def test_equal_probability():
""" Check particles have equal probability of movement. """
from numpy import array, sqrt, count_nonzero
mc = MonteCarlo()
density = array([1, 0, 99])
changes_at_zero = [(density - mc.change_density(density))[0] != 0
for i in range(10000)]
assert_almost_equal(count_nonzero(changes_at_zero),
0.01 * len(changes_at_zero),
delta=0.5 * sqrt(len(changes_at_zero)))
def test_equal_probability():
""" Check particles have equal probability of movement. """
from numpy import array, sqrt, count_nonzero
mc = MonteCarlo()
density = array([1, 0, 99])
changes_at_zero = [(density - mc.change_density(density))[0] != 0 for i in range(10000)]
assert_almost_equal(
count_nonzero(changes_at_zero),
0.01 * len(changes_at_zero),
delta = 0.5 * sqrt(len(changes_at_zero))
)
def test_move_particle_one_over():
""" Check density is change by a particle hopping left or right. """
from numpy import nonzero, multiply
from numpy.random import randint
mc = MonteCarlo()
for i in range(
100): # Do this n times, to avoid issues with random numbers
# Create density
density = randint(50, size=randint(2, 6))
# Change it
new_density = mc.change_density(density)
# Make sure any movement is by one
indices = nonzero(density - new_density)[0]
assert_equal(len(indices), 2, "densities differ in two places")
assert_equal(multiply.reduce((density - new_density)[indices]), -1,
"densities differ by + and - 1")
def test_main_algorithm():
""" Check set path through main algorithm """
from mock import Mock, call
mc = MonteCarlo(temperature=100.0, itermax=4)
# Patch mc so that it takes a pre-determined path through
acceptance = [True, True, False, True]
mc.accept_change = Mock(side_effect=acceptance)
densities = (
[0, 0, 1, 0],
[0, 1, 1, 0],
[2, 2, 2, 2],
[2, 3, 3, 2],
[5, 3, 3, 5],
)
mc.change_density = Mock(side_effect=densities[1:])
mc.observe = Mock(return_value=True)
# Fake energy method
energies = [0.1, -0.1, -0.2, -0.15, -0.25]
energy = Mock(side_effect=energies)
# Call simulation
mc(energy, densities[0])
# Now, analyze path. First check length.
assert_equal(len(mc.accept_change.mock_calls), 4)
assert_equal(len(mc.change_density.mock_calls), 4)
assert_equal(len(mc.observe.mock_calls), 4)
assert_equal(len(energy.mock_calls),
5) # one extra call to get first energy
# Easiest to look at observe, since it should have all the info about the step
observe_path = [
call(0, acceptance[0], densities[1], energies[1]),
call(1, acceptance[1], densities[2], energies[2]),
call(2, acceptance[2], densities[2], energies[2]),
call(3, acceptance[3], densities[4], energies[4]),
]
assert_equal(observe_path, mc.observe.call_args_list)
def test_move_particle_one_over():
""" Check density is change by a particle hopping left or right. """
from numpy import nonzero, multiply
from numpy.random import randint
mc = MonteCarlo()
for i in range(100): # Do this n times, to avoid issues with random numbers
# Create density
density = randint(50, size=randint(2, 6))
# Change it
new_density = mc.change_density(density)
# Make sure any movement is by one
indices = nonzero(density - new_density)[0]
assert_equal(len(indices), 2, "densities differ in two places")
assert_equal(
multiply.reduce((density - new_density)[indices]),
-1,
"densities differ by + and - 1"
)
def test_main_algorithm():
""" Check set path through main algorithm """
from mock import Mock, call
mc = MonteCarlo(temperature=100.0, itermax=4)
# Patch mc so that it takes a pre-determined path through
acceptance = [True, True, False, True]
mc.accept_change = Mock(side_effect=acceptance)
densities = (
[0, 0, 1, 0],
[0, 1, 1, 0],
[2, 2, 2, 2],
[2, 3, 3, 2],
[5, 3, 3, 5],
)
mc.change_density = Mock(side_effect=densities[1:])
mc.observe = Mock(return_value=True)
# Fake energy method
energies = [0.1, -0.1, -0.2, -0.15, -0.25]
energy = Mock(side_effect=energies)
# Call simulation
mc(energy, densities[0])
# Now, analyze path. First check length.
assert_equal(len(mc.accept_change.mock_calls), 4)
assert_equal(len(mc.change_density.mock_calls), 4)
assert_equal(len(mc.observe.mock_calls), 4)
assert_equal(len(energy.mock_calls), 5) # one extra call to get first energy
# Easiest to look at observe, since it should have all the info about the step
observe_path = [
call(0, acceptance[0], densities[1], energies[1]),
call(1, acceptance[1], densities[2], energies[2]),
call(2, acceptance[2], densities[2], energies[2]),
call(3, acceptance[3], densities[4], energies[4])
]
assert_equal(observe_path, mc.observe.call_args_list)
