def compute_frequency(client, city, entity, k=200):
"""Splits `city` in k^2 rectangles and save the frequency of `entity` in
each of them as a matrix."""
assert entity in [Entity.photo, Entity.checkin]
freq_name = FREQUENCE_FILE.format(entity.name, city, k)
try:
mat_count = sio.loadmat(freq_name)['c']
return mat_count
except IOError:
pass
count = (k * k + 1) * [
0,
]
get_data = {Entity.photo: get_photos, Entity.checkin: get_checkins}[entity]
coords = get_data(client, city)
bbox = (cities.US + cities.EU)[cities.INDEX[city]]
rectangles, rect_to_index, _ = mq.k_split_bbox(bbox, k)
# count[0] is for potential points that do not fall in any region (it
# must only happens because of rounding inprecision)
count = (len(rectangles) + 1) * [
0,
]
for loc in coords:
count[rect_to_index(loc) + 1] += 1
mat_count = np.array(count[1:])
sio.savemat(freq_name, {'c': mat_count}, do_compression=True)
return mat_count
def compute_frequency(client, city, entity, k=200):
"""Splits `city` in k^2 rectangles and save the frequency of `entity` in
each of them as a matrix."""
assert entity in [Entity.photo, Entity.checkin]
freq_name = FREQUENCE_FILE.format(entity.name, city, k)
try:
mat_count = sio.loadmat(freq_name)['c']
return mat_count
except IOError:
pass
count = (k*k+1)*[0, ]
get_data = {Entity.photo: get_photos, Entity.checkin: get_checkins}[entity]
coords = get_data(client, city)
bbox = (cities.US+cities.EU)[cities.INDEX[city]]
rectangles, rect_to_index, _ = mq.k_split_bbox(bbox, k)
# count[0] is for potential points that do not fall in any region (it
# must only happens because of rounding inprecision)
count = (len(rectangles)+1)*[0, ]
for loc in coords:
count[rect_to_index(loc)+1] += 1
mat_count = np.array(count[1:])
sio.savemat(freq_name, {'c': mat_count}, do_compression=True)
return mat_count
for val, poly in polys:
if point.intersects(poly) and \
point.intersection(poly).area > .6*size:
res.append((tag, val))
break
return sorted(res, key=lambda x: x[1], reverse=True)
GRID_SIZE = 80
TOP_K = 2000
MIN_WIDTH = 1
MIN_HEIGHT = 1
MAX_SIZE = 4
MAX_SUPPORT = 250
REJECTED = 0
rectangles, dummy, index_to_rect = k_split_bbox(BBOX, GRID_SIZE)
if __name__ == '__main__':
import sys
# import random
# random.seed(135)
tag = 'museum' if len(sys.argv) <= 1 else sys.argv[1]
tt = clock()
# tmp = persistent.load_var('supported')
# tags = [v[0] for v in tmp]
# random.shuffle(tags)
# tt = clock()
# p = Pool(3)
# p.map(spatial_scan, tags)
# p.map(post_process, tags)
# p.close()
# consolidate(tags)
for tag, polys in tags.items():
for val, poly in polys:
if point.intersects(poly) and \
point.intersection(poly).area > .6*size:
res.append((tag, val))
break
return sorted(res, key=lambda x: x[1], reverse=True)
GRID_SIZE = 80
TOP_K = 2000
MIN_WIDTH = 1
MIN_HEIGHT = 1
MAX_SIZE = 4
MAX_SUPPORT = 250
REJECTED = 0
rectangles, dummy, index_to_rect = k_split_bbox(BBOX, GRID_SIZE)
if __name__ == '__main__':
import sys
# import random
# random.seed(135)
tag = 'museum' if len(sys.argv) <= 1 else sys.argv[1]
tt = clock()
# tmp = persistent.load_var('supported')
# tags = [v[0] for v in tmp]
# random.shuffle(tags)
# tt = clock()
# p = Pool(3)
# p.map(spatial_scan, tags)
# p.map(post_process, tags)
# p.close()
# consolidate(tags)