feat: Update patient name extraction and enhance page context generation in PageGenerator

app/report_gen/page_1.html

@@ -26,7 +26,7 @@
         <!-- Name and Date Section -->
         <div class="text-right mt-16">
             <h2 class="text-4xl font-bold tracking-wider mb-2">
-                {{ name|upper }}
+                {{ first_name|upper }}
             </h2>
             <h2 class="text-4xl font-bold tracking-wider mb-6">
                 {{ surname|upper }}

app/services/page_generator.py

@@ -1,5 +1,8 @@
+import datetime
+import pandas as pd
+import matplotlib.pyplot as plt
 class PageGenerator:
-    def __init__(self, pnoe_df, seca_df, spirometry_df, patient_info):
+    def __init__(self, pnoe_df: pd.DataFrame, seca_df: pd.DataFrame, spirometry_df: pd.DataFrame, patient_info: dict):
         self.pnoe_df = pnoe_df
         self.seca_df = seca_df
         self.spirometry_df = spirometry_df
@@ -9,33 +12,180 @@ class PageGenerator:
     def page_1_context(self):
         # Extract patient information
         patient_name = self.patient_info.get("patient_name", "N/A")
-        age = self.patient_info.get("age", "N/A")
-        height = self.patient_info.get("height", "N/A")
-        weight = self.patient_info.get("weight", "N/A")
-        focus = self.patient_info.get("focus", "N/A")
-        session_id = self.patient_info.get("session_id", "N/A")
-
-        # Extract PNOE data
-        pnoe_summary = self.pnoe_df.describe().to_dict()
-
-        # Extract SECA data
-        seca_summary = self.seca_df.describe().to_dict()
-
-        # Extract Spirometry data
-        spirometry_summary = self.spirometry_df.describe().to_dict()
-
         context = {
-            "patient_name": patient_name,
-            "age": age,
-            "height": height,
-            "weight": weight,
-            "focus": focus,
-            "session_id": session_id,
-            "pnoe_summary": pnoe_summary,
-            "seca_summary": seca_summary,
-            "spirometry_summary": spirometry_summary,
+            "first_name": patient_name.split()[0] if patient_name else "N/A",
+            "surname": patient_name.split()[-1] if patient_name else "N/A",
+            "date": datetime.datetime.now().strftime("%B %d, %Y"),
         }
 
         return context
     
-    
+    def page_3_context(self):
+        # Example: Extract detailed PNOE data for page 3
+        pnoe_details = self.pnoe_df.head(10).to_dict(orient="records")
+
+        context = {
+            "pnoe_details": pnoe_details,
+        }
+
+        return context
+    
+    def page_4_context(self):
+        # Example: Extract detailed Spirometry data for page 4
+        # Filter df_2 for Keirstyn Moran
+        patient_data = self.patient_info[self.patient_info['LastName'].str.contains('Moran', case=False, na=False)]
+        fat_percentage = patient_data['Adult_FMP'].iloc[0]
+        weight_kg = patient_data['Weight'].iloc[0]
+        lean_percentage = 100 - fat_percentage
+
+        fat_mass_lbs = weight_kg * (fat_percentage / 100) * 2.20462
+        lean_mass_lbs = weight_kg * (lean_percentage / 100) * 2.20462
+
+        total_weight = fat_mass_lbs + lean_mass_lbs
+        fat_percentage = (fat_mass_lbs / total_weight) * 100
+        lean_percentage = (lean_mass_lbs / total_weight) * 100
+
+        sizes = [fat_percentage, lean_percentage]
+        colors = ['#fde3ac', '#ff9966'] # Light yellow/tan and orange from the image
+
+        plt.figure(figsize=(8, 8))
+
+        wedges, texts, autotexts = plt.pie(sizes, autopct='', startangle=90, wedgeprops=dict(width=0.5, edgecolor='w'), colors=colors, labels=['', ''])  # Remove default labels
+
+        plt.text(-1, 1, f'Fat Mass ({fat_mass_lbs:.1f}lbs)\n{fat_percentage:.1f}%', 
+                fontsize=14, fontweight='bold', ha='center', va='center',
+                bbox=dict(boxstyle="round,pad=0.3", facecolor='white', alpha=0.8))
+
+        plt.text(1, -1, f'Lean Mass ({lean_mass_lbs:.1f}lbs)\n{lean_percentage:.1f}%', 
+                fontsize=14, fontweight='bold', ha='center', va='center',
+                bbox=dict(boxstyle="round,pad=0.3", facecolor='white', alpha=0.8))
+
+        plt.axis('equal') # Equal aspect ratio ensures that pie is drawn as a circle
+        spirometry_details = self.spirometry_df.head(10).to_dict(orient="records")
+
+        context = {
+            "spirometry_details": spirometry_details,
+        }
+
+        return context
+    
+    def page_5_context(self):
+        # Example: Summary and conclusions for page 5
+        summary = {
+            "pnoe_summary": self.pnoe_df.describe().to_dict(),
+            "seca_summary": self.seca_df.describe().to_dict(),
+            "spirometry_summary": self.spirometry_df.describe().to_dict(),
+        }
+
+        context = {
+            "summary": summary,
+        }
+
+        return context
+    
+    def page_6_context(self):
+        # Example: Recommendations based on data for page 6
+        recommendations = [
+            "Increase cardiovascular training.",
+            "Incorporate strength training twice a week.",
+            "Monitor respiratory function regularly.",
+        ]
+
+        context = {
+            "recommendations": recommendations,
+        }
+
+        return context
+    
+    def page_7_context(self):
+        # Example: Additional notes or references for page 7
+        notes = "This report is generated based on the provided data. Consult a healthcare professional for personalized advice."
+
+        context = {
+            "notes": notes,
+        }
+
+        return context
+    
+    def page_8_context(self):
+        # Example: Contact information and disclaimers for page 8
+        contact_info = {
+            "clinic_name": "Health Clinic",
+            "address": "123 Wellness St, Healthy City, HC 12345",
+            "phone": "(123) 456-7890",
+            "email": "contact@healthclinic.com"
+        }
+
+        context = {
+            "contact_info": contact_info,
+        }
+
+        return context
+
+    def page_9_context(self):
+        # Example: Graphs and visualizations for page 9
+        graphs = [
+            "graph1.png",
+            "graph2.png",
+            "graph3.png"
+        ]
+
+        context = {
+            "graphs": graphs,
+        }
+
+        return context
+    
+    def page_10_context(self):
+        # Example: Final remarks and next steps for page 10
+        final_remarks = "Thank you for using our health assessment services. We look forward to assisting you in your health journey."
+
+        context = {
+            "final_remarks": final_remarks,
+        }
+
+        return context
+    
+    def page_11_context(self):
+        # Example: Additional resources and references for page 11
+        resources = [
+            {"title": "Healthy Living Guide", "link": "http://example.com/healthy-living"},
+            {"title": "Exercise Tips", "link": "http://example.com/exercise-tips"},
+            {"title": "Nutrition Advice", "link": "http://example.com/nutrition-advice"}
+        ]
+
+        context = {
+            "resources": resources,
+        }
+
+        return context
+    
+    def page_12_context(self):
+        # Example: Feedback and survey information for page 12
+        feedback_info = "We value your feedback. Please visit http://example.com/feedback to share your experience."
+
+        context = {
+            "feedback_info": feedback_info,
+        }
+
+        return context
+    
+    def page_13_context(self):
+        # Example: Acknowledgments and credits for page 13
+        acknowledgments = "This report was generated using data analysis techniques and the expertise of our medical team."
+
+        context = {
+            "acknowledgments": acknowledgments,
+        }
+
+        return context
+    
+    def page_18_context(self):
+        # Example: Legal disclaimers and terms for page 18
+        legal_disclaimer = "This report is for informational purposes only and does not constitute medical advice."
+
+        context = {
+            "legal_disclaimer": legal_disclaimer,
+        }
+
+        return context