Update app.py

app.py

@@ -1,9 +1,8 @@
 import streamlit as st
 import plotly.graph_objects as go
-import time
 import random
 
-# Data
+# Data Initialization
 agents = {
     "Doctors": 10,
     "Nurses": 4,
@@ -11,25 +10,19 @@ agents = {
     "Patients": 200
 }
 
-# Patient conditions and distribution
+# Distribute patients into conditions
 conditions = ["Healthy", "Mild Illness", "Chronic Illness", "Emergency"]
-condition_counts = {
-    "Healthy": 0,
-    "Mild Illness": 0,
-    "Chronic Illness": 0,
-    "Emergency": 0
-}
+condition_counts = {condition: 0 for condition in conditions}
 
-# Create random patient condition distribution
 def distribute_patients():
     remaining_patients = agents["Patients"]
     for condition in conditions:
         count = random.randint(0, remaining_patients)
         condition_counts[condition] = count
         remaining_patients -= count
-    condition_counts[conditions[-1]] += remaining_patients  # Add remaining patients to last condition
+    condition_counts[conditions[-1]] += remaining_patients
 
-# Randomly generate metrics for treatment
+# Generate random treatment metrics
 def generate_treatment_metrics():
     total_treatments = random.randint(50, 150)
     successful_treatments = random.randint(0, total_treatments)
@@ -37,80 +30,100 @@ def generate_treatment_metrics():
     patients_waiting = agents["Patients"] - total_treatments
     return total_treatments, successful_treatments, unsuccessful_treatments, patients_waiting
 
-# Create the gauge chart
-def create_gauge(title, value, max_value):
+# Generate random doctor actions
+def generate_doctor_actions(total_treatments):
+    actions = ["Prescribe Medication", "Recommend Tests", "Consult Clinician", "Schedule Surgery"]
+    action_counts = {action: 0 for action in actions}
+    for _ in range(total_treatments):
+        action = random.choice(actions)
+        action_counts[action] += 1
+    return action_counts
+
+# Generate random penalties
+def generate_penalties(total_treatments):
+    penalties = ["Wrong Medication", "Missed Diagnosis", "Incorrect Test Recommendation", "Stress-Induced Mistake"]
+    penalty_counts = {penalty: 0 for penalty in penalties}
+    for _ in range(total_treatments // 6):
+        penalty = random.choice(penalties)
+        penalty_counts[penalty] += 1
+    return penalty_counts
+
+# Generate random patient feedback
+def generate_feedback(total_treatments):
+    feedback = ["Completely Recovered", "Further Treatment Needed", "Complication"]
+    feedback_counts = {fb: 0 for fb in feedback}
+    for _ in range(total_treatments):
+        fb = random.choice(feedback)
+        feedback_counts[fb] += 1
+    return feedback_counts
+
+# Function to create gauge chart
+def create_gauge(title, value, max_value, domain, gauge_color):
     fig = go.Figure()
     fig.add_trace(go.Indicator(
         mode="gauge+number",
         value=value,
         title={'text': title},
-        gauge={'axis': {'range': [0, max_value]}}
+        domain=domain,
+        gauge={'axis': {'range': [0, max_value]}, 'bar': {'color': gauge_color}}
     ))
     fig.update_layout(template='plotly_dark')
     return fig
 
-# Data Preparation
+# Prepare data
 distribute_patients()
 total_treatments, successful_treatments, unsuccessful_treatments, patients_waiting = generate_treatment_metrics()
+doctor_actions = generate_doctor_actions(total_treatments)
+penalties = generate_penalties(total_treatments)
+feedback = generate_feedback(total_treatments)
 
 # Streamlit setup
 st.title("Interactive Healthcare Metrics")
 
 # Slider to choose the animation
-animation_index = st.slider("Select Animation", min_value=1, max_value=7, value=1)
+animation_index = st.slider("Select Animation", min_value=1, max_value=5, value=1)
 
-# Animation 1: Total Number of Agents
+# Animation 1: Patient Conditions
 if animation_index == 1:
-    st.subheader("Total Number of Agents")
-    for agent_type, count in agents.items():
-        fig = create_gauge(f"{agent_type}", count, 200)
-        st.plotly_chart(fig, use_container_width=True)
-        time.sleep(2)
-
-# Animation 2: Distribution of Patients by Condition
-elif animation_index == 2:
-    st.subheader("Patient Conditions Distribution")
+    st.subheader("Patients by Condition")
     for condition, count in condition_counts.items():
-        fig = create_gauge(f"Patients with {condition}", count, agents["Patients"])
+        fig = create_gauge(f"Patients with {condition}", count, agents["Patients"], {'x': [0, 1], 'y': [0, 1]}, 'blue')
         st.plotly_chart(fig, use_container_width=True)
-        time.sleep(2)
+        st.markdown("---")
 
-# Animation 3: Number of Patients Treated
+# Animation 2: Treatment Metrics
+elif animation_index == 2:
+    st.subheader("Treatment Metrics")
+    fig1 = create_gauge("Total Patients", agents["Patients"], agents["Patients"], {'x': [0, 0.5], 'y': [0, 1]}, 'green')
+    fig2 = create_gauge("Successful Treatments", successful_treatments, total_treatments, {'x': [0.5, 1], 'y': [0, 0.5]}, 'orange')
+    fig3 = create_gauge("Unsuccessful Treatments", unsuccessful_treatments, total_treatments, {'x': [0.5, 1], 'y': [0.5, 1]}, 'red')
+    st.plotly_chart(fig1, use_container_width=True)
+    st.plotly_chart(fig2, use_container_width=True)
+    st.plotly_chart(fig3, use_container_width=True)
+    st.markdown("---")
+
+# Animation 3: Doctor Actions
 elif animation_index == 3:
-    st.subheader("Patients Treated by Doctors")
-    fig = create_gauge("Total Treatments", total_treatments, agents["Patients"])
-    st.plotly_chart(fig, use_container_width=True)
-    time.sleep(2)
+    st.subheader("Doctor Actions")
+    for action, count in doctor_actions.items():
+        fig = create_gauge(f"Doctor Action: {action}", count, total_treatments, {'x': [0, 1], 'y': [0, 1]}, 'purple')
+        st.plotly_chart(fig, use_container_width=True)
+        st.markdown("---")
 
-# Animation 4: Number of Successful Treatments
+# Animation 4: Penalties
 elif animation_index == 4:
-    st.subheader("Successful Treatments")
-    fig = create_gauge("Successful Treatments", successful_treatments, total_treatments)
-    st.plotly_chart(fig, use_container_width=True)
-    time.sleep(2)
+    st.subheader("Penalties")
+    for penalty, count in penalties.items():
+        fig = create_gauge(f"Penalty: {penalty}", count, total_treatments // 6, {'x': [0, 1], 'y': [0, 1]}, 'red')
+        st.plotly_chart(fig, use_container_width=True)
+        st.markdown("---")
 
-# Animation 5: Number of Unsuccessful Treatments
+# Animation 5: Patient Feedback
 elif animation_index == 5:
-    st.subheader("Unsuccessful Treatments")
-    fig = create_gauge("Unsuccessful Treatments", unsuccessful_treatments, total_treatments)
-    st.plotly_chart(fig, use_container_width=True)
-    time.sleep(2)
-
-# Animation 6: Number of Patients Waiting for Treatment
-elif animation_index == 6:
-    st.subheader("Patients Waiting for Treatment")
-    fig = create_gauge("Patients Waiting", patients_waiting, agents["Patients"])
-    st.plotly_chart(fig, use_container_width=True)
-    time.sleep(2)
-
-# Animation 7: Remaining Metrics (Optional)
-elif animation_index == 7:
-    remaining_metrics = agents["Patients"] - (total_treatments + patients_waiting)
-    st.subheader("Remaining Metrics")
-    fig = create_gauge("Remaining Metrics", remaining_metrics, agents["Patients"])
-    st.plotly_chart(fig, use_container_width=True)
-    time.sleep(2)
-
-# Final summary
-if animation_index == 7:
-    st.write("**All animations complete: Healthcare metrics have been updated.**")
+    st.subheader("Patient Feedback")
+    for fb, count in feedback.items():
+        fig = create_gauge(f"Feedback: {fb}", count, total_treatments, {'x': [0, 1], 'y': [0, 1]}, 'blue')
+        st.plotly_chart(fig, use_container_width=True)
+        st.markdown("---")
+
+st.write("**End of Animations.**")