ufl.corealg package

Submodules

ufl.corealg.dag_traverser module

Base class for dag traversers.

class ufl.corealg.dag_traverser.DAGTraverser(compress: bool | None = True, visited_cache: dict[tuple, Expr] | None = None, result_cache: dict[Expr, Expr] | None = None)

Bases: object

Base class for DAG traversers.

Args:

compress: If True, result_cache will be used. visited_cache: cache of intermediate results; expr -> r = self.process(expr, …). result_cache: cache of result objects for memory reuse, r -> r.

static postorder(method)

Postorder decorator.

It is more natural for users to write a post-order singledispatchmethod whose arguments are (self, o, *processed_operands, *additional_args), while DAGTraverser expects one whose arguments are (self, o, *additional_args). This decorator takes the former and converts the latter, processing o.ufl_operands behind the users.

static postorder_only_children(indices)

Postorder decorator with child indices.

This decorator is the same as DAGTraverser.postorder except that the decorated method is only to take processed operands corresponding to indices.

process(o: Expr, *args) → Expr

Process node by type.

Args:

o: Expr to start DAG traversal from. args: arguments to the process singledispatchmethod.

Returns:

Processed Expr.

reuse_if_untouched(o: Expr) → Expr

Reuse if touched.

Args:

o: Expr to start DAG traversal from. new_ufl_operands: new ufl_operands of o.

Returns:

Processed Expr.

ufl.corealg.map_dag module

Basic algorithms for applying functions to subexpressions.

ufl.corealg.map_dag.map_expr_dag(function, expression, compress=True, vcache=None, rcache=None)

Apply a function to each subexpression node in an expression DAG.

If the same function is called multiple times in a transformation (as for example in apply_derivatives), then to reuse caches across the call, use the arguments vcache and rcache.

Args:

function: The function expression: An expression compress: If True (default), the output object from

the function is cached in a dict and reused such that the resulting expression DAG does not contain duplicate objects

vcache: Optional dict for caching results of intermediate

transformations

rcache: Optional dict for caching results for compression

Returns:

The result of the final function call

ufl.corealg.map_dag.map_expr_dags(function, expressions, compress=True, vcache=None, rcache=None)

Apply a function to each sub-expression node in an expression DAG.

If compress is True (default) the output object from the function is cached in a dict and reused such that the resulting expression DAG does not contain duplicate objects.

If the same function is called multiple times in a transformation (as for example in apply_derivatives), then to reuse caches across the call, use the arguments vcache and rcache.

Args:

function: The function expressions: An expression compress: If True (default), the output object from

the function is cached in a dict and reused such that the resulting expression DAG does not contain duplicate objects

vcache: Optional dict for caching results of intermediate transformations rcache: Optional dict for caching results for compression

Returns:

a list with the result of the final function call for each expression

ufl.corealg.multifunction module

Base class for multifunctions with UFL Expr type dispatch.

class ufl.corealg.multifunction.MultiFunction

Bases: object

Base class for collections of non-recursive expression node handlers.

Subclass this (remember to call the __init__ method of this class), and implement handler functions for each Expr type, using the lower case handler name of the type (exprtype._ufl_handler_name_).

This class is optimized for efficient type based dispatch in the __call__ operator via typecode based lookup of the handler function bound to the algorithm object. Of course Python’s function call overhead still applies.

reuse_if_untouched(o, *ops)

Reuse object if operands are the same objects.

Use in your own subclass by setting e.g.

expr = MultiFunction.reuse_if_untouched

as a default rule.

ufl_type(o, *args)

Trigger error for types with missing handlers.

undefined(o, *args)

Trigger error for types with missing handlers.

ufl.corealg.multifunction.get_num_args(function)

Return the number of arguments accepted by function.

ufl.corealg.multifunction.memoized_handler(handler)

Function decorator to memoize MultiFunction handlers.

ufl.corealg.traversal module

Various expression traversal utilities.

The algorithms here are non-recursive, which is faster than recursion by a factor of 10 or so because of the function call overhead.

ufl.corealg.traversal.cutoff_post_traversal(expr, cutofftypes)

Cut-off post-tranversal.

Yield o for each node o in expr, child before parent, but skipping subtrees of the cutofftypes.

ufl.corealg.traversal.cutoff_unique_post_traversal(expr, cutofftypes, visited=None)

Yield o for each node o in expr, child before parent.

Never visit a node twice.

ufl.corealg.traversal.post_traversal(expr)

Yield o for each node o in expr, child before parent.

ufl.corealg.traversal.pre_traversal(expr)

Yield o for each tree node o in expr, parent before child.

ufl.corealg.traversal.traverse_terminals(expr)

Traverse terminals.

ufl.corealg.traversal.traverse_unique_terminals(expr, visited=None)

Traverse unique terminals.

ufl.corealg.traversal.unique_post_traversal(expr, visited=None)

Yield o for each node o in expr, child before parent.

Never visit a node twice.

ufl.corealg.traversal.unique_pre_traversal(expr, visited=None)

Yield o for each tree node o in expr, parent before child.

This version only visits each node once.

Module contents

Core algorithms.