From e8cd8795f14efc0537624f724df357e85c18ba02 Mon Sep 17 00:00:00 2001
From: Izzy Cole <ic419@cam.ac.uk>
Date: Sat, 1 Nov 2025 15:37:35 +0000
Subject: [PATCH] writing encode fn

---
 engine.py        | 38 ++++++++++++++++++++++++++++++++++++--
 requirements.txt |  3 +++
 2 files changed, 39 insertions(+), 2 deletions(-)

diff --git a/engine.py b/engine.py
index db18b61..fb5374c 100755
--- a/engine.py
+++ b/engine.py
@@ -1,6 +1,11 @@
 #!/usr/bin/env python
 
 import overpy
+import numpy as np
+import pandas as pd
+import geopy.distance as distance
+
+from tqdm import tqdm
 
 # brandname : overpass query filters
 BRANDS: dict[str, str] = {
@@ -35,6 +40,35 @@ def fetch_data(brand: str) -> list[tuple[float | None, float | None]]:
 def encode(location: tuple[float, float]) -> EncodedLocation:
     """Encode a location."""
 
+    print("fetching")
+    greggs = fetch_data("greggs")
+    print("fetched")
+    #greggs = [(55.85,-4.02),(52.443,-1.833),(51.28,-1.0)]
+
+    #relative distance matrix
+    dist_matrix = np.zeros((len(greggs),len(greggs)))
+    for i in tqdm(range(len(greggs))):
+        first=greggs[i]
+        for j in range(len(greggs)):
+            second=greggs[j]
+            #calculate the distance between i and j coordinates
+            #dist_matrix[i,j] = np.sqrt((first[0]-second[0])**2 + (first[1]-second[1])**2 )
+            dist_matrix[i,j] = distance.distance(distance.lonlat(*first), distance.lonlat(*second)).km*1000
+    print(dist_matrix)
+
+    #find closest greggs
+    distances = pd.Series(np.zeros(len(greggs)))
+    for i in range(len(greggs)):
+        current = greggs[i]
+        #distances[i] = np.sqrt((current[0]-location[0])**2 + (current[1]-location[1])**2 
+        distances[i] = distance.distance(distance.lonlat(*current), distance.lonlat(*location)).km*1000
+
+    print(distances)
+    distances = distances.sort_values()
+    top3 = distances.head(3)
+    print(top3)
+
+
     # Stub
     return [
         (5., [1., 2., 3.]),
@@ -67,8 +101,8 @@ def parse_location(location: str) -> EncodedLocation:
 def main():
     """Testing."""
     print("Running query...")
-    greggs = fetch_data("greggs")
-    print(f"Query done - got {len(greggs)} Greggs!")
+    #greggs = fetch_data("greggs")
+    #print(f"Query done - got {len(greggs)} Greggs!")
 
     print(format_location(encode((0.091659, 52.210796))))
 
diff --git a/requirements.txt b/requirements.txt
index 13026f7..821f95a 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,2 +1,5 @@
 overpy
 django
+numpy
+pandas
+geopy