def scaleMap(lat, long, zoom, map_size):
'''
Args:
lat: latitude of the map centroid in decimal format
long: longitutde of the map centroid in decimal format
zoom: a number between 1 and 20 giving the zoom level of the map
map_size: the pixel size of the map, e.g., 256 (by 256)
Returns: A list of the southwest and northeast boundingbox points. Points are ordered LONGITUDE, LATITUDE
'''
scale_pix = {
20: 0.1493,
19: 0.2986,
18: 0.5972,
17: 1.1943,
16: 2.3887,
15: 4.7773,
14: 9.5546,
13: 19.109,
12: 38.219,
11: 76.437,
10: 152.87,
9: 305.75,
8: 611.50,
7: 1222.99,
6: 2445.98,
5: 4891.97,
4: 9783.94,
3: 19567.88,
2: 39135.76,
1: 78271.52
}
total_scale = np.cos(
lat *
(np.pi /
180)) * scale_pix[zoom] * map_size * 0.001 # Convert to Kilometers
ctr_dist = total_scale / np.sqrt(2)
center_point = LatLon(lat, long)
headings = [-135 + i * 180 for i in range(0, 2)]
bounding_box = list()
for heading in headings:
temp_point = center_point.offset(heading, ctr_dist)
lat_tmp, long_tmp = temp_point.to_string('D')
bounding_box.append(
(long_tmp, lat_tmp)) # Need to get the correct accessor
return bounding_box
def degreesToMove(lat, long, pixels, zoom, dir_str, map_size):
'''
given a lat long centroid and an amount of pixels to move the centroid, returns a new bounding box of a map moved by the number of "pixels"
Args:
lat: latitude of the map centroid in decimal format
long: longitutde of the map centroid in decimal format
pixels: the number of pixels to move the centroid
zoom: a number between 1 and 20 giving the zoom level of the map
dir_str: A letter indicating the direction to move "n","e","s" or "w" for north, east, south or west
map_size: the map_size of the map, e.g., 256 (by 256)
Returns: a bounding box with the centroid moved 'pixels' in 'dir_str',
That is, a list of the southwest and northeast boundingbox points. Points are ordered LONGITUDE, LATITUDE
'''
scale_pix = {
20: 0.1493,
19: 0.2986,
18: 0.5972,
17: 1.1943,
16: 2.3887,
15: 4.7773,
14: 9.5546,
13: 19.109,
12: 38.219,
11: 76.437,
10: 152.87,
9: 305.75,
8: 611.50,
7: 1222.99,
6: 2445.98,
5: 4891.97,
4: 9783.94,
3: 19567.88,
2: 39135.76,
1: 78271.52
}
heading = {"e": 90.0, "n": 0.0, "w": 270.0, "s": 180.0}
shift_dist = np.cos(lat * (np.pi / 180)) * scale_pix[zoom] * float(
pixels) * 0.001 # Convert to Kilometers
center_point = LatLon(lat, long)
new_center_point = center_point.offset(heading[dir_str], shift_dist)
lat_tmp, long_tmp = new_center_point.to_string('D')
bounding_box = scaleMap(float(lat_tmp), float(long_tmp), zoom, map_size)
return bounding_box
def degrees_to_move(lat, long, pixels, zoom, dir_str, size):
'''
given a lat long centroid and amount of pixels to move the centroid, return a new bounding box
'''
# scale_pix = {20 : 0.07465, 19 : 0.1493, 18 : 0.2986, 17 : 0.5972, 16 : 1.1943, 15 : 2.3887 , 14 : 4.7773 , 13 : 9.5546 , 12 : 19.109, 11 : 38.219, 10 : 76.437, 9 : 152.87, 8 : 305.75, 7 : 611.50, 6 : 1222.99, 5 : 2445.98, 4 : 4891.97, 3 : 9783.94, 2 : 19567.88, 1 : 39135.76, 0 : 78271.52}
scale_pix = {
20: 0.1493,
19: 0.2986,
18: 0.5972,
17: 1.1943,
16: 2.3887,
15: 4.7773,
14: 9.5546,
13: 19.109,
12: 38.219,
11: 76.437,
10: 152.87,
9: 305.75,
8: 611.50,
7: 1222.99,
6: 2445.98,
5: 4891.97,
4: 9783.94,
3: 19567.88,
2: 39135.76,
1: 78271.52
}
heading = {"e": 90.0, "n": 0.0, "w": 270.0, "s": 180.0}
shift_dist = np.cos(lat * (np.pi / 180)) * scale_pix[zoom] * float(
pixels) * 0.001 # Convert to Kilometers
# total_scale = np.cos(lat*(np.pi/180)) * scale_pix[zoom_level] * pixel_size * 0.001
center_point = LatLon(lat, long)
new_center_point = center_point.offset(heading[dir_str], shift_dist)
lat_tmp, long_tmp = new_center_point.to_string('D')
# print lat_tmp, long_tmp
bounding_box = scale_map(float(lat_tmp), float(long_tmp), zoom, size)
return bounding_box
DES_LAND_LONG = 360 + DES_LAND_LONG
# Initial prediction for where a balloon launced from desired landing site would end up
response = retrieve_prediction(DES_LAND_LAT, DES_LAND_LONG, LAUNCH_DAY, LAUNCH_HOUR)
lat_land_from_des, long_land_from_des = extract_results(response)
landing=('Launch from desired',LAUNCH_HOUR,lat_land_from_des,long_land_from_des,'red')
pprint('Got landing - calculating distance and bearing')
sites.append(landing)
# Calc distance travelled and bearing
'''loc_lnd_from_des = LatLon(lat_land_from_des,long_land_from_des)
dist_from_des = loc_des.distance(loc_lnd_from_des)
bearing_from_des = loc_des.heading_initial(loc_lnd_from_des)'''
dist_from_des, bearing_from_des = how_close(DES_LAND_LAT, DES_LAND_LONG,lat_land_from_des, long_land_from_des)
# Calc estimated launch site that will have a balloon land at desired landing site
new_launch = loc_des.offset(calc_backbearing(bearing_from_des),dist_from_des)
GUESS_LAT = float(new_launch.to_string('D')[0])
GUESS_LONG = float(new_launch.to_string('D')[1])
guess = ('guess',LAUNCH_HOUR,GUESS_LAT,GUESS_LONG,'purple')
sites.append(guess)
if GUESS_LONG < 0:
GUESS_LONG = 360 + GUESS_LONG
#print new_launch.to_string('D')
# Now run prediction based on estimated landing site
response = retrieve_prediction(GUESS_LAT, GUESS_LONG, LAUNCH_DAY, LAUNCH_HOUR)
lat_land_from_guess, long_land_from_guess = extract_results(response)
landing_from_guess = ('lfg',LAUNCH_HOUR,lat_land_from_guess,long_land_from_guess,'green')
sites.append(landing_from_guess)
def scale_map(lat, long, zoom_level, pixel_size):
scale_dic = {
20: 1128.497220,
19: 2256.994440,
18: 4513.988880,
17: 9027.977761,
16: 18055.955520,
15: 36111.911040,
14: 72223.822090,
13: 144447.644200,
12: 288895.288400,
11: 577790.576700,
10: 1155581.153000,
9: 2311162.307000,
8: 4622324.614000,
7: 9244649.227000,
6: 18489298.450000,
5: 36978596.910000,
4: 73957193.820000,
3: 147914387.600000,
2: 295828775.300000,
1: 591657550.500000
}
scale_pix = {
20: 0.1493,
19: 0.2986,
18: 0.5972,
17: 1.1943,
16: 2.3887,
15: 4.7773,
14: 9.5546,
13: 19.109,
12: 38.219,
11: 76.437,
10: 152.87,
9: 305.75,
8: 611.50,
7: 1222.99,
6: 2445.98,
5: 4891.97,
4: 9783.94,
3: 19567.88,
2: 39135.76,
1: 78271.52
}
# scale_pix = {20 : 0.07465, 19 : 0.1493, 18 : 0.2986, 17 : 0.5972, 16 : 1.1943, 15 : 2.3887 , 14 : 4.7773 , 13 : 9.5546 , 12 : 19.109, 11 : 38.219, 10 : 76.437, 9 : 152.87, 8 : 305.75, 7 : 611.50, 6 : 1222.99, 5 : 2445.98, 4 : 4891.97, 3 : 9783.94, 2 : 19567.88, 1 : 39135.76, 0 : 78271.52}
# center=-28.496109,-48.752528&zoom=17&size=256x256&
# output= bounding box in lat,long
santa_catarina = (-28.496109, -48.752528)
# pixel_size = 256
total_scale = np.cos(
lat * (np.pi / 180)
) * scale_pix[zoom_level] * pixel_size * 0.001 # Convert to Kilometers
# ctr_dist = sqrt(0.5*total_scale*total_scale)
ctr_dist = total_scale / np.sqrt(2)
center_point = LatLon(lat, long)
headings = [-135 + i * 180 for i in range(0, 2)]
bounding_box = list()
for heading in headings:
temp_point = center_point.offset(heading, ctr_dist)
lat_tmp, long_tmp = temp_point.to_string('D')
bounding_box.append(
(long_tmp, lat_tmp)) # Need to get the correct accessor
return bounding_box
