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')
rads += pi / 2.0
return degrees(rads)
# print angle_bwn_two_points(0,0,1,-1)
def distance_km(lat1, lon1, lat2, lon2):
"""
Distance between two geographical locations
"""
R = 6371 # km
dLat = math.radians(abs(lat2 - lat1))
dLon = math.radians(abs(lon2 - lon1))
lat1 = math.radians(lat1)
lat2 = math.radians(lat2)
a = math.sin(dLat / 2) * math.sin(dLat / 2) + math.sin(
dLon / 2) * math.sin(dLon / 2) * math.cos(lat1) * math.cos(lat2)
c = 2 * math.atan2(math.sqrt(a), math.sqrt(1 - a))
d = R * c
return d
if False:
# test
box = np.array([[1.5, 1.5], [2.5, 3.5]])
param = Params(1000)
param.GRID_SIZE = 5
param.x_min, param.y_min, param.x_max, param.y_max = 0, 0, 5, 5
print mbr_to_cellids(box, param)
rads = atan2(-dy,dx)
# rads %= 2*pi
rads += pi/2.0;
return degrees(rads)
# print angle_bwn_two_points(0,0,1,-1)
def distance_km(lat1, lon1, lat2, lon2):
"""
Distance between two geographical locations
"""
R = 6371 # km
dLat = math.radians(abs(lat2 - lat1))
dLon = math.radians(abs(lon2 - lon1))
lat1 = math.radians(lat1)
lat2 = math.radians(lat2)
a = math.sin(dLat / 2) * math.sin(dLat / 2) + math.sin(dLon / 2) * math.sin(dLon / 2) * math.cos(lat1) * math.cos(
lat2)
c = 2 * math.atan2(math.sqrt(a), math.sqrt(1 - a))
d = R * c
return d
if False:
# test
box = np.array([[1.5,1.5],[2.5,3.5]])
param = Params(1000)
param.GRID_SIZE = 5
param.x_min,param.y_min,param.x_max,param.y_max = 0,0,5,5
print mbr_to_cellids(box,param)
