slerp_nan

ahrs.common.quaternion.QuaternionArray.slerp_nan(self, inplace: bool = True) → ndarray

SLERP over NaN values in Quaternion array.

Parameters:

inplace (bool, default: True) – If True, the quaternion array is modified in-place, and the method returns None. Otherwise, a NumPy array is returned.

Returns:

interpolated_quaternions – Full array with interpolated values if inplace is set to False. Otherwise the QuaternionArray is modified in-place and None is returned.

Return type:

numpy.ndarray or None

Examples

>>> qts = np.tile([1., -2., 3., -4], (5, 1))    # Five equal arrays
>>> v = np.random.randn(5, 4)*0.1               # Gaussian noise
>>> Q = QuaternionArray(qts + v)
>>> Q[1:3] = np.nan    # 2nd and 3rd Quaternions are NaN
>>> Q.view()
QuaternionArray([[ 0.17614144, -0.39173347,  0.56303067, -0.70605634],
                 [        nan,         nan,         nan,         nan],
                 [        nan,         nan,         nan,         nan],
                 [ 0.17094453, -0.3723117 ,  0.54109885, -0.73442086],
                 [ 0.1862619 , -0.38421818,  0.5260265 , -0.73551276]])
>>> Q.slerp_nan()
>>> Q.view()
QuaternionArray([[ 0.17614144, -0.39173347,  0.56303067, -0.70605634],
                 [ 0.1721561 , -0.37614515,  0.53987073, -0.7320696 ],
                 [ 0.16823806, -0.35898889,  0.53664261, -0.74487424],
                 [ 0.17094453, -0.3723117 ,  0.54109885, -0.73442086],
                 [ 0.1862619 , -0.38421818,  0.5260265 , -0.73551276]])