KinematicsData

class myoverse.datatypes.KinematicsData(input_data, sampling_frequency)

Class for storing kinematics data.

Parameters:

• input_data (np.ndarray) –

  The raw kinematics data. The shape of the array should be (n_joints, 3, n_samples) or (n_chunks, n_joints, 3, n_samples).

  Important

  The class will only accept 3D or 4D arrays.

  There is no way to check if you actually have it in (n_chunks, n_joints, 3, n_samples) format. Please make sure to provide the correct shape of the data.

• sampling_frequency (float) – The sampling frequency of the kinematics data.

input_data

The raw kinematics data. The shape of the array should be (n_joints, 3, n_samples) or (n_chunks, n_joints, 3, n_samples). The 3 represents the x, y, and z coordinates of the joints.

Type:

np.ndarray

sampling_frequency

The sampling frequency of the kinematics data.

Type:

float

processed_data

A dictionary where the keys are the names of filters applied to the kinematics data and the values are the processed kinematics data.

Type:

Dict[str, np.ndarray]

Examples

>>> import numpy as np
>>> from myoverse.datatypes import KinematicsData
>>>
>>> # Create sample kinematics data (16 joints, 3 coordinates, 1000 samples)
>>> # Each joint has x, y, z coordinates
>>> joint_data = np.random.randn(16, 3, 1000)
>>>
>>> # Create a KinematicsData object with 100 Hz sampling rate
>>> kinematics = KinematicsData(joint_data, 100)
>>>
>>> # Access the raw data
>>> raw_data = kinematics.input_data
>>> print(f"Data shape: {raw_data.shape}")
Data shape: (16, 3, 1000)

Methods

__init__(input_data, sampling_frequency)
plot(representation, nr_of_fingers[, ...])	Plots the data.

plot(representation, nr_of_fingers, wrist_included=True)

Plots the data.

Parameters:

• representation (str) – The representation to plot. .. important :: The representation should be a 3D tensor with shape (n_joints, 3, n_samples).

• nr_of_fingers (int) – The number of fingers to plot.

• wrist_included (bool, optional) – Whether the wrist is included in the representation. The default is True. .. note :: The wrist is always the first joint in the representation.

Raises:

KeyError – If the representation does not exist.

Examples

>>> import numpy as np
>>> from myoverse.datatypes import KinematicsData
>>>
>>> # Create sample kinematics data for a hand with 5 fingers
>>> # 16 joints: 1 wrist + 3 joints for each of the 5 fingers
>>> joint_data = np.random.randn(16, 3, 100)
>>> kinematics = KinematicsData(joint_data, 100)
>>>
>>> # Plot the kinematics data
>>> kinematics.plot('Input', nr_of_fingers=5)
>>>
>>> # Plot without wrist
>>> kinematics.plot('Input', nr_of_fingers=5, wrist_included=False)