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Checkpoint 3

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This commit is contained in:
bolade
2025-11-28 16:19:32 +01:00
parent fc62b64624
commit 35ea522283
10 changed files with 113 additions and 72 deletions
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app/services/context_generator.py
+64 -32
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@@ -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(