BroadcastFunction

symbolica.community.spenso Class

BroadcastFunction(name: str, *, is_symmetric: Optional[bool] = None, is_antisymmetric: Optional[bool] = None, is_cyclesymmetric: Optional[bool] = None, is_linear: Optional[bool] = None, is_flat: Optional[bool] = None, is_scalar: Optional[bool] = None, is_real: Optional[bool] = None, is_integer: Optional[bool] = None, is_positive: Optional[bool] = None, tags: Optional[Sequence[str]] = None, aliases: Optional[Sequence[str]] = None, normalization: Optional[Transformer | Callable[[Expression], Expression]] = None, print: Optional[Any] = None, derivative: Optional[Any] = None, series: Optional[Any] = None, eval: Optional[Any] = None, data: Optional[Expression | int | Float | int | float | str | decimal.Decimal | ComplexFloat | Float | int | float | str | decimal.Decimal | complex | tuple[Float | int | float | str | decimal.Decimal, Float | int | float | str | decimal.Decimal] | str | dict | list | bytes] = None)

A unary Symbolica function whose action is broadcast over tensor entries.

Constructor

The function is always tagged as a Spenso broadcast and cannot also be a tensor head.

Parameters

Name	Type	Default	Description
`name`	`str`	`—`	—
`is_symmetric`	`Optional[bool]`	`None`	—
`is_antisymmetric`	`Optional[bool]`	`None`	—
`is_cyclesymmetric`	`Optional[bool]`	`None`	—
`is_linear`	`Optional[bool]`	`None`	—
`is_flat`	`Optional[bool]`	`None`	—
`is_scalar`	`Optional[bool]`	`None`	—
`is_real`	`Optional[bool]`	`None`	—
`is_integer`	`Optional[bool]`	`None`	—
`is_positive`	`Optional[bool]`	`None`	—
`tags`	`Optional[Sequence[str]]`	`None`	—
`aliases`	`Optional[Sequence[str]]`	`None`	—
`normalization`	`Optional[Transformer \| Callable[[Expression], Expression]]`	`None`	—
`print`	`Optional[Any]`	`None`	—
`derivative`	`Optional[Any]`	`None`	—
`series`	`Optional[Any]`	`None`	—
`eval`	`Optional[Any]`	`None`	—
`data`	`Optional[Expression \| int \| Float \| int \| float \| str \| decimal.Decimal \| ComplexFloat \| Float \| int \| float \| str \| decimal.Decimal \| complex \| tuple[Float \| int \| float \| str \| decimal.Decimal, Float \| int \| float \| str \| decimal.Decimal] \| str \| dict \| list \| bytes]`	`None`	—

Member details

`conj`

Static method

conj() -> BroadcastFunction

Return Spenso's registered complex-conjugation broadcast function.

`repr`

Method

__repr__() -> str

No description is available for this member.

`str`

Method

__str__() -> str

No description is available for this member.

`to_expression`

Method

to_expression() -> Expression

Return the registered function as a Symbolica variable expression.

`has_tag`

Method

has_tag(tag: str) -> bool

Whether the registered function carries tag.

Unqualified names also match tags registered in Symbolica's Python namespace.

Parameters

Name	Type	Default	Description
`tag`	`str`	`—`	—

`get_tags`

Method

get_tags() -> list[str]

Return the fully qualified tags attached to the registered function.

`call`

Method

Overloads

Overload 1 #

__call__(arg: Tensor | TensorNetwork) -> TensorNetwork

Apply this unary function lazily to a concrete tensor or tensor network.

Parameters

Name	Type	Default	Description
`arg`	`Tensor \| TensorNetwork`	`—`	—

Overload 2 #

__call__(arg: TensorExpression) -> TensorExpression

Apply this unary function elementwise, preserving a structured interface.

Parameters

Name	Type	Default	Description
`arg`	`TensorExpression`	`—`	—

Overload 3 #

__call__(arg: Expression | int | Float | int | float | str | decimal.Decimal | ComplexFloat | Float | int | float | str | decimal.Decimal | complex | tuple[Float | int | float | str | decimal.Decimal, Float | int | float | str | decimal.Decimal]) -> Expression

Apply this unary function to an ordinary scalar expression.

Parameters

Name	Type	Default	Description
`arg`	`Expression \| int \| Float \| int \| float \| str \| decimal.Decimal \| ComplexFloat \| Float \| int \| float \| str \| decimal.Decimal \| complex \| tuple[Float \| int \| float \| str \| decimal.Decimal, Float \| int \| float \| str \| decimal.Decimal]`	`—`	—

View generated signature source: docs/api/python/spynso3.pyi:15