def test_within_radius(self):
""" Get the points near to another point using a quadtree approach. """
crs = karta.crs.LonLatWGS84
pt = karta.Point((0.0, 30.0), crs=crs)
np.random.seed(42)
x = (np.random.random(1000) - 0.5) * 180.0
y = (np.random.random(1000) - 0.5) * 30.0
mp_noindex = karta.Multipoint(zip(x, y), crs=crs, build_index=False)
mp = karta.Multipoint(zip(x, y), crs=crs, build_index=True)
subset_noindex = mp_noindex.within_radius(pt, 5e6)
subset = mp.within_radius(pt, 5e6)
self.assertEqual(len(subset), len(subset_noindex))
for i in range(0, len(subset), 50):
self.assertTrue(subset[i] in subset_noindex)
return
def test_sample_multipoint(self):
grid = RegularGrid([0.0, 0.0, 1.0, 1.0, 0.0, 0.0],
values=np.array([[0, 1], [1, 0.5]]))
mp = karta.Multipoint([(0.6, 0.7), (0.6, 1.3), (1.4, 0.3), (1.6, 1.3)],
crs=grid.crs)
self.assertTrue(
np.all(
np.allclose(grid.sample(mp, method="nearest"),
np.array([0.0, 1.0, 1.0, 0.5]))))
def test_polygon_contains(self):
""" Search for points contained within a polygon, using a quadtree. """
crs = karta.crs.SphericalEarth
th = np.linspace(-np.pi, np.pi, 18)
xp = 5 * np.cos(th)
yp = 5 * np.sin(th)
poly = karta.Polygon(zip(xp, yp), crs=crs)
np.random.seed(42)
x = (np.random.random(1000) - 0.5) * 180.0
y = (np.random.random(1000) - 0.5) * 30.0
mp_noindex = karta.Multipoint(zip(x, y), crs=crs, build_index=False)
mp = karta.Multipoint(zip(x, y), crs=crs, build_index=True)
contained_noindex = mp_noindex.within_polygon(poly)
contained = mp.within_polygon(poly)
self.assertEqual(len(contained), len(contained_noindex))
for i in range(len(contained)):
self.assertTrue(contained[i] in contained_noindex)
return
