warp.fem#

The warp.fem module is designed to facilitate solving physical systems described as differential equations. For example, it can solve PDEs for diffusion, convection, fluid flow, and elasticity problems using finite-element-based (FEM) Galerkin methods, and allows users to quickly experiment with various FEM formulations and discretization schemes.

Integrands#

The core functionality of the FEM toolkit is the ability to integrate constant, linear, and bilinear forms over various domains and using arbitrary interpolation basis.

The main mechanism is the integrand() decorator, for instance:

@integrand
def linear_form(
    s: Sample,
    v: Field,
):
    return v(s)


@integrand
def diffusion_form(s: Sample, u: Field, v: Field, nu: float):
    return nu * wp.dot(
        grad(u, s),
        grad(v, s),
    )

Integrands are normal Warp kernels, meaning any usual Warp function can be used. However, they accept a few special parameters:

Sample contains information about the current integration sample point, such as the element index and coordinates in element.

Field designates an abstract field, which will be replaced at call time by the actual field type: for instance a DiscreteField, field.TestField or field.TrialField defined over an arbitrary FunctionSpace. A field u can be evaluated at a given sample s using the inner() operator, i.e, inner(u, s), or as a shortcut using the usual call operator, u(s). Several other operators are available, such as grad(); see the Operators section.
Domain designates an abstract integration domain. Several operators are also provided for domains, for example in the example below evaluating the normal at the current sample position:
@integrand
def boundary_form(
    s: Sample,
    domain: Domain,
    u: Field,
):
    nor = normal(domain, s)
    return wp.dot(u(s), nor)

Integrands cannot be used directly with warp.launch(), but must be called through integrate() or interpolate() instead. The root integrand (integrand argument passed to integrate() or interpolate() call) will automatically get passed Sample and Domain parameters. Field parameters must be passed as a dictionary in the fields argument of the launcher function, and all other standard Warp types arguments must be passed as a dictionary in the values argument of the launcher function, for instance:

integrate(diffusion_form, fields={"u": trial, "v": test}, values={"nu": viscosity})

Basic workflow#

The typical steps for solving a linear PDE are as follow:

Define a Geometry (grid, mesh, etc). At the moment, 2D and 3D regular grids, triangle, quadrilateral, tetrahedron and hexahedron meshes are supported.

Define one or more FunctionSpace, by equipping the geometry elements with shape functions. See make_polynomial_space(). At the moment, continuous/discontinuous Lagrange (\(P_{k[d]}, Q_{k[d]}\)) and Serendipity (\(S_k\)) shape functions of order \(k \leq 3\) are supported.

Define an integration GeometryDomain, for instance the geometry’s cells (Cells) or boundary sides (BoundarySides).

Integrate linear forms to build the system’s right-hand-side. Define a test function over the function space using make_test(), a Quadrature formula (or let the module choose one based on the function space degree), and call integrate() with the linear form integrand. The result is a warp.array containing the integration result for each of the function space degrees of freedom.

Integrate bilinear forms to build the system’s left-hand-side. Define a trial function over the function space using make_trial(), then call integrate() with the bilinear form integrand. The result is a warp.sparse.BsrMatrix containing the integration result for each pair of test and trial function space degrees of freedom. Note that the trial and test functions do not have to be defined over the same function space, so that Mixed FEM is supported.

Solve the resulting linear system using the solver of your choice

The following excerpt from the introductory example warp/examples/fem/example_diffusion.py outlines this procedure:

# Grid geometry
geo = Grid2D(n=50, cell_size=2)

# Domain and function spaces
domain = Cells(geometry=geo)
scalar_space = make_polynomial_space(geo, degree=3)

# Right-hand-side (forcing term)
test = make_test(space=scalar_space, domain=domain)
rhs = integrate(linear_form, fields={"v": test})

# Weakly-imposed boundary conditions on Y sides
boundary = BoundarySides(geo)
bd_test = make_test(space=scalar_space, domain=boundary)
bd_trial = make_trial(space=scalar_space, domain=boundary)
bd_matrix = integrate(y_mass_form, fields={"u": bd_trial, "v": bd_test})

# Diffusion form
trial = make_trial(space=scalar_space, domain=domain)
matrix = integrate(diffusion_form, fields={"u": trial, "v": test}, values={"nu": viscosity})

# Assemble linear system (add diffusion and boundary condition matrices)
bsr_axpy(x=bd_matrix, y=matrix, alpha=boundary_strength, beta=1)

# Solve linear system using Conjugate Gradient
x = wp.zeros_like(rhs)
bsr_cg(matrix, b=rhs, x=x)

Note

The integrate() function does not check that the passed integrands are actually linear or bilinear forms; it is up to the user to ensure that they are. To solve non-linear PDEs, one can use an iterative procedure and pass the current value of the studied function DiscreteField argument to the integrand, on which arbitrary operations are permitted. However, the result of the form must remain linear in the test and trial fields.

Introductory examples#

warp.fem ships with a list of examples in the warp/examples/fem directory illustrating common model problems.

example_diffusion.py: 2D diffusion with homogeneous Neumann and Dirichlet boundary conditions

example_diffusion_3d.py: 3D variant of the diffusion problem

example_convection_diffusion.py: 2D convection-diffusion using semi-Lagrangian advection

example_diffusion_dg0.py: 2D convection-diffusion using finite-volume and upwind transport

example_diffusion_dg.py: 2D convection-diffusion using Discontinuous Galerkin with upwind transport and Symmetric Interior Penalty

example_stokes.py: 2D incompressible Stokes flow using mixed \(P_k/P_{k-1}\) or \(Q_k/P_{(k-1)d}\) elements

example_navier_stokes.py: 2D Navier-Stokes flow using mixed \(P_k/P_{k-1}\) elements

example_mixed_elasticity.py: 2D linear elasticity using mixed continuous/discontinuous \(S_k/P_{(k-1)d}\) elements

Advanced usages#

High-order (curved) geometries#

It is possible to convert any Geometry (grids and explicit meshes) into a curved, high-order variant by deforming them with an arbitrary-order displacement field using the make_deformed_geometry() method. The process looks as follow:

# Define a base geometry
base_geo = fem.Grid3D(res=resolution)

# Define a displacement field on the base geometry
deformation_space = fem.make_polynomial_space(base_geo, degree=deformation_degree, dtype=wp.vec3)
deformation_field = deformation_space.make_field()

# Populate the field value by interpolating an expression
fem.interpolate(deformation_field_expr, dest=deformation_field)

# Construct the deformed geometry from the displacement field
deform_geo = deformation_field.make_deformed_geometry()

# Define new function spaces on the deformed geometry
scalar_space = fem.make_polynomial_space(deformed_geo, degree=scalar_space_degree)

See also example_deformed_geometry.py for a complete example.

Particle-based quadrature#

The PicQuadrature provides a way to define Particle-In-Cell quadratures from a set or arbitrary particles, which can be helpful to develop MPM-like methods. The particles are automatically bucketed to the geometry cells when the quadrature is initialized. This is illustrated by the example_stokes_transfer.py and example_apic_fluid.py examples.

Partitioning#

The FEM toolkit makes it possible to perform integration on a subset of the domain elements, possibly re-indexing degrees of freedom so that the linear system contains the local ones only. This is useful for distributed computation (see warp/examples/fem/example_diffusion_mgpu.py), or simply to limit the simulation domain to a subset of active cells (see warp/examples/fem/example_stokes_transfer.py).

A partition of the simulation geometry can be defined using subclasses of GeometryPartition such as LinearGeometryPartition or ExplicitGeometryPartition.

Function spaces can then be partitioned according to the geometry partition using make_space_partition(). The resulting SpacePartition object allows translating between space-wide and partition-wide node indices, and differentiating interior, frontier and exterior nodes.

Memory management#

Several warp.fem functions require allocating temporary buffers to perform their computations. If such functions are called many times in a tight loop, those many allocations and de-allocations may degrade performance. To overcome this issue, a cache.TemporaryStore object may be created to persist and reuse temporary allocations across calls, either globally using set_default_temporary_store() or at a per-function granularity using the corresponding argument.

Operators#

warp.fem.position(domain: Domain, s: Sample)#: Evaluates the world position of the sample point s

warp.fem.normal(domain: Domain, s: Sample)#: Evaluates the element normal at the sample point s. Null for interior points.

warp.fem.lookup(domain: Domain, x)#

Looks-up the sample point corresponding to a world position x, projecting to the closest point on the domain.

Arg:: x: world position of the point to look-up in the geometry guess: (optional) Sample initial guess, may help perform the query

Notes

Currently this operator is only fully supported for Grid2D and Grid3D geometries. For TriangleMesh2D and Tetmesh geometries, the operator requires providing guess.

warp.fem.measure(domain: Domain, s: Sample)#: Returns the measure (volume, area, or length) determinant of an element at a sample point s

warp.fem.measure_ratio(domain: Domain, s: Sample)#: Returns the maximum ratio between the measure of this element and that of higher-dimensional neighbours.

warp.fem.deformation_gradient(domain: Domain, s: Sample)#: Evaluates the gradient of the domain position with respect to the element reference space at the sample point s

warp.fem.degree(f: Field)#: Polynomial degree of a field

warp.fem.inner(f: Field, s: Sample)#: Evaluates the field at a sample point s. On oriented sides, uses the inner element

warp.fem.outer(f: Field, s: Sample)#: Evaluates the field at a sample point s. On oriented sides, uses the outer element. On interior points and on domain boundaries, this is equivalent to inner().

warp.fem.grad(f: Field, s: Sample)#: Evaluates the field gradient at a sample point s. On oriented sides, uses the inner element

warp.fem.grad_outer(f: Field, s: Sample)#: Evaluates the field gradient at a sample point s. On oriented sides, uses the outer element. On interior points and on domain boundaries, this is equivalent to grad().

warp.fem.div(f: Field, s: Sample)#: Evaluates the field divergence at a sample point s. On oriented sides, uses the inner element

warp.fem.div_outer(f: Field, s: Sample)#: Evaluates the field divergence at a sample point s. On oriented sides, uses the outer element. On interior points and on domain boundaries, this is equivalent to div().

warp.fem.at_node(f: Field, s: Sample)#: For a Test or Trial field, returns a copy of the Sample s moved to the coordinates of the node being evaluated

warp.fem.D(f: Field, s: Sample)#: Symmetric part of the (inner) gradient of the field at s

warp.fem.curl(f: Field, s: Sample)#: Skew part of the (inner) gradient of the field at s, as a vector such that wp.cross(curl(u), v) = skew(grad(u)) v

warp.fem.jump(f: Field, s: Sample)#: Jump between inner and outer element values on an interior side. Zero for interior points or domain boundaries

warp.fem.average(f: Field, s: Sample)#: Average between inner and outer element values

warp.fem.grad_jump(f: Field, s: Sample)#: Jump between inner and outer element gradients on an interior side. Zero for interior points or domain boundaries

warp.fem.grad_average(f: Field, s: Sample)#: Average between inner and outer element gradients

warp.fem.operator.operator(resolver)#

Decorator for functions operating on Field-like or Domain-like data inside warp.fem integrands

Parameters:: resolver (Callable) –

Integration#

warp.fem.integrate(integrand, domain=None, quadrature=None, nodal=False, fields=None, values=None, accumulate_dtype=<class 'warp.types.float64'>, output_dtype=None, output=None, device=None, temporary_store=None, kernel_options=None)#

Integrates a constant, linear or bilinear form, and returns a scalar, array, or sparse matrix, respectively.

Parameters:

integrand (Integrand) – Form to be integrated, must have integrand() decorator
domain (GeometryDomain | None) – Integration domain. If None, deduced from fields
quadrature (Quadrature | None) – Quadrature formula. If None, deduced from domain and fields degree.
nodal (bool) – For linear or bilinear form only, use the test function nodes as the quadrature points. Assumes Lagrange interpolation functions are used, and no differential or DG operator is evaluated on the test or trial functions.
fields (Dict[str, FieldLike] | None) – Discrete, test, and trial fields to be passed to the integrand. Keys in the dictionary must match integrand parameter names.
values (Dict[str, Any] | None) – Additional variable values to be passed to the integrand, can be of any type accepted by warp kernel launches. Keys in the dictionary must match integrand parameter names.
temporary_store (TemporaryStore | None) – shared pool from which to allocate temporary arrays
accumulate_dtype (type) – Scalar type to be used for accumulating integration samples
output (array | BsrMatrix | None) – Sparse matrix or warp array into which to store the result of the integration
output_dtype (type | None) – Scalar type for returned results in output is not provided. If None, defaults to accumulate_dtype
device – Device on which to perform the integration
kernel_options (Dict[str, Any] | None) – Overloaded options to be passed to the kernel builder (e.g, {"enable_backward": True})

warp.fem.interpolate(integrand, dest=None, quadrature=None, fields=None, values=None, device=None, kernel_options=None)#

Interpolates a function at a finite set of sample points and optionally assigns the result to a discrete field or a raw warp array.

Parameters:

integrand (Integrand) – Function to be interpolated, must have integrand() decorator
dest (DiscreteField | FieldRestriction | array | None) –
Where to store the interpolation result. Can be either
- a DiscreteField, or restriction of a discrete field to a domain (from make_restriction()). In this case, interpolation will be performed at each node.
- a normal warp array. In this case, the quadrature argument defining the interpolation locations must be provided and the result of the integrand at each quadrature point will be assigned to the array.
- None. In this case, the quadrature argument must also be provided and the integrand function is responsible for dealing with the interpolation result.
quadrature (Quadrature | None) – Quadrature formula defining the interpolation samples if dest is not a discrete field or field restriction.
fields (Dict[str, FieldLike] | None) – Discrete fields to be passed to the integrand. Keys in the dictionary must match integrand parameters names.
values (Dict[str, Any] | None) – Additional variable values to be passed to the integrand, can be of any type accepted by warp kernel launches. Keys in the dictionary must match integrand parameter names.
device – Device on which to perform the interpolation
kernel_options (Dict[str, Any] | None) – Overloaded options to be passed to the kernel builder (e.g, {"enable_backward": True})

warp.fem.integrand(func)#

Decorator for functions to be integrated (or interpolated) using warp.fem

Parameters:: func (Callable) –

class warp.fem.Sample#: Per-sample point context for evaluating fields and related operators in integrands.

class warp.fem.Field#: Tag for field-like integrand arguments

class warp.fem.Domain#: Tag for domain-like integrand arguments

Geometry#

class warp.fem.Grid2D(res, bounds_lo=None, bounds_hi=None)#

Bases: Geometry

Two-dimensional regular grid geometry

Constructs a dense 2D grid

Parameters:

res (vec2i) – Resolution of the grid along each dimension
bounds_lo (vec2f | None) – Position of the lower bound of the axis-aligned grid
bounds_up – Position of the upper bound of the axis-aligned grid
bounds_hi (vec2f | None) –

class warp.fem.Trimesh2D(tri_vertex_indices, positions, temporary_store=None)#

Bases: Geometry

Two-dimensional triangular mesh geometry

Constructs a two-dimensional triangular mesh.

Parameters:

tri_vertex_indices (array) – warp array of shape (num_tris, 3) containing vertex indices for each tri
positions (array) – warp array of shape (num_vertices, 2) containing 2d position for each vertex
temporary_store (TemporaryStore | None) – shared pool from which to allocate temporary arrays

class warp.fem.Quadmesh2D(quad_vertex_indices, positions, temporary_store=None)#

Bases: Geometry

Two-dimensional quadrilateral mesh geometry

Constructs a two-dimensional quadrilateral mesh.

Parameters:

quad_vertex_indices (array) – warp array of shape (num_tris, 4) containing vertex indices for each quad, in counter-clockwise order
positions (array) – warp array of shape (num_vertices, 2) containing 2d position for each vertex
temporary_store (TemporaryStore | None) – shared pool from which to allocate temporary arrays

class warp.fem.Grid3D(res, bounds_lo=None, bounds_hi=None)#

Bases: Geometry

Three-dimensional regular grid geometry

Constructs a dense 3D grid

Parameters:

res (vec3i) – Resolution of the grid along each dimension
bounds_lo (vec3f | None) – Position of the lower bound of the axis-aligned grid
bounds_up – Position of the upper bound of the axis-aligned grid
bounds_hi (vec3f | None) –

class warp.fem.Tetmesh(tet_vertex_indices, positions, temporary_store=None)#

Bases: Geometry

Tetrahedral mesh geometry

Constructs a tetrahedral mesh.

Parameters:

tet_vertex_indices (array) – warp array of shape (num_tets, 4) containing vertex indices for each tet
positions (array) – warp array of shape (num_vertices, 3) containing 3d position for each vertex
temporary_store (TemporaryStore | None) – shared pool from which to allocate temporary arrays

class warp.fem.Hexmesh(hex_vertex_indices, positions, temporary_store=None)#

Bases: Geometry

Hexahedral mesh geometry

Constructs a tetrahedral mesh.

Parameters:

hex_vertex_indices (array) – warp array of shape (num_hexes, 8) containing vertex indices for each hex following standard ordering (bottom face vertices in counter-clockwise order, then similarly for upper face)
positions (array) – warp array of shape (num_vertices, 3) containing 3d position for each vertex
temporary_store (TemporaryStore | None) – shared pool from which to allocate temporary arrays

class warp.fem.LinearGeometryPartition(geometry, partition_rank, partition_count, device=None, temporary_store=None)#

Creates a geometry partition by uniformly partionning cell indices

Parameters:

geometry (Geometry) – the geometry to partition
partition_rank (int) – the index of the partition being created
partition_count (int) – the number of partitions that will be created over the geometry
device – Warp device on which to perform and store computations
temporary_store (TemporaryStore) –

class warp.fem.ExplicitGeometryPartition(geometry, cell_mask, temporary_store=None)#

Creates a geometry partition by uniformly partionning cell indices

Parameters:

geometry (Geometry) – the geometry to partition
cell_mask (wp.array(dtype=int)) – warp array of length geometry.cell_count() indicating which cells are selected. Array values must be either 1 (selected) or 0 (not selected).
temporary_store (TemporaryStore) –

class warp.fem.Cells(geometry)#

Bases: GeometryDomain

A Domain containing all cells of the geometry or geometry partition

Parameters:: geometry (Geometry | GeometryPartition) –

class warp.fem.Sides(geometry)#

Bases: GeometryDomain

A Domain containing all (interior and boundary) sides of the geometry or geometry partition

Parameters:: geometry (Geometry | GeometryPartition) –

class warp.fem.BoundarySides(geometry)#

Bases: Sides

A Domain containing boundary sides of the geometry or geometry partition

Parameters:: geometry (Geometry | GeometryPartition) –

class warp.fem.FrontierSides(geometry)#

Bases: Sides

A Domain containing frontier sides of the geometry partition (sides shared with at least another partition)

Parameters:: geometry (Geometry | GeometryPartition) –

class warp.fem.Polynomial(value)#

Polynomial family defining interpolation nodes over an interval

GAUSS_LEGENDRE = 0#: Gauss–Legendre 1D polynomial family (does not include endpoints)

LOBATTO_GAUSS_LEGENDRE = 1#: Lobatto–Gauss–Legendre 1D polynomial family (includes endpoints)

EQUISPACED_CLOSED = 2#: Closed 1D polynomial family with uniformly distributed nodes (includes endpoints)

EQUISPACED_OPEN = 3#: Open 1D polynomial family with uniformly distributed nodes (does not include endpoints)

class warp.fem.RegularQuadrature(domain, order, family=None)#

Bases: Quadrature

Regular quadrature formula, using a constant set of quadrature points per element

Parameters:

domain (GeometryDomain) –
order (int) –
family (Polynomial) –

class warp.fem.NodalQuadrature(domain, space)#

Bases: Quadrature

Quadrature using space node points as quadrature points

Note that in contrast to the nodal=True flag for integrate(), this quadrature odes not make any assumption about orthogonality of shape functions, and is thus safe to use for arbitrary integrands.

Parameters:

domain (GeometryDomain) –
space (FunctionSpace) –

class warp.fem.ExplicitQuadrature(domain, points, weights)#

Bases: Quadrature

Quadrature using explicit per-cell points and weights. The number of quadrature points per cell is assumed to be constant and deduced from the shape of the points and weights arrays.

Parameters:

domain (GeometryDomain) – Domain of definition of the quadrature formula
points (wp.array2d(dtype=Coords)) – 2d array of shape (domain.geometry_element-count(), points_per_cell) containing the coordinates of each quadrature point.
weights (wp.array2d(dtype=float)) – 2d array of shape (domain.geometry_element-count(), points_per_cell) containing the weight for each quadrature point.

Function Spaces#

warp.fem.make_polynomial_space(geo, dtype=<class 'float'>, dof_mapper=None, degree=1, element_basis=None, discontinuous=False, family=None)#

Equips a geometry with a collocated, polynomial function space. Equivalent to successive calls to make_polynomial_basis_space() and make_collocated_function_space.

Parameters:

geo (Geometry) – the Geometry on which to build the space
dtype (type) – value type the function space. If dof_mapper is provided, the value type from the DofMapper will be used instead.
dof_mapper (DofMapper | None) – mapping from node degrees of freedom to function values, defaults to Identity. Useful for reduced coordinates, e.g. SymmetricTensorMapper maps 2x2 (resp 3x3) symmetric tensors to 3 (resp 6) degrees of freedom.
degree (int) – polynomial degree of the per-element shape functions
discontinuous (bool) – if True, use Discontinuous Galerkin shape functions. Discontinuous is implied if degree is 0, i.e, piecewise-constant shape functions.
element_basis (ElementBasis | None) – type of basis function for the individual elements
family (Polynomial | None) – Polynomial family used to generate the shape function basis. If not provided, a reasonable basis is chosen.

Returns:

the constructed function space

Return type:

CollocatedFunctionSpace

warp.fem.make_polynomial_basis_space(geo, degree=1, element_basis=None, discontinuous=False, family=None)#

Equips a geometry with a polynomial basis.

Parameters:

geo (Geometry) – the Geometry on which to build the space
degree (int) – polynomial degree of the per-element shape functions
discontinuous (bool) – if True, use Discontinuous Galerkin shape functions. Discontinuous is implied if degree is 0, i.e, piecewise-constant shape functions.
element_basis (ElementBasis | None) – type of basis function for the individual elements
family (Polynomial | None) – Polynomial family used to generate the shape function basis. If not provided, a reasonable basis is chosen.

Returns:

the constructed basis space

Return type:

BasisSpace

warp.fem.make_collocated_function_space(basis_space, dtype=<class 'float'>, dof_mapper=None)#

Constructs a function space from a basis space and a value type, such that all degrees of freedom of the value type are stored at each of the basis nodes.

Parameters:

geo – the Geometry on which to build the space
dtype (type) – value type the function space. If dof_mapper is provided, the value type from the DofMapper will be used instead.
dof_mapper (DofMapper | None) – mapping from node degrees of freedom to function values, defaults to Identity. Useful for reduced coordinates, e.g. SymmetricTensorMapper maps 2x2 (resp 3x3) symmetric tensors to 3 (resp 6) degrees of freedom.
basis_space (BasisSpace) –

Returns:

the constructed function space

Return type:

CollocatedFunctionSpace

warp.fem.make_space_partition(space=None, geometry_partition=None, space_topology=None, with_halo=True, device=None, temporary_store=None)#

Computes the subset of nodes from a function space topology that touch a geometry partition

Either space_topology or space must be provided (and will be considered in that order).

Parameters:

space (FunctionSpace | None) – (deprecated) the function space defining the topology if space_topology is None.
geometry_partition (GeometryPartition | None) – The subset of the space geometry. If not provided, use the whole geometry.
space_topology (SpaceTopology | None) – the topology of the function space to consider. If None, deduced from space.
with_halo (bool) – if True, include the halo nodes (nodes from exterior frontier cells to the partition)
device – Warp device on which to perform and store computations
temporary_store (TemporaryStore | None) –

Returns:

the resulting space partition

Return type:

SpacePartition

warp.fem.make_space_restriction(space=None, space_partition=None, domain=None, space_topology=None, device=None, temporary_store=None)#

Restricts a function space partition to a Domain, i.e. a subset of its elements.

One of space_partition, space_topology, or space must be provided (and will be considered in that order).

Parameters:

space (FunctionSpace | None) – (deprecated) if neither space_partition nor space_topology are provided, the space defining the topology to restrict
space_partition (SpacePartition | None) – the subset of nodes from the space topology to consider
domain (GeometryDomain | None) – the domain to restrict the space to, defaults to all cells of the space geometry or partition.
space_topology (SpaceTopology | None) – the space topology to be restricted, if space_partition is None.
device – device on which to perform and store computations
temporary_store (Optional[warp.fem.cache.TemporaryStore]) – shared pool from which to allocate temporary arrays

Return type:

SpaceRestriction

class warp.fem.ElementBasis(value)#

Choice of basis function to equip individual elements

LAGRANGE = 0#: Lagrange basis functions \(P_k\) for simplices, tensor products \(Q_k\) for squares and cubes

SERENDIPITY = 1#: Serendipity elements \(S_k\), corresponding to Lagrange nodes with interior points removed (for degree <= 3)

NONCONFORMING_POLYNOMIAL = 2#: Simplex Lagrange basis functions \(P_{kd}\) embedded into non conforming reference elements (e.g. squares or cubes). Discontinuous only.

class warp.fem.SymmetricTensorMapper(dtype, mapping=Mapping.VOIGT)#

Bases: DofMapper

Orthonormal isomorphism from R^{n (n+1)} to nxn symmetric tensors, using usual L2 norm for vectors and half Frobenius norm, (tau : tau)/2 for tensors.

Parameters:

dtype (type) –
mapping (Mapping) –

class warp.fem.SkewSymmetricTensorMapper(dtype)#

Bases: DofMapper

Orthonormal isomorphism from R^{n (n-1)} to nxn skew-symmetric tensors, using usual L2 norm for vectors and half Frobenius norm, (tau : tau)/2 for tensors.

Parameters:: dtype (type) –

class warp.fem.PointBasisSpace(quadrature)#

Bases: BasisSpace

An unstructured BasisSpace that is non-zero at a finite set of points only.

The node locations and nodal quadrature weights are defined by a Quadrature formula.

Parameters:: quadrature (Quadrature) –

Fields#

warp.fem.make_test(space, space_restriction=None, space_partition=None, domain=None, device=None)#

Constructs a test field over a function space or its restriction

Parameters:

space (FunctionSpace) – the function space
space_restriction (SpaceRestriction | None) – restriction of the space topology to a domain
space_partition (SpacePartition | None) – if space_restriction is None, the optional subset of node indices to consider
domain (GeometryDomain | None) – if space_restriction is None, optional subset of elements to consider
device – Warp device on which to perform and store computations

Returns:

the test field

Return type:

TestField

warp.fem.make_trial(space, space_restriction=None, space_partition=None, domain=None)#

Constructs a trial field over a function space or partition

Parameters:

space (FunctionSpace) – the function space or function space restriction
space_restriction (SpaceRestriction | None) – restriction of the space topology to a domain
space_partition (SpacePartition | None) – if space_restriction is None, the optional subset of node indices to consider
domain (GeometryDomain | None) – if space_restriction is None, optional subset of elements to consider
device – Warp device on which to perform and store computations

Returns:

the trial field

Return type:

TrialField

warp.fem.make_restriction(field, space_restriction=None, domain=None, device=None)#

Restricts a discrete field to a subset of elements.

Parameters:

field (DiscreteField) – the discrete field to restrict
space_restriction (SpaceRestriction | None) – the function space restriction defining the subset of elements to consider
domain (GeometryDomain | None) – if space_restriction is not provided, the Domain defining the subset of elements to consider
device – Warp device on which to perform and store computations

Returns:

the field restriction

Return type:

FieldRestriction

Boundary Conditions#

warp.fem.normalize_dirichlet_projector(projector_matrix, fixed_value=None)#

Scale projector so that it becomes idempotent, and apply the same scaling to fixed_value if provided

Parameters:

projector_matrix (BsrMatrix) –
fixed_value (array | None) –

warp.fem.project_linear_system(system_matrix, system_rhs, projector_matrix, fixed_value=None, normalize_projector=True)#

Projects both the left-hand-side and right-hand-side of a linear system to enforce Dirichlet boundary conditions

If normalize_projector is True, first apply scaling so that the projector_matrix is idempotent

Parameters:

system_matrix (BsrMatrix) –
system_rhs (array) –
projector_matrix (BsrMatrix) –
fixed_value (array | None) –

Memory management#

warp.fem.set_default_temporary_store(temporary_store)#

Globally sets the default TemporaryStore instance to use for temporary allocations in warp.fem functions.

If the default temporary store is set to None, temporary allocations are not persisted unless a TemporaryStore is provided at a per-function granularity.

Parameters:: temporary_store (TemporaryStore | None) –

warp.fem.borrow_temporary(temporary_store, shape, dtype, pinned=False, requires_grad=False, device=None)#

Borrows and returns a temporary array with specified attributes from a shared pool.

If an array with sufficient capacity and matching desired attributes is already available in the pool, it will be returned. Otherwise, a new allocation will be performed.

Parameters:

temporary_store (TemporaryStore | None) – the shared pool to borrow the temporary from. If temporary_store is None, the global default temporary store, if set, will be used.
shape (int | Tuple[int]) – desired dimensions for the temporary array
dtype (type) – desired data type for the temporary array
pinned (bool) – whether a pinned allocation is desired
device – device on which the memory should be allocated; if None, the current device will be used.
requires_grad (bool) –

Return type:

Temporary

warp.fem.borrow_temporary_like(array, temporary_store)#

Borrows and returns a temporary array with the same attributes as another array or temporary.

Parameters:

array (array | Temporary) – Warp or temporary array to read the desired attributes from
temporary_store (TemporaryStore | None) – the shared pool to borrow the temporary from. If temporary_store is None, the global default temporary store, if set, will be used.

Return type:

Temporary

Interfaces#

Interface classes are not meant to be constructed directly, but can be derived from extend the built-in functionality.

class warp.fem.Geometry#

Interface class for discrete geometries

A geometry is composed of cells and sides. Sides may be boundary or interior (between cells).

cell_count()#: Number of cells in the geometry

side_count()#: Number of sides in the geometry

boundary_side_count()#: Number of boundary sides (sides with a single neighbour cell) in the geometry

class warp.fem.GeometryPartition(geometry)#

Base class for geometry partitions, i.e. subset of cells and sides

Parameters:: geometry (Geometry) –

cell_count()#

Number of cells that are ‘owned’ by this partition

Return type:: int

side_count()#

Number of sides that are ‘owned’ by this partition

Return type:: int

boundary_side_count()#

Number of geo-boundary sides that are ‘owned’ by this partition

Return type:: int

frontier_side_count()#

Number of sides with neighbors owned by this and another partition

Return type:: int

class warp.fem.GeometryDomain(geometry)#

Interface class for domains, i.e. (partial) views of elements in a Geometry

Parameters:: geometry (Geometry | GeometryPartition) –

class ElementKind(value)#: Possible kinds of elements contained in a domain

property element_kind: ElementKind#: Kind of elements that this domain contains (cells or sides)

property dimension: int#: Dimension of the elements of the domain

element_count()#

Number of elements in the domain

Return type:: int

class warp.fem.Quadrature(domain)#

Interface class for quadrature rules

Parameters:: domain (GeometryDomain) –

property domain#: Domain over which this quadrature is defined

total_point_count()#: Total number of quadrature points over the domain

class warp.fem.FunctionSpace(topology)#

Interface class for function spaces, i.e. geometry + interpolation basis

Parameters:: topology (SpaceTopology) –

dtype: type#: Value type of the interpolation functions

property topology: SpaceTopology#: Underlying geometry

property geometry: Geometry#: Underlying geometry

property dimension: int#: Function space embedding dimension

property degree: int#: Maximum polynomial degree of the underlying basis

trace()#

Trace of the function space over lower-dimensional elements of the geometry

Return type:: FunctionSpace

make_field(space_partition=None)#

Creates a zero-initialized discrete field over the function space holding values for all degrees of freedom of nodes in a space partition

space_arg:: space_partition: If provided, the subset of nodes to consider