Add all local circuit work — year-by-year SVGs and tooling

models/geo_json/geometry.py

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+from dataclasses import dataclass
+from typing import List, Dict, Any
+
+import numpy as np
+
+
+@dataclass
+class GeoJSONGeometry:
+    type: str
+    coordinates: List[tuple[float, float]]
+
+    @classmethod
+    def from_dict(cls, data: Dict[str, Any]) -> 'GeoJSONGeometry':
+        return cls(
+            type=data['type'],
+            coordinates=data['coordinates']
+        )
+
+    def find_longest_straight(self, window_size=5) -> (List[float], List[float]):
+        """Find the longest approximately straight section of the track, including wrap-around."""
+        max_distance = 0
+        best_start_idx = 0
+        n = len(self.coordinates)
+
+        # Helper function to check straightness
+        def is_straight(points, start, end, length):
+            direction = (end - start) / length
+            distances = []
+            for point in points:
+                projection = start + np.dot(point - start, direction) * direction
+                distance = np.linalg.norm(point - projection)
+                distances.append(distance)
+            return max(distances) < length * 0.05  # 5% tolerance
+
+        # Check all possible segments, including wrap-around
+        for i in range(n):
+            # Get window_size points, handling wrap-around
+            segment = []
+            for j in range(window_size):
+                idx = (i + j) % n
+                segment.append(np.array(self.coordinates[idx]))
+
+            start = np.array(segment[0])
+            end = np.array(segment[-1])
+            length = np.linalg.norm(end - start)
+
+            if length > max_distance:
+                # Check if all points are roughly on the line
+                if is_straight(segment, start, end, length):
+                    max_distance = length
+                    best_start_idx = i
+
+        # Return indices that might wrap around
+        end_idx = (best_start_idx + window_size) % len(self.coordinates)
+        return self.coordinates[best_start_idx], self.coordinates[end_idx]
+