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