Segment

class caf.base.data_structures.Segment(*, name, values, alias=None, values_aliases=<factory>, exclusions=<factory>, lookups=<factory>)

Bases: BaseConfig

Class containing info on a Segment, which combined with other Segments form a segmentation.

Parameters:

• name (str) – The name of the segmentation. Generally this is short form (e.g. ‘p’ instead of ‘purpose’)

• values (dict[int, str]) – The values forming the segment. Keys are the values, and values are descriptions, e.g. for ‘p’, 1: ‘HB work’. Descriptions don’t tend to get used in DVectors so can be as verbose as desired for clarity.

• alias (str | None) – Optional alias to use when producing filenames (or other names) from segmentation slices, if not given then name will be used.

• values_aliases (dict[int, str]) – Optional separate aliases for each value, can be used instead of name and value, e.g. “nhb” for direction 0.

• exclusions (list[Exclusion]) – Define incompatibilities between segments. See Correspondence class

• lookups (list[Exclusion]) – Define lookups between segments, essentially the reverse of exclusions. More efficient for segments with mappings, e.g. different defintions of age.

Attributes

exclusion_segs	List the names of segs excluded by this one.
int_values	Return integer values of segment.
lookup_segs	List names of segs with lookups from self.
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.
name
values
alias
values_aliases
exclusions
lookups

Methods

__init__(**data)	Create a new model by parsing and validating input data from keyword arguments.
add_corr_from_df(to_seg[, exclusion])	Add either a lookup or exclusion to a segment from a lookup file.
construct([_fields_set])
copy(*[, include, exclude, update, deep])	Returns a copy of the model.
dict(*[, include, exclude, by_alias, ...])
drop_indices(other_seg)	Return indices to drop based on exclusions.
extract_values(text)	Extract segment values from string.
from_orm(obj)
from_yaml(text)	Parse class attributes from YAML text.
get_alias()	Get segment alias for use in filenames, if available.
get_value_alias(value)	Get value alias if exists, otherwise return name and value int.
json(*[, include, exclude, by_alias, ...])
load_yaml(path)	Read YAML file and load the data using from_yaml.
lookup_indices(other_seg)	Return indices to include based on lookups.
model_construct([_fields_set])	Creates a new instance of the Model class with validated data.
model_copy(*[, update, deep])	!!! abstract "Usage Documentation"
model_dump(*[, mode, include, exclude, ...])	!!! abstract "Usage Documentation"
model_dump_json(*[, indent, ensure_ascii, ...])	!!! abstract "Usage Documentation"
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(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, extra, ...])	Validate a pydantic model instance.
model_validate_json(json_data, *[, strict, ...])	!!! abstract "Usage Documentation"
model_validate_strings(obj, *[, strict, ...])	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_yaml(path[, datetime_comment, ...])	Write data from self to a YAML file.
schema([by_alias, ref_template])
schema_json(*[, by_alias, ref_template])
to_yaml()	Convert attributes from self to YAML string.
translate_exclusion(new_seg)	Translate an exclusion from one segment to another.
translate_segment(new_seg[, reverse])	Translate self to new_seg.
update_forward_refs(**localns)
validate(value)
value_regex()	Generate a regular expression to extract segment values.
write_example(path_, /[, comment_])	Write examples to a config file.

Attributes Documentation

exclusion_segs

List the names of segs excluded by this one.

int_values

Return integer values of segment.

lookup_segs

List names of segs with lookups from self.

model_computed_fields = {}

model_config = {'arbitrary_types_allowed': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_extra

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to “allow”.

model_fields = {'alias': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'exclusions': FieldInfo(annotation=list[Exclusion], required=False, default_factory=list), 'lookups': FieldInfo(annotation=list[Exclusion], required=False, default_factory=list), 'name': FieldInfo(annotation=str, required=True), 'values': FieldInfo(annotation=dict[int, str], required=True), 'values_aliases': FieldInfo(annotation=dict[int, str], required=False, default_factory=dict)}

model_fields_set

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

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

name: str

values: dict[int, str]

alias: str | None

values_aliases: dict[int, str]

exclusions: list[Exclusion]

lookups: list[Exclusion]