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from collections.abc import Sequence
import enum
from typing import Annotated, overload
import numpy
from numpy.typing import NDArray, ArrayLike
def topology(arg: CellType, /) -> list[list[list[int]]]: ...
def geometry(arg: CellType, /) -> NDArray[numpy.float64]: ...
def sub_entity_type(arg0: CellType, arg1: int, arg2: int, /) -> CellType: ...
def sub_entity_connectivity(arg: CellType, /) -> list[list[list[list[int]]]]: ...
def sub_entity_geometry(arg0: CellType, arg1: int, arg2: int, /) -> NDArray[numpy.float64]: ...
def subentity_types(arg: CellType, /) -> list[list[CellType]]: ...
def sobolev_space_intersection(arg0: SobolevSpace, arg1: SobolevSpace, /) -> SobolevSpace: ...
class LatticeType(enum.IntEnum):
"""Lattice type."""
equispaced = 0
gll = 1
chebyshev = 2
gl = 4
class LatticeSimplexMethod(enum.IntEnum):
"""Lattice simplex method."""
none = 0
warp = 1
isaac = 2
centroid = 3
class PolynomialType(enum.IntEnum):
"""Polynomial type."""
legendre = 0
lagrange = 1
bernstein = 2
def tabulate_polynomials(arg0: PolynomialType, arg1: CellType, arg2: int, arg3: Annotated[NDArray[numpy.float64], dict(shape=(None, None), order='C', writable=False)], /) -> NDArray[numpy.float64]: ...
def polynomials_dim(arg0: PolynomialType, arg1: CellType, arg2: int, /) -> int: ...
def create_lattice(arg0: CellType, arg1: int, arg2: LatticeType, arg3: bool, arg4: LatticeSimplexMethod, /) -> NDArray[numpy.float64]: ...
class MapType(enum.IntEnum):
"""Element map type."""
identity = 0
L2Piola = 1
covariantPiola = 2
contravariantPiola = 3
doubleCovariantPiola = 4
doubleContravariantPiola = 5
class SobolevSpace(enum.IntEnum):
"""Sobolev space."""
L2 = 0
H1 = 1
H2 = 2
H3 = 3
HInf = 8
HDiv = 10
HCurl = 11
HEin = 12
HDivDiv = 13
class QuadratureType(enum.IntEnum):
"""Quadrature type."""
default = 0
gauss_jacobi = 1
gll = 2
xiao_gimbutas = 3
class CellType(enum.IntEnum):
"""Cell type."""
point = 0
interval = 1
triangle = 2
tetrahedron = 3
quadrilateral = 4
hexahedron = 5
prism = 6
pyramid = 7
def cell_volume(arg: CellType, /) -> float: ...
def cell_facet_normals(arg: CellType, /) -> NDArray[numpy.float64]: ...
def cell_facet_reference_volumes(arg: CellType, /) -> NDArray[numpy.float64]: ...
def cell_facet_outward_normals(arg: CellType, /) -> NDArray[numpy.float64]: ...
def cell_facet_orientations(arg: CellType, /) -> list[int]: ...
def cell_facet_jacobians(arg: CellType, /) -> NDArray[numpy.float64]: ...
def cell_edge_jacobians(arg: CellType, /) -> NDArray[numpy.float64]: ...
class ElementFamily(enum.IntEnum):
"""Finite element family."""
custom = 0
P = 1
BDM = 4
RT = 2
N1E = 3
N2E = 5
Regge = 7
HHJ = 11
bubble = 9
serendipity = 10
DPC = 8
CR = 6
Hermite = 12
iso = 13
class LagrangeVariant(enum.IntEnum):
"""Lagrange element variant."""
unset = 0
equispaced = 1
gll_warped = 2
gll_isaac = 3
gll_centroid = 4
chebyshev_warped = 5
chebyshev_isaac = 6
chebyshev_centroid = 7
gl_warped = 8
gl_isaac = 9
gl_centroid = 10
legendre = 11
bernstein = 12
class DPCVariant(enum.IntEnum):
"""DPC variant."""
unset = 0
simplex_equispaced = 1
simplex_gll = 2
horizontal_equispaced = 3
horizontal_gll = 4
diagonal_equispaced = 5
diagonal_gll = 6
legendre = 7
def create_element(arg0: ElementFamily, arg1: CellType, arg2: int, arg3: LagrangeVariant, arg4: DPCVariant, arg5: bool, arg6: Sequence[int], arg7: str, /) -> FiniteElement_float32 | FiniteElement_float64: ...
def create_tp_element(arg0: ElementFamily, arg1: CellType, arg2: int, arg3: LagrangeVariant, arg4: DPCVariant, arg5: bool, arg6: str, /) -> FiniteElement_float32 | FiniteElement_float64: ...
def tp_factors(arg0: ElementFamily, arg1: CellType, arg2: int, arg3: LagrangeVariant, arg4: DPCVariant, arg5: bool, arg6: Sequence[int], arg7: str, /) -> list[list[FiniteElement_float32]] | list[list[FiniteElement_float64]]: ...
def tp_dof_ordering(arg0: ElementFamily, arg1: CellType, arg2: int, arg3: LagrangeVariant, arg4: DPCVariant, arg5: bool, /) -> list[int]: ...
def lex_dof_ordering(arg0: ElementFamily, arg1: CellType, arg2: int, arg3: LagrangeVariant, arg4: DPCVariant, arg5: bool, /) -> list[int]: ...
class PolysetType(enum.IntEnum):
"""Polyset type."""
standard = 0
macroedge = 1
def superset(arg0: CellType, arg1: PolysetType, arg2: PolysetType, /) -> PolysetType: ...
def restriction(arg0: PolysetType, arg1: CellType, arg2: CellType, /) -> PolysetType: ...
def make_quadrature(arg0: QuadratureType, arg1: CellType, arg2: PolysetType, arg3: int, /) -> tuple[NDArray[numpy.float64], NDArray[numpy.float64]]: ...
def gauss_jacobi_rule(arg0: float, arg1: int, /) -> tuple[NDArray[numpy.float64], NDArray[numpy.float64]]: ...
@overload
def index(arg: int, /) -> int: ...
@overload
def index(arg0: int, arg1: int, /) -> int: ...
@overload
def index(arg0: int, arg1: int, arg2: int, /) -> int: ...
class FiniteElement_float32:
def tabulate(self, arg0: int, arg1: Annotated[NDArray[numpy.float32], dict(shape=(None, None), order='C', writable=False)], /) -> NDArray[numpy.float32]: ...
def __eq__(self, arg: object, /) -> bool: ...
def hash(self) -> int: ...
@overload
def permute_subentity_closure(self, arg0: Annotated[NDArray[numpy.int32], dict(shape=(None,), order='C')], arg1: int, arg2: CellType, /) -> None: ...
@overload
def permute_subentity_closure(self, arg0: Annotated[NDArray[numpy.int32], dict(shape=(None,), order='C')], arg1: int, arg2: CellType, arg3: int, /) -> None: ...
@overload
def permute_subentity_closure_inv(self, arg0: Annotated[NDArray[numpy.int32], dict(shape=(None,), order='C')], arg1: int, arg2: CellType, /) -> None: ...
@overload
def permute_subentity_closure_inv(self, arg0: Annotated[NDArray[numpy.int32], dict(shape=(None,), order='C')], arg1: int, arg2: CellType, arg3: int, /) -> None: ...
def push_forward(self, arg0: Annotated[NDArray[numpy.float32], dict(shape=(None, None, None), order='C', writable=False)], arg1: Annotated[NDArray[numpy.float32], dict(shape=(None, None, None), order='C', writable=False)], arg2: Annotated[NDArray[numpy.float32], dict(shape=(None,), order='C', writable=False)], arg3: Annotated[NDArray[numpy.float32], dict(shape=(None, None, None), order='C', writable=False)], /) -> NDArray[numpy.float32]: ...
def pull_back(self, arg0: Annotated[NDArray[numpy.float32], dict(shape=(None, None, None), order='C', writable=False)], arg1: Annotated[NDArray[numpy.float32], dict(shape=(None, None, None), order='C', writable=False)], arg2: Annotated[NDArray[numpy.float32], dict(shape=(None,), order='C', writable=False)], arg3: Annotated[NDArray[numpy.float32], dict(shape=(None, None, None), order='C', writable=False)], /) -> NDArray[numpy.float32]: ...
def T_apply(self, arg0: Annotated[NDArray[numpy.float32], dict(shape=(None,), order='C')], arg1: int, arg2: int, /) -> None: ...
def Tt_apply_right(self, arg0: Annotated[NDArray[numpy.float32], dict(shape=(None,), order='C')], arg1: int, arg2: int, /) -> None: ...
def Tt_inv_apply(self, arg0: Annotated[NDArray[numpy.float32], dict(shape=(None,), order='C')], arg1: int, arg2: int, /) -> None: ...
def base_transformations(self) -> NDArray[numpy.float32]: ...
def entity_transformations(self) -> dict: ...
def get_tensor_product_representation(self) -> list[list[FiniteElement_float32]]: ...
@property
def degree(self) -> int: ...
@property
def embedded_superdegree(self) -> int: ...
@property
def embedded_subdegree(self) -> int: ...
@property
def cell_type(self) -> CellType: ...
@property
def polyset_type(self) -> PolysetType: ...
@property
def dim(self) -> int: ...
@property
def num_entity_dofs(self) -> list[list[int]]: ...
@property
def entity_dofs(self) -> list[list[list[int]]]: ...
@property
def num_entity_closure_dofs(self) -> list[list[int]]: ...
@property
def entity_closure_dofs(self) -> list[list[list[int]]]: ...
@property
def value_size(self) -> int: ...
@property
def value_shape(self) -> list[int]: ...
@property
def discontinuous(self) -> bool: ...
@property
def family(self) -> ElementFamily: ...
@property
def lagrange_variant(self) -> LagrangeVariant: ...
@property
def dpc_variant(self) -> DPCVariant: ...
@property
def dof_transformations_are_permutations(self) -> bool: ...
@property
def dof_transformations_are_identity(self) -> bool: ...
@property
def interpolation_is_identity(self) -> bool: ...
@property
def map_type(self) -> MapType: ...
@property
def sobolev_space(self) -> SobolevSpace: ...
@property
def points(self) -> Annotated[NDArray[numpy.float32], dict(shape=(None, None), writable=False)]: ...
@property
def interpolation_matrix(self) -> Annotated[NDArray[numpy.float32], dict(shape=(None, None), writable=False)]: ...
@property
def dual_matrix(self) -> Annotated[NDArray[numpy.float32], dict(shape=(None, None), writable=False)]: ...
@property
def coefficient_matrix(self) -> Annotated[NDArray[numpy.float32], dict(shape=(None, None), writable=False)]:
"""Coefficient matrix."""
@property
def wcoeffs(self) -> Annotated[NDArray[numpy.float32], dict(shape=(None, None), writable=False)]: ...
@property
def M(self) -> list[list[Annotated[NDArray[numpy.float32], dict(writable=False)]]]: ...
@property
def x(self) -> list[list[Annotated[NDArray[numpy.float32], dict(writable=False)]]]: ...
@property
def has_tensor_product_factorisation(self) -> bool: ...
@property
def interpolation_nderivs(self) -> int: ...
@property
def dof_ordering(self) -> list[int]: ...
@property
def dtype(self) -> str: ...
def create_custom_element_float32(cell_type: CellType, value_shape: Sequence[int], wcoeffs: Annotated[NDArray[numpy.float32], dict(shape=(None, None), order='C', writable=False)], x: Sequence[Sequence[Annotated[NDArray[numpy.float32], dict(shape=(None, None), order='C', writable=False)]]], M: Sequence[Sequence[Annotated[NDArray[numpy.float32], dict(shape=(None, None, None, None), order='C', writable=False)]]], interpolation_nderivs: int, map_type: MapType, sobolev_space: SobolevSpace, discontinuous: bool, embedded_subdegree: int, embedded_superdegree: int, poly_type: PolysetType) -> FiniteElement_float32: ...
@overload
def compute_interpolation_operator(arg0: FiniteElement_float32, arg1: FiniteElement_float32, /) -> NDArray[numpy.float32]: ...
@overload
def compute_interpolation_operator(arg0: FiniteElement_float64, arg1: FiniteElement_float64, /) -> NDArray[numpy.float64]: ...
def tabulate_polynomial_set(celltype: CellType, polytype: PolysetType, d: int, n: int, x: Annotated[ArrayLike, dict(dtype='float64', writable=False, shape=(None, None), order='C')]) -> Annotated[ArrayLike, dict(dtype='float64', )]: ...
class FiniteElement_float64:
def tabulate(self, arg0: int, arg1: Annotated[NDArray[numpy.float64], dict(shape=(None, None), order='C', writable=False)], /) -> NDArray[numpy.float64]: ...
def __eq__(self, arg: object, /) -> bool: ...
def hash(self) -> int: ...
@overload
def permute_subentity_closure(self, arg0: Annotated[NDArray[numpy.int32], dict(shape=(None,), order='C')], arg1: int, arg2: CellType, /) -> None: ...
@overload
def permute_subentity_closure(self, arg0: Annotated[NDArray[numpy.int32], dict(shape=(None,), order='C')], arg1: int, arg2: CellType, arg3: int, /) -> None: ...
@overload
def permute_subentity_closure_inv(self, arg0: Annotated[NDArray[numpy.int32], dict(shape=(None,), order='C')], arg1: int, arg2: CellType, /) -> None: ...
@overload
def permute_subentity_closure_inv(self, arg0: Annotated[NDArray[numpy.int32], dict(shape=(None,), order='C')], arg1: int, arg2: CellType, arg3: int, /) -> None: ...
def push_forward(self, arg0: Annotated[NDArray[numpy.float64], dict(shape=(None, None, None), order='C', writable=False)], arg1: Annotated[NDArray[numpy.float64], dict(shape=(None, None, None), order='C', writable=False)], arg2: Annotated[NDArray[numpy.float64], dict(shape=(None,), order='C', writable=False)], arg3: Annotated[NDArray[numpy.float64], dict(shape=(None, None, None), order='C', writable=False)], /) -> NDArray[numpy.float64]: ...
def pull_back(self, arg0: Annotated[NDArray[numpy.float64], dict(shape=(None, None, None), order='C', writable=False)], arg1: Annotated[NDArray[numpy.float64], dict(shape=(None, None, None), order='C', writable=False)], arg2: Annotated[NDArray[numpy.float64], dict(shape=(None,), order='C', writable=False)], arg3: Annotated[NDArray[numpy.float64], dict(shape=(None, None, None), order='C', writable=False)], /) -> NDArray[numpy.float64]: ...
def T_apply(self, arg0: Annotated[NDArray[numpy.float64], dict(shape=(None,), order='C')], arg1: int, arg2: int, /) -> None: ...
def Tt_apply_right(self, arg0: Annotated[NDArray[numpy.float64], dict(shape=(None,), order='C')], arg1: int, arg2: int, /) -> None: ...
def Tt_inv_apply(self, arg0: Annotated[NDArray[numpy.float64], dict(shape=(None,), order='C')], arg1: int, arg2: int, /) -> None: ...
def base_transformations(self) -> NDArray[numpy.float64]: ...
def entity_transformations(self) -> dict: ...
def get_tensor_product_representation(self) -> list[list[FiniteElement_float64]]: ...
@property
def degree(self) -> int: ...
@property
def embedded_superdegree(self) -> int: ...
@property
def embedded_subdegree(self) -> int: ...
@property
def cell_type(self) -> CellType: ...
@property
def polyset_type(self) -> PolysetType: ...
@property
def dim(self) -> int: ...
@property
def num_entity_dofs(self) -> list[list[int]]: ...
@property
def entity_dofs(self) -> list[list[list[int]]]: ...
@property
def num_entity_closure_dofs(self) -> list[list[int]]: ...
@property
def entity_closure_dofs(self) -> list[list[list[int]]]: ...
@property
def value_size(self) -> int: ...
@property
def value_shape(self) -> list[int]: ...
@property
def discontinuous(self) -> bool: ...
@property
def family(self) -> ElementFamily: ...
@property
def lagrange_variant(self) -> LagrangeVariant: ...
@property
def dpc_variant(self) -> DPCVariant: ...
@property
def dof_transformations_are_permutations(self) -> bool: ...
@property
def dof_transformations_are_identity(self) -> bool: ...
@property
def interpolation_is_identity(self) -> bool: ...
@property
def map_type(self) -> MapType: ...
@property
def sobolev_space(self) -> SobolevSpace: ...
@property
def points(self) -> Annotated[NDArray[numpy.float64], dict(shape=(None, None), writable=False)]: ...
@property
def interpolation_matrix(self) -> Annotated[NDArray[numpy.float64], dict(shape=(None, None), writable=False)]: ...
@property
def dual_matrix(self) -> Annotated[NDArray[numpy.float64], dict(shape=(None, None), writable=False)]: ...
@property
def coefficient_matrix(self) -> Annotated[NDArray[numpy.float64], dict(shape=(None, None), writable=False)]:
"""Coefficient matrix."""
@property
def wcoeffs(self) -> Annotated[NDArray[numpy.float64], dict(shape=(None, None), writable=False)]: ...
@property
def M(self) -> list[list[Annotated[NDArray[numpy.float64], dict(writable=False)]]]: ...
@property
def x(self) -> list[list[Annotated[NDArray[numpy.float64], dict(writable=False)]]]: ...
@property
def has_tensor_product_factorisation(self) -> bool: ...
@property
def interpolation_nderivs(self) -> int: ...
@property
def dof_ordering(self) -> list[int]: ...
@property
def dtype(self) -> str: ...
def create_custom_element_float64(cell_type: CellType, value_shape: Sequence[int], wcoeffs: Annotated[NDArray[numpy.float64], dict(shape=(None, None), order='C', writable=False)], x: Sequence[Sequence[Annotated[NDArray[numpy.float64], dict(shape=(None, None), order='C', writable=False)]]], M: Sequence[Sequence[Annotated[NDArray[numpy.float64], dict(shape=(None, None, None, None), order='C', writable=False)]]], interpolation_nderivs: int, map_type: MapType, sobolev_space: SobolevSpace, discontinuous: bool, embedded_subdegree: int, embedded_superdegree: int, poly_type: PolysetType) -> FiniteElement_float64: ...
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