def test_derivative(self):
coeff = [4.0, 3.0, 2.0, 1.0]
cahn = CahnHilliard(degree=3, coeff=coeff)
cython_cahn = PyCahnHilliard(coeff)
x_values = [2.0, 3.0, -1.0]
for x in x_values:
self.assertAlmostEqual(cahn.deriv(x), cython_cahn.deriv(x))
def main(conc):
prefix = "/work/sophus/cahn_hilliard_phase_separation3D/ch_{}_".format(
int(100 * conc))
dim = 3
dx = 10.0 # Step size in angstrom
L = 128
num_gl_fields = 0
M = 0.1
alpha = 5.0
dt = 0.5
gl_damping = M
gradient_coeff = []
with open(FNAME, 'r') as infile:
info = json.load(infile)
alpha = info["alpha"] / dx**2
cahn_free = PyCahnHilliard(info["poly"], bounds=[-0.05, 1.05], penalty=0.0)
sim = PyCahnHilliardPhaseField(3, L, prefix, cahn_free, M, dt, alpha)
#sim.from_npy_array(random_init(L, conc))
sim.set_adaptive(1E-10, 0.05)
#sim.build3D()
sim.from_file(prefix + "00000160000.grid")
sim.run(100000, 10000, start=160000)
def test_regularization_consistentcy(self):
coeff = [4.0, 3.0, 2.0, 1.0]
cahn = CahnHilliard(degree=3,
coeff=coeff,
bounds=[0.0, 1.0],
penalty=10.0,
range_frac=0.1)
cython_cahn = PyCahnHilliard(coeff,
penalty=10.0,
bounds=[0.0, 1.0],
range_scale=0.1)
x_values = [-0.1, 1.1, -0.5]
for x in x_values:
self.assertAlmostEqual(cahn.deriv(x), cython_cahn.deriv(x))
for x in x_values:
self.assertAlmostEqual(cahn.evaluate(x), cython_cahn.evaluate(x))
def test_run_without_errors(self):
coeff = [5.0, 4.0, 3.0, 2.0, 1.0]
free = PyCahnHilliard(coeff)
# Initialize a small 2D calculation
L = 64
M = 1.0
dt = 0.01
alpha = 1.0
sim = PyCahnHilliardPhaseField(2, L, "cahnhill", free, M, dt, alpha)
sim.run(100, 20)
def test_numpy_init(self):
coeff = [5.0, 4.0, 3.0, 2.0, 1.0]
free = PyCahnHilliard(coeff)
L = 64
M = 1.0
dt = 0.01
alpha = 1.0
sim = PyCahnHilliardPhaseField(2, L, "cahnhill", free, M, dt, alpha)
array = np.random.rand(L, L)
sim.from_npy_array(array)
from_sim = sim.to_npy_array()
self.assertTrue(np.allclose(from_sim, array))
array2 = np.random.rand(L)
with self.assertRaises(ValueError):
sim.from_npy_array(array2)
array3 = np.random.rand(2 * L, L)
with self.assertRaises(ValueError):
sim.from_npy_array(array3)