def test_find_centroid_identical(self):
point_a = point.Point(49.258071, 4.310359) # near Reims, FR
point_b = point.Point(49.258071, 4.310359) # near Reims, FR
point_c = point.Point(49.258071, 4.310359) # near Reims, FR
point_d = point.Point(49.258071, 4.310359) # near Reims, FR
coordinates = [point_a, point_b, point_c, point_d]
self.assertEqual(location.find_centroid(coordinates), point_a)
def test_find_centroid_close(self):
point_a = point.Point(51.449457, -0.149099) # Balham
point_b = point.Point(51.399944, 0.016419) # Bromley
point_c = point.Point(51.316882, -0.143389) # Coulsdon
point_d = point.Point(51.403266, -0.303545) # Kingston u/t
coordinates = [point_a, point_b, point_c, point_d]
self.assertEqual(location.find_centroid(coordinates),
point.Point(51.392441720782934, -0.14489879977683245))
def test_find_centroid_mid(self):
point_a = point.Point(53.434721, -0.244350) # Stainton le Vale
point_b = point.Point(54.761073, -1.564506) # Durham
point_c = point.Point(55.608358, -3.007014) # Scottish Borders
point_d = point.Point(55.213541, -4.518828) # South Ayrshire
coordinates = [point_a, point_b, point_c, point_d]
self.assertEqual(location.find_centroid(coordinates),
point.Point(54.76499345622335, -2.307015824636315))
def test_find_centroid_far(self):
point_a = point.Point(49.258071, 4.310359) # near Reims, FR
point_b = point.Point(47.176878, 6.130848) # near Besancon
point_c = point.Point(45.002795, 5.631141) # near Grenoble
point_d = point.Point(43.360261, -0.213497) # near Pau
point_e = point.Point(48.049537, -1.970780) # near Rennes
coordinates = [point_a, point_b, point_c, point_d, point_e]
self.assertEqual(location.find_centroid(coordinates),
point.Point(46.61597667033897, 2.7632532505451315))
def test_mean_dist_from_centroid_mid(self):
point_a = point.Point(53.434721, -0.244350) # Stainton le Vale
point_b = point.Point(54.761073, -1.564506) # Durham
point_c = point.Point(55.608358, -3.007014) # Scottish Borders
point_d = point.Point(55.213541, -4.518828) # South Ayrshire
coordinates = [point_a, point_b, point_c, point_d]
centroid = location.find_centroid(coordinates)
self.assertEqual(
location.mean_dist_from_centroid(coordinates, centroid),
125240.97021434733)
def test_mean_dist_from_centroid_close(self):
point_a = point.Point(51.449457, -0.149099) # Balham
point_b = point.Point(51.399944, 0.016419) # Bromley
point_c = point.Point(51.316882, -0.143389) # Coulsdon
point_d = point.Point(51.403266, -0.303545) # Kingston u/t
coordinates = [point_a, point_b, point_c, point_d]
centroid = location.find_centroid(coordinates)
self.assertEqual(
location.mean_dist_from_centroid(coordinates, centroid),
9260.933838113526)
def test_mean_dist_from_centroid_far(self):
point_a = point.Point(49.258071, 4.310359) # near Reims, FR
point_b = point.Point(47.176878, 6.130848) # near Besancon
point_c = point.Point(45.002795, 5.631141) # near Grenoble
point_d = point.Point(43.360261, -0.213497) # near Pau
point_e = point.Point(48.049537, -1.970780) # near Rennes
coordinates = [point_a, point_b, point_c, point_d, point_e]
centroid = location.find_centroid(coordinates)
self.assertEqual(
location.mean_dist_from_centroid(coordinates, centroid),
337243.52725888294)
def get_suggestions(request_id, event_id, place_type, suggestions_mode):
"""
Calculate meeting place suggestions of place_type for an event, based on
requested suggestion mode.
:param request_id: requesting user
:param event_id: event
:param place_type: type of place to suggest
:param suggestions_mode: suggestions mode (e.g. "distance" or "transit")
:return: list of places in requested order (e.g. distance, transit time)
"""
ids = [
member["user_id"] for member in events.get_members(
request_id, event_id
)
]
users = user_store.get_users_by_ids(ids)
user_coordinates = [Point(*user.get_location()) for user in users]
centroid = location.find_centroid(user_coordinates)
mean_dist = location.mean_dist_from_centroid(
user_coordinates,
centroid
)
radius = max(1500, math.ceil(mean_dist * MEAN_DIST_TO_RADIUS_RATIO))
potential_places = places.get_places_around_centroid(
centroid,
radius,
place_type
)
if not potential_places:
return []
if len(potential_places) > MAX_PLACES_PER_SUGGESTION:
potential_places = places.sort_places_by_rating(
potential_places
)[:MAX_PLACES_PER_SUGGESTION]
if suggestions_mode == "distance":
potential_places = places.get_distance_for_places(
user_coordinates,
potential_places
)
else:
potential_places = places.get_travel_time_for_places(
user_coordinates,
potential_places,
suggestions_mode
)
return places.sort_places_by_travel_total(potential_places)