def compute_coverage_map(grid_size = 100):
swlat=34.018212
swlng=-118.291716
nelat=34.025296
nelng=-118.279826
videos = get_videos(swlat, swlng, nelat, nelng)
map = np.ndarray(shape=(grid_size, grid_size), dtype=int)
for video in videos:
if IS_FROM_MEDIAQ:
if video.properties['vid']:
vid = str(video.properties['vid'])
fovs = getFOVs(vid)
if fovs and len(fovs) > 0:
for fov in fovs.features:
f = FOV(fov)
param = Params(200, swlat, swlng, nelat, nelng)
param.GRID_SIZE = grid_size
for cid in f.cellids(param):
cell_lat, cell_lng = cell_coord(cid, param)
if f.cover(cell_lat, cell_lng):
y_idx = cid/param.GRID_SIZE
x_idx = cid - y_idx*param.GRID_SIZE
# print x_idx, y_idx, map[x_idx][y_idx]
map[x_idx][y_idx] = map[x_idx][y_idx] + 1
else:
for f in video.fovs:
param = Params(200, swlat, swlng, nelat, nelng)
param.GRID_SIZE = grid_size
for cid in f.cellids(param):
cell_lat, cell_lng = cell_coord(cid, param)
if f.cover(cell_lat, cell_lng):
y_idx = cid/param.GRID_SIZE
x_idx = cid - y_idx*param.GRID_SIZE
# print x_idx, y_idx, map[x_idx][y_idx]
map[x_idx][y_idx] = map[x_idx][y_idx] + 1
fig, ax = plt.subplots()
heatmap = ax.pcolor(map, cmap=plt.cm.Reds)
plt.show()
plt.close()
np.savetxt("mediaq_coverage_heatmap.txt" , map, fmt='%i\t')
def compute_coverage_map(grid_size=100):
swlat = 34.018212
swlng = -118.291716
nelat = 34.025296
nelng = -118.279826
videos = get_videos(swlat, swlng, nelat, nelng)
map = np.ndarray(shape=(grid_size, grid_size), dtype=int)
for video in videos:
if IS_FROM_MEDIAQ:
if video.properties['vid']:
vid = str(video.properties['vid'])
fovs = getFOVs(vid)
if fovs and len(fovs) > 0:
for fov in fovs.features:
f = FOV(fov)
param = Params(200, swlat, swlng, nelat, nelng)
param.GRID_SIZE = grid_size
for cid in f.cellids(param):
cell_lat, cell_lng = cell_coord(cid, param)
if f.cover(cell_lat, cell_lng):
y_idx = cid / param.GRID_SIZE
x_idx = cid - y_idx * param.GRID_SIZE
# print x_idx, y_idx, map[x_idx][y_idx]
map[x_idx][y_idx] = map[x_idx][y_idx] + 1
else:
for f in video.fovs:
param = Params(200, swlat, swlng, nelat, nelng)
param.GRID_SIZE = grid_size
for cid in f.cellids(param):
cell_lat, cell_lng = cell_coord(cid, param)
if f.cover(cell_lat, cell_lng):
y_idx = cid / param.GRID_SIZE
x_idx = cid - y_idx * param.GRID_SIZE
# print x_idx, y_idx, map[x_idx][y_idx]
map[x_idx][y_idx] = map[x_idx][y_idx] + 1
fig, ax = plt.subplots()
heatmap = ax.pcolor(map, cmap=plt.cm.Reds)
plt.show()
plt.close()
np.savetxt("mediaq_coverage_heatmap.txt", map, fmt='%i\t')
def optimization(tree, fov_count, seed, param):
np.random.seed(seed)
fovs_file = re.sub(r"\.dat$", "", param.dataset) + ".txt"
videos = read_data(fovs_file)
fovs = []
for v in videos:
leaf_node = tree.leafCover(v.location())
if leaf_node:
v.size = np.random.zipf(param.ZIPFIAN_SKEW)
if v.size > 20:
v.size = 20
v.fov_count = int(v.size)
fovs = fovs + v.get_fovs()
# else:
# print "not a leaf node", v.location()
universe = Set([i for i in range(param.GRID_SIZE * param.GRID_SIZE)])
all_sets = {}
for i in range(len(fovs)):
all_sets[i] = fovs[i].cellids(param)
weights = {}
count = 0
last_weight = 0
for item in universe:
coord = cell_coord(item, param)
# print coord
leaf_node = tree.leafCover(coord)
if leaf_node is not None:
compute_urgency(leaf_node)
boundary = np.array([[param.x_min, param.y_min], [param.x_max, param.y_max]])
coverage_ratio = min(
1, rect_area(boundary) / (param.GRID_SIZE * param.GRID_SIZE * rect_area(leaf_node.n_box))
)
weights[item] = leaf_node.urgency * coverage_ratio
last_weight = weights[item]
else:
weights[item] = last_weight
count = count + 1
# print count
# print universe
# print all_sets
# print fov_count
# print weights
start = time.time()
covered_sets, covered_items, covered_weight = max_cover(universe, all_sets, fov_count, weights)
print "time ", time.time() - start
print covered_weight
return covered_weight
def optimization(tree, fov_count, seed, param):
np.random.seed(seed)
fovs = read_image_data(param.dataset)
universe = Set([i for i in range(param.GRID_SIZE*param.GRID_SIZE)])
all_sets = {}
for i in range(len(fovs)):
all_sets[i] = fovs[i].cellids(param)
weights = {}
count = 0
last_weight = 0
for item in universe:
coord = cell_coord(item, param)
# print coord
leaf_node = tree.leafCover(coord)
if leaf_node is not None:
compute_urgency(leaf_node)
boundary = np.array([[param.x_min, param.y_min],[param.x_max, param.y_max]])
coverage_ratio = min(1, rect_area(boundary)/(param.GRID_SIZE*param.GRID_SIZE*rect_area(leaf_node.n_box)))
weights[item] = leaf_node.urgency*coverage_ratio
last_weight = weights[item]
else:
weights[item] = last_weight
count = count + 1
# print count
# print universe
# print all_sets
# print fov_count
# print weights
start = time.time()
covered_sets, covered_items, covered_weight = max_cover(universe, all_sets, fov_count, weights)
print "time ", time.time() - start
print covered_weight
return covered_weight
