def eval_s(itp: object, exo_grid: EmptyGrid, endo_grid: CartesianGrid,
interp_type: Cubic, s: object):
from interpolation.splines import eval_cubic
assert (s.ndim == 2)
coeffs = itp.coefficients
gg = endo_grid.__numba_repr__()
return eval_cubic(gg, coeffs, s)
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 eval_is(itp: object, exo_grid: UnstructuredGrid, endo_grid: CartesianGrid, interp_type: Linear, i: object, s: object):
from interpolation.splines import eval_linear
assert(s.ndim==2)
coeffs = itp.coefficients[i]
gg = endo_grid.__numba_repr__()
return eval_linear(gg, coeffs, s)
def get_coefficients(
itp: object,
exo_grid: EmptyGrid,
endo_grid: CartesianGrid,
interp_type: Cubic,
x: object,
):
from interpolation.splines.prefilter_cubic import prefilter_cubic
grid = endo_grid # one single CartesianGrid
gg = endo_grid.__numba_repr__()
return prefilter_cubic(gg, x[0].reshape(tuple(grid.n) + (-1, )))
def eval_s(
itp: object,
exo_grid: EmptyGrid,
endo_grid: CartesianGrid,
interp_type: Linear,
s: object,
):
from interpolation.splines import eval_linear
assert s.ndim == 2
coeffs = itp.coefficients
gg = endo_grid.__numba_repr__()
return eval_linear(gg, coeffs, s)