Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

add matrix_mode: False option to sim params yaml to allow vectorized batch params #158

Merged
merged 1 commit into from
Aug 30, 2023
Merged

add matrix_mode: False option to sim params yaml to allow vectorized batch params #158

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
37 changes: 30 additions & 7 deletions buoy_gazebo/scripts/mbari_wec_batch
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -45,6 +45,14 @@ from rclpy.node import Node
DEFAULT_PHYSICS_MAX_STEP_SIZE = 0.001 # seconds


def to_shape(a, shape):
y_ = shape[0]
y = a.shape[0]
y_pad = (y_-y)
return np.pad(a, (0, y_pad),
mode = 'constant', constant_values=a[-1])


class MonoChromatic(object):
def __init__(self, A, T):
self.A, self.T = A, T
Expand Down Expand Up @@ -349,13 +357,28 @@ def generate_simulations(sim_params_yaml):
os.path.join(batch_results_dir,
sim_params_date_yaml))

# generate test matrix
batch_params = list(zip(*[param.ravel() for param in np.meshgrid(physics_step,
door_state,
scale_factor,
battery_state,
mean_piston_position,
incident_waves)]))
if 'matrix_mode' not in sim_params or \
('matrix_mode' in sim_params and sim_params['matrix_mode']):
# generate test matrix
batch_params = list(zip(*[param.ravel() for param in np.meshgrid(physics_step,
door_state,
scale_factor,
battery_state,
mean_piston_position,
incident_waves)]))
elif 'matrix_mode' in sim_params and not sim_params['matrix_mode']:
# generate test arrays
batch_params = [physics_step,
door_state,
scale_factor,
battery_state,
mean_piston_position,
incident_waves]
shape = max(batch_params, key=len).shape
for idx, param in enumerate(batch_params):
if np.array(param).shape != shape:
batch_params[idx] = to_shape(np.array(param), shape)
batch_params = list(zip(*[np.array(param).ravel() for param in batch_params]))

node.get_logger().info(f'Generated {len(batch_params)} simulation runs')
node.get_logger().debug('PhysicsStep, PhysicsRTF, Seed, Duration, DoorState, ScaleFactor' +
Expand Down