def __init__(self, workloads):
# q or r = - (-q and -r)
# W = 1 x 1 - (Q1 x R1)
self.A = Kronecker([Ones(*W.shape) for W in workloads]) # totals
self.B = -1 * Kronecker([Ones(*W.shape) - W
for W in workloads]) # negations
Sum.__init__(self, [self.A, self.B])
def sum_kron_canonical(WtW):
if isinstance(WtW, Kronecker):
return Sum([1.0 * WtW])
elif isinstance(WtW, Weighted) and isinstance(WtW.base, Kronecker):
return Sum([WtW])
elif isinstance(WtW, Sum):
return Sum([1.0 * X for X in WtW.matrices])
elif isinstance(WtW, Weighted) and isinstance(WtW.base, Sum):
c = WtW.weight
return Sum([c * X for X in WtW.base.matrices])
else:
raise ValueError('Input format not recognized')
def __init__(self, domain, weights):
self.domain = tuple(domain)
self.weights = weights
subs = []
n, d = np.prod(domain), len(domain)
mult = np.ones(2**d)
for key, wgt in enumerate(weights):
Q = Marginal(domain, key)
mult[key] = n / Q.shape[0]
if wgt != 0: subs.append(wgt * Q.gram())
self._mult = mult
Sum.__init__(self, subs)
def gram(self):
return Sum([
self.A.gram(), self.A.T @ self.B, self.B.T @ self.A,
self.B.gram()
])