def check_user_can_add_pin(self, lat, lon, author, session_key):
""" """
tc_start = time()
catalog = self.context.catalog
# modify if map_distance limit changes
lat_min, lat_max = lat - 5., lat + 5.
# lon distances differ with latitude (but for performance)
lon_min, lon_max = lon - 20., lon + 20.
date_min, date_max = datetime.now() - timedelta(
weeks=1), datetime.now()
filters = {
'latitude': {
'query': (lat_min, lat_max),
'range': 'min:max'
},
'longitude': {
'query': (lon_min, lon_max),
'range': 'min:max'
},
'date': {
'query': (date_min, date_max),
'range': 'min:max'
},
'author': author,
'session_key': session_key
}
rids = filter_rids(catalog, filters)
if rids is None:
r_list = []
else:
r_list = list(set(rids))
tc_start_apply_idxs = time()
lat_dict = get_index_dict('latitude', catalog, lat_min, lat_max)
lon_dict = get_index_dict('longitude', catalog, lon_min, lon_max)
tc_end_apply_idxs = time()
print 'apply indexes', tc_end_apply_idxs - tc_start_apply_idxs
ret = True
for rid in r_list:
clat, clon = lat_dict[rid], lon_dict[rid]
if map_distance(lat, lon, clat, clon) < 1: #km
ret = False
break
tc_end = time()
print 'check user can add pin', tc_end - tc_start
return ret
def get_countries(self, q):
""" """
def country_matches(country, q):
return country.lower().startswith(q.lower())
catalog = self.context.catalog
country_dict = get_index_dict('country', catalog)
country_set = set(country_dict.values())
return '\n'.join([country for country in country_set
if country_matches(country, q)])
def country_statistics(self, country):
catalog = self.context.catalog
tc_start_apply_idxs = time()
country_dict = get_index_dict('country', catalog, country, country)
type_dict = get_index_dict('type', catalog)
rating_dict = get_index_dict('rating', catalog)
tc_end_apply_idxs = time()
print 'apply indexes', tc_end_apply_idxs - tc_start_apply_idxs
statistics = {}
for type in TYPE_VALUES:
ratings = [rating_dict[rid] for rid in country_dict.keys()
if type_dict[rid] == type]
type_stats = {'num_ratings': len(ratings)}
if len(ratings) > 0:
average_rating = sum(ratings) / float(len(ratings))
type_stats['average_rating'] = average_rating
statistics[type] = type_stats
return statistics
def get_countries(self, q):
""" """
def country_matches(country, q):
return country.lower().startswith(q.lower())
catalog = self.context.catalog
country_dict = get_index_dict('country', catalog)
country_set = set(country_dict.values())
return '\n'.join([
country for country in country_set if country_matches(country, q)
])
def check_user_can_add_pin(self, lat, lon, author, session_key):
""" """
tc_start = time()
catalog = self.context.catalog
# modify if map_distance limit changes
lat_min, lat_max = lat - 5., lat + 5.
# lon distances differ with latitude (but for performance)
lon_min, lon_max = lon - 20., lon + 20.
date_min, date_max = datetime.now() - timedelta(weeks=1), datetime.now()
filters = {'latitude': {'query': (lat_min, lat_max),
'range': 'min:max'},
'longitude': {'query': (lon_min, lon_max),
'range': 'min:max'},
'date': {'query': (date_min, date_max),
'range': 'min:max'},
'author': author,
'session_key': session_key}
rids = filter_rids(catalog, filters)
if rids is None:
r_list = []
else:
r_list = list(set(rids))
tc_start_apply_idxs = time()
lat_dict = get_index_dict('latitude', catalog, lat_min, lat_max)
lon_dict = get_index_dict('longitude', catalog, lon_min, lon_max)
tc_end_apply_idxs = time()
print 'apply indexes', tc_end_apply_idxs - tc_start_apply_idxs
ret = True
for rid in r_list:
clat, clon = lat_dict[rid], lon_dict[rid]
if map_distance(lat, lon, clat, clon) < 1: #km
ret = False
break
tc_end = time()
print 'check user can add pin', tc_end - tc_start
return ret
def country_statistics(self, country):
catalog = self.context.catalog
tc_start_apply_idxs = time()
country_dict = get_index_dict('country', catalog, country, country)
type_dict = get_index_dict('type', catalog)
rating_dict = get_index_dict('rating', catalog)
tc_end_apply_idxs = time()
print 'apply indexes', tc_end_apply_idxs - tc_start_apply_idxs
statistics = {}
for type in TYPE_VALUES:
ratings = [
rating_dict[rid] for rid in country_dict.keys()
if type_dict[rid] == type
]
type_stats = {'num_ratings': len(ratings)}
if len(ratings) > 0:
average_rating = sum(ratings) / float(len(ratings))
type_stats['average_rating'] = average_rating
statistics[type] = type_stats
return statistics
def xrjs_getClusters(self, lat_min, lat_max, lon_min, lon_max):
""" """
def make_points(r_list, lan_dict, lon_dict, type_dict, rating_dict):
points = []
for i, rid in enumerate(r_list):
point = Point(i, float(lat_dict[rid]), float(lon_dict[rid]))
point.type = type_dict[rid]
point.rating = rating_dict[rid]
points.append(point)
return points
def make_points_by_type(points):
points_by_type = {}
for point in points:
if not point.type in points_by_type:
points_by_type[point.type] = []
points_by_type[point.type].append(point)
return points_by_type
def make_clusters(points_by_type, lat_min, lat_max, lon_min, lon_max,
grid_size):
def average_rating(points):
assert len(points) > 0
ratings = [point.rating for point in points]
return sum(ratings) / float(len(ratings))
all_clusters = []
for type, points in points_by_type.iteritems():
centers, groups = kmeans(lat_min, lat_max, lon_min, lon_max,
points, grid_size)
clusters = []
for i, points in enumerate(groups):
if len(points) > 0:
clusters.append({
'center':
centers[i],
'points':
points,
'type':
type,
'averageRating':
average_rating(points),
})
all_clusters.extend(clusters)
return all_clusters
def point_data(cluster, r_list):
def cluster_tooltip(cluster, r_list):
cluster_rids = [
r_list[point.id] for point in cluster['points']
]
pins = [
getObjectFromCatalog(catalog, rid) for rid in cluster_rids
]
return self.cluster_index(pins=pins)
num_points = len(cluster['points'])
if num_points == 1:
point = cluster['points'][0]
pin = getObjectFromCatalog(catalog, r_list[point.id])
icon_name = 'mk_single_rating_%s_%d' % (pin.type, pin.rating)
return {
'id': pin.id,
'icon_name': icon_name,
'lat': pin.latitude,
'lon': pin.longitude,
'display_tooltip': False,
'tooltip': '',
'label': ''
}
else:
rating = int(cluster['averageRating'])
display_tooltip = (lat_max - lat_min) < 1.
if display_tooltip:
tooltip = cluster_tooltip(cluster, r_list)
else:
tooltip = ''
icon_name = 'mk_rating_%s_%d_%d' % (cluster['type'], rating,
num_points)
return {
'id': '',
'icon_name': icon_name,
'lat': cluster['center'].lat,
'lon': cluster['center'].lon,
'display_tooltip': display_tooltip,
'tooltip': tooltip,
'label': 'cluster',
'num_points': num_points
}
tc_start = time()
lat_min, lat_max = float(lat_min), float(lat_max)
lon_min, lon_max = float(lon_min), float(lon_max)
grid_size = 7
tlat_min, tlat_max, tlon_min, tlon_max = get_discretized_limits(
lat_min, lat_max, lon_min, lon_max, grid_size)
catalog = self.context.catalog
tc_start_apply_idxs = time()
type_dict = get_index_dict('type', catalog)
lat_dict = get_index_dict('latitude', catalog, tlat_min, tlat_max)
lon_dict = get_index_dict('longitude', catalog, tlon_min, tlon_max)
rating_dict = get_index_dict('rating', catalog)
tc_end_apply_idxs = time()
print 'apply indexes', tc_end_apply_idxs - tc_start_apply_idxs
map_filters = {
'latitude': {
'query': (tlat_min, tlat_max),
'range': 'min:max'
},
'longitude': {
'query': (tlon_min, tlon_max),
'range': 'min:max'
}
}
rids = filter_rids(catalog, map_filters)
if rids is None:
r_list = []
else:
r_list = list(set(rids))
points = make_points(r_list, lat_dict, lon_dict, type_dict,
rating_dict)
points_by_type = make_points_by_type(points)
clusters = make_clusters(points_by_type, tlat_min, tlat_max, tlon_min,
tlon_max, grid_size)
points = [point_data(cluster, r_list) for cluster in clusters]
tc_end = time()
print 'clusters', tc_end - tc_start
return json.dumps({'points': points})
def xrjs_getClusters(self, lat_min, lat_max, lon_min, lon_max):
""" """
def make_points(r_list, lan_dict, lon_dict, type_dict, rating_dict):
points = []
for i, rid in enumerate(r_list):
point = Point(i, float(lat_dict[rid]), float(lon_dict[rid]))
point.type = type_dict[rid]
point.rating = rating_dict[rid]
points.append(point)
return points
def make_points_by_type(points):
points_by_type = {}
for point in points:
if not point.type in points_by_type:
points_by_type[point.type] = []
points_by_type[point.type].append(point)
return points_by_type
def make_clusters(points_by_type, lat_min, lat_max,
lon_min, lon_max, grid_size):
def average_rating(points):
assert len(points) > 0
ratings = [point.rating for point in points]
return sum(ratings) / float(len(ratings))
all_clusters = []
for type, points in points_by_type.iteritems():
centers, groups = kmeans(lat_min, lat_max,
lon_min, lon_max,
points, grid_size)
clusters = []
for i, points in enumerate(groups):
if len(points) > 0:
clusters.append({
'center': centers[i],
'points': points,
'type': type,
'averageRating': average_rating(points),
})
all_clusters.extend(clusters)
return all_clusters
def point_data(cluster, r_list):
def cluster_tooltip(cluster, r_list):
cluster_rids = [r_list[point.id] for point in cluster['points']]
pins = [getObjectFromCatalog(catalog, rid) for rid in cluster_rids]
return self.cluster_index(pins=pins)
num_points = len(cluster['points'])
if num_points == 1:
point = cluster['points'][0]
pin = getObjectFromCatalog(catalog, r_list[point.id])
icon_name = 'mk_single_rating_%s_%d' % (pin.type, pin.rating)
return {'id': pin.id,
'icon_name': icon_name,
'lat': pin.latitude,
'lon': pin.longitude,
'display_tooltip': False,
'tooltip': '',
'label': ''}
else:
rating = int(cluster['averageRating'])
display_tooltip = (lat_max - lat_min) < 1.
if display_tooltip:
tooltip = cluster_tooltip(cluster, r_list)
else:
tooltip = ''
icon_name = 'mk_rating_%s_%d_%d' % (cluster['type'],
rating,
num_points)
return {'id': '',
'icon_name': icon_name,
'lat': cluster['center'].lat,
'lon': cluster['center'].lon,
'display_tooltip': display_tooltip,
'tooltip': tooltip,
'label': 'cluster',
'num_points': num_points}
tc_start = time()
lat_min, lat_max = float(lat_min), float(lat_max)
lon_min, lon_max = float(lon_min), float(lon_max)
grid_size = 7
tlat_min, tlat_max, tlon_min, tlon_max = get_discretized_limits(
lat_min, lat_max, lon_min, lon_max, grid_size)
catalog = self.context.catalog
tc_start_apply_idxs = time()
type_dict = get_index_dict('type', catalog)
lat_dict = get_index_dict('latitude', catalog, tlat_min, tlat_max)
lon_dict = get_index_dict('longitude', catalog, tlon_min, tlon_max)
rating_dict = get_index_dict('rating', catalog)
tc_end_apply_idxs = time()
print 'apply indexes', tc_end_apply_idxs - tc_start_apply_idxs
map_filters = {'latitude': {'query': (tlat_min, tlat_max),
'range': 'min:max'},
'longitude': {'query': (tlon_min, tlon_max),
'range': 'min:max'}}
rids = filter_rids(catalog, map_filters)
if rids is None:
r_list = []
else:
r_list = list(set(rids))
points = make_points(r_list, lat_dict, lon_dict, type_dict, rating_dict)
points_by_type = make_points_by_type(points)
clusters = make_clusters(points_by_type, tlat_min, tlat_max,
tlon_min, tlon_max, grid_size)
points = [point_data(cluster, r_list) for cluster in clusters]
tc_end = time()
print 'clusters', tc_end - tc_start
return json.dumps({'points': points})