gdsfactory.cross_section.Transition

class gdsfactory.cross_section.Transition(*, sections: tuple[Section, ...] = None, components_along_path: tuple[ComponentAlongPath, ...] = None, radius: float | None = None, radius_min: float | None = None, bbox_layers: list[tuple[int, int] | str] | tuple[tuple[int, int] | str, ...] | None = None, bbox_offsets: tuple[float, ...] | None = None, cross_section1: CrossSection | str | dict[str, Any] | Callable[[...], CrossSection], cross_section2: CrossSection | str | dict[str, Any] | Callable[[...], CrossSection], width_type: Literal['sine', 'linear', 'parabolic'] | Callable = 'sine')

Waveguide information to extrude a path between two CrossSection.

cladding_layers follow path shape

Parameters:

• cross_section1 – input cross_section.

• cross_section2 – output cross_section.

• width_type – sine or linear. Sets the type of width transition used if widths are different between the two input CrossSections.

__init__(**data: Any) → None

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Methods

__init__(**data)	Create a new model by parsing and validating input data from keyword arguments.
add_bbox(component[, top, bottom, right, left])	Add bounding box layers to a component.
add_pins(component, *args, **kwargs)	Add pins to a target component according to CrossSection.
append_sections(sections)
construct([_fields_set])
copy([width, layer, width_function, ...])	Returns copy of the cross_section with new parameters.
dict(*[, include, exclude, by_alias, ...])
from_orm(obj)
get_xmin_xmax()	Returns the min and max extent of the cross_section across all sections.
json(*[, include, exclude, by_alias, ...])
mirror()	Returns a mirrored copy of the cross_section.
model_construct([_fields_set])	Creates a new instance of the Model class with validated data.
model_copy(*[, update, deep])	Usage docs: https://docs.pydantic.dev/2.7/concepts/serialization/#model_copy
model_dump(*[, mode, include, exclude, ...])	Usage docs: https://docs.pydantic.dev/2.7/concepts/serialization/#modelmodel_dump
model_dump_json(*[, indent, include, ...])	Usage docs: https://docs.pydantic.dev/2.7/concepts/serialization/#modelmodel_dump_json
model_json_schema([by_alias, ref_template, ...])	Generates a JSON schema for a model class.
model_parametrized_name(params)	Compute the class name for parametrizations of generic classes.
model_post_init(_BaseModel__context)	Override this method to perform additional initialization after __init__ and model_construct.
model_rebuild(*[, force, raise_errors, ...])	Try to rebuild the pydantic-core schema for the model.
model_validate(obj, *[, strict, ...])	Validate a pydantic model instance.
model_validate_json(json_data, *[, strict, ...])	Usage docs: https://docs.pydantic.dev/2.7/concepts/json/#json-parsing
model_validate_strings(obj, *[, strict, context])	Validate the given object contains string data against the Pydantic model.
parse_file(path, *[, content_type, ...])
parse_obj(obj)
parse_raw(b, *[, content_type, encoding, ...])
schema([by_alias, ref_template])
schema_json(*[, by_alias, ref_template])
serialize_width(width_type)
update_forward_refs(**localns)
validate(value)
validate_radius(radius[, error_type])

Attributes

layer
model_computed_fields	A dictionary of computed field names and their corresponding ComputedFieldInfo objects.
model_config	Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
model_extra	Get extra fields set during validation.
model_fields	Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].
model_fields_set	Returns the set of fields that have been explicitly set on this model instance.
name
width
cross_section1
cross_section2
width_type
sections
components_along_path
radius
radius_min
bbox_layers
bbox_offsets