ClosedInterval Pattern#
- class paspailleur.bip.ClosedIntervalPattern(value: PatternValueType)#
A class representing a closed interval as a pattern.
This class extends IntervalPattern to specifically handle closed intervals.
Attributes#
- PatternValueType :
The type of the pattern’s value, which is a tuple of two floats.
Properties#
- lower_bound
Return the lower bound of the closed interval.
- upper_bound
Return the upper bound of the closed interval.
- is_lower_bound_closed
Check if the lower bound is closed.
- is_upper_bound_closed
Check if the upper bound is closed.
- PatternValueType#
alias of
tuple[float,float]
- property lower_bound: float#
Return the lower bound of the closed interval.
- Returns:
bound – The lower bound of the closed interval.
- Return type:
float
Examples
>>> ClosedIntervalPattern((1.0, 5.0)).lower_bound 1.0
- property upper_bound: float#
Return the upper bound of the closed interval.
- Returns:
bound – The upper bound of the closed interval.
- Return type:
float
Examples
>>> ClosedIntervalPattern((1.0, 5.0)).upper_bound 5.0
- property is_lower_bound_closed: bool#
Check if the lower bound is closed.
- Returns:
closed – True, indicating that the lower bound is always closed.
- Return type:
bool
Examples
>>> ClosedIntervalPattern((1.0, 5.0)).is_lower_bound_closed True
- property is_upper_bound_closed: bool#
Check if the upper bound is closed.
- Returns:
closed – True, indicating that the upper bound is always closed.
- Return type:
bool
Examples
>>> ClosedIntervalPattern((1.0, 5.0)).is_upper_bound_closed True
- classmethod parse_string_description(value: str) tuple[float, float]#
Parse a string description into a closed interval pattern value.
- Parameters:
value (str) – The string description of the closed interval pattern.
- Returns:
parsed – The parsed closed interval pattern value.
- Return type:
PatternValueType
- Raises:
AssertionError – If the bounds are not enclosed in square brackets.
Examples
>>> ClosedIntervalPattern.parse_string_description('[1,5]') (1.0, 5.0)
- classmethod preprocess_value(value) tuple[float, float]#
Preprocess the value before storing it in the closed interval pattern.
- Parameters:
value – The value to preprocess.
- Returns:
value – The preprocessed value as a tuple of two floats.
- Return type:
PatternValueType
- Raises:
ValueError – If the value cannot be preprocessed into a ClosedIntervalPattern.
Examples
>>> ClosedIntervalPattern.preprocess_value([1, 5]) (1.0, 5.0)
- atomise(atoms_configuration: Literal['min', 'max'] = 'min') set[Self]#
Split the pattern into atomic patterns, i.e. the set of one-sided intervals
- Parameters:
atoms_configuration (Literal['min', 'max']) – If equals to ‘min’, return up to 2 atomic patterns each representing a bound of the original interval. If equals to ‘max’, return _all_ less precise one-sided intervals, where the bounds are defined by BoundUniverse class attribute.
- Returns:
atomic_patterns – The set of atomic patterns, i.e. the set of unsplittable patterns whose join equals to the pattern.
- Return type:
set[Self]
Notes
Speaking in terms of Ordered Set Theory: We say that every pattern can be represented as the join of a subset of atomic patterns, that are join-irreducible elements of the lattice of all patterns.
Considering the set of atomic patterns as a partially ordered set (where the order follows the order on patterns), every pattern can be represented by an _antichain_ of atomic patterns (when atoms_configuration = ‘min’), and by an order ideal of atomic patterns (when atoms_configuration = ‘max’).