def test_ode_integrate_with_event(self):
# Constant
solver = pybamm.ScikitsOdeSolver(rtol=1e-8, atol=1e-8)
def constant_decay(t, y):
return -2 * np.ones_like(y)
def y_equal_0(t, y):
return y[0]
y0 = np.array([1])
t_eval = np.linspace(0, 1, 100)
solution = solver.integrate(constant_decay,
y0,
t_eval,
events=[y_equal_0])
np.testing.assert_allclose(1 - 2 * solution.t, solution.y[0])
self.assertLess(len(solution.t), len(t_eval))
np.testing.assert_array_less(0, solution.y[0])
np.testing.assert_array_less(solution.t, 0.5)
np.testing.assert_allclose(solution.t_event, 0.5)
np.testing.assert_allclose(solution.y_event, 0)
self.assertEqual(solution.termination, "event")
# Expnonential growth
solver = pybamm.ScikitsOdeSolver(rtol=1e-8, atol=1e-8)
def exponential_growth(t, y):
return y
def y_eq_9(t, y):
return y - 9
def ysq_eq_7(t, y):
return y**2 - 7
y0 = np.array([1])
t_eval = np.linspace(0, 3, 100)
solution = solver.integrate(exponential_growth,
y0,
t_eval,
events=[ysq_eq_7, y_eq_9])
self.assertLess(len(solution.t), len(t_eval))
np.testing.assert_allclose(np.exp(solution.t),
solution.y[0],
rtol=1e-4)
np.testing.assert_array_less(solution.y, 9)
np.testing.assert_array_less(solution.y**2, 7)
np.testing.assert_allclose(solution.t_event, np.log(7) / 2, rtol=1e-4)
np.testing.assert_allclose(solution.y_event**2, 7, rtol=1e-4)
self.assertEqual(solution.termination, "event")
def test_solver_citations(self):
# Test that solving each solver adds the right citations
citations = pybamm.citations
citations._reset()
self.assertNotIn("virtanen2020scipy", citations._papers_to_cite)
pybamm.ScipySolver()
self.assertIn("virtanen2020scipy", citations._papers_to_cite)
citations._reset()
self.assertNotIn("virtanen2020scipy", citations._papers_to_cite)
pybamm.AlgebraicSolver()
self.assertIn("virtanen2020scipy", citations._papers_to_cite)
if pybamm.have_scikits_odes():
citations._reset()
self.assertNotIn("scikits-odes", citations._papers_to_cite)
pybamm.ScikitsOdeSolver()
self.assertIn("scikits-odes", citations._papers_to_cite)
citations._reset()
self.assertNotIn("scikits-odes", citations._papers_to_cite)
pybamm.ScikitsDaeSolver()
self.assertIn("scikits-odes", citations._papers_to_cite)
if pybamm.have_idaklu():
citations._reset()
self.assertNotIn("hindmarsh2005sundials",
citations._papers_to_cite)
pybamm.IDAKLUSolver()
self.assertIn("hindmarsh2005sundials", citations._papers_to_cite)
def test_model_step_ode_python(self):
model = pybamm.BaseModel()
model.convert_to_format = "python"
whole_cell = ["negative electrode", "separator", "positive electrode"]
var = pybamm.Variable("var", domain=whole_cell)
model.rhs = {var: -0.1 * var}
model.initial_conditions = {var: 1}
disc = get_discretisation_for_testing()
disc.process_model(model)
solver = pybamm.ScikitsOdeSolver(rtol=1e-9, atol=1e-9)
# Step once
dt = 1
step_sol = solver.step(None, model, dt)
np.testing.assert_array_equal(step_sol.t, [0, dt])
np.testing.assert_allclose(step_sol.y[0], np.exp(-0.1 * step_sol.t))
# Step again (return 5 points)
step_sol_2 = solver.step(step_sol, model, dt, npts=5)
np.testing.assert_array_equal(
step_sol_2.t,
np.concatenate([np.array([0]),
np.linspace(dt, 2 * dt, 5)]))
np.testing.assert_allclose(step_sol_2.y[0],
np.exp(-0.1 * step_sol_2.t))
# Check steps give same solution as solve
t_eval = step_sol.t
solution = solver.solve(model, t_eval)
np.testing.assert_allclose(solution.y[0], step_sol.y[0])
def test_model_solver_ode_events_casadi(self):
# Create model
model = pybamm.BaseModel()
model.convert_to_format = "casadi"
whole_cell = ["negative electrode", "separator", "positive electrode"]
var = pybamm.Variable("var", domain=whole_cell)
model.rhs = {var: 0.1 * var}
model.initial_conditions = {var: 1}
model.events = [
pybamm.Event("2 * var = 2.5", pybamm.min(2 * var - 2.5)),
pybamm.Event("var = 1.5", pybamm.min(var - 1.5)),
]
disc = get_discretisation_for_testing()
disc.process_model(model)
# Solve
solver = pybamm.ScikitsOdeSolver(rtol=1e-9, atol=1e-9)
t_eval = np.linspace(0, 10, 100)
solution = solver.solve(model, t_eval)
np.testing.assert_allclose(solution.y[0], np.exp(0.1 * solution.t))
np.testing.assert_array_less(solution.y[0:, -1], 1.5)
np.testing.assert_array_less(solution.y[0:, -1], 1.25 + 1e-6)
np.testing.assert_equal(solution.t_event[0], solution.t[-1])
np.testing.assert_array_equal(solution.y_event[:, 0], solution.y[:,
-1])
def test_model_step_ode(self):
# Create model
model = pybamm.BaseModel()
whole_cell = ["negative electrode", "separator", "positive electrode"]
var = pybamm.Variable("var", domain=whole_cell)
model.rhs = {var: 0.1 * var}
model.initial_conditions = {var: 1}
disc = get_discretisation_for_testing()
disc.process_model(model)
solver = pybamm.ScikitsOdeSolver(rtol=1e-9, atol=1e-9)
# Step once
dt = 0.1
step_sol = solver.step(model, dt)
np.testing.assert_array_equal(step_sol.t, [0, dt])
np.testing.assert_allclose(step_sol.y[0], np.exp(0.1 * step_sol.t))
# Step again (return 5 points)
step_sol_2 = solver.step(model, dt, npts=5)
np.testing.assert_array_equal(step_sol_2.t, np.linspace(dt, 2 * dt, 5))
np.testing.assert_allclose(step_sol_2.y[0], np.exp(0.1 * step_sol_2.t))
# Check steps give same solution as solve
t_eval = np.concatenate((step_sol.t, step_sol_2.t[1:]))
solution = solver.solve(model, t_eval)
concatenated_steps = np.concatenate((step_sol.y[0], step_sol_2.y[0,
1:]))
np.testing.assert_allclose(solution.y[0], concatenated_steps)
def test_model_solver_ode_jacobian_python(self):
model = pybamm.BaseModel()
model.convert_to_format = "python"
whole_cell = ["negative electrode", "separator", "positive electrode"]
var1 = pybamm.Variable("var1", domain=whole_cell)
var2 = pybamm.Variable("var2", domain=whole_cell)
model.rhs = {var1: var1, var2: 1 - var1}
model.initial_conditions = {var1: 1.0, var2: -1.0}
model.variables = {"var1": var1, "var2": var2}
disc = get_discretisation_for_testing()
disc.process_model(model)
# Add user-supplied Jacobian to model
mesh = get_mesh_for_testing()
combined_submesh = mesh.combine_submeshes(
"negative electrode", "separator", "positive electrode"
)
N = combined_submesh[0].npts
# Solve
solver = pybamm.ScikitsOdeSolver(rtol=1e-9, atol=1e-9)
t_eval = np.linspace(0, 1, 100)
solution = solver.solve(model, t_eval)
np.testing.assert_array_equal(solution.t, t_eval)
T, Y = solution.t, solution.y
np.testing.assert_array_almost_equal(
model.variables["var1"].evaluate(T, Y),
np.ones((N, T.size)) * np.exp(T[np.newaxis, :]),
)
np.testing.assert_array_almost_equal(
model.variables["var2"].evaluate(T, Y),
np.ones((N, T.size)) * (T[np.newaxis, :] - np.exp(T[np.newaxis, :])),
)
def test_ode_solver_fail_with_dae(self):
model = pybamm.BaseModel()
a = pybamm.Scalar(1)
model.algebraic = {a: a}
model.concatenated_initial_conditions = a
solver = pybamm.ScikitsOdeSolver()
with self.assertRaisesRegex(pybamm.SolverError, "Cannot use ODE solver"):
solver.set_up(model)
def test_model_solver_ode_jacobian(self):
# Create model
model = pybamm.BaseModel()
whole_cell = ["negative electrode", "separator", "positive electrode"]
var1 = pybamm.Variable("var1", domain=whole_cell)
var2 = pybamm.Variable("var2", domain=whole_cell)
model.rhs = {var1: var1, var2: 1 - var1}
model.initial_conditions = {var1: 1.0, var2: -1.0}
model.variables = {"var1": var1, "var2": var2}
disc = get_discretisation_for_testing()
disc.process_model(model)
# Add user-supplied Jacobian to model
mesh = get_mesh_for_testing()
combined_submesh = mesh.combine_submeshes("negative electrode",
"separator",
"positive electrode")
N = combined_submesh[0].npts
# construct jacobian in order of model.rhs
J = []
for var in model.rhs.keys():
if var.id == var1.id:
J.append([np.eye(N), np.zeros((N, N))])
else:
J.append([-1.0 * np.eye(N), np.zeros((N, N))])
J = np.block(J)
def jacobian(t, y):
return J
model.jacobian = jacobian
# Solve
solver = pybamm.ScikitsOdeSolver(rtol=1e-9, atol=1e-9)
t_eval = np.linspace(0, 1, 100)
solution = solver.solve(model, t_eval)
np.testing.assert_array_equal(solution.t, t_eval)
T, Y = solution.t, solution.y
np.testing.assert_array_almost_equal(
model.variables["var1"].evaluate(T, Y),
np.ones((N, T.size)) * np.exp(T[np.newaxis, :]),
)
np.testing.assert_array_almost_equal(
model.variables["var2"].evaluate(T, Y),
np.ones(
(N, T.size)) * (T[np.newaxis, :] - np.exp(T[np.newaxis, :])),
)
def test_ode_integrate(self):
# Constant
solver = pybamm.ScikitsOdeSolver(rtol=1e-8, atol=1e-8)
def constant_growth(t, y):
return 0.5 * np.ones_like(y)
y0 = np.array([0])
t_eval = np.linspace(0, 1, 100)
solution = solver.integrate(constant_growth, y0, t_eval)
np.testing.assert_array_equal(solution.t, t_eval)
np.testing.assert_allclose(0.5 * solution.t, solution.y[0])
# Exponential decay
solver = pybamm.ScikitsOdeSolver(rtol=1e-8, atol=1e-8)
def exponential_decay(t, y):
return -0.1 * y
y0 = np.array([1])
t_eval = np.linspace(0, 1, 100)
solution = solver.integrate(exponential_decay, y0, t_eval)
np.testing.assert_allclose(solution.y[0], np.exp(-0.1 * solution.t))
self.assertEqual(solution.termination, "final time")
def test_model_solver_ode_python(self):
model = pybamm.BaseModel()
model.convert_to_format = "python"
whole_cell = ["negative electrode", "separator", "positive electrode"]
var = pybamm.Variable("var", domain=whole_cell)
model.rhs = {var: 0.1 * var}
model.initial_conditions = {var: 1}
disc = get_discretisation_for_testing()
disc.process_model(model)
# Solve
solver = pybamm.ScikitsOdeSolver(rtol=1e-9, atol=1e-9)
t_eval = np.linspace(0, 1, 100)
solution = solver.solve(model, t_eval)
np.testing.assert_array_equal(solution.t, t_eval)
np.testing.assert_allclose(solution.y[0], np.exp(0.1 * solution.t))
def test_ode_integrate_failure(self):
# Turn off warnings to ignore sqrt error
warnings.simplefilter("ignore")
def sqrt_decay(t, y):
return -np.sqrt(y)
y0 = np.array([1])
t_eval = np.linspace(0, 3, 100)
solver = pybamm.ScikitsOdeSolver()
# Expect solver to fail when y goes negative
with self.assertRaises(pybamm.SolverError):
solver.integrate(sqrt_decay, y0, t_eval)
# Turn warnings back on
warnings.simplefilter("default")
def test_model_ode_integrate_failure(self):
# Turn off warnings to ignore sqrt error
warnings.simplefilter("ignore")
model = pybamm.BaseModel()
var = pybamm.Variable("var")
model.rhs = {var: -pybamm.sqrt(var)}
model.initial_conditions = {var: 1}
disc = pybamm.Discretisation()
disc.process_model(model)
t_eval = np.linspace(0, 3, 100)
solver = pybamm.ScikitsOdeSolver()
# Expect solver to fail when y goes negative
with self.assertRaises(pybamm.SolverError):
solver.solve(model, t_eval)
# Turn warnings back on
warnings.simplefilter("default")
def test_model_solver_ode_events(self):
# Create model
model = pybamm.BaseModel()
whole_cell = ["negative electrode", "separator", "positive electrode"]
var = pybamm.Variable("var", domain=whole_cell)
model.rhs = {var: 0.1 * var}
model.initial_conditions = {var: 1}
model.events = {
"2 * var = 2.5": pybamm.min(2 * var - 2.5),
"var = 1.5": pybamm.min(var - 1.5),
}
disc = get_discretisation_for_testing()
disc.process_model(model)
# Solve
solver = pybamm.ScikitsOdeSolver(rtol=1e-9, atol=1e-9)
t_eval = np.linspace(0, 10, 100)
solution = solver.solve(model, t_eval)
np.testing.assert_allclose(solution.y[0], np.exp(0.1 * solution.t))
np.testing.assert_array_less(solution.y[0], 1.5)
np.testing.assert_array_less(solution.y[0], 1.25)
def test_init(self):
# linsolver deprecated
with self.assertRaisesRegex(ValueError,
"linsolver has been deprecated"):
pybamm.ScikitsOdeSolver(linsolver="lapackdense")
def test_ode_integrate_with_jacobian(self):
# Linear
solver = pybamm.ScikitsOdeSolver(rtol=1e-8, atol=1e-8)
def linear_ode(t, y):
return np.array([0.5, 2 - y[0]])
J = np.array([[0.0, 0.0], [-1.0, 0.0]])
sJ = sparse.csr_matrix(J)
def jacobian(t, y):
return J
def sparse_jacobian(t, y):
return sJ
y0 = np.array([0.0, 0.0])
t_eval = np.linspace(0, 1, 100)
solution = solver.integrate(linear_ode, y0, t_eval, jacobian=jacobian)
np.testing.assert_array_equal(solution.t, t_eval)
np.testing.assert_allclose(0.5 * solution.t, solution.y[0])
np.testing.assert_allclose(2.0 * solution.t - 0.25 * solution.t**2,
solution.y[1],
rtol=1e-4)
y0 = np.array([0.0, 0.0])
t_eval = np.linspace(0, 1, 100)
solution = solver.integrate(linear_ode,
y0,
t_eval,
jacobian=sparse_jacobian)
np.testing.assert_array_equal(solution.t, t_eval)
np.testing.assert_allclose(2.0 * solution.t - 0.25 * solution.t**2,
solution.y[1],
rtol=1e-4)
np.testing.assert_allclose(0.5 * solution.t, solution.y[0])
solver = pybamm.ScikitsOdeSolver(rtol=1e-8,
atol=1e-8,
linsolver="spgmr")
solution = solver.integrate(linear_ode, y0, t_eval, jacobian=jacobian)
np.testing.assert_array_equal(solution.t, t_eval)
np.testing.assert_allclose(0.5 * solution.t, solution.y[0])
np.testing.assert_allclose(2.0 * solution.t - 0.25 * solution.t**2,
solution.y[1],
rtol=1e-4)
solution = solver.integrate(linear_ode,
y0,
t_eval,
jacobian=sparse_jacobian)
np.testing.assert_array_equal(solution.t, t_eval)
np.testing.assert_allclose(2.0 * solution.t - 0.25 * solution.t**2,
solution.y[1],
rtol=1e-4)
np.testing.assert_allclose(0.5 * solution.t, solution.y[0])
# Nonlinear exponential grwoth
solver = pybamm.ScikitsOdeSolver(rtol=1e-8, atol=1e-8)
def exponential_growth(t, y):
return np.array([y[0], (1.0 - y[0]) * y[1]])
def jacobian(t, y):
return np.array([[1.0, 0.0], [-y[1], 1 - y[0]]])
def sparse_jacobian(t, y):
return sparse.csr_matrix(jacobian(t, y))
y0 = np.array([1.0, 1.0])
t_eval = np.linspace(0, 1, 100)
solution = solver.integrate(exponential_growth,
y0,
t_eval,
jacobian=jacobian)
np.testing.assert_array_equal(solution.t, t_eval)
np.testing.assert_allclose(np.exp(solution.t),
solution.y[0],
rtol=1e-4)
np.testing.assert_allclose(np.exp(1 + solution.t - np.exp(solution.t)),
solution.y[1],
rtol=1e-4)
solution = solver.integrate(exponential_growth,
y0,
t_eval,
jacobian=sparse_jacobian)
np.testing.assert_array_equal(solution.t, t_eval)
np.testing.assert_allclose(np.exp(solution.t),
solution.y[0],
rtol=1e-4)
np.testing.assert_allclose(np.exp(1 + solution.t - np.exp(solution.t)),
solution.y[1],
rtol=1e-4)
solver = pybamm.ScikitsOdeSolver(rtol=1e-8,
atol=1e-8,
linsolver="spgmr")
solution = solver.integrate(exponential_growth,
y0,
t_eval,
jacobian=jacobian)
np.testing.assert_array_equal(solution.t, t_eval)
np.testing.assert_allclose(np.exp(solution.t),
solution.y[0],
rtol=1e-4)
np.testing.assert_allclose(np.exp(1 + solution.t - np.exp(solution.t)),
solution.y[1],
rtol=1e-4)
solution = solver.integrate(exponential_growth,
y0,
t_eval,
jacobian=sparse_jacobian)
np.testing.assert_array_equal(solution.t, t_eval)
np.testing.assert_allclose(np.exp(solution.t),
solution.y[0],
rtol=1e-4)
np.testing.assert_allclose(np.exp(1 + solution.t - np.exp(solution.t)),
solution.y[1],
rtol=1e-4)
def default_solver(self):
"""
Create and return the default solver for this model
"""
return pybamm.ScikitsOdeSolver()
