started writing decoder

engine.py

@@ -108,6 +108,36 @@ def encode(location: tuple[float, float]) -> EncodedLocation:
 def decode(location: EncodedLocation) -> tuple[float, float]:
     """Decode into a location."""
 
+    #form the distances matrix
+    greggs = np.array(fetch_data("greggs"))
+    repeat_rows = np.tile(greggs, (len(greggs), 1, 1))
+    repeat_cols = np.transpose(repeat_rows, (1, 0, 2))
+    dist_matrix = spherical_dist(repeat_rows, repeat_cols)
+
+    #split the distances matrix into a list of series, which allows us to sort each row
+    dist_series_list = []
+    for i in dist_matrix:
+        dist_series_list.append(pd.Series(i).sort_values().head(len(location[0][1])+1)[1:])
+    
+    #part 1: find the ID of each gregg's
+    closest_greggs = []
+    for i in range(len(location)):
+        dists = location[i][1]
+
+        errors = []
+        for j in dist_series_list:
+                errors.append(sum((j-dists)**2))
+        minerr = min(errors)
+        if minerr > 1:
+            print(f"warning: high error value of {minerr}")
+            
+        closest_greggs = [errors.index(min(errors))]
+
+        
+
+
+    #part 2: trilaterate
+
     # Stub
     return (0.091659, 52.210796)
 
@@ -141,7 +171,8 @@ def main():
     #greggs = fetch_data("greggs")
     #print(f"Query done - got {len(greggs)} Greggs!")
 
-    # print(format_location(encode((52.210796, 0.091659))))
+    outcome = encode((52.210796, 0.091659))
+    decode(outcome)
 
 
 if __name__ == "__main__":