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-rw-r--r--dashboard_website/router.py7
1 files changed, 5 insertions, 2 deletions
diff --git a/dashboard_website/router.py b/dashboard_website/router.py
index 5d5a909..1a90a9e 100644
--- a/dashboard_website/router.py
+++ b/dashboard_website/router.py
@@ -2,13 +2,14 @@ import numpy as np
import requests
from sklearn.cluster import KMeans
import time
-from datetime import datetime
+import datetime
from datastructs import *
host = "http://acetyl.net:5000" # queries acetyl.net:5000, the OSRM engine
+endtime = datetime.datetime(2023, 11, 18, 18, 35) # 11/18/2023 6:35pm
# external facing functions
@@ -77,6 +78,8 @@ 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
"""
+ # OVERRIDE MAX TIME
+ max_time = datetime.datetime.now() - endtime
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
@@ -106,7 +109,7 @@ def cluster_and_optimize(clues: [Clue], bikes: [Bike], end: Point, time_diff=0.2
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")
+ eta_str = datetime.datetime.fromtimestamp(eta).strftime("%I:%M:%S%p")
times.append(eta_str)
# Use the waypoint_index to reorder each route