Class swarmauri_standard.similarities.GaussianRBFSimilarity.GaussianRBFSimilarity
swarmauri_standard.similarities.GaussianRBFSimilarity.GaussianRBFSimilarity
GaussianRBFSimilarity(gamma=1.0, **kwargs)
Bases: SimilarityBase
Gaussian Radial Basis Function (RBF) similarity measure.
This similarity measure uses the Gaussian kernel to calculate similarity between vectors, where similarity decays exponentially with the squared Euclidean distance between points.
The similarity is defined as: s(x,y) = exp(-gamma * ||x-y||^2)
Attributes
type : Literal["GaussianRBFSimilarity"] Type identifier for the similarity measure gamma : float The scaling parameter for the squared distance (must be positive)
Initialize the Gaussian RBF similarity measure.
Parameters
gamma : float, default=1.0 The scaling parameter for the squared distance. Higher values make the similarity more localized (decay faster with distance).
Raises
ValueError If gamma is not positive
Source code in swarmauri_standard/similarities/GaussianRBFSimilarity.py
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type
class-attribute
instance-attribute
type = 'GaussianRBFSimilarity'
gamma
instance-attribute
gamma
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'
similarity
similarity(x, y)
Calculate the Gaussian RBF similarity between two objects.
Parameters
x : ComparableType First object to compare y : ComparableType Second object to compare
Returns
float Similarity score between x and y, in range [0, 1]
Raises
ValueError If the objects have incompatible dimensions TypeError If the input types are not supported
Source code in swarmauri_standard/similarities/GaussianRBFSimilarity.py
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similarities
similarities(x, ys)
Calculate similarities between one object and multiple other objects.
Parameters
x : ComparableType Reference object ys : Sequence[ComparableType] Sequence of objects to compare against the reference
Returns
List[float] List of similarity scores between x and each element in ys
Raises
ValueError If any objects have incompatible dimensions TypeError If any input types are not supported
Source code in swarmauri_standard/similarities/GaussianRBFSimilarity.py
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dissimilarity
dissimilarity(x, y)
Calculate the dissimilarity between two objects.
Parameters
x : ComparableType First object to compare y : ComparableType Second object to compare
Returns
float Dissimilarity score between x and y, in range [0, 1]
Source code in swarmauri_standard/similarities/GaussianRBFSimilarity.py
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check_bounded
check_bounded()
Check if the similarity measure is bounded.
The Gaussian RBF kernel always produces values in [0,1], with 1 for identical vectors and approaching 0 as distance increases.
Returns
bool True as this similarity measure is bounded in [0,1]
Source code in swarmauri_standard/similarities/GaussianRBFSimilarity.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:
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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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dissimilarities
dissimilarities(x, ys)
Calculate dissimilarities between one object and multiple other objects.
Parameters
x : ComparableType Reference object ys : Sequence[ComparableType] Sequence of objects to compare against the reference
Returns
List[float] List of dissimilarity scores between x and each element in ys
Raises
NotImplementedError This method must be implemented by subclasses ValueError If any objects are incomparable or have incompatible dimensions TypeError If any input types are not supported
Source code in swarmauri_base/similarities/SimilarityBase.py
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check_reflexivity
check_reflexivity(x)
Check if the similarity measure is reflexive: s(x,x) = 1.
Parameters
x : ComparableType Object to check reflexivity with
Returns
bool True if s(x,x) = 1, False otherwise
Raises
TypeError If the input type is not supported
Source code in swarmauri_base/similarities/SimilarityBase.py
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check_symmetry
check_symmetry(x, y)
Check if the similarity measure is symmetric: s(x,y) = s(y,x).
Parameters
x : ComparableType First object to compare y : ComparableType Second object to compare
Returns
bool True if s(x,y) = s(y,x), False otherwise
Raises
ValueError If the objects are incomparable or have incompatible dimensions TypeError If the input types are not supported
Source code in swarmauri_base/similarities/SimilarityBase.py
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check_identity_of_discernibles
check_identity_of_discernibles(x, y)
Check if the similarity measure satisfies the identity of discernibles: s(x,y) = 1 ⟺ x = y.
Parameters
x : ComparableType First object to compare y : ComparableType Second object to compare
Returns
bool True if the identity of discernibles property holds, False otherwise
Raises
ValueError If the objects are incomparable or have incompatible dimensions TypeError If the input types are not supported
Source code in swarmauri_base/similarities/SimilarityBase.py
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