def test_bounded_single(self):
# The will ideally require a 5x4 grid, but the limit on two cells in
# the y-direction should redirect to a 10x2.
nx = np.array([100, 2])
target = 20
coarse = partition.determine_coarse_dimensions(target, nx)
assert np.array_equal(np.sort(coarse), np.array([2, 10]))
def test_two_bounds(self):
# This will seemingly require 900^1/3 ~ 10 cells in each direction, but
# the z-dimension has only 1, thus the two other have to do 30 each. y
# can only do 15, so the loop has to be reset once more to get the
# final 60.
nx = np.array([2000, 15, 1])
target = 900
coarse = partition.determine_coarse_dimensions(target, nx)
assert np.array_equal(np.sort(coarse), np.array([1, 15, 60]))
def test_round_up_and_down(self):
nx = np.array([10, 10])
target = 19
coarse = partition.determine_coarse_dimensions(target, nx)
assert np.array_equal(np.sort(coarse), np.array([4, 5]))
def test_round_down(self):
nx = np.array([10, 10])
target = 17
coarse = partition.determine_coarse_dimensions(target, nx)
assert np.array_equal(coarse, np.array([4, 4]))
def test_anisotropic_2d(self):
nx = np.array([10, 4])
target = 4
coarse = partition.determine_coarse_dimensions(target, nx)
assert np.array_equal(coarse, np.array([2, 2]))
def test_coarse_dimensions_single_coarse(self):
nx = np.array([5, 5, 5])
target = 1
coarse = partition.determine_coarse_dimensions(target, nx)
assert np.array_equal(coarse, np.ones_like(nx))
def test_coarse_dimensions_all_fine(self):
nx = np.array([5, 5, 5])
target = nx.prod()
coarse = partition.determine_coarse_dimensions(target, nx)
assert np.array_equal(nx, coarse)