def test_eval_splines():
from interpolation.splines.eval_splines import eval_linear, eval_cubic
from interpolation.multilinear.mlinterp import mlinterp
import numpy as np
N = 1000
K = 100
d = 2
grid = ((0.0, 1.0, K), ) * d
grid_nu = ((0.0, 1.0, K), np.linspace(0, 1, K))
n_x = 6
V = np.random.random((K, K))
VV = np.random.random((K, K, n_x))
C = np.random.random((K + 2, K + 2))
CC = np.random.random((K + 2, K + 2, n_x))
points = np.random.random((N, 2))
out = np.random.random((N))
Cout = np.random.random((N, n_x))
eval_linear(grid, V, points, out)
# eval_cubic(grid, C, points[0,:], out[0,0])
eval_linear(grid, VV, points, Cout)
eval_linear(grid, VV, points[0, :], Cout[0, :])
mlinterp(grid, V, points)
eval_linear(grid, V, points)
eval_linear(grid, V, points)
eval_linear(grid, V, points, out)
print("OK 2")
eval_linear(grid, V, points[0, :])
res_0 = eval_linear(grid, VV, points)
res_1 = eval_linear(grid, VV, points[0, :])
#nonuniform grid:
res_0_bis = eval_linear(grid_nu, VV, points)
res_1_bis = eval_linear(grid_nu, VV, points[0, :])
assert abs(res_0 - res_0_bis).max() < 1e-10
assert abs(res_1 - res_1_bis).max() < 1e-10
print("OK 3")
eval_cubic(grid, C, points, out)
# eval_cubic(grid, C, points[0,:], out[0,0])
eval_cubic(grid, CC, points, Cout)
eval_cubic(grid, CC, points[0, :], Cout[0, :])
print("OK 4")
eval_cubic(grid, C, points)
eval_cubic(grid, C, points[0, :])
eval_cubic(grid, CC, points)
eval_cubic(grid, CC, points[0, :])
print("OK 5")
def test_mlinterp():
# simple multilinear interpolation api
import numpy as np
from interpolation import mlinterp
# from interpolation.multilinear.mlinterp import mlininterp, mlininterp_vec
x1 = np.linspace(0, 1, 10)
x2 = np.linspace(0, 1, 20)
y = np.random.random((10, 20))
z1 = np.linspace(0, 1, 30)
z2 = np.linspace(0, 1, 30)
pp = np.random.random((2000, 2))
res0 = mlinterp((x1, x2), y, pp)
res0 = mlinterp((x1, x2), y, (0.1, 0.2))