def testZoomLevel(self):
projection_small = ComplexLogProjection(LatLng(0, 0), LatLng(10, 10),
math.pi / 4)
projection_large = ComplexLogProjection(LatLng(-10, -10),
LatLng(10, 10), math.pi / 4)
data = np.array([[-1, -2, 1, 2], [1, 1, 1, 1]])
# expected = np.array([np.exp(1), np.exp(2), np.exp(1), np.exp(2)])
r1 = projection_small.getZoomLevel(data, 100)
r2 = projection_large.getZoomLevel(data, 100)
r3 = projection_small.getZoomLevel(data, 200)
diff = r1 - r2
np.testing.assert_almost_equal(diff, np.array([1, 1, 1, 1]))
assert r1[0] < r1[1]
np.testing.assert_almost_equal(r3[0] - r1[0], 1)
pass
def to_leaflet(lat1, lng1, lat2, lng2, cutoff, smoothing):
if request.method != "POST":
return ""
json_i = request.get_json(force=True)
if json_i is None:
return "Could not parse JSON", 500
precision = int(request.args.get("precision", 5)) # number of digits
c1latlng = LatLng(lat1, lng1)
c2latlng = LatLng(lat2, lng2)
proj = ComplexLogProjection(
c1latlng,
c2latlng,
math.radians(cutoff),
smoothing_function_type=parse_smoothing(smoothing))
center_distance = c1latlng.distanceTo(c2latlng)
pixel_per_m = 256.0 / (156412.0)
elements = json_i['data']
ret_v = []
for e in elements:
xy = np.array([[e[0]], [e[0]]])
xy, clipping = proj(xy, calculate_clipping=True)
z = proj.getZoomLevel(xy, pixel_per_m)
latlng = tiling.to_leaflet_LatLng(xy[0, 0], xy[1, 0])
clipping = bool(clipping[0])
ret_element = [
round(latlng.lat, precision),
round(latlng.lng, precision),
round(z[0], precision), clipping
]
ret_v.append(ret_element)
z_values = list(map(lambda x: x[2], ret_v))
min_z = min(*z_values)
max_z = max(*z_values)
response = app.response_class(response=json.dumps(
{
"data": ret_v,
"min_z": min_z,
"max_z": max_z
},
check_circular=False,
indent=None),
status=200,
mimetype='application/json')
return response
def test_vis_zoomLevel(self):
projection1 = ComplexLogProjection(LatLng(0, 0), LatLng(10, 10),
math.pi / 4)
projection2 = ComplexLogProjection(LatLng(-10, -10), LatLng(10, 10),
math.pi / 4)
projector = RasterProjector(projection1,
OSMRasterDataProvider(dummy_resolver))
grid = projector.build_grid(
TargetSectionDescription(-4, 4, 400, -2, 2, 200))
zoom = projection1.getZoomLevel(grid, 100)
import matplotlib.pyplot as plt
plt.imshow(zoom.reshape(200, 400))
plt.colorbar()
plt.show()
plt.scatter(range(400), zoom.reshape(200, 400)[10, :])
plt.show()
def cities_projected(lat1, lng1, lat2, lng2, cutoff, smoothing):
with t.time("loading_cities_lat_lng"):
cities_lat_lng = np.array(
list(map(lambda e: [e['lat'], e['lon']],
get_cities()['elements']))).transpose()
with t.time("parsing_params"):
precision = int(request.args.get("precision", 5)) # number of digits
c1latlng = LatLng(lat1, lng1)
c2latlng = LatLng(lat2, lng2)
proj = ComplexLogProjection(
c1latlng,
c2latlng,
math.radians(cutoff),
smoothing_function_type=parse_smoothing(smoothing))
center_distance = c1latlng.distanceTo(c2latlng)
pixel_per_m = 256.0 / (156412.0)
num_cities = cities_lat_lng.shape[1]
with t.time("projection"):
xy, clipping = proj(cities_lat_lng, calculate_clipping=True)
with t.time("zoomlevel"):
z = proj.getZoomLevel(xy, pixel_per_m)
with t.time("tiling"):
latlngs = [None] * num_cities
for i in range(num_cities):
latlng = tiling.to_leaflet_LatLng(xy[0, i], xy[1, i])
latlngs[i] = latlng
with t.time("packaging"):
ret_v = [None] * num_cities
p_x_int = 10**precision
p_x_float = 10.**precision
my_round = lambda x: int(x * (p_x_int)) / (p_x_float)
for i in range(num_cities):
clipping_v = bool(clipping[i])
latlng = latlngs[i]
ret_element = [
my_round(latlng.lat),
my_round(latlng.lng),
my_round(z[i]), clipping_v
]
ret_v[i] = ret_element
with t.time("assembly"):
z_values = list(map(lambda x: x[2], ret_v))
min_z = min(*z_values)
max_z = max(*z_values)
response = app.response_class(response=json.dumps(
{
"data": ret_v,
"min_z": min_z,
"max_z": max_z
},
check_circular=False,
indent=None),
status=200,
mimetype='application/json')
return response