gdsfactory.technology.LogicalLayer

gdsfactory.technology.LogicalLayer#

class gdsfactory.technology.LogicalLayer(*, sizings_xoffsets: Sequence[int] = (0,), sizings_yoffsets: Sequence[int] = (0,), sizings_modes: Sequence[int] = (2,), layer: tuple[int, int] | str | int | LayerEnum)[source]#

GDS design layer.

__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.

construct([_fields_set])

copy(*[, include, exclude, update, deep])

Returns a copy of the model.

dict(*[, include, exclude, by_alias, ...])

from_orm(obj)

get_shapes(component)

Return the shapes of the component argument corresponding to this layer.

json(*[, include, exclude, by_alias, ...])

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/2.10/concepts/serialization/#model_copy

model_dump(*[, mode, include, exclude, ...])

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

model_dump_json(*[, indent, include, ...])

Usage docs: https://docs.pydantic.dev/2.10/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/2.10/concepts/json/#json-parsing

model_validate_strings(obj, *[, strict, context])

Validate the given object with 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])

sized(xoffset[, yoffset, mode])

Accumulates a list of sizing operations for the layer by the provided offset (in dbu).

update_forward_refs(**localns)

validate(value)

Attributes

model_computed_fields

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

model_fields_set

Returns the set of fields that have been explicitly set on this model instance.

layer

sizings_xoffsets

sizings_yoffsets

sizings_modes