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Allow passing of arrays for bounds as well as scalars. Fixes #529. #532

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Merged
moorepants merged 5 commits into from
Apr 2, 2026
Merged

Allow passing of arrays for bounds as well as scalars. Fixes #529. #532

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4d0001c
Allow passing of arrays for bounds as well as scalars. Fixes #529.
moorepants Apr 1, 2026
7a5a710
Adjust plotting bounds to use arrays not scalars.
moorepants Apr 1, 2026
857343e
Raise error if bounds not scalar, support array bounds in conflict ch…
moorepants Apr 1, 2026
6193d02
Fix create_linear_guess to work with bound arrays.
moorepants Apr 2, 2026
c72739f
Added test for averaging the bound arrays in create linear guess.
moorepants Apr 2, 2026
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69 changes: 40 additions & 29 deletions opty/direct_collocation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -160,9 +160,11 @@ def __init__(self, obj, obj_grad, equations_of_motion, state_symbols,
bounds : dictionary, optional
This dictionary should contain a mapping from any of the symbolic
states, unknown trajectories, unknown parameters, or unknown time
interval to a 2-tuple of floats, the first being the lower bound
and the second the upper bound for that free variable, e.g.
``{x(t): (-1.0, 5.0)}``.
interval to a 2-tuple of floats. If setting states or unknown
trajectories, an ndarray of shape(N,) can be supplied instead of a
float. The first entry of the 2-tuple is the lower bound and the
second the upper bound for that free variable, e.g. ``{x(t): (-1.0,
5.0)}`` or ``{x(t): (-1.0, np.ones(N))}``.
eom_bounds : dictionary, optional
Optional lower and upper bounds for the equations of motion,
default is ``(0.0, 0.0)`` for each equation making them equality
Expand Down Expand Up @@ -347,7 +349,7 @@ def check_bounds_conflict(self, free):
if self.bounds is not None:
# check for reversed bounds
for key in self.bounds.keys():
if self.bounds[key][0] > self.bounds[key][1]:
if np.any(self.bounds[key][0] > self.bounds[key][1]):
errors2.append(key)

errors = errors1 + errors2
Expand Down Expand Up @@ -430,14 +432,26 @@ def _generate_bound_arrays(self):
i = state_syms.index(var)
start = i * N
stop = start + N
lb[start:stop] = bounds[0] * np.ones(N)
ub[start:stop] = bounds[1] * np.ones(N)
if np.isscalar(bounds[0]):
lb[start:stop] = bounds[0] * np.ones(N)
else:
lb[start:stop] = bounds[0]
if np.isscalar(bounds[1]):
ub[start:stop] = bounds[1] * np.ones(N)
else:
ub[start:stop] = bounds[1]
elif var in unk_traj:
i = unk_traj.index(var)
start = num_state_nodes + i * N
stop = start + N
lb[start:stop] = bounds[0] * np.ones(N)
ub[start:stop] = bounds[1] * np.ones(N)
if np.isscalar(bounds[0]):
lb[start:stop] = bounds[0] * np.ones(N)
else:
lb[start:stop] = bounds[0]
if np.isscalar(bounds[1]):
ub[start:stop] = bounds[1] * np.ones(N)
else:
ub[start:stop] = bounds[1]
elif var in unk_par:
i = unk_par.index(var)
idx = num_non_par_nodes + i
Expand Down Expand Up @@ -670,10 +684,12 @@ def plot_trajectories(self, vector, axes=None, show_bounds=False):

if self.bounds is not None and show_bounds:
if symbol in self.bounds.keys():
ax.axhline(self.bounds[symbol][0], color='C1', lw=1.0,
linestyle='--')
ax.axhline(self.bounds[symbol][1], color='C1', lw=1.0,
linestyle='--')
ax.plot(time, self.extract_values(self.lower_bound,
symbol), color='C1',
lw=1.0, linestyle='--')
ax.plot(time, self.extract_values(self.upper_bound,
symbol), color='C1',
lw=1.0, linestyle='--')
ax.set_xlabel('Time')
axes[0].set_title('State Trajectories')
if (self.collocator.num_unknown_input_trajectories +
Expand Down Expand Up @@ -1336,9 +1352,9 @@ def create_linear_initial_guess(self, end_time=1.0):
for symb in self.collocator.unknown_input_trajectories:
idx = self.collocator.unknown_input_trajectories.index(symb)
if symb in self.bounds.keys():
if self.bounds[symb][0] == -np.inf:
if np.any(self.bounds[symb][0] <= -self.INF):
wert = self.bounds[symb][1]
elif self.bounds[symb][1] == np.inf:
elif np.any(self.bounds[symb][1] >= self.INF):
wert = self.bounds[symb][0]
else:
wert = 0.5*(self.bounds[symb][0] +
Expand All @@ -1355,9 +1371,9 @@ def create_linear_initial_guess(self, end_time=1.0):
for symb in self.collocator.unknown_parameters:
idx = self.collocator.unknown_parameters.index(symb)
if symb in self.bounds.keys():
if self.bounds[symb][0] == -np.inf:
if self.bounds[symb][0] <= -self.INF:
wert = self.bounds[symb][1]
elif self.bounds[symb][1] == np.inf:
elif self.bounds[symb][1] >= self.INF:
wert = self.bounds[symb][0]
else:
wert = 0.5*(self.bounds[symb][0] +
Expand All @@ -1367,20 +1383,15 @@ def create_linear_initial_guess(self, end_time=1.0):
# set the value of the variable time interval.
if isinstance(self.collocator.node_time_interval, sm.Symbol):
if self.bounds is not None:
if self.collocator.node_time_interval in self.bounds.keys():
if (self.bounds[self.collocator.node_time_interval][0] ==
-np.inf):
wert = self.bounds[
self.collocator.node_time_interval][1]
elif (self.bounds[self.collocator.node_time_interval][1] ==
np.inf):
wert = self.bounds[self.collocator.
node_time_interval][0]
symb = self.collocator.node_time_interval
if symb in self.bounds.keys():
lb, ub = self.bounds[symb][0], self.bounds[symb][1]
if lb <= -self.INF:
wert = ub
elif ub >= self.INF:
wert = lb
else:
wert = 0.5*(self.bounds[self.collocator.
node_time_interval][0] +
self.bounds[self.collocator.
node_time_interval][1])
wert = 0.5*(lb + ub)
initial_guess[-1] = wert

if self.bounds is None:
Expand Down
49 changes: 48 additions & 1 deletion opty/tests/test_direct_collocation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -468,7 +468,7 @@ def test_extra_algebraic(plot=False):
plt.show()


def test_pendulum():
def test_pendulum(plot=False):

target_angle = np.pi
duration = 10.0
Expand Down Expand Up @@ -530,6 +530,53 @@ def test_pendulum():
expected_upp_con_bounds[50:100] = 10.0
np.testing.assert_allclose(prob._upp_con_bounds, expected_upp_con_bounds)

# now test bounds set to arrays and scalars
theta_bounds = (-np.ones(num_nodes), 4.0*np.ones(num_nodes))
torque_low = -np.ones(num_nodes)
torque_low[0:20] = 3.0*torque_low[0:20]
torque_bounds = (torque_low, 2.0)

prob = Problem(
obj, obj_grad, eom, state_symbols, num_nodes, interval_value,
known_parameter_map=par_map,
instance_constraints=instance_constraints,
time_symbol=t,
bounds={
theta(t): theta_bounds,
T(t): torque_bounds,
},
backend='numpy',
)

np.testing.assert_allclose(prob.lower_bound,
np.hstack((theta_bounds[0],
-10e19*np.ones(num_nodes),
torque_low
)))

np.testing.assert_allclose(prob.upper_bound,
np.hstack((theta_bounds[1],
10e19*np.ones(num_nodes),
2.0*np.ones(num_nodes),
)))

init = prob.create_linear_initial_guess()

np.testing.assert_allclose(
init,
np.hstack((
np.linspace(0.0, target_angle, num=num_nodes),
np.zeros(num_nodes),
0.5*(torque_low + 2.0),
))
)
if plot:
prob.plot_trajectories(init)
import matplotlib.pyplot as plt
plt.show()

prob.check_bounds_conflict(init)


def TestProblem():

Expand Down
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