How to use the libceed.EVAL_INTERP function in libceed
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CEED / libCEED / tests / python / test-3-ceed-basis.py View on Github 
for d in range(dim):
for i in range(Xdim):
x[d*Xdim + i] = 1 if (i % (2**(dim-d))) // (2**(dim-d-1)) else -1
X = ceed.Vector(Xdim*dim)
X.set_array(x, cmode=libceed.USE_POINTER)
Xq = ceed.Vector(Qdim*dim)
Xq.set_value(0)
U = ceed.Vector(Qdim)
U.set_value(0)
Uq = ceed.Vector(Qdim)
bxl = ceed.BasisTensorH1Lagrange(dim, dim, 2, Q, libceed.GAUSS_LOBATTO)
bul = ceed.BasisTensorH1Lagrange(dim, 1, Q, Q, libceed.GAUSS_LOBATTO)
bxl.apply(1, libceed.EVAL_INTERP, X, Xq)
xq = Xq.get_array_read()
for i in range(Qdim):
xx = np.empty(dim, dtype="float64")
for d in range(dim):
xx[d] = xq[d*Qdim + i]
uq[i] = eval(dim, xx)
Xq.restore_array_read()
Uq.set_array(uq, cmode=libceed.USE_POINTER)
# This operation is the identity because the quadrature is collocated
bul.T.apply(1, libceed.EVAL_INTERP, Uq, U)
bxg = ceed.BasisTensorH1Lagrange(dim, dim, 2, Q, libceed.GAUSS)
bug = ceed.BasisTensorH1Lagrange(dim, 1, Q, Q, libceed.GAUSS)# Bases
bx_hex = ceed.BasisTensorH1Lagrange(dim, dim, p_hex, q_hex, libceed.GAUSS)
bu_hex = ceed.BasisTensorH1Lagrange(dim, 1, p_hex, q_hex, libceed.GAUSS)
# QFunctions
qf_setup_hex = ceed.QFunction(1, qfs.setup_mass_2d,
os.path.join(file_dir, "test-qfunctions.h:setup_mass_2d"))
qf_setup_hex.add_input("weights", 1, libceed.EVAL_WEIGHT)
qf_setup_hex.add_input("dx", dim*dim, libceed.EVAL_GRAD)
qf_setup_hex.add_output("rho", 1, libceed.EVAL_NONE)
qf_mass_hex = ceed.QFunction(1, qfs.apply_mass,
os.path.join(file_dir, "test-qfunctions.h:apply_mass"))
qf_mass_hex.add_input("rho", 1, libceed.EVAL_NONE)
qf_mass_hex.add_input("u", 1, libceed.EVAL_INTERP)
qf_mass_hex.add_output("v", 1, libceed.EVAL_INTERP)
# Operators
op_setup_hex = ceed.Operator(qf_setup_tet)
op_setup_hex.set_field("weights", rxi_hex, bx_hex, libceed.VECTOR_NONE)
op_setup_hex.set_field("dx", rx_hex, bx_hex, libceed.VECTOR_ACTIVE)
op_setup_hex.set_field("rho", rui_hex, libceed.BASIS_COLLOCATED,
qdata_hex)
op_mass_hex = ceed.Operator(qf_mass_hex)
op_mass_hex.set_field("rho", rui_hex, libceed.BASIS_COLLOCATED, qdata_hex)
op_mass_hex.set_field("u", ru_hex, bu_hex, libceed.VECTOR_ACTIVE)
op_mass_hex.set_field("v", ru_hex, bu_hex, libceed.VECTOR_ACTIVE)
## ------------------------- Composite Operators -------------------------interp, grad = bm.buildmats(qref, qweight)
b = ceed.BasisH1(libceed.TRIANGLE, 1, P, Q, interp, grad, qref, qweight)
# Interpolate function to quadrature points
for i in range(P):
in_array[i] = feval(xr[0*P+i], xr[1*P+i])
in_vec = ceed.Vector(P)
in_vec.set_array(in_array, cmode=libceed.USE_POINTER)
out_vec = ceed.Vector(Q)
out_vec.set_value(0)
weights_vec = ceed.Vector(Q)
weights_vec.set_value(0)
b.apply(1, libceed.EVAL_INTERP, in_vec, out_vec)
b.apply(1, libceed.EVAL_WEIGHT, libceed.VECTOR_NONE, weights_vec)
# Check values at quadrature points
out_array = out_vec.get_array_read()
weights_array = weights_vec.get_array_read()
sum = 0
for i in range(Q):
sum += out_array[i]*weights_array[i]
if math.fabs(sum - 17./24.) > 1E-10:
print("%f != %f"%(sum, 17./24.))
out_vec.restore_array_read()
weights_vec.restore_array_read()for i in range(Qdim):
xx = np.empty(dim, dtype="float64")
for d in range(dim):
xx[d] = xq[d*Qdim + i]
uq[i] = eval(dim, xx)
Xq.restore_array_read()
Uq.set_array(uq, cmode=libceed.USE_POINTER)
# This operation is the identity because the quadrature is collocated
bul.T.apply(1, libceed.EVAL_INTERP, Uq, U)
bxg = ceed.BasisTensorH1Lagrange(dim, dim, 2, Q, libceed.GAUSS)
bug = ceed.BasisTensorH1Lagrange(dim, 1, Q, Q, libceed.GAUSS)
bxg.apply(1, libceed.EVAL_INTERP, X, Xq)
bug.apply(1, libceed.EVAL_INTERP, U, Uq)
xq = Xq.get_array_read()
u = Uq.get_array_read()
for i in range(Qdim):
xx = np.empty(dim, dtype="float64")
for d in range(dim):
xx[d] = xq[d*Qdim + i]
fx = eval(dim, xx)
assert math.fabs(u[i] - fx) < 1E-4
Xq.restore_array_read()
Uq.restore_array_read()def test_412(ceed_resource):
ceed = libceed.Ceed(ceed_resource)
size = 3
qf = ceed.IdentityQFunction(size, libceed.EVAL_INTERP, libceed.EVAL_INTERP)
q = 8
u_array = np.zeros(q*size, dtype="float64")
for i in range(q*size):
u_array[i] = i*i
u = ceed.Vector(q*size)
u.set_array(u_array, cmode=libceed.USE_POINTER)
v = ceed.Vector(q*size)
v.set_value(0)
inputs = [ u ]
outputs = [ v ]
qf.apply(q, inputs, outputs)qweight = np.empty(Q, dtype="float64")
interp, grad = bm.buildmats(qref, qweight)
b = ceed.BasisH1(libceed.TRIANGLE, 1, P, Q, interp, grad, qref, qweight)
# Interpolate function to quadrature points
for i in range(P):
in_array[i] = feval(xr[0*P+i], xr[1*P+i])
in_vec = ceed.Vector(P)
in_vec.set_array(in_array, cmode=libceed.USE_POINTER)
out_vec = ceed.Vector(Q)
out_vec.set_value(0)
b.apply(1, libceed.EVAL_INTERP, in_vec, out_vec)
# Check values at quadrature points
out_array = out_vec.get_array_read()
for i in range(Q):
value = feval(xq[0*Q+i], xq[1*Q+i])
if math.fabs(out_array[i] - value) > 1E-10:
# LCOV_EXCL_START
printf("[%d] %f != %f"%(i, out[i], value))
# LCOV_EXCL_STOP
out_vec.restore_array_read()bu = ceed.BasisTensorH1Lagrange(1, 1, p, q, libceed.GAUSS)
# QFunctions
file_dir = os.path.dirname(os.path.abspath(__file__))
qfs = load_qfs_so()
qf_setup = ceed.QFunction(1, qfs.setup_mass,
os.path.join(file_dir, "test-qfunctions.h:setup_mass"))
qf_setup.add_input("weights", 1, libceed.EVAL_WEIGHT)
qf_setup.add_input("dx", 1, libceed.EVAL_GRAD)
qf_setup.add_output("rho", 1, libceed.EVAL_NONE)
qf_mass = ceed.QFunction(1, qfs.apply_mass,
os.path.join(file_dir, "test-qfunctions.h:apply_mass"))
qf_mass.add_input("rho", 1, libceed.EVAL_NONE)
qf_mass.add_input("u", 1, libceed.EVAL_INTERP)
qf_mass.add_output("v", 1, libceed.EVAL_INTERP)
# Operators
op_setup = ceed.Operator(qf_setup)
op_setup.set_field("weights", rxi, bx, libceed.VECTOR_NONE)
op_setup.set_field("dx", rx, bx, libceed.VECTOR_ACTIVE)
op_setup.set_field("rho", rui, libceed.BASIS_COLLOCATED,
libceed.VECTOR_ACTIVE)
op_mass = ceed.Operator(qf_mass)
op_mass.set_field("rho", rui, libceed.BASIS_COLLOCATED, qdata)
op_mass.set_field("u", ru, bu, libceed.VECTOR_ACTIVE)
op_mass.set_field("v", ru, bu, libceed.VECTOR_ACTIVE)
# Setup
op_setup.apply(x, qdata)def test_400(ceed_resource):
ceed = libceed.Ceed(ceed_resource)
file_dir = os.path.dirname(os.path.abspath(__file__))
qfs = load_qfs_so()
qf_setup = ceed.QFunction(1, qfs.setup_mass,
os.path.join(file_dir, "test-qfunctions.h:setup_mass"))
qf_setup.add_input("w", 1, libceed.EVAL_WEIGHT)
qf_setup.add_input("dx", 1, libceed.EVAL_GRAD)
qf_setup.add_output("qdata", 1, libceed.EVAL_NONE)
qf_mass = ceed.QFunction(1, qfs.apply_mass,
os.path.join(file_dir, "test-qfunctions.h:apply_mass"))
qf_mass.add_input("qdata", 1, libceed.EVAL_NONE)
qf_mass.add_input("u", 1, libceed.EVAL_INTERP)
qf_mass.add_output("v", 1, libceed.EVAL_INTERP)
q = 8
w_array = np.zeros(q, dtype="float64")
u_array = np.zeros(q, dtype="float64")
v_true = np.zeros(q, dtype="float64")
for i in range(q):
x = 2.*i/(q-1) - 1
w_array[i] = 1 - x*x
u_array[i] = 2 + 3*x + 5*x*x
v_true[i] = w_array[i] * u_array[i]
dx = ceed.Vector(q)
dx.set_value(1)
w = ceed.Vector(q)libceed
libCEED: Code for Efficient Extensible Discretization
Package Health Score
61 / 100Popular libceed functions
- libceed.Basis.get_num_nodes
- libceed.Basis.get_num_quadrature_points
- libceed.Basis.qr_factorization
- libceed.Basis.simultaneous_diagonalization
- libceed.Basis.symmetric_schur_decomposition
- libceed.BASIS_COLLOCATED
- libceed.Ceed
- libceed.CEED_MEM_DEVICE
- libceed.CEED_MEM_HOST
- libceed.CEED_USE_POINTER
- libceed.EVAL_GRAD
- libceed.EVAL_INTERP
- libceed.EVAL_NONE
- libceed.EVAL_WEIGHT
- libceed.GAUSS
- libceed.MEM_HOST
- libceed.TRIANGLE
- libceed.USE_POINTER
- libceed.VECTOR_NONE