def test_tensor2():
B0 = shenfun.FunctionSpace(8, 'C')
T = shenfun.TensorProductSpace(comm, (B0, B0))
x, y = sp.symbols('x,y')
ue = x**2 + y**2
ua = shenfun.Array(T, buffer=ue)
uh = ua.forward()
M = shenfun.VectorSpace(T)
gradu = shenfun.project(grad(uh), M)
def test_tensor2():
B0 = shenfun.FunctionSpace(8, 'C')
T = shenfun.TensorProductSpace(comm, (B0, B0))
x, y = sp.symbols('x,y')
ue = x**2 + y**2
ua = shenfun.Array(T, buffer=ue)
uh = ua.forward()
M = shenfun.VectorSpace(T)
gradu = shenfun.project(grad(uh), M)
V = shenfun.TensorSpace(T)
gradgradu = shenfun.project(grad(grad(uh)), V)
g = gradgradu.backward()
assert np.allclose(g.v[0], 2)
assert np.allclose(g.v[1], 0)
assert np.allclose(g.v[2], 0)
assert np.allclose(g.v[3], 2)
def _setup_function_space(self):
self._nonhomogeneous_bcs = False
self._function_spaces = []
vec_space = []
for i in range(self._dim):
tens_space = []
for j in range(self._dim):
basis = sf.FunctionSpace(self._N[j],
family='legendre',
bc=self._bcs[i][j],
domain=tuple(self._domain[j]))
if basis.has_nonhomogeneous_bcs:
self._nonhomogeneous_bcs = True
tens_space.append(basis)
self._function_spaces.append(tens_space)
vec_space.append(sf.TensorProductSpace(comm, tuple(tens_space)))
self._V = sf.VectorSpace(vec_space)
def get_dimensional_solution(self):
assert hasattr(self, "_solution")
vec_space = list()
for i in range(self._dim):
tens_space = []
for j in range(self._dim):
basis = sf.FunctionSpace(self._N[j], family='legendre',
bc=self._bcs[i][j],
domain=tuple(self._domain[j]))
tens_space.append(basis)
vec_space.append(sf.TensorProductSpace(sf.comm, tuple(tens_space)))
V = sf.VectorSpace(vec_space)
u_hat = sf.Function(V)
for i in range(self._dim):
# u has the same expansions coefficients as u_dimless
u_hat[i] = self._u_ref * self._solution[i]
return u_hat
import numpy as np
import sympy as sp
from mpi4py import MPI
import shenfun
from shenfun import inner, div, grad, curl
N = 8
comm = MPI.COMM_WORLD
V = shenfun.FunctionSpace(N, 'C')
u0 = shenfun.TrialFunction(V)
T = shenfun.TensorProductSpace(comm, (V, V))
u1 = shenfun.TrialFunction(V)
TT = shenfun.VectorSpace(T)
u2 = shenfun.TrialFunction(TT)
@pytest.mark.parametrize('basis', (u0, u1, u2))
def test_mul(basis):
e = shenfun.Expr(basis)
e2 = 2 * e
assert np.allclose(np.array(e2.scales()).astype(np.int), 2)
e2 = e * 2
assert np.allclose(np.array(e2.scales()).astype(np.int), 2.)
if e.expr_rank() == 1:
a = tuple(range(e.dimensions))
e2 = a * e
assert np.allclose(np.array(e2.scales()).astype(np.int)[:, 0], (0, 1))