models.trajectory package

Submodules

models.trajectory.FilterTraj module

class models.trajectory.FilterTraj.FilterTraj(name, filepath=None)

Bases: TrajectoryBase

append_propagated_states(t, state)
append_updated_states(t, state)
labels: List[str] = ['t', 'x', 'y', 'z', 'vx', 'vy', 'vz', 'rx', 'ry', 'rz', 'qw', 'qx', 'qy', 'qz', 'dof1', 'dof2', 'dof3', 'dof4', 'dof5', 'dof6', 'xc', 'yc', 'zc', 'rx_degc', 'ry_degc', 'rz_degc', 'qwc', 'qxc', 'qyc', 'qzc']
labels_camera = ['xc', 'yc', 'zc', 'rx_degc', 'ry_degc', 'rz_degc', 'qwc', 'qxc', 'qyc', 'qzc']
labels_imu = ['x', 'y', 'z', 'vx', 'vy', 'vz', 'rx', 'ry', 'rz', 'qw', 'qx', 'qy', 'qz']
labels_imu_dofs = ['dof1', 'dof2', 'dof3', 'dof4', 'dof5', 'dof6']
property rx_degc_unwrapped
property rx_unwrapped
property ry_degc_unwrapped
property ry_unwrapped
property rz_degc_unwrapped
property rz_unwrapped

models.trajectory.ImuRefTraj module

class models.trajectory.ImuRefTraj.ImuRefTraj(name: str, imu: Imu, filepath: Optional[str] = None)

Bases: TrajectoryBase

Desired traj of the IMU.

append_value(t: float, cam_meas_vec: List[np.ndarray], current_notch: np.ndarray)

Appends new measurement from current state.

labels: List[str] = ['t', 'x', 'y', 'z', 'vx', 'vy', 'vz', 'rx', 'ry', 'rz', 'qw', 'qx', 'qy', 'qz']

models.trajectory.ImuTrajectory module

class models.trajectory.ImuTrajectory.ImuTraj(name='imu', filepath=None, interframe_vals: int = 0, covariance: List[float] = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0], unnoised: bool = False)

Bases: TrajectoryBase

IMU trajectory containing the acceleration and angular velocity measurements.

labels: List[str] = ['t', 'ax', 'ay', 'az', 'gx', 'gy', 'gz']
reconstruct(R_WB, W_p_BW_0, WW_v_BW_0)

For validation. Generates trajectory from IMU data. The IMU trajectory is obtained via numerical integration using the available initial conditions.

reconstruct_vis_traj()

Generates trajectory from IMU data using the available initial conditions.

models.trajectory.Interpolator module

class models.trajectory.Interpolator.Interpolator(interframe_vals: int, uninterp_camera: Camera)

Bases: object

property flag_done: bool
interpolate() → None

Interpolates data and stores it in self.interp_traj. Also generates quats_array in self.interp_traj.

property interpolated: VisualTraj

models.trajectory.TrajectoryBase module

class models.trajectory.TrajectoryBase.TrajectoryBase(name: str, filepath: Optional[str] = None, cap: Optional[int] = None, interframe_vals: int = 0)

Bases: ABC

Base trajectory class which requires a trajectory name, trajectory labels, and a filepath.

labels: List[str] = ['t']
property num_values: int

Number of values stored.

reset()

Reinitialises data labels.

models.trajectory.VisualTrajectory module

class models.trajectory.VisualTrajectory.VisualTraj(name: str, filepath: Optional[str] = None, notch_filepath: Optional[str] = None, cap: Optional[int] = None, scale: Optional[float] = None, with_notch: bool = False, start_at: Optional[int] = None)

Bases: TrajectoryBase

Visual trajectory containing time and pose.

at_index(index: int) → VisualMeasurementPoint

Returns single visual measurement at the given index.

gen_angle_arrays() → None

Updates angles.

labels: List[str] = ['t', 'x', 'y', 'z', 'qx', 'qy', 'qz', 'qw']
property lims
read_notch_from_file()
t: Optional[np.ndarray]
property x_lims
property y_lims
property z_lims

Module contents