def test_numeric_right_hand_side():
m, k, c, g, F, x, v = np.random.random(7)
args = {
'constants': np.array([m, k, c, g]),
'specified': np.array([F]),
'num_coordinates': 1
}
states = np.array([x, v])
mass_matrix, forcing_vector, constants, coordinates, speeds, specified = \
generate_mass_spring_damper_equations_of_motion()
expected_dx = np.array([v, 1.0 / m * (-c * v + m * g - k * x + F)])
backends = ['lambdify', 'theano', 'cython']
for backend in backends:
rhs = numeric_right_hand_side(mass_matrix,
forcing_vector,
constants,
coordinates,
speeds,
specified,
generator=backend)
dx = rhs(states, 0.0, args)
testing.assert_allclose(dx, expected_dx)
# Now try it without specified values.
mass_matrix, forcing_vector, constants, coordinates, speeds, specified = \
generate_mass_spring_damper_equations_of_motion(external_force=False)
expected_dx = np.array([v, 1.0 / m * (-c * v + m * g - k * x)])
# TODO : There is an import issue here, where the previous cython code
# is loaded from the module and the import needs to be reloaded. Not
# sure how to fix that.
for backend in backends:
rhs = numeric_right_hand_side(mass_matrix,
forcing_vector,
constants,
coordinates,
speeds,
specified,
generator=backend)
dx = rhs(states, 0.0, args)
testing.assert_allclose(dx, expected_dx)
# clean up the cython crud
files = glob.glob('multibody_system*')
for f in files:
os.remove(f)
shutil.rmtree('build')
def test_generate_ode_function(self):
m, k, c, g, F, x, v = np.random.random(7)
args = {'constants': np.array([m, k, c, g]),
'specified': np.array([F])}
states = np.array([x, v])
mass_matrix, forcing_vector, constants, coordinates, speeds, specified = \
generate_mass_spring_damper_equations_of_motion()
expected_dx = np.array([v, 1.0 / m * (-c * v + m * g - k * x + F)])
backends = ['lambdify', 'theano', 'cython']
for backend in backends:
rhs = generate_ode_function(mass_matrix, forcing_vector,
constants, coordinates, speeds,
specified, generator=backend)
dx = rhs(states, 0.0, args)
testing.assert_allclose(dx, expected_dx)
# Now try it with a function defining the specified quantities.
args['specified'] = lambda x, t: np.sin(t)
t = 14.345
expected_dx = np.array([v, 1.0 / m * (-c * v + m * g - k * x +
np.sin(t))])
for backend in backends:
rhs = generate_ode_function(mass_matrix, forcing_vector,
constants, coordinates, speeds,
specified, generator=backend)
dx = rhs(states, t, args)
testing.assert_allclose(dx, expected_dx)
# Now try it without specified values.
mass_matrix, forcing_vector, constants, coordinates, speeds, specified = \
generate_mass_spring_damper_equations_of_motion(external_force=False)
expected_dx = np.array([v, 1.0 / m * (-c * v + m * g - k * x)])
for backend in backends:
rhs = generate_ode_function(mass_matrix, forcing_vector,
constants, coordinates, speeds,
specified, generator=backend)
dx = rhs(states, 0.0, args)
testing.assert_allclose(dx, expected_dx)
def test_numeric_right_hand_side():
m, k, c, g, F, x, v = np.random.random(7)
args = {'constants': np.array([m, k, c, g]),
'specified': np.array([F]),
'num_coordinates': 1}
states = np.array([x, v])
mass_matrix, forcing_vector, constants, coordinates, speeds, specified = \
generate_mass_spring_damper_equations_of_motion()
expected_dx = np.array([v, 1.0 / m * (-c * v + m * g - k * x + F)])
backends = ['lambdify', 'theano', 'cython']
for backend in backends:
rhs = numeric_right_hand_side(mass_matrix, forcing_vector,
constants, coordinates, speeds,
specified, generator=backend)
dx = rhs(states, 0.0, args)
testing.assert_allclose(dx, expected_dx)
# Now try it without specified values.
mass_matrix, forcing_vector, constants, coordinates, speeds, specified = \
generate_mass_spring_damper_equations_of_motion(external_force=False)
expected_dx = np.array([v, 1.0 / m * (-c * v + m * g - k * x)])
# TODO : There is an import issue here, where the previous cython code
# is loaded from the module and the import needs to be reloaded. Not
# sure how to fix that.
for backend in backends:
rhs = numeric_right_hand_side(mass_matrix, forcing_vector,
constants, coordinates, speeds,
specified, generator=backend)
dx = rhs(states, 0.0, args)
testing.assert_allclose(dx, expected_dx)
# clean up the cython crud
files = glob.glob('multibody_system*')
for f in files:
os.remove(f)
shutil.rmtree('build')
def test_write_cython_code(self):
results = generate_mass_spring_damper_equations_of_motion()
generator = CythonGenerator(self.prefix, *results)
generator._write_cython_code()
file_dir = os.path.split(__file__)[0]
expected_files = [
'desired_mass_forcing_c.c', 'desired_mass_forcing_c.h',
'desired_mass_forcing.pyx', 'desired_mass_forcing_setup.py'
]
endings = ['_c.c', '_c.h', '.pyx', '_setup.py']
for ending, expected_file in zip(endings, expected_files):
created = self.prefix + ending
expected = os.path.join(file_dir, 'expected_cython', expected_file)
assert filecmp.cmp(created, expected)
def test_write_cython_code(self):
results = generate_mass_spring_damper_equations_of_motion()
generator = CythonGenerator(self.prefix, *results)
generator._write_cython_code()
file_dir = os.path.split(__file__)[0]
expected_files = ['desired_mass_forcing_c.c',
'desired_mass_forcing_c.h',
'desired_mass_forcing.pyx',
'desired_mass_forcing_setup.py']
endings = ['_c.c', '_c.h', '.pyx', '_setup.py']
for ending, expected_file in zip(endings, expected_files):
created = self.prefix + ending
expected = os.path.join(file_dir, 'expected_cython',
expected_file)
assert filecmp.cmp(created, expected)
def test_generate_ode_function(self):
m, k, c, g, F, x, v = np.random.random(7)
args = {
'constants': np.array([m, k, c, g]),
'specified': np.array([F])
}
states = np.array([x, v])
mass_matrix, forcing_vector, constants, coordinates, speeds, specified = \
generate_mass_spring_damper_equations_of_motion()
expected_dx = np.array([v, 1.0 / m * (-c * v + m * g - k * x + F)])
backends = ['lambdify', 'theano', 'cython']
for backend in backends:
rhs = generate_ode_function(mass_matrix,
forcing_vector,
constants,
coordinates,
speeds,
specified,
generator=backend)
dx = rhs(states, 0.0, args)
testing.assert_allclose(dx, expected_dx)
# Now try it with a function defining the specified quantities.
args['specified'] = lambda x, t: np.sin(t)
t = 14.345
expected_dx = np.array(
[v, 1.0 / m * (-c * v + m * g - k * x + np.sin(t))])
for backend in backends:
rhs = generate_ode_function(mass_matrix,
forcing_vector,
constants,
coordinates,
speeds,
specified,
generator=backend)
dx = rhs(states, t, args)
testing.assert_allclose(dx, expected_dx)
# Now try it without specified values.
mass_matrix, forcing_vector, constants, coordinates, speeds, specified = \
generate_mass_spring_damper_equations_of_motion(external_force=False)
expected_dx = np.array([v, 1.0 / m * (-c * v + m * g - k * x)])
for backend in backends:
rhs = generate_ode_function(mass_matrix,
forcing_vector,
constants,
coordinates,
speeds,
specified,
generator=backend)
dx = rhs(states, 0.0, args)
testing.assert_allclose(dx, expected_dx)
