ROUGH DRAFT

1 files changed, 48 insertions, 31 deletions

diff --git a/dashboard_website/router.py b/dashboard_website/router.py
index 5bafd1e..5d5a909 100644
--- a/dashboard_website/router.py
+++ b/dashboard_website/router.py
@@ -1,9 +1,12 @@
 import numpy as np
 import requests
 from sklearn.cluster import KMeans
+import time
+from datetime import datetime
 
 from datastructs import *
 
+
 host = "http://acetyl.net:5000"  # queries acetyl.net:5000, the OSRM engine
 
 
@@ -12,22 +15,26 @@ host = "http://acetyl.net:5000"  # queries acetyl.net:5000, the OSRM engine
 # gets single leg route between bike and clue
 # should be HD and GeoJSON
 def getRouteFullJSON(bike, clue):
+    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 = response.get(url)
+    r = requests.get(url)
     return r.json()
 
 
 def getRouteHDPolyline(bike, clue):
+    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 = response.get(url)
-    p = r.json()['trips'][0]['geometry']['coordinates']
+    r = requests.get(url)
+
+    p = r.json()['routes'][0]['geometry']['coordinates']
     return p
 
 
 def getRouteFastPolyline(bike, clue):
+    bike = bike.toJSON(); clue = clue.toJSON()
     url = f"{host}/route/v1/bike/{bike['longitude']},{bike['latitude']};{clue['longitude']},{clue['latitude']}?geometries=geojson"
-    r = response.get(url)
-    p = r.json()['trips'][0]['geometry']['coordinates']
+    r = requests.get(url)
+    p = r.json()['routes'][0]['geometry']['coordinates']
     return p
 
 
@@ -37,23 +44,25 @@ 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 ]
+    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"]
     if len(active_bikes) == 0:
-        return clusters, route_geos
+        return clusters, route_geos, times
     active_clues = [clue for clue in clues if clue.status == "UNVISITED"]
     # select only active bikes
     # select only unvisited clues
-    clusters_t, route_geos_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]
 
     # return list of clue clusters corresponding to bikes
-    return clusters, route_geos
+    return clusters, route_geos, times
 
 
 # utility functions (internal)
@@ -68,39 +77,46 @@ def cluster_and_optimize(clues: [Clue], bikes: [Bike], end: Point, time_diff=0.2
     :param n: the number of routes to create
     :return: a list of lists of clues (ordered by position on route), and a list of json route geojsons
     """
-
-    # Create a new column with normalized gps coordinates and centroids
-    normalized_points, norm_centroids = __normalize_points(clues, bikes)
-    print(norm_centroids)
-    # Cluster the coordinates
-    kmeans = KMeans(n_clusters=len(norm_centroids), init=norm_centroids)
-    kmeans.fit(normalized_points)
-
-    # Split the clues into clusters based on the cluster labels
-    routes = [[] for i in range(len(norm_centroids))]
-    for i, label in enumerate(kmeans.labels_):
-        routes[label].append(clues[i])
-
-    routes = __minimize_route_time_diff(routes, bikes, end, time_diff, n)
-
+    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)
+        # Cluster the coordinates
+        kmeans = KMeans(n_clusters=len(norm_centroids), init=norm_centroids)
+        kmeans.fit(normalized_points)
+
+        # Split the clues into clusters based on the cluster labels
+        routes = [[] for i in range(len(norm_centroids))]
+        for i, label in enumerate(kmeans.labels_):
+            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)
+        eta_str = 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):
-        route = [ route[ j['waypoint_index']-1 ] for j in route_waypoints[i] if route_waypoints[i].index(j) < (len(route_waypoints[i])-1) ]
-        routes[i] = route
+        route2 = ["" for x in route]
+        for j,k in enumerate(route_waypoints[i][1:-1]):
+            route2[ k['waypoint_index']-1 ] = route[j]
+        routes[i] = route2
 
-    return routes, geometries
+    return routes, geometries, times
 
 
 def __clues_to_string(points: [Clue]):
@@ -125,13 +141,13 @@ 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')
+        '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):
+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
@@ -147,7 +163,8 @@ def __get_trip_time(coordinate_string, num_waypoints, start, end, time_per_waypo
 
     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)
     total_time_hours = (travel_time_seconds + waypoint_time_seconds) / 3600
 
     return total_time_hours