galactic.algebras.convex.descriptions.category.basic.core

galactic.algebras.convex.descriptions.category.basic.core#

galactic.algebras.convex.descriptions.category.basic.core module

Define classes for representing category descriptions and predicates.

One class for representing category predicates:

One class for representing category descriptions:

class CategoryPredicate(**data)#

Bases: Predicate

The CategoryPredicate class is used to represent a category predicate.

Parameters:

  • space – The space of the predicate, which should be a tuple of one String, Integer or Boolean.

  • elements – The elements of the subset.

Example

>>> from galactic.algebras.concept.core import Item
>>> from galactic.algebras.convex.characteristics.core import Component, String
>>> from galactic.algebras.convex.descriptions.category.basic.core import (
...     CategoryPredicate,
... )
>>> space = (String(components=(Component(),), name="category"),)
>>> predicate = CategoryPredicate(space=space, elements=("a", "b", "c"))
>>> predicate
<galactic.algebras.convex.descriptions.category.basic.core.CategoryPredicate object at 0x...>
>>> str(predicate)
"category ∈ {'a', 'b', 'c'}"
>>> predicate(Item(value="a"))
True
>>> predicate(Item(value="b"))
True
>>> predicate(Item(value="d"))
False
>>> print(predicate(Item(value=None)))
None
>>> print(predicate(Item()))
None
property template: str#

Get the template.

Returns:

The template

Return type:

str

model_config: ClassVar[ConfigDict] = {}#

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

model_post_init(context, /)#

This function is meant to behave like a BaseModel method to initialize private attributes.

It takes context as an argument since that’s what pydantic-core passes when calling it.

Parameters:

  • self (BaseModel) – The BaseModel instance.

  • context (Any) – The context.

Return type:

None

class CategoryDescription(**data)#

Bases: Description

Represent a categorical description space.

It computes the descriptions of a collection of individuals by computing a category predicate.

Parameters:

space (tuple[String | Integer | Boolean]) – A tuple of one characteristic representing the space of the description. The characteristic must be an instance of String, Integer or Boolean.

ALIAS#

The alias of the type in the resource registry.

Type:

ClassVar[str] = “category.description.Category”

Example

>>> from galactic.algebras.concept.core import Item
>>> from galactic.algebras.convex.characteristics.core import Component, String
>>> from galactic.algebras.convex.descriptions.category.basic.core import (
...     CategoryDescription,
... )
>>> space = (String(components=(Component(),)),)
>>> description = CategoryDescription(space=space)
>>> items = [
...     Item(value="a"),
...     Item(value="b"),
...     Item(value="c"),
... ]
>>> [str(attr) for attr in description(items)]
["str(@) ∈ {'a', 'b', 'c'}"]
>>> [str(attr) for attr in description([])]
['⊥']
>>> [str(attr) for attr in description([Item()])]
[]

Configuration

If you want to specify a categorical description in a TOML file, you can use the following syntax:

[components.my_component]
"$type" = "core.Component"
expr = "value"

[characteristics.my_characteristic]
"$type" = "core.characteristic.String"
components = [
  {"$ref" = "components.my_component"}
]
name = "my_name"

[descriptions.my_description]
"$type" = "category.description.Category"
space = [
  {"$ref" = "characteristics.my_characteristic"},
]
Raises:

TypeError – If any element in the space is not an instance of String, Integer or Boolean.

model_config: ClassVar[ConfigDict] = {'validate_assignment': True}#

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