def solve2(objective, constraint, step, limit):
""" Solve a maximization problem for 2 states.
:param objective: The objective function.
:type objective: function
:param constraint: A tuple representing the constraint.
:type constraint: tuple(function, function, number)
:param step: The step size.
:type step: number,>0
:param limit: The maximum value of the variables.
:type limit: number,>0
:return: The problem solution.
:rtype: list(number)
"""
res_best = 0
solution = []
for x in frange(0, limit, step):
for y in frange(0, limit, step):
try:
res = objective(x, y)
if res > res_best and \
constraint[1](constraint[0](x, y), constraint[2]):
res_best = res
solution = [x, y]
except ZeroDivisionError:
pass
return solution
def test_frange(self):
self.assertEqual([round(x, 1) for x in common.frange(0, 1.0, 0.5)],
[0.0, 0.5, 1.0])
self.assertEqual([round(x, 1) for x in common.frange(0, 1.0, 0.2)],
[0.0, 0.2, 0.4, 0.6, 0.8, 1.0])
def test_frange(self):
self.assertEqual([round(x, 1) for x in common.frange(0, 1.0, 0.5)],
[0.0, 0.5, 1.0])
self.assertEqual([round(x, 1) for x in common.frange(0, 1.0, 0.2)],
[0.0, 0.2, 0.4, 0.6, 0.8, 1.0])
