Fix wealth distribution chart functionality

- Add get_wealth_histogram() method to EconomicModel for histogram data
- Add new API endpoint /simulation/<id>/distribution for chart data
- Extend main data API with include_distribution parameter
- Update real-time progress updates to include distribution data
- Fix frontend updateCharts() to handle wealth distribution chart
- Add distribution data processing in simulation.js
- Update test_charts.py to verify histogram functionality

Resolves issue where wealth distribution chart was not updating during simulations.

app/models/economic_model.py

@@ -177,8 +177,8 @@ class EconomicSimulation:
             gini_coefficient=gini,
             wealth_concentration_top10=wealth_conc,
             capital_share=capital_share,
-            average_wealth=np.mean(total_wealth_data),
-            median_wealth=np.median(total_wealth_data)
+            average_wealth=float(np.mean(total_wealth_data)),
+            median_wealth=float(np.median(total_wealth_data))
         )
     
     def _calculate_gini_coefficient(self, wealth_data: List[float]) -> float:
@@ -296,6 +296,67 @@ class EconomicSimulation:
         
         return distribution
     
+    def get_wealth_histogram(self, num_bins: int = 10) -> Tuple[List[str], List[int]]:
+        """
+        Get wealth distribution as histogram data for charting.
+        
+        Args:
+            num_bins: Number of bins for the histogram
+            
+        Returns:
+            Tuple of (bin_labels, bin_counts) for histogram chart
+        """
+        if not self.agents:
+            return [], []
+        
+        # Get current total wealth for all agents (capital + consumption)
+        wealth_values = []
+        for agent in self.agents:
+            if agent.wealth_history and agent.consumption_history:
+                total_wealth = agent.wealth_history[-1] + agent.consumption_history[-1]
+            else:
+                total_wealth = agent.initial_capital + agent.initial_consumption
+            wealth_values.append(total_wealth)
+        
+        if not wealth_values:
+            return [], []
+        
+        # Calculate histogram bins
+        min_wealth = min(wealth_values)
+        max_wealth = max(wealth_values)
+        
+        if min_wealth == max_wealth:
+            # All agents have same wealth
+            return [f"${min_wealth:.0f}"], [len(wealth_values)]
+        
+        # Create bins
+        bin_width = (max_wealth - min_wealth) / num_bins
+        bins = [min_wealth + i * bin_width for i in range(num_bins + 1)]
+        
+        # Count agents in each bin
+        bin_counts = [0] * num_bins
+        bin_labels = []
+        
+        for i in range(num_bins):
+            # Create label for this bin
+            bin_start = bins[i]
+            bin_end = bins[i + 1]
+            if i == num_bins - 1:  # Last bin includes upper bound
+                bin_labels.append(f"${bin_start:.0f} - ${bin_end:.0f}")
+            else:
+                bin_labels.append(f"${bin_start:.0f} - ${bin_end:.0f}")
+            
+            # Count agents in this bin
+            for wealth in wealth_values:
+                if i == num_bins - 1:  # Last bin includes upper bound
+                    if bin_start <= wealth <= bin_end:
+                        bin_counts[i] += 1
+                else:
+                    if bin_start <= wealth < bin_end:
+                        bin_counts[i] += 1
+        
+        return bin_labels, bin_counts
+    
     def update_parameters(self, new_parameters: SimulationParameters):
         """
         Update simulation parameters and restart with new settings.