graph_primitives

Edge metadata and graph error definitions.

pysatl_core.distributions.registry.graph_primitives.DEFAULT_COMPUTATION_KEY: LabelName = 'PySATL_default_computation'

Default label for computation edges when no specific label is provided.

class pysatl_core.distributions.registry.graph_primitives.EdgeMeta(method, constraint=<factory>, is_analytical=False)[source]

Bases: ABC

Metadata for a computation edge in the characteristic graph.

Parameters:

  • method (EdgeMethod) – The computation method that defines the edge.

  • constraint (GraphPrimitiveConstraint) – Constraint determining when this edge is applicable to a distribution. Defaults to a pass-through constraint that always allows.

  • is_analytical (bool) – Whether this edge represents an analytical computation.

method: TypeAliasType
constraint: GraphPrimitiveConstraint
is_analytical: bool
abstract edge_kind()[source]

Return edge kind identifier.

Return type:

str

__init__(method, constraint=<factory>, is_analytical=False)
Parameters:
Return type:

None

class pysatl_core.distributions.registry.graph_primitives.ComputationEdgeMeta(method, constraint=<factory>, is_analytical=False, options_descriptor=<factory>)[source]

Bases: EdgeMeta

Edge metadata for conversion computations from the registry graph.

The options_descriptor field stores the compact, graph-level form of the originating FitterDescriptor / EvaluatorDescriptor options. The strategy uses it to resolve user-supplied **options for this specific edge while walking a conversion path, without touching the heavy descriptor object or rebuilding edges.

Edges declared programmatically (e.g. in tests) without an originating descriptor get a default empty EdgeOptionsDescriptor, which behaves as a no-op during option resolution.

Parameters:
options_descriptor: EdgeOptionsDescriptor
edge_kind()[source]

Return edge kind identifier.

Return type:

str

__init__(method, constraint=<factory>, is_analytical=False, options_descriptor=<factory>)
Parameters:
Return type:

None

class pysatl_core.distributions.registry.graph_primitives.AnalyticalLoopEdgeMeta(method, constraint=<factory>, is_analytical=True)[source]

Bases: EdgeMeta

Edge metadata for self-loop analytical computations from a distribution.

Parameters:
edge_kind()[source]

Return edge kind identifier.

Return type:

str

__init__(method, constraint=<factory>, is_analytical=True)
Parameters:
Return type:

None

class pysatl_core.distributions.registry.graph_primitives.TransformationLoopEdgeMeta(method, constraint=<factory>, is_analytical=False)[source]

Bases: EdgeMeta

Edge metadata for transformation-provided self-loops.

Such loops are attached from analytical_computations as regular stopping points for the strategy, but they are not considered fully analytical by the graph semantics.

Parameters:
edge_kind()[source]

Return edge kind identifier.

Return type:

str

__init__(method, constraint=<factory>, is_analytical=False)
Parameters:
Return type:

None

exception pysatl_core.distributions.registry.graph_primitives.GraphInvariantError[source]

Bases: RuntimeError

Raised when characteristic graph invariants are violated.

This error occurs when creating a RegistryView and the filtered graph does not satisfy the required invariants (e.g., definitive subgraph is not strongly connected).