def kNearestNeighbours(self,
points,
k=10,
use_multi_core=True,
return_points=False):
return covertreec.kNearestNeighbours(self.this, points, k,
use_multi_core, return_points)
def kNearestNeighbours(self,
points,
k=10,
use_multi_core=-1,
return_points=False):
"""main nearest neighbor function."""
ret_val = list(
covertreec.kNearestNeighbours(self.this, points, k, use_multi_core,
return_points))
norm = np.sqrt((points**2).sum(1))[:, np.newaxis]
ret_val[1] = 0.5 * (1.0 / norm + norm - ret_val[1]**2 / norm)
return tuple(ret_val)
def kNearestNeighbours(self,
points,
k=10,
use_multi_core=-1,
return_points=False):
"""main nearest neighbor function."""
modified_points = np.hstack(
(points, np.zeros((points.shape[0], 1), dtype=points.dtype)))
import time
st_t = time.time()
ret_val = list(
covertreec.kNearestNeighbours(self.this, modified_points, k,
use_multi_core, return_points))
st_e = time.time()
norm2 = (points**2).sum(1)[:, np.newaxis]
ret_val[1] = 0.5 * (self.phi2 + norm2 - ret_val[1]**2)
return tuple(ret_val)
def kNearestNeighbours(self, points, k=10):
return covertreec.kNearestNeighbours(self.this, points, k)
def kNearestNeighbours(self, points, k=10):
return covertreec.kNearestNeighbours(self.this, points, k)