Module fcmpy.expert_fcm.aggregation
Expand source code
import numpy as np
from abc import ABC, abstractmethod
from fcmpy.expert_fcm.input_validator import type_check
class Aggregate(ABC):
"""
Fuzzy aggregation rule.
"""
@abstractmethod
def aggregate() -> np.ndarray:
raise NotImplementedError('aggregate method is not defined.')
class Fmax(Aggregate):
"""
Family max aggregation rule.
"""
@staticmethod
@type_check
def aggregate(**kwargs) -> np.ndarray:
"""
Family max aggregation rule.
Other Parameters
----------
**x, **y: numpy.ndarray,
"activated" membership functions of the linguistic terms
that need to be aggregated
Return
-------
y: np.ndarray
an aggregated membership function
"""
x = kwargs['x']
y = kwargs['y']
return np.fmax(x, y)
class AlgSum(Aggregate):
"""
Family Algebraic Sum.
"""
@staticmethod
@type_check
def aggregate(**kwargs) -> np.ndarray:
"""
Family Algebraic sum aggregation rule.
Other Parameters
----------
**x, **y: numpy.ndarray,
"activated" membership functions of the linguistic terms that need to be aggregated
Return
-------
y: np.ndarray
an aggregated membership function
"""
x = kwargs['x']
y = kwargs['y']
return x+y - (x*y)
class EinsteinSum(Aggregate):
"""
Family Einstein Sum.
"""
@staticmethod
@type_check
def aggregate(**kwargs) -> np.ndarray:
"""
Family Einstein sum aggregation rule.
Other Parameters
----------
**x, **y: numpy.ndarray,
"activated" membership functions of the linguistic terms that need to be aggregated
Return
-------
y: float
an aggregated membership function
"""
x = kwargs['x']
y = kwargs['y']
return (x+y) / (1.0 + x*y)
class HamacherSum(Aggregate):
"""
Family Hamacher Sum.
"""
@staticmethod
@type_check
def aggregate(**kwargs) -> np.ndarray:
"""
Family Hamacher sum aggregation rule.
Other Parameters
----------------
**x, **y: numpy.ndarray,
"activated" membership functions of the linguistic terms that need
to be aggregated
Return
-------
y: np.ndarray
an aggregated membership function
"""
x = kwargs['x']
y = kwargs['y']
if x * y != 1.0:
return (x+y - 2.0*x*y) / (1.0 - x*y)
else:
return 1.0Classes
class Aggregate-
Fuzzy aggregation rule.
Expand source code
class Aggregate(ABC): """ Fuzzy aggregation rule. """ @abstractmethod def aggregate() -> np.ndarray: raise NotImplementedError('aggregate method is not defined.')Ancestors
- abc.ABC
Subclasses
Methods
def aggregate() ‑> numpy.ndarray-
Expand source code
@abstractmethod def aggregate() -> np.ndarray: raise NotImplementedError('aggregate method is not defined.')
class AlgSum-
Family Algebraic Sum.
Expand source code
class AlgSum(Aggregate): """ Family Algebraic Sum. """ @staticmethod @type_check def aggregate(**kwargs) -> np.ndarray: """ Family Algebraic sum aggregation rule. Other Parameters ---------- **x, **y: numpy.ndarray, "activated" membership functions of the linguistic terms that need to be aggregated Return ------- y: np.ndarray an aggregated membership function """ x = kwargs['x'] y = kwargs['y'] return x+y - (x*y)Ancestors
- Aggregate
- abc.ABC
Static methods
def aggregate(**kwargs) ‑> numpy.ndarray-
Family Algebraic sum aggregation rule.
Other Parameters
**x,**y:numpy.ndarray,- "activated" membership functions of the linguistic terms that need to be aggregated
Return
y: np.ndarray an aggregated membership function
Expand source code
@staticmethod @type_check def aggregate(**kwargs) -> np.ndarray: """ Family Algebraic sum aggregation rule. Other Parameters ---------- **x, **y: numpy.ndarray, "activated" membership functions of the linguistic terms that need to be aggregated Return ------- y: np.ndarray an aggregated membership function """ x = kwargs['x'] y = kwargs['y'] return x+y - (x*y)
class EinsteinSum-
Family Einstein Sum.
Expand source code
class EinsteinSum(Aggregate): """ Family Einstein Sum. """ @staticmethod @type_check def aggregate(**kwargs) -> np.ndarray: """ Family Einstein sum aggregation rule. Other Parameters ---------- **x, **y: numpy.ndarray, "activated" membership functions of the linguistic terms that need to be aggregated Return ------- y: float an aggregated membership function """ x = kwargs['x'] y = kwargs['y'] return (x+y) / (1.0 + x*y)Ancestors
- Aggregate
- abc.ABC
Static methods
def aggregate(**kwargs) ‑> numpy.ndarray-
Family Einstein sum aggregation rule.
Other Parameters
**x,**y:numpy.ndarray,- "activated" membership functions of the linguistic terms that need to be aggregated
Return
y: float an aggregated membership function
Expand source code
@staticmethod @type_check def aggregate(**kwargs) -> np.ndarray: """ Family Einstein sum aggregation rule. Other Parameters ---------- **x, **y: numpy.ndarray, "activated" membership functions of the linguistic terms that need to be aggregated Return ------- y: float an aggregated membership function """ x = kwargs['x'] y = kwargs['y'] return (x+y) / (1.0 + x*y)
class Fmax-
Family max aggregation rule.
Expand source code
class Fmax(Aggregate): """ Family max aggregation rule. """ @staticmethod @type_check def aggregate(**kwargs) -> np.ndarray: """ Family max aggregation rule. Other Parameters ---------- **x, **y: numpy.ndarray, "activated" membership functions of the linguistic terms that need to be aggregated Return ------- y: np.ndarray an aggregated membership function """ x = kwargs['x'] y = kwargs['y'] return np.fmax(x, y)Ancestors
- Aggregate
- abc.ABC
Static methods
def aggregate(**kwargs) ‑> numpy.ndarray-
Family max aggregation rule.
Other Parameters
**x,**y:numpy.ndarray,- "activated" membership functions of the linguistic terms that need to be aggregated
Return
y: np.ndarray an aggregated membership function
Expand source code
@staticmethod @type_check def aggregate(**kwargs) -> np.ndarray: """ Family max aggregation rule. Other Parameters ---------- **x, **y: numpy.ndarray, "activated" membership functions of the linguistic terms that need to be aggregated Return ------- y: np.ndarray an aggregated membership function """ x = kwargs['x'] y = kwargs['y'] return np.fmax(x, y)
class HamacherSum-
Family Hamacher Sum.
Expand source code
class HamacherSum(Aggregate): """ Family Hamacher Sum. """ @staticmethod @type_check def aggregate(**kwargs) -> np.ndarray: """ Family Hamacher sum aggregation rule. Other Parameters ---------------- **x, **y: numpy.ndarray, "activated" membership functions of the linguistic terms that need to be aggregated Return ------- y: np.ndarray an aggregated membership function """ x = kwargs['x'] y = kwargs['y'] if x * y != 1.0: return (x+y - 2.0*x*y) / (1.0 - x*y) else: return 1.0Ancestors
- Aggregate
- abc.ABC
Static methods
def aggregate(**kwargs) ‑> numpy.ndarray-
Family Hamacher sum aggregation rule.
Other Parameters
**x,**y:numpy.ndarray,- "activated" membership functions of the linguistic terms that need to be aggregated
Return
y: np.ndarray an aggregated membership function
Expand source code
@staticmethod @type_check def aggregate(**kwargs) -> np.ndarray: """ Family Hamacher sum aggregation rule. Other Parameters ---------------- **x, **y: numpy.ndarray, "activated" membership functions of the linguistic terms that need to be aggregated Return ------- y: np.ndarray an aggregated membership function """ x = kwargs['x'] y = kwargs['y'] if x * y != 1.0: return (x+y - 2.0*x*y) / (1.0 - x*y) else: return 1.0