def test_solve(self):
# Create model and solver parameters.
mp = solver.ModelParams()
mp.k_on = 0
mp.k_off = 0
mp.t_cut = 1
sp = solver.SolverParams()
sp.n = 100
sp.m = 10
# Define initial values.
def const(x):
return 1.0
# Initialise tracers.
x = np.array(np.linspace(0, 1, num=5))
# Run solver.
rho, ca, v, sigma, x, idx = solver.solve(mp, sp, const, const, x)
# Check returned arrays.
const_exp = np.vectorize(const)(np.zeros((sp.m + 1, sp.n)))
np.testing.assert_equal(rho.shape, (sp.m + 1, sp.n))
np.testing.assert_equal(ca.shape, (sp.m + 1, sp.n))
np.testing.assert_allclose(rho, const_exp, atol=1e-7)
np.testing.assert_allclose(ca, const_exp, atol=1e-7)
np.testing.assert_allclose(v,
np.zeros((sp.m + 1, sp.n + 1)),
atol=1e-7)
# Set path where results are saved.
resultpath = 'results/{0}'.format(
datetime.datetime.now().strftime('%Y-%m-%d-%H-%M-%S'))
if not os.path.exists(resultpath):
os.makedirs(resultpath)
# Create model and solver parameters.
mp = solver.ModelParams()
mp.eta = 1
mp.xi = 0.1
mp.chi = 1
mp.t_cut = 0
mp.k_on = 200
mp.k_off = 10
sp = solver.SolverParams()
sp.n = 300
sp.m = 300
sp.T = 0.1
sp.dt = 2.5e-6
sp.delta = 1e-2
# Define initial values.
def ca_init(x):
return stats.uniform.pdf(x, 0, 1) * 20 \
- math.sin(40 * x + math.cos(40 * x)) / 5
def rho_init(x):
return stats.uniform.pdf(x, 0, 1) \