def test_accept_change():
""" Check that move is accepted if second energy is lower """
from numpy import sqrt, count_nonzero, exp
energy = MagicMock
mc = MonteCarlo(energy, [1, 1, 1], temperature=100.0)
# Should always be true.
# But do more than one draw,
# in case randomness incorrectly crept into
# implementation
for i in range(10):
assert mc.accept_change(0.5, 0.4)
assert mc.accept_change(0.5, 0.5)
# This should be accepted only part of the time,
# depending on exponential distribution
prior, successor = 0.4, 0.5
accepted = [mc.accept_change(prior, successor) for i in range(10000)]
assert count_nonzero(accepted) / float(len(accepted)) == approx(
exp(-(successor - prior) / mc.temperature), 3e0 / sqrt(len(accepted)))
def test_main_algorithm():
import numpy as np
from numpy import testing
from unittest.mock import Mock
density = [1, 1, 1, 1, 1]
energy = MagicMock()
mc = MonteCarlo(energy, density, itermax=5)
acceptance = [True, True, True, True, True]
mc.accept_change = Mock(side_effect=acceptance)
mc.random_agent = Mock(side_effect=[0, 1, 2, 3, 4])
mc.random_direction = Mock(side_effect=[1, 1, 1, 1, -1])
np.testing.assert_equal(mc.step()[1], [0, 1, 1, 2, 1])
