def type_parameters():
r"""Get dictionary with functions for checking values of parameters.
Returns:
Dict[str, Callable[[Union[list, dict]], bool]]:
* alpha (Callable[[Union[float, int]], bool]): TODO.
* gamma (Callable[[Union[float, int]], bool]): TODO.
* theta (Callable[[Union[float, int]], bool]): TODO.
* nl (Callable[[Union[float, int]], bool]): TODO.
* F (Callable[[Union[float, int]], bool]): TODO.
* CR (Callable[[Union[float, int]], bool]): TODO.
See Also:
* :func:`WeOptPy.algorithms.Algorithm.typeParameters`
"""
d = Algorithm.type_parameters()
d.update({
'alpha': lambda x: True,
'gamma': lambda x: True,
'theta': lambda x: True,
'nl': lambda x: True,
'F': lambda x: isinstance(x, (int, float)) and x > 0,
'CR': lambda x: isinstance(x, float) and 0 <= x <= 1
})
return d
def type_parameters():
r"""Return functions for checking values of parameters.
Returns:
Dict[str, Callable]:
* Limit (Callable[Union[float, numpy.ndarray[float]]]): TODO
See Also:
* :func:`WeOptPy.algorithms.Algorithm.typeParameters`
"""
d = Algorithm.type_parameters()
d.update({'Limit': lambda x: isinstance(x, int) and x > 0})
return d
def type_parameters():
r"""Get dictionary with functions for checking values of parameters.
Returns:
Dict[str, Callable]:
* F (Callable[[Union[float, int]], bool]): Check for correct value of parameter.
* CR (Callable[[float], bool]): Check for correct value of parameter.
See Also:
* :func:`WeOptPy.algorithms.Algorithm.typeParameters`
"""
d = Algorithm.type_parameters()
d.update({
'F': lambda x: isinstance(x, (float, int)) and 0 < x <= 2,
'CR': lambda x: isinstance(x, float) and 0 <= x <= 1
})
return d
def type_parameters():
r"""TODO.
Returns:
Dict[str, Callable]:
* p (function): TODO
* beta (function): TODO
See Also:
* :func:`WeOptPy.algorithms.Algorithm.typeParameters`
"""
d = Algorithm.type_parameters()
d.update({
'p': lambda x: isinstance(x, float) and 0 <= x <= 1,
'beta': lambda x: isinstance(x, (float, int)) and x > 0,
})
return d
def type_parameters():
r"""Get dictionary with functions for checking values of parameters.
Returns:
Dict[str, Callable]:
* a (Callable[[Union[float, int]], bool]): TODO.
* Rmin (Callable[[Union[float, int]], bool]): TODO.
* Rmax (Callable[[Union[float, int]], bool]): TODO.
See Also:
* :func:`NiaPy.algorithms.Algorithm.typeParameters`
"""
d = Algorithm.type_parameters()
d.update({
'a': lambda x: isinstance(x, (float, int)) and x > 0,
'Rmin': lambda x: isinstance(x, (float, int)),
'Rmax': lambda x: isinstance(x, (float, int))
})
return d
def type_parameters():
r"""TODO.
Returns:
Dict[str, Callable]:
* alpha (Callable[[Union[float, int]], bool]): TODO.
* betamin (Callable[[Union[float, int]], bool]): TODO.
* gamma (Callable[[Union[float, int]], bool]): TODO.
See Also:
* :func:`WeOptPy.algorithms.Algorithm.typeParameters`
"""
d = Algorithm.type_parameters()
d.update({
'alpha': lambda x: isinstance(x, (float, int)) and x > 0,
'betamin': lambda x: isinstance(x, (float, int)) and x > 0,
'gamma': lambda x: isinstance(x, (float, int)) and x > 0,
})
return d
def type_parameters():
r"""Get dictionary with function for testing correctness of parameters.
Returns:
Dict[str, Callable]:
* alpha (Callable[[Union[int, float]], bool])
* gamma (Callable[[Union[int, float]], bool])
* rho (Callable[[Union[int, float]], bool])
* sigma (Callable[[Union[int, float]], bool])
See Also
* :func:`NiaPy.algorithms.Algorithm.typeParameters`
"""
d = Algorithm.type_parameters()
d.update({
'alpha': lambda x: isinstance(x, (int, float)) and x >= 0,
'gamma': lambda x: isinstance(x, (int, float)) and x >= 0,
'rho': lambda x: isinstance(x, (int, float)),
'sigma': lambda x: isinstance(x, (int, float))
})
return d
def type_parameters():
r"""Return dict with where key of dict represents parameter name and values represent checking functions for selected parameter.
Returns:
Dict[str, Callable]:
* a (Callable[[Union[float, int]], bool]): Loudness.
* r (Callable[[Union[float, int]], bool]): Pulse rate.
* Qmin (Callable[[Union[float, int]], bool]): Minimum frequency.
* Qmax (Callable[[Union[float, int]], bool]): Maximum frequency.
See Also:
* :func:`WeOptPy.algorithms.Algorithm.typeParameters`
"""
d = Algorithm.type_parameters()
d.update({
'a': lambda x: isinstance(x, (float, int)) and x > 0,
'r': lambda x: isinstance(x, (float, int)) and x > 0,
'Qmin': lambda x: isinstance(x, (float, int)),
'Qmax': lambda x: isinstance(x, (float, int))
})
return d
def test_type_parameters_fine(self):
d = Algorithm.type_parameters()
self.assertIsNotNone(d)
