Class swarmauri_standard.distances.CanberraDistance.CanberraDistance
swarmauri_standard.distances.CanberraDistance.CanberraDistance
Bases: DistanceBase
Concrete implementation of the IDistanceSimiliarity interface using the Canberra distance metric. This class now processes Vector instances instead of raw lists.
type
class-attribute
instance-attribute
type = 'CanberraDistance'
model_config
class-attribute
instance-attribute
model_config = ConfigDict(
extra="allow", arbitrary_types_allowed=True
)
id
class-attribute
instance-attribute
id = Field(default_factory=generate_id)
members
class-attribute
instance-attribute
members = None
owners
class-attribute
instance-attribute
owners = None
host
class-attribute
instance-attribute
host = None
default_logger
class-attribute
default_logger = None
logger
class-attribute
instance-attribute
logger = None
name
class-attribute
instance-attribute
name = None
version
class-attribute
instance-attribute
version = '0.1.0'
distance
distance(vector_a, vector_b)
Computes the Canberra distance between two Vector instances.
PARAMETER | DESCRIPTION |
---|---|
vector_a
|
The first vector in the comparison.
TYPE:
|
vector_b
|
The second vector in the comparison.
TYPE:
|
RETURNS | DESCRIPTION |
---|---|
float
|
The computed Canberra distance between the vectors.
TYPE:
|
Source code in swarmauri_standard/distances/CanberraDistance.py
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|
similarity
similarity(vector_a, vector_b)
Compute similarity using the Canberra distance. Since this distance metric isn't directly interpretable as a similarity, a transformation is applied to map the distance to a similarity score.
PARAMETER | DESCRIPTION |
---|---|
vector_a
|
The first vector in the comparison.
TYPE:
|
vector_b
|
The second vector to compare with the first vector.
TYPE:
|
RETURNS | DESCRIPTION |
---|---|
float
|
A similarity score between vector_a and vector_b.
TYPE:
|
Source code in swarmauri_standard/distances/CanberraDistance.py
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|
distances
distances(vector_a, vectors_b)
Source code in swarmauri_standard/distances/CanberraDistance.py
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|
similarities
similarities(vector_a, vectors_b)
Source code in swarmauri_standard/distances/CanberraDistance.py
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|
register_model
classmethod
register_model()
Decorator to register a base model in the unified registry.
RETURNS | DESCRIPTION |
---|---|
Callable
|
A decorator function that registers the model class.
TYPE:
|
Source code in swarmauri_base/DynamicBase.py
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|
register_type
classmethod
register_type(resource_type=None, type_name=None)
Decorator to register a subtype under one or more base models in the unified registry.
PARAMETER | DESCRIPTION |
---|---|
resource_type
|
The base model(s) under which to register the subtype. If None, all direct base classes (except DynamicBase) are used.
TYPE:
|
type_name
|
An optional custom type name for the subtype.
TYPE:
|
RETURNS | DESCRIPTION |
---|---|
Callable
|
A decorator function that registers the subtype.
TYPE:
|
Source code in swarmauri_base/DynamicBase.py
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|
model_validate_toml
classmethod
model_validate_toml(toml_data)
Validate a model from a TOML string.
Source code in swarmauri_base/TomlMixin.py
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|
model_dump_toml
model_dump_toml(
fields_to_exclude=None, api_key_placeholder=None
)
Return a TOML representation of the model.
Source code in swarmauri_base/TomlMixin.py
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|
model_validate_yaml
classmethod
model_validate_yaml(yaml_data)
Validate a model from a YAML string.
Source code in swarmauri_base/YamlMixin.py
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|
model_dump_yaml
model_dump_yaml(
fields_to_exclude=None, api_key_placeholder=None
)
Return a YAML representation of the model.
Source code in swarmauri_base/YamlMixin.py
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model_post_init
model_post_init(logger=None)
Assign a logger instance after model initialization.
Source code in swarmauri_base/LoggerMixin.py
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