def __init__(self, table):
"""
Args:
table: A n-dimension tensor that maps a set of assignment to a value.
"""
Function.__init__(self)
self.table = table
def __init__(self, sig):
"""
Args:
sig: The variance value.
"""
Function.__init__(self)
self.sig = sig
def __init__(self, mu, sig):
"""
Args:
mu: The mean vector (must be 1 dimensional).
sig: The covariance matrix (must be 2 dimensional).
"""
Function.__init__(self)
self.set_parameters(mu, sig)
def __init__(self, distant_cof, scaling_cof, max_threshold):
Function.__init__(self)
self.distant_cof = distant_cof
self.scaling_cof = scaling_cof
self.max_threshold = max_threshold
self.v = pow(e, -self.max_threshold / self.scaling_cof)
def __init__(self, mu, sig):
Function.__init__(self)
self.mu = mu
self.sig = sig
