feat: Add NPV comparison and distribution charts to reporting

- Implemented NPV comparison chart generation using Plotly in ReportingService.
- Added distribution histogram for Monte Carlo results.
- Updated reporting templates to include new charts and improved layout.
- Created new settings and currencies management pages.
- Enhanced sidebar navigation with dynamic URL handling.
- Improved CSS styles for chart containers and overall layout.
- Added new simulation and theme settings pages with placeholders for future features.

services/reporting.py

@@ -8,6 +8,9 @@ import math
 from typing import Mapping, Sequence
 from urllib.parse import urlencode
 
+import plotly.graph_objects as go
+import plotly.io as pio
+
 from fastapi import Request
 
 from models import FinancialCategory, Project, Scenario
@@ -515,6 +518,7 @@ class ReportingService:
                     "label": "Download JSON",
                 }
             ],
+            "chart_data": self._generate_npv_comparison_chart(reports),
         }
 
     def build_scenario_comparison_context(
@@ -611,8 +615,64 @@ class ReportingService:
                     "label": "Download JSON",
                 }
             ],
+            "chart_data": self._generate_distribution_histogram(report.monte_carlo) if report.monte_carlo else "{}",
         }
 
+    def _generate_npv_comparison_chart(self, reports: Sequence[ScenarioReport]) -> str:
+        """Generate Plotly chart JSON for NPV comparison across scenarios."""
+        scenario_names = []
+        npv_values = []
+
+        for report in reports:
+            scenario_names.append(report.scenario.name)
+            npv_values.append(report.deterministic.npv or 0)
+
+        fig = go.Figure(data=[
+            go.Bar(
+                x=scenario_names,
+                y=npv_values,
+                name='NPV',
+                marker_color='lightblue'
+            )
+        ])
+
+        fig.update_layout(
+            title="NPV Comparison Across Scenarios",
+            xaxis_title="Scenario",
+            yaxis_title="NPV",
+            showlegend=False
+        )
+
+        return pio.to_json(fig) or "{}"
+
+    def _generate_distribution_histogram(self, monte_carlo: ScenarioMonteCarloResult) -> str:
+        """Generate Plotly histogram for Monte Carlo distribution."""
+        if not monte_carlo.available or not monte_carlo.result or not monte_carlo.result.samples:
+            return "{}"
+
+        # Get NPV samples
+        npv_samples = monte_carlo.result.samples.get(SimulationMetric.NPV, [])
+        if len(npv_samples) == 0:
+            return "{}"
+
+        fig = go.Figure(data=[
+            go.Histogram(
+                x=npv_samples,
+                nbinsx=50,
+                name='NPV Distribution',
+                marker_color='lightgreen'
+            )
+        ])
+
+        fig.update_layout(
+            title="Monte Carlo NPV Distribution",
+            xaxis_title="NPV",
+            yaxis_title="Frequency",
+            showlegend=False
+        )
+
+        return pio.to_json(fig) or "{}"
+
 
 def _build_cash_flows(scenario: Scenario) -> tuple[list[CashFlow], ScenarioFinancialTotals]:
     cash_flows: list[CashFlow] = []