from mystic.constraints import as_penalty
from mystic import random_seed
random_seed(123)
t = t1,t2,t3 = (impose_sum, impose_product, impose_mean)
#c = [lambda x: ti(xi, x) for (xi,ti) in zip(x,t)] #XXX
c1 = lambda x: t1(x1, x)
c2 = lambda x: t2(x2, x)
c3 = lambda x: t3(x3, x)
c = (c1,c2,c3)
k=1
solver = 'buckshot' #'diffev'
ptype = linear_equality #quadratic_equality
p = [as_penalty(ci, ptype) for ci in c]
penalty = and_(*p, k=k)
constraint = as_constraint(penalty, solver=solver)
x = [1,2,3,4,5]
x_ = constraint(x)
# print("target: %s, %s, %s" % (x1, x2, x3))
# print("solved: %s, %s, %s" % (f1(x_), f2(x_), f3(x_)))
assert round(f1(x_)) == round(x1)
assert round(f2(x_)) == round(x2)
assert round(f3(x_)) == round(x3)
# etc: more coupling of constraints
from mystic.constraints import as_penalty
from mystic import random_seed
random_seed(123)
t = t1,t2,t3 = (impose_sum, impose_product, impose_mean)
#c = [lambda x: ti(xi, x) for (xi,ti) in zip(x,t)] #XXX
c1 = lambda x: t1(x1, x)
c2 = lambda x: t2(x2, x)
c3 = lambda x: t3(x3, x)
c = (c1,c2,c3)
k=1
solver = 'buckshot' #'diffev'
ptype = linear_equality #quadratic_equality
p = [as_penalty(ci, ptype) for ci in c]
penalty = and_(*p, k=k)
constraint = as_constraint(penalty, solver=solver)
x = [1,2,3,4,5]
x_ = constraint(x)
# print("target: %s, %s, %s" % (x1, x2, x3))
# print("solved: %s, %s, %s" % (f1(x_), f2(x_), f3(x_)))
assert round(f1(x_)) == round(x1)
assert round(f2(x_)) == round(x2)
assert round(f3(x_)) == round(x3)
# etc: more coupling of constraints