reformatted code

1 files changed, 94 insertions, 42 deletions

diff --git a/dashboard_website/router.py b/dashboard_website/router.py
index 8f73c99..e0e0720 100644
--- a/dashboard_website/router.py
+++ b/dashboard_website/router.py
@@ -8,33 +8,37 @@ from datastructs import *
 
 host = "http://acetyl.net:5000"  # queries acetyl.net:5000, the OSRM engine
 
-endtime = datetime.datetime(2023, 11, 18, hour=18, minute=45) # 11/18/2023 6:35pm
+endtime = datetime.datetime(2023, 11, 18, hour=18, minute=45)  # 11/18/2023 6:35pm
 
 # external facing functions
 
+
 # gets single leg route between bike and clue
 # should be HD and GeoJSON
 def getRouteFullJSON(bike, clue):
-    bike = bike.toJSON(); clue = clue.toJSON()
+    bike = bike.toJSON()
+    clue = clue.toJSON()
     url = f"{host}/route/v1/bike/{bike['longitude']},{bike['latitude']};{clue['longitude']},{clue['latitude']}?steps=true&overview=full&geometries=geojson"
     r = requests.get(url)
     return r.json()
 
 
 def getRouteHDPolyline(bike, clue):
-    bike = bike.toJSON(); clue = clue.toJSON()
+    bike = bike.toJSON()
+    clue = clue.toJSON()
     url = f"{host}/route/v1/bike/{bike['longitude']},{bike['latitude']};{clue['longitude']},{clue['latitude']}?overview=full&geometries=geojson"
     r = requests.get(url)
 
-    p = r.json()['routes'][0]['geometry']['coordinates']
+    p = r.json()["routes"][0]["geometry"]["coordinates"]
     return p
 
 
 def getRouteFastPolyline(bike, clue):
-    bike = bike.toJSON(); clue = clue.toJSON()
+    bike = bike.toJSON()
+    clue = clue.toJSON()
     url = f"{host}/route/v1/bike/{bike['longitude']},{bike['latitude']};{clue['longitude']},{clue['latitude']}?geometries=geojson"
     r = requests.get(url)
-    p = r.json()['routes'][0]['geometry']['coordinates']
+    p = r.json()["routes"][0]["geometry"]["coordinates"]
     return p
 
 
@@ -44,8 +48,8 @@ def getZSP(bike, home, clue_cluster):
 
 # determines clusters based on current bikes and clues
 def getClusters(bikes, clues, endpoint):
-    clusters = [[] for bike in bikes ]
-    route_geos = [[] for bike in bikes ]
+    clusters = [[] for bike in bikes]
+    route_geos = [[] for bike in bikes]
     times = {}
     active_indices = [i for i in range(len(bikes)) if bikes[i].status == "ACTIVE"]
     active_bikes = [bike for bike in bikes if bike.status == "ACTIVE"]
@@ -54,10 +58,12 @@ def getClusters(bikes, clues, endpoint):
     active_clues = [clue for clue in clues if clue.status == "UNVISITED"]
     # select only active bikes
     # select only unvisited clues
-    clusters_t, route_geos_t, times_t = cluster_and_optimize(active_clues, active_bikes, endpoint)
+    clusters_t, route_geos_t, times_t = cluster_and_optimize(
+        active_clues, active_bikes, endpoint
+    )
     for i in range(len(active_indices)):
         route_geos[active_indices[i]] = route_geos_t[i]
-        clusters[active_indices[i]] = clusters_t[i] 
+        clusters[active_indices[i]] = clusters_t[i]
         bikes[active_indices[i]].setCluster(clusters_t[i])
         times[bikes[active_indices[i]].name] = times_t[i]
 
@@ -66,7 +72,9 @@ def getClusters(bikes, clues, endpoint):
 
 
 # utility functions (internal)
-def cluster_and_optimize(clues: [Clue], bikes: [Bike], end: Point, time_diff=0.25, max_time=24, n=2):
+def cluster_and_optimize(
+    clues: [Clue], bikes: [Bike], end: Point, time_diff=0.25, max_time=24, n=2
+):
     """
     Takes a dataframe of gps coordinates, a list of centroids, and an end point and returns a dataframe with a cluster
     :param clues: a list of clues
@@ -79,8 +87,10 @@ def cluster_and_optimize(clues: [Clue], bikes: [Bike], end: Point, time_diff=0.2
     """
     # OVERRIDE MAX TIME
     max_time = datetime.datetime.now() - endtime
-    max_time = max_time.seconds/3600
-    routes = [clues] # one bike = one set of routes. only need to remove the faraway waypoints
+    max_time = max_time.seconds / 3600
+    routes = [
+        clues
+    ]  # one bike = one set of routes. only need to remove the faraway waypoints
     if len(bikes) > 1:
         # Create a new column with normalized gps coordinates and centroids
         normalized_points, norm_centroids = __normalize_points(clues, bikes)
@@ -94,29 +104,32 @@ def cluster_and_optimize(clues: [Clue], bikes: [Bike], end: Point, time_diff=0.2
             routes[label].append(clues[i])
 
         routes = __minimize_route_time_diff(routes, bikes, end, time_diff, n)
-    
+
     # Remove waypoints from the longest route until the trip time is less than the max time
     for i in range(len(routes)):
         routes[i] = __remove_longest_waypoints(routes[i], bikes[i], end, max_time)
-    
 
     # Get the json of the routes
     route_waypoints = []
     geometries = []
     times = []
     for i, route in enumerate(routes):
-        route_json = __get_json(__clues_to_string(route), __clues_to_string([bikes[i]]), __clues_to_string([end])[:-1])
-        geometries.append(route_json['trips'][0]['geometry']['coordinates'])
-        route_waypoints.append(route_json['waypoints'])
-        eta = time.time() + route_json['trips'][0]['duration'] + 90 * len(route)
+        route_json = __get_json(
+            __clues_to_string(route),
+            __clues_to_string([bikes[i]]),
+            __clues_to_string([end])[:-1],
+        )
+        geometries.append(route_json["trips"][0]["geometry"]["coordinates"])
+        route_waypoints.append(route_json["waypoints"])
+        eta = time.time() + route_json["trips"][0]["duration"] + 90 * len(route)
         eta_str = datetime.datetime.fromtimestamp(eta).strftime("%I:%M:%S%p")
         times.append(eta_str)
 
     # Use the waypoint_index to reorder each route
     for i, route in enumerate(routes):
         route2 = ["" for x in route]
-        for j,k in enumerate(route_waypoints[i][1:-1]):
-            route2[ k['waypoint_index']-1 ] = route[j]
+        for j, k in enumerate(route_waypoints[i][1:-1]):
+            route2[k["waypoint_index"] - 1] = route[j]
         routes[i] = route2
 
     return routes, geometries, times
@@ -128,9 +141,9 @@ def __clues_to_string(points: [Clue]):
     :param points: a list of points
     :return: a string of the list of points
     """
-    string = ''
+    string = ""
     for i in points:
-        string += str(i.longitude) + ',' + str(i.latitude) + ';'
+        string += str(i.longitude) + "," + str(i.latitude) + ";"
 
     return string
 
@@ -144,13 +157,20 @@ def __get_json(coordinate_string, start, end):
     :return: the json of the route
     """
     coordinates = requests.get(
-        'http://acetyl.net:5000/trip/v1/bike/' + start + coordinate_string + end + '?roundtrip=false&source=first&destination=last&geometries=geojson&overview=full')
+        "http://acetyl.net:5000/trip/v1/bike/"
+        + start
+        + coordinate_string
+        + end
+        + "?roundtrip=false&source=first&destination=last&geometries=geojson&overview=full"
+    )
     coordinates = coordinates.json()
 
     return coordinates
 
 
-def __get_trip_time(coordinate_string, num_waypoints, start, end, time_per_waypoint=90, seconds=False):
+def __get_trip_time(
+    coordinate_string, num_waypoints, start, end, time_per_waypoint=90, seconds=False
+):
     """
     Takes a string of coordinates and returns the trip time in hours
     :param coordinate_string: a string of coordinates
@@ -161,19 +181,26 @@ def __get_trip_time(coordinate_string, num_waypoints, start, end, time_per_waypo
     :return: the trip time in hours
     """
     coordinates = requests.get(
-        'http://acetyl.net:5000/trip/v1/bike/' + start + coordinate_string + end + '?roundtrip=false&source=first&destination=last')
+        "http://acetyl.net:5000/trip/v1/bike/"
+        + start
+        + coordinate_string
+        + end
+        + "?roundtrip=false&source=first&destination=last"
+    )
     coordinates = coordinates.json()
 
-    travel_time_seconds = int(coordinates['trips'][0]['duration'])
+    travel_time_seconds = int(coordinates["trips"][0]["duration"])
     waypoint_time_seconds = num_waypoints * time_per_waypoint
     if seconds:
-        return (travel_time_seconds + waypoint_time_seconds)
+        return travel_time_seconds + waypoint_time_seconds
     total_time_hours = (travel_time_seconds + waypoint_time_seconds) / 3600
 
     return total_time_hours
 
 
-def __minimize_route_time_diff(routes: [Clue], starts: [Point], end: Point, time_diff, n):
+def __minimize_route_time_diff(
+    routes: [Clue], starts: [Point], end: Point, time_diff, n
+):
     """
     Takes a list of lists of coordinates, a list of start points, an end point, a time difference, and a number of routes
     :param routes: the list of lists of coordinates
@@ -186,8 +213,14 @@ def __minimize_route_time_diff(routes: [Clue], starts: [Point], end: Point, time
     times = []
 
     for i, route in enumerate(routes):
-        times.append(__get_trip_time(__clues_to_string(route), len(route), __clues_to_string([starts[i]]),
-                                     __clues_to_string([end])[:-1]))
+        times.append(
+            __get_trip_time(
+                __clues_to_string(route),
+                len(route),
+                __clues_to_string([starts[i]]),
+                __clues_to_string([end])[:-1],
+            )
+        )
 
     # Find the average trip time
     average_time = np.mean(times)
@@ -201,8 +234,9 @@ def __minimize_route_time_diff(routes: [Clue], starts: [Point], end: Point, time
     # If the difference is greater than the time difference, move a coordinate from the longest route to the shortest route
     if time_difference > time_diff:
         # Move a coordinate from the longest route to the shortest route
-        closest_coordinate = __find_closest_coordinate(routes[sorted_indices[-1]],
-                                                       __mean_center(routes[sorted_indices[0]]))
+        closest_coordinate = __find_closest_coordinate(
+            routes[sorted_indices[-1]], __mean_center(routes[sorted_indices[0]])
+        )
         routes[sorted_indices[0]].append(closest_coordinate)
         routes[sorted_indices[-1]].remove(closest_coordinate)
 
@@ -213,7 +247,9 @@ def __minimize_route_time_diff(routes: [Clue], starts: [Point], end: Point, time
     return routes
 
 
-def __remove_longest_waypoints(route_coordinates: [Clue], start: Bike, end: Point, max_time):
+def __remove_longest_waypoints(
+    route_coordinates: [Clue], start: Bike, end: Point, max_time
+):
     """
     Takes a list of coordinates, a start point, an end point, and a maximum time and returns a list of coordinates
     :param route_coordinates: the list of coordinates
@@ -223,8 +259,12 @@ def __remove_longest_waypoints(route_coordinates: [Clue], start: Bike, end: Poin
     :return: a list of coordinates
     """
     # Find the trip time for the route
-    route_time = __get_trip_time(__clues_to_string(route_coordinates), len(route_coordinates),
-                                 __clues_to_string([start]), __clues_to_string([end])[:-1])
+    route_time = __get_trip_time(
+        __clues_to_string(route_coordinates),
+        len(route_coordinates),
+        __clues_to_string([start]),
+        __clues_to_string([end])[:-1],
+    )
 
     # If the trip time is greater than the max time, remove the waypoint with the longest distance from the mean
     if route_time > max_time:
@@ -262,10 +302,18 @@ def __normalize_points(clues: [Clue], bikes: [Bike]):
 
     for i in clues:
         normalized_coordinates.append(
-            [__min_max_normalize(i.latitude, min_lat, max_lat), __min_max_normalize(i.longitude, min_lon, max_lon)])
+            [
+                __min_max_normalize(i.latitude, min_lat, max_lat),
+                __min_max_normalize(i.longitude, min_lon, max_lon),
+            ]
+        )
     for i in bikes:
         normalized_centroids.append(
-            [__min_max_normalize(i.latitude, min_lat, max_lat), __min_max_normalize(i.longitude, min_lon, max_lon)])
+            [
+                __min_max_normalize(i.latitude, min_lat, max_lat),
+                __min_max_normalize(i.longitude, min_lon, max_lon),
+            ]
+        )
 
     return normalized_coordinates, normalized_centroids
 
@@ -324,8 +372,10 @@ def __mean_center(clues: [Clue]):
     :param clues: the list of coordinates
     :return: the mean center of the coordinates
     """
-    return Point(np.mean([coordinate.latitude for coordinate in clues]),
-                    np.mean([coordinate.longitude for coordinate in clues]))
+    return Point(
+        np.mean([coordinate.latitude for coordinate in clues]),
+        np.mean([coordinate.longitude for coordinate in clues]),
+    )
 
 
 def __distance(coordinate1: Clue, coordinate2: Point):
@@ -335,5 +385,7 @@ def __distance(coordinate1: Clue, coordinate2: Point):
     :param coordinate2: the second coordinate
     :return: the distance between the two coordinates
     """
-    return ((coordinate1.latitude - coordinate2.latitude) ** 2 + (
-            coordinate1.longitude - coordinate2.longitude) ** 2) ** 0.5
+    return (
+        (coordinate1.latitude - coordinate2.latitude) ** 2
+        + (coordinate1.longitude - coordinate2.longitude) ** 2
+    ) ** 0.5