def interpolate_prid_point_index(self, point):
tmat = num.array(self._GridVectors).T
float_coords = tmat <<num.solve>> (point - self._Origin)
rounded_down_int_coords = [int(math.floor(c)) for c in float_coords]
neighbors = [rounded_down_int_coords]
for d in range(len(self._GridVectors)):
new_neighbors = []
for item in neighbors:
new_neighbors.append(item)
new_neighbor = item[:]
new_neighbor[d] += 1
new_neighbors.append(new_neighbor)
neighbors = new_neighbors
weights = []
for neighbor in neighbors:
weight = product([1-abs(a-b) for a,b in zip(float_coords, neighbor)])
if abs(weight) >= 1e-5:
weights.append((weight, tuple(neighbor)))
return weights
def __call__(self, x):
import pylinear.array as num
return num.array([[func(x) for func in flist ] for flist in self.FunctionList])
def find_closest_grid_point_index(self, point):
tmat = num.array(self._GridVectors).T
float_coords = tmat <<num.solve>> (point - self._Origin)
return tuple([int(round(c)) for c in float_coords])