pytransform3d.transform_manager.NumpyTimeseriesTransform

class pytransform3d.transform_manager.NumpyTimeseriesTransform(time, pqs, time_clipping=False)

Bases: TimeVaryingTransform

Transformation sequence, represented in a numpy array.

The interpolation is computed using screw linear interpolation (ScLERP) method.

Parameters:

time: array, shape (n_steps,)

Numeric timesteps corresponding to the transformation samples. You can use, for example, unix timestamps, relative time (starting with 0).

pqsarray, shape (n_steps, 7)

Time-sequence of transformations, with each row representing a single sample as position-quarternion (PQ) structure.

time_clippingbool, optional (default: False)

Clip time to minimum or maximum respectively when query time is out of range of the time series. If this deactivated, we will raise a ValueError when the query time is out of range.

__init__(time, pqs, time_clipping=False)

Methods

__init__(time, pqs[, time_clipping])
as_matrix(query_time)	Get transformation matrix at given time.
check_transforms()	Checks all transformations.

as_matrix(query_time)

Get transformation matrix at given time.

Parameters:

query_timeUnion[float, array-like shape (…)]

Query time

Returns:

A2B_tarray, shape (4, 4) or (…, 4, 4)

Homogeneous transformation matrix / matrices at given time / times.

check_transforms()

Checks all transformations.

Returns:

selfTimeVaryingTransform

Validated transformations.

Examples using pytransform3d.transform_manager.NumpyTimeseriesTransform

Managing Transformations over Time

Managing Transformations over Time