synpivimage.laser.Laser

class synpivimage.laser.Laser(*, shape_factor, width)

Laser class. This class will be used to illuminate the particles.

Note

The Gaussian distribution is found for shape_factor=1, not =2 as in the literature (which is wrong, e.g. see Raffel et al.)! width is the width of the laser, where the intensity drops to 0.67, i.e. not the effective laser width, with is defined by the noise level or where the intensity drops to e^(-1).

__init__(**data)

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)
illuminate(particles, **kwargs)	Illuminate the particles.
json(*[, include, exclude, by_alias, ...])
load_jsonld(filename)	Load the Laser from a JSON-LD file
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/2.9/concepts/serialization/#model_copy
model_dump(*[, mode, include, exclude, ...])	Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump
model_dump_json(*[, indent, include, ...])	Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json
model_dump_jsonld()	Return JSON-LD string representation
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/2.9/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, ...])
save_json(filename)	Save the component to JSON
save_jsonld(filename)	Save the component to JSON.
schema([by_alias, ref_template])
schema_json(*[, by_alias, ref_template])
update_forward_refs(**localns)
validate(value)

Attributes

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] objects.
model_fields_set	Returns the set of fields that have been explicitly set on this model instance.
shape_factor
width