GenerationResult

Symbolica documentation for getting started, symbolic expressions, numerical evaluation, pattern matching, and APIs in Python and Rust.

`GenerationResult`

class GenerationResult

Feynman diagrams and diagnostics produced for one process.

The result retains generated diagrams in deterministic order and may also contain numerator-equivalence groups for efficient downstream evaluation.

Examples

from symbolica import S, E
from symbolica.community import hepkit as hep
model = hep.Model.phi4()
process = model.process(["phi", "phi"], ["phi", "phi"])
result = process.generate_diagrams(loops=1)
diagram = result.diagrams[0]
diagrams = result.diagrams
assert result.report.retained_count == len(diagrams)

Attributes

Name	Description
`diagrams`	Return every retained diagram in generated order.
`groups`	Return the numerator groups in deterministic master-index order.
`report`	Return generation counts and completion status.

`diagrams`

GenerationResult.diagrams: builtins.list[FeynmanDiagram]

Return every retained diagram in generated order.

Examples

Using the setup in the GenerationResult class example:

numerators = [diagram.numerator_expression() for diagram in result.diagrams]

`groups`

GenerationResult.groups: builtins.list[DiagramGroup]

Return the numerator groups in deterministic master-index order.

Examples

Using the setup in the GenerationResult class example:

masters = [result.diagrams[group.master] for group in result.groups]

`report`

GenerationResult.report: GenerationReport

Return generation counts and completion status.

Examples

Using the setup in the GenerationResult class example:

assert result.report.completed

Methods

Name	Description
`__getitem__`	Return one retained diagram by generated-order index.
`__iter__`	Iterate over retained diagrams in deterministic generated order.
`__len__`	Return the number of retained diagrams.
`__repr__`	Return a concise summary of the retained diagrams and groups.
`_repr_html_`	Render a thumbnail strip and one shared interactive diagram viewer
`_repr_pretty_`	Write a concise result summary to an IPython pretty printer.

`getitem`

GenerationResult.__getitem__(index: builtins.int) -> FeynmanDiagram

Return one retained diagram by generated-order index.

Examples

Using the setup in the GenerationResult class example:

first_diagram = result[0]

Parameters

index (int) Zero-based index; negative indices count from the end.

`iter`

GenerationResult.__iter__() -> collections.abc.Iterator[FeynmanDiagram]

Iterate over retained diagrams in deterministic generated order.

Examples

Using the setup in the GenerationResult class example:

one_loop = [diagram for diagram in result if diagram.loop_count == 1]

`len`

GenerationResult.__len__() -> builtins.int

Return the number of retained diagrams.

Examples

Using the setup in the GenerationResult class example:

number_of_diagrams = len(result)

`repr`

GenerationResult.__repr__() -> builtins.str

Return a concise summary of the retained diagrams and groups.

Examples

Using the setup in the GenerationResult class example:

print(result)

`_repr_html_`

GenerationResult._repr_html_() -> builtins.str

Render a thumbnail strip and one shared interactive diagram viewer.

At most six diagrams are rendered so that displaying a large generation result remains responsive. Access result.diagrams to inspect the complete collection.

Examples

Using the setup in the GenerationResult class example:

from IPython.display import display
display(result)

`_repr_pretty_`

GenerationResult._repr_pretty_(pretty: typing.Any, cycle: builtins.bool) -> None

Write a concise result summary to an IPython pretty printer.

Examples

Using the setup in the GenerationResult class example:

from IPython.lib.pretty import pretty
text = pretty(result)

Parameters

pretty (object) The IPython pretty-printer object.
cycle (bool) Whether this object is part of a recursive formatting cycle.