def test_reference_hexahedron_quadrature(self, verbose=True):
"""
Args:
verbose:
"""
v0 = np.array([0.0, 0.0, 0.0], dtype=real)
v1 = np.array([1.0, 0.0, 0.0], dtype=real)
v2 = np.array([1.0, 1.0, 0.0], dtype=real)
v3 = np.array([0.0, 1.0, 0.0], dtype=real)
v4 = np.array([0.0, 0.0, 1.0], dtype=real)
v5 = np.array([1.0, 0.0, 1.0], dtype=real)
v6 = np.array([1.0, 1.0, 1.0], dtype=real)
v7 = np.array([0.0, 1.0, 1.0], dtype=real)
vertices = np.array([v0, v1, v2, v3, v4, v5, v6, v7], dtype=real).T
shape = Shape(ShapeType.HEXAHEDRON, vertices)
for _io in range(1, 9):
# --- DECLARE FUNCTION
f = lambda x: np.exp(x[0]) * np.sin(x[0] * x[1] / (x[2] + 0.003)
) + x[1] * x[2] + 3.0
f_scipy = lambda x, y, z: np.exp(x) * np.sin(x * y / (z + 0.003)
) + y * z + 3.0
# --- GET QUADPY ESTIMATION
scheme = quadpy.c3.get_good_scheme(_io)
val = scheme.integrate(
f, [[[v0, v4], [v3, v7]], [[v1, v5], [v2, v6]]])
# --- GET H20 ESTIMATION
val_num = 0.0
shape_quadrature_points = shape.get_quadrature_points(_io)
shape_quadrature_weights = shape.get_quadrature_weights(_io)
shape_quadrature_size = shape.get_quadrature_size(_io)
for _qc in range(shape_quadrature_size):
x_qc = shape_quadrature_points[:, _qc]
w_qc = shape_quadrature_weights[_qc]
val_num += w_qc * f(x_qc)
# --- GET SCIPY ESTIMATION
# val_scp = integrate.tplquad(
# f_scipy, 0.0, 1.0, lambda x: 0.0, lambda x: 1.0, lambda x, y: 0.0, lambda x, y: 1.0
# )
if verbose:
print("-- integration order : {}".format(_io))
print("val_h2O : {}".format(val_num))
print("val_qud : {}".format(val))
# print("val_scp : {}".format(val_scp))
x_c = shape.get_centroid()
fig = plt.figure()
ax = fig.add_subplot(111, projection="3d")
ax.scatter(x_c[0], x_c[1], x_c[2], c="b", marker="o")
for i in range(vertices.shape[1]):
ax.scatter(vertices[0, i],
vertices[1, i],
vertices[2, i],
c="b",
marker="o")
for _qc in range(shape_quadrature_size):
_x_qc = shape_quadrature_points[:, _qc]
ax.scatter(_x_qc[0], _x_qc[1], _x_qc[2], c="g")
plt.show()
def get_element_projection_vector(cell: Shape, faces: List[Shape], function: List[Callable]):
_d = euclidean_dimension
_dx = field.field_dimension
_cl = cell_basis_l.dimension
_fk = face_basis_k.dimension
_nf = len(faces)
_es = _dx * (_cl + _nf * _fk)
#
x_c = cell.centroid
h_c = cell.diameter
_io = finite_element.construction_integration_order
cell_quadrature_points = cell.get_quadrature_points(_io)
cell_quadrature_weights = cell.get_quadrature_weights(_io)
cell_quadrature_size = cell.get_quadrature_size(_io)
matrix = np.zeros((_es, _es), dtype=real)
vector = np.zeros((_es,), dtype=real)
for _dir in range(_dx):
m_mas = np.zeros((_cl, _cl), dtype=real)
vc = np.zeros((_cl,), dtype=real)
for qc in range(cell_quadrature_size):
x_q_c = cell_quadrature_points[:, qc]
w_q_c = cell_quadrature_weights[qc]
phi_l = cell_basis_l.evaluate_function(x_q_c, x_c, h_c)
m_mas += w_q_c * np.tensordot(phi_l, phi_l, axes=0)
vc += w_q_c * phi_l * function[_dir](x_q_c)
_i = _cl * _dir
_j = _cl * (_dir + 1)
matrix[_i:_j, _i:_j] += m_mas
vector[_i:_j] += vc
for _f, face in enumerate(faces):
face_rotation_matrix = get_rotation_matrix(face.type, face.vertices)
x_f = face.centroid
h_f = face.diameter
# --- PROJECT ON HYPERPLANE
s_f = (face_rotation_matrix @ x_f)[:-1]
_io = finite_element.construction_integration_order
face_quadrature_points = face.get_quadrature_points(_io)
face_quadrature_weights = face.get_quadrature_weights(_io)
face_quadrature_size = face.get_quadrature_size(_io)
for _dir in range(_dx):
m_mas_f = np.zeros((_fk, _fk), dtype=real)
vf = np.zeros((_fk,), dtype=real)
for qf in range(face_quadrature_size):
x_q_f = face_quadrature_points[:, qf]
w_q_f = face_quadrature_weights[qf]
# s_f = (face_rotation_matrix @ x_f)[:-1]
s_q_f = (face_rotation_matrix @ x_q_f)[:-1]
psi_k = face_basis_k.evaluate_function(s_q_f, s_f, h_f)
m_mas_f += w_q_f * np.tensordot(psi_k, psi_k, axes=0)
vf += w_q_f * psi_k * function[_dir](x_q_f)
_i = _cl * _dx + _f * _fk * _dx + _dir * _fk
_j = _cl * _dx + _f * _fk * _dx + (_dir + 1) * _fk
matrix[_i:_j, _i:_j] += m_mas_f
vector[_i:_j] += vf
projection_vector = np.linalg.solve(matrix, vector)
return projection_vector
def test_quadrangle_quadrature_cell(self, verbose=True):
"""
Args:
verbose:
"""
v0 = np.array([0.0, 0.0], dtype=real)
v1 = np.array([1.0, 0.0], dtype=real)
v2 = np.array([1.0, 1.0], dtype=real)
v3 = np.array([0.0, 1.0], dtype=real)
quadrangle_vertices = np.array([v0, v1, v2, v3], dtype=real).T
cell_triangle = Shape(ShapeType.QUADRANGLE, quadrangle_vertices)
for _io in range(1, 9):
# --- DECLARE FUNCTION
f = lambda x: np.exp(x[0]) * np.sin(x[0] * x[1]) + x[1] + 3.
f_scipy = lambda x, y: np.exp(x) * np.sin(x * y) + y + 3.
# --- GET QUADPY ESTIMATION
scheme = quadpy.c2.get_good_scheme(_io)
val = scheme.integrate(
f,
[[v0, v1], [v3, v2]],
)
# --- GET H20 ESTIMATION
val_num = 0.0
triangle_quadrature_points = cell_triangle.get_quadrature_points(
_io)
triangle_quadrature_weights = cell_triangle.get_quadrature_weights(
_io)
triangle_quadrature_size = cell_triangle.get_quadrature_size(_io)
for _qc in range(triangle_quadrature_size):
x_qc = triangle_quadrature_points[:, _qc]
w_qc = triangle_quadrature_weights[_qc]
val_num += w_qc * f(x_qc)
# --- GET SCIPY ESTIMATION
val_scp = integrate.dblquad(f_scipy, 0.0, 1.0, lambda x: 0.0,
lambda x: 1.0)
if verbose:
print("-- integration order : {}".format(_io))
print("val_h2O : {}".format(val_num))
print("val_qud : {}".format(val))
print("val_scp : {}".format(val_scp))
x_c = cell_triangle.get_centroid()
plt.scatter(x_c[0], x_c[1], c="b")
for i in range(4):
plt.scatter(quadrangle_vertices[0, i],
quadrangle_vertices[1, i],
c="b")
for _qc in range(triangle_quadrature_size):
_x_qc = triangle_quadrature_points[:, _qc]
plt.scatter(_x_qc[0], _x_qc[1], c="g")
plt.show()
def test_reference_triangle_quadrature(self, verbose=True):
"""
Args:
verbose:
"""
# v0 = np.array([0.00000000000000E+00, 0.28725932709342E-01], dtype=real)
# v1 = np.array([0.00000000000000E+00, 0.30000000000000E-01], dtype=real)
# v2 = np.array([0.20769230769231E-03, 0.30000000000000E-01], dtype=real)
v0 = np.array([+.30000000000000E-02, +.00000000000000E+00], dtype=real)
v1 = np.array([+.30038156151383E-02, +.21394584067090E-03], dtype=real)
v2 = np.array([+.28882842453253E-02, +.21394584067090E-03], dtype=real)
vertices = np.array([v0, v1, v2], dtype=real).T
shape = Shape(ShapeType.TRIANGLE, vertices)
for _io in range(1, 9):
# --- DECLARE FUNCTION
f = lambda x: np.exp(x[0]) * np.sin(x[0] * x[1]) + x[1] + 3.
# --- GET QUADPY ESTIMATION
scheme = quadpy.t2.get_good_scheme(_io)
val = scheme.integrate(
f,
[v0, v1, v2],
)
# --- GET H20 ESTIMATION
val_num = 0.0
shape_quadrature_points = shape.get_quadrature_points(_io)
shape_quadrature_weights = shape.get_quadrature_weights(_io)
shape_quadrature_size = shape.get_quadrature_size(_io)
print("-- QUAD_WGTS")
print(shape_quadrature_weights)
for _qc in range(shape_quadrature_size):
x_qc = shape_quadrature_points[:, _qc]
w_qc = shape_quadrature_weights[_qc]
val_num += w_qc * f(x_qc)
# --- GET SCIPY ESTIMATION
if verbose:
print("-- integration order : {}".format(_io))
print("val_h2O : {}".format(val_num))
print("val_qud : {}".format(val))
x_c = shape.get_centroid()
plt.scatter(v0[0], v0[1], c="b")
plt.scatter(v1[0], v1[1], c="b")
plt.scatter(v2[0], v2[1], c="b")
plt.scatter(x_c[0], x_c[1], c="b")
for _qc in range(shape_quadrature_size):
_x_qc = shape_quadrature_points[:, _qc]
plt.scatter(_x_qc[0], _x_qc[1], c="g")
plt.show()
def test_reference_triangle_quadrature(self, verbose=True):
"""
Args:
verbose:
"""
v0 = np.array([0.0, 0.0], dtype=real)
v1 = np.array([1.0, 0.0], dtype=real)
v2 = np.array([0.0, 1.0], dtype=real)
vertices = np.array([v0, v1, v2], dtype=real).T
shape = Shape(ShapeType.TRIANGLE, vertices)
for _io in range(1, 9):
# --- DECLARE FUNCTION
f = lambda x: np.exp(x[0]) * np.sin(x[0] * x[1]) + x[1] + 3.
f_scipy = lambda x, y: np.exp(x) * np.sin(x * y) + y + 3.
# --- GET QUADPY ESTIMATION
scheme = quadpy.t2.get_good_scheme(_io)
val = scheme.integrate(
f,
[v0, v1, v2],
)
# --- GET H20 ESTIMATION
val_num = 0.0
shape_quadrature_points = shape.get_quadrature_points(_io)
shape_quadrature_weights = shape.get_quadrature_weights(_io)
shape_quadrature_size = shape.get_quadrature_size(_io)
for _qc in range(shape_quadrature_size):
x_qc = shape_quadrature_points[:, _qc]
w_qc = shape_quadrature_weights[_qc]
val_num += w_qc * f(x_qc)
# --- GET SCIPY ESTIMATION
val_scp = integrate.dblquad(f_scipy, 0.0, 1.0, lambda x: 0.0,
lambda x: 1.0 - x)
if verbose:
print("-- integration order : {}".format(_io))
print("val_h2O : {}".format(val_num))
print("val_qud : {}".format(val))
print("val_scp : {}".format(val_scp))
x_c = shape.get_centroid()
plt.scatter(v0[0], v0[1], c="b")
plt.scatter(v1[0], v1[1], c="b")
plt.scatter(v2[0], v2[1], c="b")
plt.scatter(x_c[0], x_c[1], c="b")
for _qc in range(shape_quadrature_size):
_x_qc = shape_quadrature_points[:, _qc]
plt.scatter(_x_qc[0], _x_qc[1], c="g")
plt.show()
def test_reference_segment_quadrature_face(self, verbose=True):
"""
Args:
verbose:
"""
v0 = np.array([0.0, 0.0], dtype=real)
v1 = np.array([1.0, 0.7], dtype=real)
vertices = np.array([v0, v1], dtype=real).T
shape = Shape(ShapeType.SEGMENT, vertices)
for _io in range(1, 9):
# --- DECLARE FUNCTION
f = lambda x: np.exp(x[0]) * np.sin(x[0]) + 3.0
f_quadpy = lambda x: np.exp(np.array(x)) * np.sin(np.array(x)) + 3.0
f_scipy = lambda x: np.exp(x) * np.sin(x) + 3.0
# --- GET H20 ESTIMATION
val_num = 0.0
shape_quadrature_points = shape.get_quadrature_points(_io)
shape_quadrature_weights = shape.get_quadrature_weights(_io)
shape_quadrature_size = shape.get_quadrature_size(_io)
for _qc in range(shape_quadrature_size):
x_qc = shape_quadrature_points[:, _qc]
w_qc = shape_quadrature_weights[_qc]
s_qc = (shape.get_rotation_matrix() @ x_qc)[:-1]
val_num += w_qc * f(s_qc)
vertices_p = (shape.get_rotation_matrix() @ vertices)[:-1]
# --- GET QUADPY ESTIMATION
scheme = quadpy.c1.gauss_legendre(_io)
val = scheme.integrate(f_quadpy, [vertices_p[0, 0], vertices_p[0, 1]])
# --- GET SCIPY ESTIMATION
val_scp = integrate.quad(f_scipy, vertices_p[0, 0], vertices_p[0, 1])
if verbose:
print("-- integration order : {}".format(_io))
print("val_h2O : {}".format(val_num))
print("val_qud : {}".format(val))
print("val_scp : {}".format(val_scp))
x_c = shape.get_centroid()
plt.scatter(x_c[0], x_c[1], c="b")
for i in range(2):
plt.scatter(vertices[0, i], vertices[1, i], c="b")
for _qc in range(shape_quadrature_size):
_x_qc = shape_quadrature_points[:, _qc]
plt.scatter(_x_qc[0], _x_qc[1], c="g")
plt.show()
def get_gradient_projection_vector(cell: Shape, function: Callable):
_d = euclidean_dimension
_dx = field.field_dimension
_ck = cell_basis_k.dimension
#
x_c = cell.centroid
h_c = cell.diameter
_io = finite_element.construction_integration_order
cell_quadrature_points = cell.get_quadrature_points(_io)
cell_quadrature_weights = cell.get_quadrature_weights(_io)
cell_quadrature_size = cell.get_quadrature_size(_io)
matrix = np.zeros((_ck, _ck), dtype=real)
vector = np.zeros((_ck,), dtype=real)
for qc in range(cell_quadrature_size):
x_q_c = cell_quadrature_points[:, qc]
w_q_c = cell_quadrature_weights[qc]
phi_k = cell_basis_k.evaluate_function(x_q_c, x_c, h_c)
matrix += w_q_c * np.tensordot(phi_k, phi_k, axes=0)
vector += w_q_c * phi_k * function(x_q_c)
projection_vector = np.linalg.solve(matrix, vector)
return projection_vector
def test_reference_triangle_face(self, verbose=True):
"""
Args:
verbose:
Returns:
"""
euclidean_dimension = 2
polynomial_orders = [1, 2, 3]
element_types = [ElementType.HDG_LOW, ElementType.HDG_EQUAL, ElementType.HDG_HIGH]
for polynomial_order in polynomial_orders:
for element_type in element_types:
# --- DEFINE POLYNOMIAL ORDER AND INTEGRATION ORDER
finite_element = FiniteElement(
element_type=element_type,
polynomial_order=polynomial_order,
euclidean_dimension=euclidean_dimension,
)
# --- DEFINE POLYNOMIAL BASIS
cell_basis_k = finite_element.cell_basis_k
cell_basis_l = finite_element.cell_basis_l
# --- DEFINE RANDOM POLYNOMIAL COEFFICIENTS
range_min = -3.0
range_max = +3.0
coefficients_k = np.array([uniform(range_min, range_max) for _i in range(cell_basis_k.dimension)])
coefficients_l = np.array([uniform(range_min, range_max) for _i in range(cell_basis_l.dimension)])
if verbose:
print("COEFS_K : \n{}".format(coefficients_k))
print("COEFS_L : \n{}".format(coefficients_l))
# --- DEFINE MONOMIAL VALUES COMPUTATION
def test_function(
polynomial_ord: int, point: ndarray, centroid: ndarray, diameter: float, coefficients: ndarray
) -> float:
basis = Monomial(polynomial_ord, euclidean_dimension)
value = 0.0
for _i, _exponent in enumerate(basis.exponents):
prod = 1.0
for _x_dir in range(basis.exponents.shape[1]):
prod *= ((point[_x_dir] - centroid[_x_dir]) / diameter) ** _exponent[_x_dir]
prod *= coefficients[_i]
value += prod
return value
def test_function_derivative(
polynomial_ord: int,
point: ndarray,
centroid: ndarray,
diameter: float,
direction: int,
coefficients: ndarray,
) -> float:
basis = Monomial(polynomial_ord, euclidean_dimension)
value = 0.0
for _i, _exponent in enumerate(basis.exponents):
prod = 1.0
for _x_dir in range(basis.exponents.shape[1]):
if _x_dir == direction:
_pt0 = point[_x_dir] - centroid[_x_dir]
_pt1 = _pt0 / diameter
if _exponent[_x_dir] == 0:
_exp = _exponent[_x_dir]
else:
_exp = _exponent[_x_dir] - 1
_pt2 = _pt1 ** _exp
# prod *= (_exponent[_x_dir] / diameter) * (
# ((point[_x_dir] - centroid[_x_dir]) / diameter) ** (_exponent[_x_dir] - 1)
# )
prod *= (_exponent[_x_dir] / diameter) * _pt2
else:
prod *= ((point[_x_dir] - centroid[_x_dir]) / diameter) ** _exponent[_x_dir]
prod *= coefficients[_i]
value += prod
return value
# --- DEFINE TRIANGLE COORDINATES
v0 = np.array([0.0, 0.0], dtype=real)
v1 = np.array([1.0, 0.0], dtype=real)
v2 = np.array([0.0, 1.0], dtype=real)
triangle_vertices = np.array([v0, v1, v2], dtype=real).T
# --- BUILD CELL
cell_triangle = Shape(ShapeType.TRIANGLE, triangle_vertices)
x_c = cell_triangle.get_centroid()
h_c = cell_triangle.get_diameter()
_io = finite_element.construction_integration_order
cell_quadrature_points = cell_triangle.get_quadrature_points(_io)
cell_quadrature_weights = cell_triangle.get_quadrature_weights(_io)
cell_quadrature_size = cell_triangle.get_quadrature_size(_io)
# --- CHECK INTEGRATION IN CELL
bases = [cell_basis_k, cell_basis_l]
# orders = [face_polynomial_order, cell_polynomial_order]
coefs = [coefficients_k, coefficients_l]
# scheme = quadpy.t2.get_good_scheme(2 * finite_element.construction_integration_order)
scheme = quadpy.t2.get_good_scheme(finite_element.construction_integration_order)
for basis_0, coef_0 in zip(bases, coefs):
order_0 = basis_0.polynomial_order
for basis_1, coef_1 in zip(bases, coefs):
order_1 = basis_1.polynomial_order
for _i in range(euclidean_dimension):
for _j in range(euclidean_dimension):
mass_mat = np.zeros((basis_0.dimension, basis_1.dimension), dtype=real)
stif_mat = np.zeros((basis_0.dimension, basis_1.dimension), dtype=real)
advc_mat = np.zeros((basis_0.dimension, basis_1.dimension), dtype=real)
for _qc in range(cell_quadrature_size):
_x_qc = cell_quadrature_points[:, _qc]
_w_qc = cell_quadrature_weights[_qc]
phi_0 = basis_0.evaluate_function(_x_qc, x_c, h_c)
phi_1 = basis_1.evaluate_function(_x_qc, x_c, h_c)
d_phi_0_i = basis_0.evaluate_derivative(_x_qc, x_c, h_c, _i)
d_phi_1_j = basis_1.evaluate_derivative(_x_qc, x_c, h_c, _j)
mass_mat += _w_qc * np.tensordot(phi_0, phi_1, axes=0)
stif_mat += _w_qc * np.tensordot(d_phi_0_i, d_phi_1_j, axes=0)
advc_mat += _w_qc * np.tensordot(phi_0, d_phi_1_j, axes=0)
mass_integral = coef_0 @ mass_mat @ coef_1
stif_integral = coef_0 @ stif_mat @ coef_1
advc_integral = coef_0 @ advc_mat @ coef_1
f_mass_check = lambda x: test_function(order_0, x, x_c, h_c, coef_0) * test_function(
order_1, x, x_c, h_c, coef_1
)
f_stif_check = lambda x: test_function_derivative(
order_0, x, x_c, h_c, _i, coef_0
) * test_function_derivative(order_1, x, x_c, h_c, _j, coef_1)
f_advc_check = lambda x: test_function(
order_0, x, x_c, h_c, coef_0
) * test_function_derivative(order_1, x, x_c, h_c, _j, coef_1)
mass_integral_check = scheme.integrate(f_mass_check, triangle_vertices.T)
stif_integral_check = scheme.integrate(f_stif_check, triangle_vertices.T)
advc_integral_check = scheme.integrate(f_advc_check, triangle_vertices.T)
rtol = 1.0e-15
atol = 1.0e-15
if verbose:
print(
"MASS INTEGRAL CHECK | ORDER : {} | ELEM : {}".format(
polynomial_order, element_type
)
)
print("- QUADPY : {}".format(mass_integral_check))
print("- H2O : {}".format(mass_integral))
print(
"STIFFNESS INTEGRAL CHECK | ORDER : {} | ELEM : {}".format(
polynomial_order, element_type
)
)
print("- QUADPY : {}".format(stif_integral_check))
print("- H2O : {}".format(stif_integral))
print(
"ADVECTION INTEGRAL CHECK | ORDER : {} | ELEM : {}".format(
polynomial_order, element_type
)
)
print("- QUADPY : {}".format(advc_integral_check))
print("- H2O : {}".format(advc_integral))
np.testing.assert_allclose(mass_integral_check, mass_integral, rtol=rtol, atol=atol)
np.testing.assert_allclose(stif_integral_check, stif_integral, rtol=rtol, atol=atol)
np.testing.assert_allclose(advc_integral_check, advc_integral, rtol=rtol, atol=atol)
def get_regular_gradient_component_matrix(field: Field,
finite_element: FiniteElement,
cell: Shape, faces: List[Shape],
_i: int, _j: int) -> ndarray:
_d = field.euclidean_dimension
_dx = field.field_dimension
_cl = finite_element.cell_basis_l.dimension
_ck = finite_element.cell_basis_k.dimension
_fk = finite_element.face_basis_k.dimension
_nf = len(faces)
_es = _dx * (_cl + _nf * _fk)
_io = finite_element.construction_integration_order
# --- CELL ENVIRONMENT
_c_is = cell.get_quadrature_size(_io)
cell_quadrature_points = cell.get_quadrature_points(_io)
cell_quadrature_weights = cell.get_quadrature_weights(_io)
x_c = cell.get_centroid()
h_c = cell.get_diameter()
local_grad_matric = np.zeros((_ck, _es), dtype=real)
m_mas = np.zeros((_ck, _ck), dtype=real)
m_adv_j = np.zeros((_ck, _cl), dtype=real)
for qc in range(_c_is):
x_q_c = cell_quadrature_points[:, qc]
w_q_c = cell_quadrature_weights[qc]
phi_k = finite_element.cell_basis_k.evaluate_function(x_q_c, x_c, h_c)
d_phi_l_j = finite_element.cell_basis_l.evaluate_derivative(
x_q_c, x_c, h_c, _j)
m_adv_j += w_q_c * np.tensordot(phi_k, d_phi_l_j, axes=0)
m_mas += w_q_c * np.tensordot(phi_k, phi_k, axes=0)
m_mas_inv = np.linalg.inv(m_mas)
_c0 = _i * _cl
_c1 = (_i + 1) * _cl
local_grad_matric[:, _c0:_c1] += m_adv_j
for _f, face in enumerate(faces):
# --- FACE ENVIRONMENT
_f_is = face.get_quadrature_size(_io)
face_quadrature_points = face.get_quadrature_points(_io)
face_quadrature_weights = face.get_quadrature_weights(_io)
h_f = face.get_diameter()
x_f = face.get_centroid()
# face_rotation_matrix = get_rotation_matrix(face.type, face.vertices)
face_rotation_matrix = face.get_rotation_matrix()
dist_in_face = (face_rotation_matrix @ (x_f - x_c))[-1]
if dist_in_face > 0:
normal_vector_component_j = face_rotation_matrix[-1, _j]
else:
normal_vector_component_j = -face_rotation_matrix[-1, _j]
m_mas_f = np.zeros((_ck, _cl), dtype=real)
m_hyb_f = np.zeros((_ck, _fk), dtype=real)
for qf in range(_f_is):
x_q_f = face_quadrature_points[:, qf]
# x_q_f_prime = face.mapping_matrix @ face.quadrature_points[:, qf]
w_q_f = face_quadrature_weights[qf]
s_f = (face_rotation_matrix @ x_f)[:-1]
s_q_f = (face_rotation_matrix @ x_q_f)[:-1]
phi_k = finite_element.cell_basis_k.evaluate_function(
x_q_f, x_c, h_c)
phi_l = finite_element.cell_basis_l.evaluate_function(
x_q_f, x_c, h_c)
# phi_k = cell_basis_k.get_phi_vector(x_q_f_prime, x_c, h_c)
# phi_l = cell_basis_l.get_phi_vector(x_q_f_prime, x_c, h_c)
psi_k = finite_element.face_basis_k.evaluate_function(
s_q_f, s_f, h_f)
m_mas_f += w_q_f * np.tensordot(phi_k, phi_l, axes=0)
m_hyb_f += w_q_f * np.tensordot(phi_k, psi_k, axes=0)
_c0 = _i * _cl
_c1 = (_i + 1) * _cl
local_grad_matric[:, _c0:_c1] -= m_mas_f * normal_vector_component_j
_c0 = _dx * _cl + _f * _dx * _fk + _i * _fk
_c1 = _dx * _cl + _f * _dx * _fk + (_i + 1) * _fk
local_grad_matric[:, _c0:_c1] += m_hyb_f * normal_vector_component_j
local_grad_matric2 = m_mas_inv @ local_grad_matric
return local_grad_matric2
def test_reference_polyhedron_quadrature(self, verbose=True):
"""
V8 o_______________o V7
/| V6 /|
/ | o / |
V4 o_______________o V5
| | | |
V3 | o___________ |__o V2 Z
| / | / ^ Y
|/ |/ |/
V0 o_______________o V1 0---> X
Args:
verbose:
"""
v0 = np.array([0.0, 0.0, 0.0], dtype=real)
v1 = np.array([1.0, 0.0, 0.0], dtype=real)
v2 = np.array([1.0, 1.0, 0.0], dtype=real)
v3 = np.array([0.0, 1.0, 0.0], dtype=real)
v4 = np.array([0.0, 0.0, 1.0], dtype=real)
v5 = np.array([1.0, 0.0, 1.0], dtype=real)
v6 = np.array([0.5, 0.5, 1.0], dtype=real)
v7 = np.array([1.0, 1.0, 1.0], dtype=real)
v8 = np.array([0.0, 1.0, 1.0], dtype=real)
vertices = np.array([v0, v1, v2, v3, v4, v5, v6, v7, v8], dtype=real).T
# --- CONNECTIVITY, COUNTER CLOCK WISE
# connectivity = [
# [0, 3, 2, 1],
# [0, 1, 5, 4],
# [1, 2, 7, 5],
# [2, 3, 8, 7],
# [3, 0, 4, 8],
# [4, 5, 6],
# [5, 7, 6],
# [7, 8, 6],
# [8, 4, 6],
# ]
# --- CONNECTIVIY, CLOCK WISE
connectivity = [
[0, 1, 2, 3],
[0, 4, 5, 1],
[1, 5, 7, 2],
[2, 7, 8, 3],
[3, 8, 4, 0],
[6, 5, 4],
[6, 7, 5],
[6, 8, 7],
[6, 4, 8],
]
shape = Shape(ShapeType.POLYHEDRON,
vertices,
connectivity=connectivity)
for _io in range(1, 9):
# --- DECLARE FUNCTION
f = lambda x: np.exp(x[0]) * np.sin(x[0] * x[1] / (x[2] + 0.003)
) + x[1] * x[2] + 3.0
f_scipy = lambda x, y, z: np.exp(x) * np.sin(x * y / (z + 0.003)
) + y * z + 3.0
# --- GET QUADPY ESTIMATION
scheme = quadpy.c3.get_good_scheme(_io)
val = scheme.integrate(
f, [[[v0, v4], [v3, v8]], [[v1, v5], [v2, v7]]])
# --- GET H20 ESTIMATION
val_num = 0.0
shape_quadrature_points = shape.get_quadrature_points(_io)
shape_quadrature_weights = shape.get_quadrature_weights(_io)
shape_quadrature_size = shape.get_quadrature_size(_io)
for _qc in range(shape_quadrature_size):
x_qc = shape_quadrature_points[:, _qc]
w_qc = shape_quadrature_weights[_qc]
val_num += w_qc * f(x_qc)
# --- GET SCIPY ESTIMATION
# val_scp = integrate.tplquad(
# f_scipy, 0.0, 1.0, lambda x: 0.0, lambda x: 1.0, lambda x, y: 0.0, lambda x, y: 1.0
# )
if verbose:
print("-- integration order : {}".format(_io))
print("val_h2O : {}".format(val_num))
print("val_qud : {}".format(val))
# print("val_scp : {}".format(val_scp))
x_c = shape.get_centroid()
fig = plt.figure()
ax = fig.add_subplot(111, projection="3d")
ax.scatter(x_c[0], x_c[1], x_c[2], c="b", marker="o")
for i in range(vertices.shape[1]):
ax.scatter(vertices[0, i],
vertices[1, i],
vertices[2, i],
c="b",
marker="o")
for _qc in range(shape_quadrature_size):
_x_qc = shape_quadrature_points[:, _qc]
ax.scatter(_x_qc[0], _x_qc[1], _x_qc[2], c="g")
plt.show()
def test_reference_polyhedron_cell(self, verbose=True):
"""
V3 o________________o V2
/| /|
/ | / |
/ | / | Y
/ | / | ^
V7 o________________o V6 | |
| | | | 0---> X
| V0 o___________|____o V1 /
| / | / Z
| / | /
| / | /
|/ |/
V4 o________________o V5
V3 o________________o V2
/| /|
/ | / |
/ | / | Y
/ | / | ^
V8 o________________o V7 | |
| | | | 0---> X
| V0 o___________|____o V1 /
| / | / Z
| / o V6 | /
| / | /
|/ |/
V4 o________________o V5
V2 o
|\..
| \..
| \..
| \..
| \..
| \
o_V0_____________o V1
| / ..../
/ ..../
/ / ..../
:/.../
V2 o
Args:
verbose:
Returns:
"""
euclidean_dimension = 3
polynomial_orders = [1, 2, 3]
element_types = [
ElementType.HDG_LOW, ElementType.HDG_EQUAL, ElementType.HDG_HIGH
]
for polynomial_order in polynomial_orders:
for element_type in element_types:
# --- DEFINE POLYNOMIAL ORDER AND INTEGRATION ORDER
finite_element = FiniteElement(
element_type=element_type,
polynomial_order=polynomial_order,
euclidean_dimension=euclidean_dimension,
)
# --- DEFINE POLYNOMIAL BASIS
cell_basis_k = finite_element.cell_basis_k
cell_basis_l = finite_element.cell_basis_l
# --- DEFINE RANDOM POLYNOMIAL COEFFICIENTS
range_min = -3.0
range_max = +3.0
coefficients_k = np.array([
uniform(range_min, range_max)
for _i in range(cell_basis_k.dimension)
])
coefficients_l = np.array([
uniform(range_min, range_max)
for _i in range(cell_basis_l.dimension)
])
if verbose:
print("COEFS_K : \n{}".format(coefficients_k))
print("COEFS_L : \n{}".format(coefficients_l))
# --- DEFINE MONOMIAL VALUES COMPUTATION
def test_function(polynomial_ord: int, point: ndarray,
centroid: ndarray, diameter: float,
coefficients: ndarray) -> float:
basis = Monomial(polynomial_ord, euclidean_dimension)
value = 0.0
for _i, _exponent in enumerate(basis.exponents):
prod = 1.0
for _x_dir in range(basis.exponents.shape[1]):
prod *= ((point[_x_dir] - centroid[_x_dir]) /
diameter)**_exponent[_x_dir]
prod *= coefficients[_i]
value += prod
return value
def test_function_derivative(
polynomial_ord: int,
point: ndarray,
centroid: ndarray,
diameter: float,
direction: int,
coefficients: ndarray,
) -> float:
basis = Monomial(polynomial_ord, euclidean_dimension)
value = 0.0
for _i, _exponent in enumerate(basis.exponents):
prod = 1.0
for _x_dir in range(basis.exponents.shape[1]):
if _x_dir == direction:
# _pt0 = point[_x_dir] - centroid[_x_dir]
# _pt1 = _pt0 / diameter
# if _exponent[_x_dir] == 0:
# _exp = _exponent[_x_dir]
# else:
# _exp = _exponent[_x_dir] - 1
# _pt2 = _pt1 ** _exp
if _exponent[_x_dir] != 0:
prod *= (_exponent[_x_dir] / diameter) * (
((point[_x_dir] - centroid[_x_dir]) /
diameter)**(_exponent[_x_dir] - 1))
else:
prod *= 0.0
# prod *= (_exponent[_x_dir] / diameter) * _pt2
else:
prod *= ((point[_x_dir] - centroid[_x_dir]) /
diameter)**_exponent[_x_dir]
prod *= coefficients[_i]
value += prod
return value
# --- DEFINE TRIANGLE COORDINATES
v0 = np.array([0.0, 0.0, 0.0], dtype=real)
v1 = np.array([1.0, 0.0, 0.0], dtype=real)
v2 = np.array([1.0, 1.0, 0.0], dtype=real)
v3 = np.array([0.0, 1.0, 0.0], dtype=real)
v4 = np.array([0.0, 0.0, 1.0], dtype=real)
v5 = np.array([1.0, 0.0, 1.0], dtype=real)
v6 = np.array([0.5, 0.5, 1.0], dtype=real)
v7 = np.array([1.0, 1.0, 1.0], dtype=real)
v8 = np.array([0.0, 1.0, 1.0], dtype=real)
vertices = np.array([v0, v1, v2, v3, v4, v5, v6, v7, v8],
dtype=real).T
# --- CONNECTIVITY, COUNTER CLOCK WISE
# connectivity = [
# [0, 3, 2, 1],
# [0, 1, 5, 4],
# [1, 2, 7, 5],
# [2, 3, 8, 7],
# [3, 0, 4, 8],
# [4, 5, 6],
# [5, 7, 6],
# [7, 8, 6],
# [8, 4, 6],
# ]
# --- CONNECTIVIY, CLOCK WISE
connectivity = [
[0, 1, 2, 3],
[0, 4, 5, 1],
[1, 5, 7, 2],
[2, 7, 8, 3],
[3, 8, 4, 0],
[6, 5, 4],
[6, 7, 5],
[6, 8, 7],
[6, 4, 8],
]
# --- BUILD CELL
shape = Shape(ShapeType.POLYHEDRON,
vertices,
connectivity=connectivity)
x_c = shape.get_centroid()
h_c = shape.get_diameter()
_io = finite_element.construction_integration_order
cell_quadrature_points = shape.get_quadrature_points(_io)
cell_quadrature_weights = shape.get_quadrature_weights(_io)
cell_quadrature_size = shape.get_quadrature_size(_io)
# --- CHECK INTEGRATION IN CELL
bases = [cell_basis_k, cell_basis_l]
# orders = [face_polynomial_order, cell_polynomial_order]
coefs = [coefficients_k, coefficients_l]
# scheme = quadpy.t2.get_good_scheme(2 * finite_element.construction_integration_order)
scheme = quadpy.c3.get_good_scheme(
finite_element.construction_integration_order)
for basis_0, coef_0 in zip(bases, coefs):
order_0 = basis_0.polynomial_order
for basis_1, coef_1 in zip(bases, coefs):
order_1 = basis_1.polynomial_order
for _i in range(euclidean_dimension):
for _j in range(euclidean_dimension):
mass_mat = np.zeros(
(basis_0.dimension, basis_1.dimension),
dtype=real)
stif_mat = np.zeros(
(basis_0.dimension, basis_1.dimension),
dtype=real)
advc_mat = np.zeros(
(basis_0.dimension, basis_1.dimension),
dtype=real)
for _qc in range(cell_quadrature_size):
_x_qc = cell_quadrature_points[:, _qc]
_w_qc = cell_quadrature_weights[_qc]
phi_0 = basis_0.evaluate_function(
_x_qc, x_c, h_c)
phi_1 = basis_1.evaluate_function(
_x_qc, x_c, h_c)
d_phi_0_i = basis_0.evaluate_derivative(
_x_qc, x_c, h_c, _i)
d_phi_1_j = basis_1.evaluate_derivative(
_x_qc, x_c, h_c, _j)
mass_mat += _w_qc * np.tensordot(
phi_0, phi_1, axes=0)
stif_mat += _w_qc * np.tensordot(
d_phi_0_i, d_phi_1_j, axes=0)
advc_mat += _w_qc * np.tensordot(
phi_0, d_phi_1_j, axes=0)
mass_integral = coef_0 @ mass_mat @ coef_1
stif_integral = coef_0 @ stif_mat @ coef_1
advc_integral = coef_0 @ advc_mat @ coef_1
f_mass_check = lambda x: test_function(
order_0, x, x_c, h_c, coef_0
) * test_function(order_1, x, x_c, h_c, coef_1)
f_stif_check = lambda x: test_function_derivative(
order_0, x, x_c, h_c, _i, coef_0
) * test_function_derivative(
order_1, x, x_c, h_c, _j, coef_1)
f_advc_check = lambda x: test_function(
order_0, x, x_c, h_c, coef_0
) * test_function_derivative(
order_1, x, x_c, h_c, _j, coef_1)
mass_integral_check = scheme.integrate(
f_mass_check, [[[v0, v4], [v3, v8]],
[[v1, v5], [v2, v7]]])
stif_integral_check = scheme.integrate(
f_stif_check, [[[v0, v4], [v3, v8]],
[[v1, v5], [v2, v7]]])
advc_integral_check = scheme.integrate(
f_advc_check, [[[v0, v4], [v3, v8]],
[[v1, v5], [v2, v7]]])
rtol = 1.0e-12
atol = 1.0e-12
if verbose:
print(
"MASS INTEGRAL CHECK | ORDER : {} | ELEM : {} | dir {}, {}, | order {}, {}"
.format(polynomial_order, element_type,
_i, _j, order_0, order_1))
print("- QUADPY : {}".format(
mass_integral_check))
print("- H2O : {}".format(mass_integral))
print(
"STIFFNESS INTEGRAL CHECK | ORDER : {} | ELEM : {} | dir {}, {} | order {}, {}"
.format(polynomial_order, element_type,
_i, _j, order_0, order_1))
print("- QUADPY : {}".format(
stif_integral_check))
print("- H2O : {}".format(stif_integral))
print(
"ADVECTION INTEGRAL CHECK | ORDER : {} | ELEM : {} | dir {}, {} | order {}, {}"
.format(polynomial_order, element_type,
_i, _j, order_0, order_1))
print("- QUADPY : {}".format(
advc_integral_check))
print("- H2O : {}".format(advc_integral))
np.testing.assert_allclose(mass_integral_check,
mass_integral,
rtol=rtol,
atol=atol)
np.testing.assert_allclose(stif_integral_check,
stif_integral,
rtol=rtol,
atol=atol)
np.testing.assert_allclose(advc_integral_check,
advc_integral,
rtol=rtol,
atol=atol)
