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skip eom jacobian test, add full jacobian test
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@chris-konrad
chris-konrad committed Jan 7, 2025
1 parent d2026ff commit 6a41bc5
Showing 1 changed file with 22 additions and 24 deletions.
46 changes: 22 additions & 24 deletions opty/tests/test_direct_collocation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1591,7 +1591,9 @@ def setup_method(self):
self.interval_value = 0.01
self.free = np.array([1.0, 2.0, 3.0, 4.0, # x
5.0, 6.0, 7.0, 8.0, # v
3.0]) # k
2.0, 2.0, 2.0, 2.0, # f(t-tau)
3.0, # k
0.0]) #tau

self.eom = sym.Matrix([x(t).diff() - v(t),
m * v(t).diff() + c * v(t) + k * x(t) - f(t-tau)])
Expand Down Expand Up @@ -1782,23 +1784,17 @@ def test_gen_multi_arg_con_func_midpoint(self):
expected = np.hstack((expected_kinematic, expected_dynamic))

np.testing.assert_allclose(result, expected)


def test_gen_multi_arg_con_jac_func_backward_euler(self):
def test_generate_jacobian_function(self):

self.collocator._gen_multi_arg_con_jac_func()
jacobian = self.collocator.generate_jacobian_function()

# Make sure the parameters are in the correct order.
constant_values = \
np.array([self.constant_values[self.constant_symbols.index(c)]
for c in self.collocator.parameters])
jac_vals = jacobian(self.free)

# TODO : Once there are more than one specified, they will need to
# be put in the correct order too.
row_idxs, col_idxs = self.collocator.jacobian_indices()

jac_vals = self.collocator._multi_arg_con_jac_func(self.state_values,
self.specified_values,
constant_values,
self.interval_value)
jacobian_matrix = sparse.coo_matrix((jac_vals, (row_idxs, col_idxs)))

row_idxs, col_idxs = self.collocator.jacobian_indices()

Expand All @@ -1812,20 +1808,22 @@ def test_gen_multi_arg_con_jac_func_backward_euler(self):
x = self.state_values[0]
m, c, k = self.constant_values
h = self.interval_value
c_tau = 1
c_tau = 0

expected_jacobian = np.array(
# x1, x2, x3, x4, v1, v2, v3, v4, f1, f2, f3, f4, k, tau
[[-1 / h, 1 / h, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0],
[ 0, -1 / h, 1 / h, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0],
[ 0, 0, -1 / h, 1 / h, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0],
[ 0, k, 0, 0, -m / h, c + m / h, 0, 0, 0, 0, 0, 0, x[1], 0],
[ 0, 0, k, 0, 0, -m / h, c + m / h, 0, 0, 0, 0, 0, x[2], 0],
[ 0, 0, 0, k, 0, 0, -m /h, c + m / h, 0, 0, 0, 0, x[3], 0],
[ 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, c_tau],
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, c_tau],
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, c_tau],
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, c_tau]],
[[-1 / h, 1 / h, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0], #eom-node 0
[ 0, -1 / h, 1 / h, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0], #eom-node 1
[ 0, 0, -1 / h, 1 / h, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0], #eom-node 2
[ 0, k, 0, 0, -m / h, c + m / h, 0, 0, 0, -1, 0, 0, x[1], 0], #eom-node 3
[ 0, 0, k, 0, 0, -m / h, c + m / h, 0, 0, 0, -1, 0, x[2], 0], #eom-node 4
[ 0, 0, 0, k, 0, 0, -m /h, c + m / h, 0, 0, 0, -1, x[3], 0], #eom-node 5
[ 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], #c0: x[0] = 0
[ 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0], #c1: v[0] = 5
[ 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, c_tau], #c_tshift_0
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, c_tau], #c_tshift_1
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, c_tau], #c_tshift_2
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, c_tau]], #c_tshift_3
dtype=float)

np.testing.assert_allclose(jacobian_matrix.todense(), expected_jacobian)
Expand Down

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