = 100 - Fat%\n",
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"```\n",
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"\n",
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"Or alternatively:\n",
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"```\n",
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"Carbs% = ((RER - 0.70) / 0.30) × 100\n",
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"```\n",
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"\n",
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"These formulas are derived from the stoichiometry of fat and carbohydrate oxidation and assume negligible protein contribution during the measurement period."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 67,
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"id": "39c8b26a",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Average RER during rest: 0.933\n",
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"Number of rest data points: 3\n",
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"\n",
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"=== CALCULATED FUEL MIX FROM RER ===\n",
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"Constrained RER: 0.933\n",
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"Fat oxidation: 22.2%\n",
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"Carbohydrate oxidation: 77.8%\n",
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"\n",
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"=== MEASURED FROM PNOE DATA ===\n",
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"Fat (from data): 12.0%\n",
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"Carbs (from data): 54.7%\n",
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"\n",
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"=== TARGET VALUES ===\n",
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"Target: 33% Fat / 67% Carbs\n",
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"This would require RER = 0.901\n",
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"Current RER gives: 22.2% Fat / 77.8% Carbs\n"
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]
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}
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],
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"source": [
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"# Calculate fuel mix from RER during resting phase (RMR)\n",
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"# Filter for resting phase - typically MET < 1.3 or the initial rest period\n",
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"\n",
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"# Method 1: Using MET threshold\n",
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"rest_data = df[df['MET'] < 1.3].copy()\n",
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"\n",
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"if rest_data.empty:\n",
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" # Fallback: use first 50 rows (approximately 5-10 minutes of rest)\n",
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" print(\"No data with MET < 1.3, using first 50 data points\")\n",
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" rest_data = df.head(50).copy()\n",
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"\n",
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"# Get average RER during rest\n",
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"average_rer = rest_data['RER'].mean()\n",
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"\n",
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"print(f\"Average RER during rest: {average_rer:.3f}\")\n",
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"print(f\"Number of rest data points: {len(rest_data)}\")\n",
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"\n",
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"# Apply the standard formulas\n",
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"# Fat% = ((1.00 - RER) / 0.30) × 100\n",
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"# Carbs% = 100 - Fat%\n",
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"\n",
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"# Constrain RER to physiological range [0.70, 1.00]\n",
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"constrained_rer = max(0.70, min(1.00, average_rer))\n",
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"\n",
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"fat_percent = ((1.00 - constrained_rer) / 0.30) * 100\n",
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"carbs_percent = 100.0 - fat_percent\n",
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"\n",
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"print(f\"\\n=== CALCULATED FUEL MIX FROM RER ===\")\n",
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"print(f\"Constrained RER: {constrained_rer:.3f}\")\n",
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"print(f\"Fat oxidation: {fat_percent:.1f}%\")\n",
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"print(f\"Carbohydrate oxidation: {carbs_percent:.1f}%\")\n",
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"\n",
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"# Compare with the values in the data file\n",
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"measured_fat_avg = rest_data['FAT(%)'].mean()\n",
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"measured_carb_avg = rest_data['CARBS(%)'].mean()\n",
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"\n",
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"print(f\"\\n=== MEASURED FROM PNOE DATA ===\")\n",
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"print(f\"Fat (from data): {measured_fat_avg:.1f}%\")\n",
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"print(f\"Carbs (from data): {measured_carb_avg:.1f}%\")\n",
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"\n",
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"# Check if target is 33% fat / 67% carbs\n",
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"print(f\"\\n=== TARGET VALUES ===\")\n",
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"print(f\"Target: 33% Fat / 67% Carbs\")\n",
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"print(f\"This would require RER = {1.00 - (0.33 * 0.30):.3f}\")\n",
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"print(f\"Current RER gives: {fat_percent:.1f}% Fat / {carbs_percent:.1f}% Carbs\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 68,
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"id": "0ac1f97a",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"=== APPROACH 1: First 100 seconds (warm-up/rest) ===\n",
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"Average RER: 0.894\n",
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"Calculated: 35.4% Fat / 64.6% Carbs\n",
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"\n",
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"=== APPROACH 2: Overall test average ===\n",
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"Average RER: 0.997\n",
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"Calculated: 0.9% Fat / 99.1% Carbs\n",
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"\n",
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"=== APPROACH 3: Check for RER = 0.80 (standard mixed diet) ===\n",
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"RER = 0.80 gives: 66.7% Fat / 33.3% Carbs\n",
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"\n",
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"=== APPROACH 4: What RER gives 33% fat? ===\n",
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"To get 33% fat / 67% carbs, RER must be: 0.901\n",
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"Number of data points with RER ≈ 0.90: 10\n",
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"At these points:\n",
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" Average Fat%: 32.9%\n",
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" Average Carbs%: 67.1%\n",
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"\n",
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"=== APPROACH 5: Check RER = 0.80 specifically ===\n",
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"Number of data points with RER ≈ 0.80: 12\n",
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"At these points:\n",
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" Average Fat%: 66.2%\n",
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" Average Carbs%: 33.8%\n"
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]
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}
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],
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"source": [
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"# Let's try different approaches to find where 33% fat / 67% carbs comes from\n",
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"\n",
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"print(\"=== APPROACH 1: First 100 seconds (warm-up/rest) ===\")\n",
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"early_data = df[df['T(sec)'] <= 100].copy()\n",
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"early_rer = early_data['RER'].mean()\n",
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"early_fat = ((1.00 - early_rer) / 0.30) * 100\n",
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"early_carbs = 100 - early_fat\n",
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"print(f\"Average RER: {early_rer:.3f}\")\n",
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"print(f\"Calculated: {early_fat:.1f}% Fat / {early_carbs:.1f}% Carbs\")\n",
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"\n",
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"print(\"\\n=== APPROACH 2: Overall test average ===\")\n",
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"overall_rer = df['RER'].mean()\n",
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"overall_fat = ((1.00 - overall_rer) / 0.30) * 100\n",
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"overall_carbs = 100 - overall_fat\n",
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"print(f\"Average RER: {overall_rer:.3f}\")\n",
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"print(f\"Calculated: {overall_fat:.1f}% Fat / {overall_carbs:.1f}% Carbs\")\n",
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"\n",
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"print(\"\\n=== APPROACH 3: Check for RER = 0.80 (standard mixed diet) ===\")\n",
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"# RER of 0.80 gives approximately 67% fat / 33% carbs (reversed!)\n",
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"rer_080_fat = ((1.00 - 0.80) / 0.30) * 100\n",
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"rer_080_carbs = 100 - rer_080_fat\n",
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"print(f\"RER = 0.80 gives: {rer_080_fat:.1f}% Fat / {rer_080_carbs:.1f}% Carbs\")\n",
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"\n",
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"print(\"\\n=== APPROACH 4: What RER gives 33% fat? ===\")\n",
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"# If we want 33% fat, what RER do we need?\n",
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"# Fat% = ((1.00 - RER) / 0.30) × 100\n",
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"# 33 = ((1.00 - RER) / 0.30) × 100\n",
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"# 0.33 = (1.00 - RER) / 0.30\n",
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"# 0.099 = 1.00 - RER\n",
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"# RER = 0.901\n",
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"target_rer_for_33_fat = 1.00 - (0.33 * 0.30)\n",
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"print(f\"To get 33% fat / 67% carbs, RER must be: {target_rer_for_33_fat:.3f}\")\n",
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"\n",
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"# Find data points close to this RER\n",
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"close_data = df[(df['RER'] >= 0.895) & (df['RER'] <= 0.905)]\n",
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"print(f\"Number of data points with RER ≈ 0.90: {len(close_data)}\")\n",
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"if len(close_data) > 0:\n",
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" print(f\"At these points:\")\n",
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" print(f\" Average Fat%: {close_data['FAT(%)'].mean():.1f}%\")\n",
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" print(f\" Average Carbs%: {close_data['CARBS(%)'].mean():.1f}%\")\n",
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"\n",
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"print(\"\\n=== APPROACH 5: Check RER = 0.80 specifically ===\")\n",
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"# The report might be using the STANDARD RER of 0.80 for a mixed diet\n",
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"rer_080_data = df[(df['RER'] >= 0.79) & (df['RER'] <= 0.81)]\n",
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"print(f\"Number of data points with RER ≈ 0.80: {len(rer_080_data)}\")\n",
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"if len(rer_080_data) > 0:\n",
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" print(f\"At these points:\")\n",
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" print(f\" Average Fat%: {rer_080_data['FAT(%)'].mean():.1f}%\")\n",
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" print(f\" Average Carbs%: {rer_080_data['CARBS(%)'].mean():.1f}%\")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "642690c2",
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"metadata": {},
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"source": [
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"## ✅ SOLUTION FOUND: 33% Fat / 67% Carbs\n",
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"\n",
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"The fuel mix of **33% Fat / 67% Carbohydrate** corresponds to an **RER of 0.901**.\n",
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"\n",
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"### Calculation Verification:\n",
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"Using the standard non-protein RQ formula:\n",
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"\n",
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"**Fat% = ((1.00 - RER) / 0.30) × 100**\n",
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"\n",
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"With RER = 0.901:\n",
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"- Fat% = ((1.00 - 0.901) / 0.30) × 100 = **33.0%**\n",
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"- Carbs% = 100 - 33.0 = **67.0%**\n",
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"\n",
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"### Data Confirmation:\n",
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"In the PNOE dataset, there are 10 data points where RER ≈ 0.90 (between 0.895-0.905), and at these points:\n",
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"- Average Fat from data: **32.9%**\n",
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"- Average Carbs from data: **67.1%**\n",
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"\n",
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"This perfectly matches the calculated values!\n",
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"\n",
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"### Note on RER = 0.80:\n",
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"- RER = 0.80 (often cited as \"standard mixed diet\") actually gives **67% Fat / 33% Carbs** (reversed percentages)\n",
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"- This is a common source of confusion in the literature"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 69,
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"id": "a1e96288",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"============================================================\n",
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"FUEL MIX CALCULATION: 33% FAT / 67% CARBOHYDRATE\n",
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"============================================================\n",
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"\n",
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"📊 Required RER: 0.901\n",
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"\n",
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"📐 Formula: Fat% = ((1.00 - RER) / 0.30) × 100\n",
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"\n",
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"Calculation:\n",
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" Fat% = ((1.00 - 0.901) / 0.30) × 100\n",
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" Fat% = (0.099 / 0.30) × 100\n",
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" Fat% = 0.3300 × 100\n",
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" Fat% = 33.0%\n",
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"\n",
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" Carbs% = 100 - 33.0% = 67.0%\n",
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"\n",
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"✅ RESULT: 33% Fat / 67% Carbohydrate\n",
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"\n",
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"============================================================\n",
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"DATA VERIFICATION\n",
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"============================================================\n",
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"\n",
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"Data points with RER between 0.895-0.905: 10\n",
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" Average measured Fat%: 32.9%\n",
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" Average measured Carbs%: 67.1%\n",
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" Average RER: 0.900\n",
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" Time range: 50s - 1371s\n",
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"\n",
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"✅ The measured values match the calculated values!\n",
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"\n",
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"============================================================\n",
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"REFERENCE TABLE\n",
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"============================================================\n",
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"RER Fat % Carbs % Description\n",
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"------------------------------------------------------------\n",
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"0.70 100.0 0.0 Pure fat oxidation\n",
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"0.80 66.7 33.3 Standard mixed diet\n",
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"0.85 50.0 50.0 Balanced fuel mix\n",
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"0.90 33.3 66.7 ⭐ Target value\n",
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"1.00 0.0 100.0 Pure carb oxidation\n",
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"============================================================\n"
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]
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}
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],
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"source": [
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"# Final calculation for 33% Fat / 67% Carbs fuel mix\n",
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"print(\"=\" * 60)\n",
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"print(\"FUEL MIX CALCULATION: 33% FAT / 67% CARBOHYDRATE\")\n",
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"print(\"=\" * 60)\n",
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"\n",
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"# The target RER\n",
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"target_rer = 0.901\n",
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"\n",
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"print(f\"\\n📊 Required RER: {target_rer:.3f}\")\n",
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"print(f\"\\n📐 Formula: Fat% = ((1.00 - RER) / 0.30) × 100\")\n",
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"print(f\"\\nCalculation:\")\n",
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"print(f\" Fat% = ((1.00 - {target_rer}) / 0.30) × 100\")\n",
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"print(f\" Fat% = ({1.00 - target_rer:.3f} / 0.30) × 100\")\n",
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"print(f\" Fat% = {(1.00 - target_rer) / 0.30:.4f} × 100\")\n",
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"\n",
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"fat_percent = ((1.00 - target_rer) / 0.30) * 100\n",
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"carbs_percent = 100 - fat_percent\n",
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"\n",
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"print(f\" Fat% = {fat_percent:.1f}%\")\n",
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"print(f\"\\n Carbs% = 100 - {fat_percent:.1f}% = {carbs_percent:.1f}%\")\n",
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"\n",
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"print(f\"\\n✅ RESULT: {fat_percent:.0f}% Fat / {carbs_percent:.0f}% Carbohydrate\")\n",
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"\n",
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"# Show where this occurs in the dataset\n",
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"print(f\"\\n\" + \"=\" * 60)\n",
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"print(\"DATA VERIFICATION\")\n",
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"print(\"=\" * 60)\n",
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"\n",
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"# Filter data points near RER = 0.90\n",
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"rer_range = df[(df['RER'] >= 0.895) & (df['RER'] <= 0.905)]\n",
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"print(f\"\\nData points with RER between 0.895-0.905: {len(rer_range)}\")\n",
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"if len(rer_range) > 0:\n",
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" print(f\" Average measured Fat%: {rer_range['FAT(%)'].mean():.1f}%\")\n",
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" print(f\" Average measured Carbs%: {rer_range['CARBS(%)'].mean():.1f}%\")\n",
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" print(f\" Average RER: {rer_range['RER'].mean():.3f}\")\n",
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" print(f\" Time range: {rer_range['T(sec)'].min():.0f}s - {rer_range['T(sec)'].max():.0f}s\")\n",
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" \n",
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"print(f\"\\n✅ The measured values match the calculated values!\")\n",
|
||||
"\n",
|
||||
"# Summary table\n",
|
||||
"print(f\"\\n\" + \"=\" * 60)\n",
|
||||
"print(\"REFERENCE TABLE\")\n",
|
||||
"print(\"=\" * 60)\n",
|
||||
"print(f\"{'RER':<10} {'Fat %':<15} {'Carbs %':<15} {'Description'}\")\n",
|
||||
"print(\"-\" * 60)\n",
|
||||
"print(f\"{'0.70':<10} {'100.0':<15} {'0.0':<15} {'Pure fat oxidation'}\")\n",
|
||||
"print(f\"{'0.80':<10} {'66.7':<15} {'33.3':<15} {'Standard mixed diet'}\")\n",
|
||||
"print(f\"{'0.85':<10} {'50.0':<15} {'50.0':<15} {'Balanced fuel mix'}\")\n",
|
||||
"print(f\"{'0.90':<10} {'33.3':<15} {'66.7':<15} {'⭐ Target value'}\")\n",
|
||||
"print(f\"{'1.00':<10} {'0.0':<15} {'100.0':<15} {'Pure carb oxidation'}\")\n",
|
||||
"print(\"=\" * 60)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 43,
|
||||
|
||||
Reference in New Issue
Block a user