Checkpoint 3
This commit is contained in:
bolade
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+3
-3
@@ -179,10 +179,10 @@ async def upload_files(
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# Prepare patient information
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patient_name = f"{first_name} {last_name}"
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print(f"DEBUG: Received next_testing_date: '{next_testing_date}'")
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# Generate session_id internally using timestamp for unique identification
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session_id = datetime.now().strftime("%Y%m%d_%H%M%S")
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patient_info = {
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"patient_name": patient_name,
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"first_name": first_name,
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@@ -642,7 +642,7 @@ async def generate_report(
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# Generate session_id internally using timestamp for unique identification
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session_id = datetime.now().strftime("%Y%m%d_%H%M%S")
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# Prepare patient information
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patient_info = {
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"patient_name": patient_name,
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@@ -15,7 +15,8 @@
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<!-- Lung Analysis -->
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<div class="flex items-start bg-gray-200 h-24">
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<div
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class="bg-black text-white text-2xl font-bold w-16 h-full flex items-center justify-center mr-8 flex-shrink-0"
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class="bg-black text-white text-4xl font-extrabold w-24 h-24 flex items-center justify-center mr-8 flex-shrink-0"
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style="border-radius: 0;"
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>
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3
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</div>
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@@ -35,7 +36,8 @@
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<!-- Cardio Metrics -->
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<div class="flex items-start bg-gray-200 h-24">
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<div
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class="bg-black text-white text-2xl font-bold w-16 h-full flex items-center justify-center mr-8 flex-shrink-0"
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class="bg-black text-white text-4xl font-extrabold w-24 h-24 flex items-center justify-center mr-8 flex-shrink-0"
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style="border-radius: 0;"
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>
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4
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</div>
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@@ -52,7 +54,8 @@
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<!-- Fuel Utilization -->
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<div class="flex items-start bg-gray-200 h-24">
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<div
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class="bg-black text-white text-2xl font-bold w-16 h-full flex items-center justify-center mr-8 flex-shrink-0"
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class="bg-black text-white text-4xl font-extrabold w-24 h-24 flex items-center justify-center mr-8 flex-shrink-0"
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style="border-radius: 0;"
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>
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5
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</div>
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@@ -66,7 +69,8 @@
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<!-- Local Muscle Activity -->
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<div class="flex items-start bg-gray-200 h-24">
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<div
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class="bg-black text-white text-2xl font-bold w-16 h-full flex items-center justify-center mr-8 flex-shrink-0"
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class="bg-black text-white text-4xl font-extrabold w-24 h-24 flex items-center justify-center mr-8 flex-shrink-0"
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style="border-radius: 0;"
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>
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9
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</div>
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@@ -80,7 +84,8 @@
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<!-- Training Recommendations -->
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<div class="flex items-start bg-gray-200 h-24">
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<div
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class="bg-black text-white text-2xl font-bold w-16 h-full flex items-center justify-center mr-8 flex-shrink-0"
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class="bg-black text-white text-4xl font-extrabold w-24 h-24 flex items-center justify-center mr-8 flex-shrink-0"
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style="border-radius: 0;"
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>
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10
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</div>
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@@ -94,7 +99,8 @@
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<!-- Next Steps -->
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<div class="flex items-start bg-gray-200 h-24">
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<div
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class="bg-black text-white text-2xl font-bold w-16 h-full flex items-center justify-center mr-8 flex-shrink-0"
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class="bg-black text-white text-4xl font-extrabold w-24 h-24 flex items-center justify-center mr-8 flex-shrink-0"
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style="border-radius: 0;"
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>
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12
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</div>
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@@ -111,7 +117,8 @@
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<!-- Glossary -->
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<div class="flex items-start bg-gray-200 h-24">
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<div
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class="bg-black text-white text-2xl font-bold w-16 h-full flex items-center justify-center mr-8 flex-shrink-0"
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class="bg-black text-white text-4xl font-extrabold w-24 h-24 flex items-center justify-center mr-8 flex-shrink-0"
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style="border-radius: 0;"
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>
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13
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</div>
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@@ -15,7 +15,8 @@
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<!-- Nutrition Guidelines -->
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<div class="flex items-start bg-gray-200 h-24">
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<div
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class="bg-black text-white text-2xl font-bold w-16 h-full flex items-center justify-center mr-8 flex-shrink-0"
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class="bg-black text-white text-4xl font-extrabold w-24 h-24 flex items-center justify-center mr-8 flex-shrink-0"
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style="border-radius: 0;"
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>
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3
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</div>
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@@ -35,7 +36,8 @@
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<!-- Nutrition Recommendations -->
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<div class="flex items-start bg-gray-200 h-24">
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<div
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class="bg-black text-white text-2xl font-bold w-16 h-full flex items-center justify-center mr-8 flex-shrink-0"
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class="bg-black text-white text-4xl font-extrabold w-24 h-24 flex items-center justify-center mr-8 flex-shrink-0"
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style="border-radius: 0;"
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>
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4
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</div>
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@@ -49,7 +51,8 @@
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<!-- Next Steps -->
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<div class="flex items-start bg-gray-200 h-24">
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<div
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class="bg-black text-white text-2xl font-bold w-16 h-full flex items-center justify-center mr-8 flex-shrink-0"
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class="bg-black text-white text-4xl font-extrabold w-24 h-24 flex items-center justify-center mr-8 flex-shrink-0"
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style="border-radius: 0;"
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>
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5
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</div>
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@@ -66,7 +69,8 @@
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<!-- Glossary -->
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<div class="flex items-start bg-gray-200 h-24">
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<div
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class="bg-black text-white text-2xl font-bold w-16 h-full flex items-center justify-center mr-8 flex-shrink-0"
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class="bg-black text-white text-4xl font-extrabold w-24 h-24 flex items-center justify-center mr-8 flex-shrink-0"
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style="border-radius: 0;"
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>
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6
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</div>
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@@ -82,8 +86,3 @@
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</div>
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</div>
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</div>
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@@ -26,7 +26,7 @@
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<!-- Indications Box -->
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<div class="bg-gray-200 rounded-lg p-4 text-center mb-2">
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<h3 class="font-semibold text-lg mb-2">Indications</h3>
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<p >{{ indication | default('No Respiratory Capacity Limitations')}}</p>
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<p >{{ indication | default('No Respiratory Capacity Limitation')}}</p>
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</div>
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</div>
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@@ -232,10 +232,15 @@ class ContextGenerator:
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if zone_key in metric_overrides:
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metrics[zone_key] = metric_overrides[zone_key]
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else:
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fat_max_idx = self.pnoe_df["FAT_smoothed"].idxmax()
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fat_max_row = self.pnoe_df.loc[fat_max_idx]
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# Use optimal fat burning zone (highest fat:carb ratio) - same as _calculate_zone_metrics
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# This ensures consistency between zone calculations and zone metrics
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self.pnoe_df["fat_carb_ratio"] = self.pnoe_df["FAT_smoothed"] / (
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self.pnoe_df["CHO_smoothed"] + 0.00000001
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)
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optimal_fat_idx = self.pnoe_df["fat_carb_ratio"].idxmax()
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optimal_row = self.pnoe_df.loc[optimal_fat_idx]
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zones = self._calculate_hr_zones(
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metrics["vt1"], metrics["vt2"], fat_max_row
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metrics["vt1"], metrics["vt2"], optimal_row
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)
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metrics.update(zones)
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@@ -280,29 +285,46 @@ class ContextGenerator:
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return vt1, vt2
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def _calculate_hr_zones(
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self, vt1: Optional[Dict], vt2: Optional[Dict], fat_max_row: pd.Series
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self, vt1: Optional[Dict], vt2: Optional[Dict], optimal_row: pd.Series
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) -> Dict:
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"""Calculate heart rate zones based on thresholds"""
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"""Calculate heart rate zones based on thresholds
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Uses optimal fat burning zone (highest fat:carb ratio) to match _calculate_zone_metrics.
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This ensures consistency between zone string calculations and zone metrics table.
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"""
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import math
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zones = {}
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if vt1 and vt2:
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zone_1_start = fat_max_row["HR(bpm)_smoothed"] - 15
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zone_2_start = fat_max_row["HR(bpm)_smoothed"]
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zone_3_start = vt1["HeartRate"]
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zone_4_start = vt2["HeartRate"] - 10
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zone_5_start = vt2["HeartRate"] + 10
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# Use same zone boundary calculation as _calculate_zone_metrics
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zone_1_start = math.floor(optimal_row["HR(bpm)_smoothed"] - 15)
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zone_2_start = math.floor(optimal_row["HR(bpm)_smoothed"])
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zone_3_start = math.floor(vt1["HeartRate"])
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zone_4_start = math.floor(vt2["HeartRate"] - 10)
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zone_5_start = math.floor(vt2["HeartRate"])
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# zone_5_end is calculated for consistency with _calculate_zone_metrics
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# (not used in string format since zone 5 is open-ended: "+bpm")
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zone_5_end = math.floor(vt2["HeartRate"] + 10) # noqa: F841
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zones["zone1_bpm"] = f"{int(zone_1_start)}-{int(zone_2_start)}bpm"
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zones["zone2_bpm"] = f"{int(zone_2_start)}-{int(vt1['HeartRate'])}bpm"
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zones["zone3_bpm"] = f"{int(zone_3_start)}-{int(zone_4_start)}bpm"
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zones["zone4_bpm"] = f"{int(zone_4_start)}-{int(zone_5_start)}bpm"
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zones["zone5_bpm"] = f"{int(zone_5_start)}+bpm"
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# Calculate zone ends to match _calculate_zone_metrics exactly
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zone_1_end = zone_2_start
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zone_2_end = math.floor(vt1["HeartRate"])
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zone_3_end = zone_4_start
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zone_4_end = zone_5_start
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# Format zones to match _calculate_zone_metrics output
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zones["zone1_bpm"] = f"{int(zone_1_start)}-{int(zone_1_end)}bpm"
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zones["zone2_bpm"] = f"{int(zone_2_start)}-{int(zone_2_end)}bpm"
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zones["zone3_bpm"] = f"{int(zone_3_start)}-{int(zone_3_end)}bpm"
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zones["zone4_bpm"] = f"{int(zone_4_start)}-{int(zone_4_end)}bpm"
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zones["zone5_bpm"] = f"{int(zone_5_start)}-{int(zone_5_end)}bpm"
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else:
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max_hr = 220 - self.patient_info["age"]
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zones["zone1_bpm"] = f"{int(max_hr * 0.55)}-{int(max_hr * 0.65)}bpm"
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zones["zone2_bpm"] = f"{int(max_hr * 0.65)}-{int(max_hr * 0.75)}bpm"
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zones["zone3_bpm"] = f"{int(max_hr * 0.75)}-{int(max_hr * 0.85)}bpm"
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zones["zone4_bpm"] = f"{int(max_hr * 0.85)}-{int(max_hr * 0.95)}bpm"
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zones["zone5_bpm"] = f"{int(max_hr * 0.95)}+bpm"
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zones["zone5_bpm"] = f"{int(max_hr * 0.95)}-{int(max_hr * 1.05)}bpm"
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return zones
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def _calculate_vo2_drop_points(self, pnoe_metrics: Dict) -> Dict:
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@@ -1180,7 +1202,9 @@ class ContextGenerator:
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"page_number": 4,
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"fat_percentage": f"{self.patient_info['fat_percentage']:.1f}",
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"body_composition_chart": graphs.get("body_composition", ""),
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"body_fat_chart": graphs.get("body_fat_percent", ""), # Alias for template
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"body_fat_chart": graphs.get(
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"body_fat_percent", ""
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), # Alias for template
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"body_fat_percent_chart": graphs.get(
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"body_fat_percent", ""
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), # Keep for consistency
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@@ -1199,29 +1223,29 @@ class ContextGenerator:
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"weight_loss_rate": rmr_metrics.get("weight_loss_rate", 1.0),
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"total_calories": rmr_metrics.get("total_calories", 1375),
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}
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# For minimal reports, also generate resting heart rate table for page_5
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if report_type == "minimal" and graph_generator:
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resting_hr_metrics = self._calculate_resting_heart_rate_metrics()
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rhr_table_info = self._calculate_rhr_table_data(
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self.patient_info["age"], self.patient_info["gender"]
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)
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# Get resting heart rate value and determine category
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rhr_value_str = resting_hr_metrics.get("resting_heart_rate", "0bpm")
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rhr_value = float(rhr_value_str.replace("bpm", "").strip())
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category = self._determine_rhr_category(
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rhr_value,
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self.patient_info["age"],
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self.patient_info["gender"],
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)
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gender_label = (
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"F" if self.patient_info["gender"].lower().startswith("f") else "M"
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)
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age_range_label = f"{rhr_table_info['age_range']} ({gender_label})"
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rhr_columns = [
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"Age",
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"Poor",
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@@ -1244,7 +1268,7 @@ class ContextGenerator:
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rhr_table_info["ranges"]["Athlete"],
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]
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]
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contexts["page_5"]["rhr_table"] = (
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graph_generator.generate_resting_heart_rate_table(
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data=rhr_data,
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@@ -1265,12 +1289,16 @@ class ContextGenerator:
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"deficit_carbs": f"{int(rmr_metrics.get('total_calories', 1600) * 0.39 / 4)}g Carbs",
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"deficit_fat": f"{int(rmr_metrics.get('total_calories', 1600) * 0.39 / 9)}g Fat",
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"deficit_fiber": "24g Fibre",
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"refeed_weekday_calories": int(rmr_metrics.get("total_calories", 1600) * 0.85),
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"refeed_weekday_calories": int(
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rmr_metrics.get("total_calories", 1600) * 0.85
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),
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"refeed_weekday_protein": f"{int(rmr_metrics.get('total_calories', 1600) * 0.85 * 0.22 / 4)}g Protein",
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"refeed_weekday_carbs": f"{int(rmr_metrics.get('total_calories', 1600) * 0.85 * 0.39 / 4)}g Carbs",
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"refeed_weekday_fat": f"{int(rmr_metrics.get('total_calories', 1600) * 0.85 * 0.39 / 9)}g Fat",
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"refeed_weekday_fiber": "20g Fibre",
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"refeed_weekend_calories": int(rmr_metrics.get("total_calories", 1600) * 1.375),
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"refeed_weekend_calories": int(
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rmr_metrics.get("total_calories", 1600) * 1.375
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),
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"refeed_weekend_protein": f"{int(rmr_metrics.get('total_calories', 1600) * 1.375 * 0.22 / 4)}g Protein",
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"refeed_weekend_carbs": f"{int(rmr_metrics.get('total_calories', 1600) * 1.375 * 0.39 / 4)}g Carbs",
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"refeed_weekend_fat": f"{int(rmr_metrics.get('total_calories', 1600) * 1.375 * 0.39 / 9)}g Fat",
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@@ -1291,12 +1319,12 @@ class ContextGenerator:
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# Page 7
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contexts["page_7"] = {
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"peak_vt": f"{pnoe_metrics['peak_vt']:.2f}",
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"peak_vt_bpm": f"{int(pnoe_metrics['peak_vt_hr'])}",
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"fev1_percentage": f"{fev1_percentage:.1f}",
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"lung_analysis_chart": graphs.get("spirometry_chart", ""),
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"respiratory_analysis_chart": graphs.get("respiratory", ""),
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}
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"peak_vt": f"{pnoe_metrics['peak_vt']:.2f}",
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"peak_vt_bpm": f"{int(pnoe_metrics['peak_vt_hr'])}",
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"fev1_percentage": f"{fev1_percentage:.1f}",
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"lung_analysis_chart": graphs.get("spirometry_chart", ""),
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"respiratory_analysis_chart": graphs.get("respiratory", ""),
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}
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# Page 8
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contexts["page_8"] = {
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@@ -1562,7 +1590,11 @@ class ContextGenerator:
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}
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# For minimal reports, create combined context for page_19_20_minimal
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if report_type == "minimal" and 19 in pages_to_generate and 20 in pages_to_generate:
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if (
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report_type == "minimal"
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and 19 in pages_to_generate
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and 20 in pages_to_generate
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):
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contexts["page_19_20_minimal"] = {
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"patient_name": self.patient_info["name"],
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"body_fat_percentage_chart": graphs.get(
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+23
-20
@@ -2,7 +2,7 @@
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"cells": [
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||||
{
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||||
"cell_type": "code",
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||||
"execution_count": null,
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||||
"execution_count": 1,
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||||
"id": "b18c1027",
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||||
"metadata": {},
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||||
"outputs": [],
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||||
@@ -88,7 +88,7 @@
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||||
},
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||||
{
|
||||
"cell_type": "code",
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||||
"execution_count": null,
|
||||
"execution_count": 3,
|
||||
"id": "56a9d655",
|
||||
"metadata": {},
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||||
"outputs": [
|
||||
@@ -104,7 +104,10 @@
|
||||
],
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||||
"source": [
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||||
"import pandas as pd\n",
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||||
"spirometry_df = pd.read_csv(\"data/spirometry_data.csv\")\n",
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"import os\n",
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||||
"\n",
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"base_dir = os.path.dirname(os.path.abspath('.'))\n",
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"spirometry_df = pd.read_csv(f\"{base_dir}/data/spirometry_data.csv\")\n",
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"\n",
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"fvc_best = spirometry_df.loc[spirometry_df['Parameters'] == 'FVC', 'Best'].values[0]\n",
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||||
"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,
|
||||
|
||||
Reference in New Issue
Block a user