def get_coefficients(itp, exo_grid: UnstructuredGrid, endo_grid: CartesianGrid, interp_type: Cubic, x):
from interpolation.splines.prefilter_cubic import prefilter_cubic
grid = endo_grid # one single CartesianGrid
d = len(grid.n)
# this gg could be stored as a member of itp
gg = tuple( [(grid.min[i], grid.max[i], grid.n[i]) for i in range(d)] )
return [prefilter_cubic(gg, x[i]) for i in range(x.shape[0])]
def get_coefficients(itp: object, exo_grid: CartesianGrid, endo_grid: CartesianGrid, interp_type: Cubic, x: object):
from interpolation.splines.prefilter_cubic import prefilter_cubic
grid = exo_grid + endo_grid # one single CartesianGrid
x = x.reshape(tuple(grid.n)+(-1,))
gg = grid.__numba_repr__()
return prefilter_cubic(gg, x)
def get_coefficients(itp: object, exo_grid: UnstructuredGrid,
endo_grid: CartesianGrid, interp_type: Cubic, x: object):
from interpolation.splines.prefilter_cubic import prefilter_cubic
gg = endo_grid.__numba_repr__()
return [
prefilter_cubic(gg, x[i].reshape(tuple(endo_grid.n) + (-1, )))
for i in range(x.shape[0])
]
def get_coefficients(itp, exo_grid: CartesianGrid, endo_grid: CartesianGrid, interp_type: Cubic, x):
from interpolation.splines.prefilter_cubic import prefilter_cubic
grid = cat_grids(exo_grid, endo_grid) # one single CartesianGrid
x = x.reshape(tuple(grid.n)+(-1,))
d = len(grid.n)
# this gg could be stored as a member of itp
gg = tuple( [(grid.min[i], grid.max[i], grid.n[i]) for i in range(d)] )
return prefilter_cubic(gg, x)