def test_namespacewriter_simple():
f = Frame()
f.addfield("Y", 1.)
f.addgroup("A")
f.A.addfield("B", 0.)
def dYdx(f, x, Y):
return -Y
f.Y.differentiator = dYdx
f.addintegrationvariable("x", 0.)
def dx(f):
return 1.
f.x.updater = dx
f.x.snapshots = [1.]
f.integrator = Integrator(f.x)
f.integrator.instructions = [Instruction(schemes.expl_1_euler, f.Y)]
f.writer = writers.namespacewriter()
f.writer.dumping = True
f.run()
Y = f.writer.read.sequence("Y")
assert np.all(Y == [1., 0.])
x = f.writer.read.sequence("x")
assert np.all(x == [0., 1.])
data = f.writer.read.all()
assert np.all(data.Y == [1., 0.])
assert np.all(data.x == [0., 1.])
f.writer.reset()
def test_field_derivative():
f = Frame()
f.addfield("Y", 1.)
f.addintegrationvariable("x", 0.)
def diff(f, x, Y):
return -Y
f.Y.differentiator = diff
with pytest.raises(RuntimeError):
f.Y.derivative()
f.integrator = Integrator(f.x)
f.integrator._var = None
with pytest.raises(RuntimeError):
f.Y.derivative()
f.integrator = Integrator(f.x)
assert np.all(f.Y.derivative() == -f.Y)
f.addfield("Y", [1., 0])
assert np.all(f.Y.derivative() == 0.)
def jac(f, x):
return [[2., 0], [0., 2.]]
f.Y.jacobinator = jac
assert np.all(f.Y.derivative() == [2., 0.])
def test_expl_5_cash_karp_adptv():
f = Frame()
f.addfield("Y", 1.)
def dYdx(f, x, Y):
return -Y
f.Y.differentiator = dYdx
f.addintegrationvariable("x", 0.)
def dx(f):
return f.x.suggested
f.x.updater = dx
f.x.snapshots = [10.]
f.x.suggest(0.1)
f.integrator = Integrator(f.x)
f.integrator.instructions = [
Instruction(schemes.expl_5_cash_karp_adptv,
f.Y,
controller={"eps": 1.e-3})
]
f.run()
assert np.allclose(f.Y, 4.57114092616805e-05)
def test_frame_run():
f = Frame()
f.verbosity = 0
f.addintegrationvariable("x", 0.)
with pytest.raises(RuntimeError):
f.run()
f.integrator = Integrator(f.x)
f.integrator._var = None
with pytest.raises(RuntimeError):
f.run()
f.integrator = Integrator(f.x)
with pytest.raises(RuntimeError):
f.run()
f.x = 3.
f.x.snapshots = [1., 2.]
with pytest.raises(RuntimeError):
f.run()
def dx(f):
return 0.1
f.x.updater = dx
f.x = 1.5
f.run()
assert np.all(f.x == 2.)
def test_expl_3_gottlieb_shu_adptv():
f = Frame()
f.addfield("Y", 1.)
def dYdx(f, x, Y):
return -Y
f.Y.differentiator = dYdx
f.addintegrationvariable("x", 0.)
def dx(f):
return f.x.suggested
f.x.updater = dx
f.x.snapshots = [10.]
f.x.suggest(0.1)
f.integrator = Integrator(f.x)
f.integrator.instructions = [
Instruction(schemes.expl_3_gottlieb_shu_adptv,
f.Y,
controller={"eps": 1.e-4})
]
f.run()
assert np.allclose(f.Y, 4.5390485375346277e-05)
def test_expl_2_heun_euler_adaptive():
f = Frame()
f.addfield("Y", 1.)
def dYdx(f, x, Y):
return -Y
f.Y.differentiator = dYdx
f.addintegrationvariable("x", 0.)
def dx(f):
return f.x.suggested
f.x.updater = dx
f.x.snapshots = [10.]
f.x.suggest(0.1)
f.integrator = Integrator(f.x)
f.integrator.instructions = [
Instruction(schemes.expl_2_heun_euler_adptv,
f.Y,
controller={"eps": 1.e-3})
]
f.run()
assert np.allclose(f.Y, 4.553150014598088e-05)
def test_impl_1_euler_gmres_fail():
f = Frame()
f.addfield("Y", 1.)
def jac(f, x):
return np.array([-1.])
f.Y.jacobinator = jac
f.addintegrationvariable("x", 0.)
def dx(f):
return 0.1
f.x.updater = dx
f.x.snapshots = [10.]
f.integrator = Integrator(f.x)
f.integrator.instructions = [
Instruction(schemes.impl_1_euler_gmres,
f.Y,
controller={
"gmres_opt": {
"atol": 0.,
"tol": 1.e-18,
"maxiter": 1
}
})
]
with pytest.raises(StopIteration):
f.run()
def test_expl_5_dormand_prince_adptv():
f = Frame()
f.addfield("Y", 1.)
def dYdx(f, x, Y):
return -Y
f.Y.differentiator = dYdx
f.addintegrationvariable("x", 0.)
def dx(f):
return f.x.suggested
f.x.updater = dx
f.x.snapshots = [10.]
f.x.suggest(0.1)
f.integrator = Integrator(f.x)
f.integrator.instructions = [
Instruction(schemes.expl_5_dormand_prince_adptv,
f.Y,
controller={"eps": 1.e-2})
]
f.run()
assert np.allclose(f.Y, 1.8016162079480785e-06)
def test_simple_read_files():
f = Frame()
f.addgroup("A")
f.A.addfield("B", [0., 0.])
f.addfield("Y", 1.)
def dYdx(f, x, Y):
return -Y
f.Y.differentiator = dYdx
f.addintegrationvariable("x", 0.)
def dx(f):
return 1.
f.x.updater = dx
f.x.snapshots = [1.]
f.integrator = Integrator(f.x)
f.integrator.instructions = [Instruction(schemes.expl_1_euler, f.Y)]
f.writer = writers.hdf5writer()
f.run()
x = f.writer.read.sequence("x")
assert np.all(x == [0., 1.])
Y = f.writer.read.sequence("Y")
assert np.all(Y == [1., 0.])
B = f.writer.read.sequence("A.B")
assert np.all(B == [0., 0.])
with pytest.raises(TypeError):
f.writer.read.sequence(1)
data = f.writer.read.all()
assert np.all(data.x == [0., 1.])
assert np.all(data.Y == [1., 0.])
assert np.all(data.A.B == [0., 0.])
data0000 = f.writer.read.output(0)
assert np.all(data0000.x == 0.)
assert np.all(data0000.Y == 1.)
assert np.all(data0000.A.B == 0.)
with pytest.raises(RuntimeError):
f.writer.read.output(2)
shutil.rmtree(f.writer.datadir)
with pytest.raises(RuntimeError):
f.writer.datadir = "temp"
f.writer.read.all()
with pytest.raises(RuntimeError):
f.writer.read.sequence("x")
f.writer.datadir = "data"
def test_simple():
f = Frame()
f.addfield("Y", 1.)
def dYdx(f, x, Y):
return -Y
f.Y.differentiator = dYdx
f.addintegrationvariable("x", 0.)
def dx(f):
return 1.
f.x.updater = dx
f.x.snapshots = [1.]
f.integrator = Integrator(f.x)
f.integrator.instructions = [Instruction(schemes.expl_1_euler, f.Y)]
f.run()
assert f.Y == 0.
assert f.x.prevstepsize == 1.
def test_group_repr_str():
f = Frame()
assert isinstance(repr(f), str)
assert isinstance(str(f), str)
f.addintegrationvariable("x", 0)
f.addfield("Y", 1.)
f.addfield("abcdefghijklm", 0.)
f.addgroup("A")
f.addgroup("BCDEFGHIJKLMN")
f.C = None
f.abcdef1234567 = None
f.A.addfield("k", 0.)
assert isinstance(repr(f), str)
assert isinstance(str(f), str)
assert isinstance(repr(f.A), str)
assert isinstance(str(f.A), str)
f.integrator = Integrator(f.x)
f.writer = writers.namespacewriter()
assert isinstance(repr(f), str)
assert isinstance(str(f), str)
def test_expl_2_heun():
f = Frame()
f.addfield("Y", 1.)
def dYdx(f, x, Y):
return -Y
f.Y.differentiator = dYdx
f.addintegrationvariable("x", 0.)
def dx(f):
return 0.1
f.x.updater = dx
f.x.snapshots = [10.]
f.integrator = Integrator(f.x)
f.integrator.instructions = [Instruction(schemes.expl_2_heun, f.Y)]
f.run()
assert np.allclose(f.Y, 4.6222977814657625e-05)
def test_impl_1_euler_gmres():
f = Frame()
f.addfield("Y", 1.)
def jac(f, x):
return np.array([-1.])
f.Y.jacobinator = jac
f.addintegrationvariable("x", 0.)
def dx(f):
return 0.1
f.x.updater = dx
f.x.snapshots = [10.]
f.integrator = Integrator(f.x)
f.integrator.instructions = [Instruction(schemes.impl_1_euler_gmres, f.Y)]
f.run()
assert np.allclose(f.Y, 7.256571590148018e-05)
def test_field_jacobian():
f = Frame()
f.addfield("Y", 1.)
f.addintegrationvariable("x", 0.)
def jac(f, x):
if x == None:
return 0.
else:
return x
f.Y.jacobinator = jac
with pytest.raises(RuntimeError):
f.Y.jacobian()
f.integrator = Integrator(f.x)
f.integrator._var = None
with pytest.raises(RuntimeError):
f.Y.jacobian()
f.integrator = Integrator(f.x)
assert f.Y.jacobian() == 0.
assert f.Y.jacobian(x=1.) == 1.
def test_expl_4_runge_kutta():
f = Frame()
f.addfield("Y", 1.)
def dYdx(f, x, Y):
return -Y
f.Y.differentiator = dYdx
f.addintegrationvariable("x", 0.)
def dx(f):
return 0.1
f.x.updater = dx
f.x.snapshots = [10.]
f.integrator = Integrator(f.x)
f.integrator.instructions = [Instruction(schemes.expl_4_runge_kutta, f.Y)]
f.run()
assert np.allclose(f.Y, 4.540034101629485e-05)
def test_expl_1_euler():
f = Frame()
f.addfield("Y", 1.)
def dYdx(f, x, Y):
return -Y
f.Y.differentiator = dYdx
f.addintegrationvariable("x", 0.)
def dx(f):
return 0.1
f.x.updater = dx
f.x.snapshots = [10.]
f.integrator = Integrator(f.x)
f.integrator.instructions = [Instruction(schemes.expl_1_euler, f.Y)]
f.run()
assert np.allclose(f.Y, 2.656139888758694e-05)
def test_adaptive_update():
f = Frame()
f.addfield("Y", 1.)
def dYdx(f, x, Y):
return -Y
f.Y.differentiator = dYdx
f.addintegrationvariable("x", 0.)
def dx(f):
return f.x.suggested
f.x.updater = dx
f.x.snapshots = [10.]
f.x.suggest(100.)
f.integrator = Integrator(f.x)
f.integrator.instructions = [Instruction(schemes.expl_5_cash_karp_adptv, f.Y),
Instruction(schemes.update, f.Y)]
f.run()
assert f.Y == 5.34990702474703e-3
def test_adaptive_fail():
f = Frame()
f.addfield("Y", 1.)
def dYdx(f, x, Y):
return -Y
f.Y.differentiator = dYdx
f.addintegrationvariable("x", 0.)
def dx(f):
return f.x.suggested
f.x.updater = dx
f.x.snapshots = [10.]
f.x.suggest(100.)
f.integrator = Integrator(f.x)
f.integrator.instructions = [Instruction(
schemes.expl_5_cash_karp_adptv, f.Y)]
f.integrator.maxit = 1
with pytest.raises(StopIteration):
f.run()
def test_impl_2_midpoint_direct():
f = Frame()
f.addfield("Y", 1.)
def jac(f, x):
return np.array([-1.])
f.Y.jacobinator = jac
f.addintegrationvariable("x", 0.)
def dx(f):
return 0.1
f.x.updater = dx
f.x.snapshots = [10.]
f.integrator = Integrator(f.x)
f.integrator.instructions = [
Instruction(schemes.impl_2_midpoint_direct, f.Y)
]
f.run()
assert np.allclose(f.Y, 4.5022605238147066e-05)