def test_compress(self):
geohashes = set(['tdnu20', 'tdnu21', 'tdnu22', 'tdnu23', 'tdnu24', 'tdnu25', 'tdnu26', 'tdnu27', 'tdnu28', 'tdnu29',
'tdnu2b', 'tdnu2c', 'tdnu2d', 'tdnu2e', 'tdnu2f', 'tdnu2g', 'tdnu2h', 'tdnu2j', 'tdnu2k', 'tdnu2m',
'tdnu2n', 'tdnu2p', 'tdnu2q', 'tdnu2r', 'tdnu2s', 'tdnu2t', 'tdnu2u', 'tdnu2v', 'tdnu2w', 'tdnu2x',
'tdnu2y', 'tdnu2z'])
final_geohash = set(['tdnu2'])
output = georaptor.compress(geohashes)
self.assertEqual(output, final_geohash)
def create_geohash(latitude, longitude, radius, precision, georaptor_flag=False, minlevel=1, maxlevel=12):
x = 0.0
y = 0.0
points = []
geohashes = []
grid_width = [5009400.0, 1252300.0, 156500.0, 39100.0, 4900.0, 1200.0, 152.9, 38.2, 4.8, 1.2, 0.149, 0.0370]
grid_height = [4992600.0, 624100.0, 156000.0, 19500.0, 4900.0, 609.4, 152.4, 19.0, 4.8, 0.595, 0.149, 0.0199]
height = (grid_height[precision - 1])/2
width = (grid_width[precision-1])/2
lat_moves = int(math.ceil(radius / height)) #4
lon_moves = int(math.ceil(radius / width)) #2
for i in range(0, lat_moves):
temp_lat = y + height*i
for j in range(0,lon_moves):
temp_lon = x + width*j
if in_circle_check(temp_lat, temp_lon, y, x, radius):
x_cen, y_cen = get_centroid(temp_lat, temp_lon, height, width)
lat, lon = convert_to_latlon(y_cen, x_cen, latitude, longitude)
points += [[lat, lon]]
lat, lon = convert_to_latlon(-y_cen, x_cen, latitude, longitude)
points += [[lat, lon]]
lat, lon = convert_to_latlon(y_cen, -x_cen, latitude, longitude)
points += [[lat, lon]]
lat, lon = convert_to_latlon(-y_cen, -x_cen, latitude, longitude)
points += [[lat, lon]]
for point in points:
geohashes += [Geohash.encode(point[0], point[1], precision)]
if georaptor_flag:
georaptor_out = georaptor.compress(set(geohashes), int(minlevel), int(maxlevel))
return ','.join(georaptor_out)
else:
return ','.join(set(geohashes))
def get_geohash_radius_approximation(latitude,
longitude,
radius,
precision,
georaptor_flag=False,
minlevel=1,
maxlevel=12):
"""
Get the list of geohashed that approximate a circle
:param latitude: Float the longitude to get the radius approximation for
:param longitude: Float the latitude to get the radius approximation for
:param radius: Integer Radius coverage in meters
:param precision: Integer the geohash precision level
:param georaptor_flag: Do you want to compress it with georaptor
:param minlevel: minimal precision level possible
:param maxlevel: maximal precision level possible
:return: A list of geohashes
"""
x = 0.0
y = 0.0
points = []
geohashes = []
grid_width = [
5009400.0, 1252300.0, 156500.0, 39100.0, 4900.0, 1200.0, 152.9, 38.2,
4.8, 1.2, 0.149, 0.0370
]
grid_height = [
4992600.0, 624100.0, 156000.0, 19500.0, 4900.0, 609.4, 152.4, 19.0,
4.8, 0.595, 0.149, 0.0199
]
height = (grid_height[precision - 1]) / 2
width = (grid_width[precision - 1]) / 2
lat_moves = int(math.ceil(radius / height)) # 4
lon_moves = int(math.ceil(radius / width)) # 2
for i in range(0, lat_moves):
temp_lat = y + height * i
for j in range(0, lon_moves):
temp_lon = x + width * j
if in_circle_check(temp_lat, temp_lon, y, x, radius):
x_cen, y_cen = get_centroid(temp_lat, temp_lon, height, width)
lat, lon = convert_to_latlon(y_cen, x_cen, latitude, longitude)
points += [[lat, lon]]
lat, lon = convert_to_latlon(-y_cen, x_cen, latitude,
longitude)
points += [[lat, lon]]
lat, lon = convert_to_latlon(y_cen, -x_cen, latitude,
longitude)
points += [[lat, lon]]
lat, lon = convert_to_latlon(-y_cen, -x_cen, latitude,
longitude)
points += [[lat, lon]]
for point in points:
geohashes += [pgh.encode(point[0], point[1], precision)]
if georaptor_flag:
georaptor_out = georaptor.compress(set(geohashes), int(minlevel),
int(maxlevel))
return list(georaptor_out)
else:
return list(set(geohashes))