Changed logic for Random trip genration

Random trips are now generated like this :

if  certain trips is are to be binned together ( by 'o','d' or 'od' or '__' (meaning NONE)) they are generated in proximity of the previous in-bin trip.  Otherwise, if they are not to be binned together, we keep generating a random trip unless we find one that would not bin with previously accepted trips.

emission/tests/modellingTests/modellingTestAssets.py

@@ -1,35 +1,145 @@
 import random
 from typing import Optional, Tuple, List, Dict
 from uuid import UUID
-import emission.analysis.modelling.trip_model.trip_model as eamtm
+import emission.analysis.modelling.trip_model.greedy_similarity_binning as eamtg
+import emission.tests.modellingTests.modellingTestAssets as etmm
 import emission.core.wrapper.confirmedtrip as ecwc
 
 import emission.core.wrapper.entry as ecwe
 import time 
 import math
 
+def setModelConfig(metric,threshold,cutoff,clustering_way,incrementalevaluation):
+    """
+    TODO: Write about each parameter to the function
+    pass in a test configuration to the binning algorithm.
+    
+    clustering_way : Part of the trip used for checking pairwise proximity.
+                        Can take one of the three values:
+                        
+                        1. 'origin' -> using origin of the trip to check if 2 points
+                                        lie within the mentioned similarity_threshold_meters
+                        2. 'destination' -> using destination of the trip to check if 2 points
+                                            lie within the mentioned similarity_threshold_meters
+                        3. 'origin-destination' -> both origin and destination of the trip to check 
+                                                if 2 points lie within the mentioned 
+                                                    similarity_threshold_meters
+    """        
+    model_config = {
+        "metric": metric,
+        "similarity_threshold_meters": threshold,  # meters,
+        "apply_cutoff": cutoff,
+        "clustering_way": clustering_way,  
+        "incremental_evaluation": incrementalevaluation
+    }
+
+    return eamtg.GreedySimilarityBinning(model_config)
+
+def generate_random_point():
+    """Generate a completetly random point valid WGS84 latitiude and longtidude"""
+    lat=random.uniform(-90,90)
+    lon=random.uniform(-180,180)
+    return [lat,lon]
+
+def generate_nearby_random_points(ref_coords,threshold):
+    """
+    Generate valid WGS84 latitiude and longtidude in threshold(m) proximity to
+    ref coordinates
+    """
+
+    thresholdInWGS84 = threshold* (0.000001/0.11)
+    dx=random.uniform(-thresholdInWGS84/2,thresholdInWGS84/2)
+    dy=random.uniform(-thresholdInWGS84/2,thresholdInWGS84/2)
+    return [ref_coords[0] +dx , ref_coords[1] +dy]
+
+def calDistanceTest(point1, point2, coordinates=False):
+    """haversine distance
+
+    :param point1: a coordinate in degrees WGS84
+    :param point2: another coordinate in degrees WGS84
+    :param coordinates: if false, expect a list of coordinates, defaults to False
+    :return: distance approximately in meters
+    """
+    earthRadius = 6371000  # meters
+    if coordinates:
+        dLat = math.radians(point1.lat-point2.lat)
+        dLon = math.radians(point1.lon-point2.lon)
+        lat1 = math.radians(point1.lat)
+        lat2 = math.radians(point2.lat)
+    else:
+        dLat = math.radians(point1[1]-point2[1])
+        dLon = math.radians(point1[0]-point2[0])
+        lat1 = math.radians(point1[1])
+        lat2 = math.radians(point2[1])
+
+
+    a = (math.sin(dLat/2) ** 2) + ((math.sin(dLon/2) ** 2) * math.cos(lat1) * math.cos(lat2))
+    c = 2 * math.atan2(math.sqrt(a), math.sqrt(1-a))
+    d = earthRadius * c
+
+    return d
+
+def setTripConfig(trips,trip_part,threshold,within_thr=None,label_data=None):
+    """
+    TODO: Write about each parameter to the function
+                trip_part: when mock trips are generated, coordinates of this part of 
+                m trips will be within the threshold. trip_part can take one
+                among the four values:
+    
+                1. '__' ->(None, meaning NEITHER origin nor destination of any trip will lie 
+                within the mentioned threshold when trips are generated),
+    
+                2. 'o_' ->(origin, meaning ONLY origin of m trips will lie within the mentioned 
+                threshold when trips are generated),
+    
+                3. '_d' ->(destination),meaning ONLY destination of m trips will lie within the 
+                mentioned threshold when trips are generated)
+    
+                4. 'od' ->(origin and destination,meaning BOTH origin and destination of m trips
+                will lie within the mentioned threshold when trips are generated)
+    """
+    if label_data == None:            
+        label_data = {
+            "mode_confirm": ['walk', 'bike', 'transit'],
+            "purpose_confirm": ['work', 'home', 'school'],
+            "replaced_mode": ['drive']
+        }
+
+    trip =etmm.generate_mock_trips(
+            user_id="joe", 
+            trips=trips, 
+            trip_part=trip_part,
+            label_data=label_data, 
+            within_threshold=within_thr, 
+            threshold=threshold,  
+        )
+    return trip  
 
 def generate_trip_coordinates(
-    ref_coords: Tuple[float, float], 
+    points_list: list[float], 
     within_threshold: bool,
-    threshold: float, 
-    max: float = 0.1  # approx. 10km in WGS84 
+    threshold_meters: float, 
     ) -> Tuple[float, float]:
-    """generates trip coordinate data to use when mocking a set of trip data.
+    """generates trip coordinate data to use when mocking a set of trip data.i
+    If the coordinate generated  is to be binned together, it is generated in proximity of
+    the previous points in the points_list. Otherwise, if this point is not to be binned together,
+    keep generating a random trip unless we find one that would not bin with previously
+    accepeted trips.
 
-    :param ref_coords: reference coordinates to use as the center of the sampling circle
-    :param within_threshold: how many of these trips are within some distance threshold
-    :param threshold: the distance threshold, in WGS84
-    :param max: max distance, in WGS84, defaults to 0.1 (approx. 10km)
+    :param points_list: list of all the previoushlt selected points 
+    :param within_threshold: is this point  supposed to be within some distance threshold
+    :param threshold_meters: the distance threshold, in meters
     :return: generated coordinate pairs sampled in a 
              circle from some coordinates up to some threshold
     """
-    angle = 2 * math.pi * random.random()
-    radius_threshold = threshold / 2
-    radius = random.uniform(0, radius_threshold) if within_threshold else random.uniform(radius_threshold, max)
-    x = radius * math.cos(angle) + ref_coords[0]
-    y = radius * math.sin(angle) + ref_coords[1]
-    return (x, y)
+
+    if within_threshold and points_list:
+        new_point = generate_nearby_random_points(random.choice(points_list), threshold_meters)    
+    else:
+        new_point = generate_random_point()
+        while not all(calDistanceTest(new_point, pt) > threshold_meters for pt in points_list):
+            new_point = generate_random_point()
+    return new_point
 
 
 def extract_trip_labels(trips: List[ecwc.Confirmedtrip]) -> Dict:
@@ -129,15 +239,12 @@ def build_mock_trip(
 def generate_mock_trips(
     user_id, 
     trips,
-    origin, 
-    destination, 
+    threshold,
     trip_part='od',
     label_data = None, 
     within_threshold = None,
     start_ts: None = None,
     end_ts: None = None,
-    threshold = 0.01,
-    max = 0.1, 
     has_label_p = 1.0,
     seed = 0):
     """mocking function that generates multiple trips for a user. some are sampled 
@@ -158,8 +265,6 @@ def generate_mock_trips(
 
     :param user_id: user UUID
     :param trips: number of trips
-    :param origin: origin coordinates
-    :param destination: destination coordinates
     :param trip_part: when mock trips are generated, coordinates of this part of 
                       the trips will be within the threshold. trip_part can take one
                       among the four values:
@@ -173,10 +278,8 @@ def generate_mock_trips(
                      will lie within the mentioned threshold when trips are generated)
     :param label_data: dictionary of label data, see above, defaults to None
     :param within_threshold: number of trips that should fall within the provided
-           distance threshold in degrees WGS84, defaults to None
-    :param threshold: distance threshold in WGS84 for sampling, defaults to 0.01
-    :param max: maximum distance beyond the threshold for trips sampled that
-                are not within the threshold, defaults to 0.1 degrees WGS84
+           distance threshold in m
+    :param threshold: distance threshold in WGS84 for sampling
     :param has_label_p: probability a trip has labels, defaults to 1.0
     :param seed: random seed, defaults to 0
     :return: randomly sampled trips
@@ -186,9 +289,16 @@ def generate_mock_trips(
     within = within_threshold if within_threshold is not None else trips
     trips_within_threshold = [i < within for i in range(trips)]
     result = []
+    origin_points=[]
+    destination_points=[]    
+
+    # generate trip number of points based on which among 'o' ,'d' or 'od' should be in threshold 
+    # proximity to each other. 
     for within in trips_within_threshold:
-        o = generate_trip_coordinates(origin, (trip_part[0] == 'o' and within), threshold, max)
-        d = generate_trip_coordinates(destination, (trip_part[1] == 'd' and within), threshold, max)
+        origin_points.append(generate_trip_coordinates(origin_points, (trip_part[0] == 'o' and within), threshold))
+        destination_points.append(generate_trip_coordinates(destination_points, (trip_part[1] == 'd' and within), threshold))
+
+    for o,d in zip(origin_points,destination_points):    
         labels = {} if label_data is None or random.random() > has_label_p \
             else sample_trip_labels(
             mode_labels=label_data.get('mode_confirm'),