Plotting (.plots)#

Most variables can easily be plotted with matplotlib or pandas as most data in this package is contained in dataframes. Some plotting is tedious however and these are functions for those plots.

worklab.plots.acc_peak_dist_plot(time, acc, dist, name='')[source]#

Plot acceleration and distance versus time, with acc_peak

Parameters

  • time (np.array, pd.Series) – time structure

  • acc (np.array, pd.Series) – acceleration structure

  • dist (np.array, pd.Series) – distance structure

  • name (str) – name of a session

Returns

ax

Return type

axis object

worklab.plots.acc_peak_plot(time, acc, name='')[source]#

Plot acceleration versus time, with acc_peak

Parameters

  • time (np.array, pd.Series) – time structure

  • acc (np.array, pd.Series) – acceleration structure

  • name (str) – name of a session

Returns

ax

Return type

axis object

worklab.plots.acc_plot(time, acc, name='')[source]#

Plot acceleration versus time

Parameters

  • time (np.array, pd.Series) – time structure

  • acc (np.array, pd.Series) – acceleration structure

  • name (str) – name of a session

Returns

ax

Return type

axis object

worklab.plots.bland_altman_plot(data1, data2, ax=None, condition=None)[source]#

Make a Bland-Altman plot.

A Bland–Altman plot (Difference plot) is a method of data plotting used in analyzing the agreement between two different assays.

Parameters

  • data1 (np.array, pd.Series) – First variable

  • data2 (np.array, pd.Series) – Second variable

  • ax (axis object, optional) – Axis to plot on, you can add your own, or it will make a new one.

  • condition (str, optional) – add labels to the plot

Returns

ax

Return type

axis object

worklab.plots.imu_push_plot(sessiondata, acc_frame=True, name='', dec=False)[source]#

Plot push detection with IMUs

Parameters

  • sessiondata (dict or pd.Series) – processed sessiondata structure or pd.Series with frame data

  • acc_frame (boolean) – set to True if frame acceleration is used, if False the wheel is used

  • name (str) – name of a session

  • dec (boolean) – set to True if main deceleration should be found

Returns

ax

Return type

axis object

worklab.plots.plot_power_speed_dist(data, title='', ylim_power=None, ylim_speed=None, ylim_distance=None)[source]#

Plot power, speed and distance versus time for left (solid line) and right (dotted line) separately

Figure scales automatically, unless you specify it manually with the ylim_* arguments

Parameters

  • data (dict) – processed ergometer data dictionary with dataframes

  • title (str) – a title for the plot

  • ylim_power (list [min, max] of float or int, optional) – list of the minimal and maximal ylim for power in W

  • ylim_speed (list [min, max] of floats or int, optional) – list of the minimal and maximal ylim for speed in km/h

  • ylim_distance (list [min, max] of floats or int, optional) – list of the minimal and maximal ylim for distance in m

Returns

  • fig (matplotlib.figure.Figure)

  • axes (tuple) – the three axes objects

worklab.plots.plot_pushes(data, pushes, var='torque', start=True, stop=True, peak=True, ax=None)[source]#

Plot pushes from measurement wheel or ergometer data.

Parameters

  • data (pd.DataFrame) – measurement wheel dataframe or the selected side from the ergometer dict, left, right or mean

  • pushes (pd.DataFrame) – measurement wheel push by push dataframe or the selected side from the ergometer dict, left, right or mean

  • var (str) – variable to plot, default is torque

  • start (bool) – plot push starts, default is True

  • stop (bool) – plot push stops, default is True

  • peak (bool) – plot push peaks, default is True

  • ax (axis object) – Axis to plot on, you can add your own, or it will make a new one.

Returns

ax

Return type

axis object

worklab.plots.plot_pushes_ergo(data, pushes, title=None, var='power', start=True, stop=True, peak=True)[source]#

Plot left, right and mean side ergometer push data

Parameters

  • data (dict) – processed ergometer data dictionary with dataframes

  • pushes (dict) – processed push_by_push ergometer data dictionary with dataframes

  • title (str) – title of the plot, optional

  • var (str) – variable to plot, default is power

  • start (bool) – plot push starts, default is True

  • stop (bool) – plot push stops, default is True

  • peak (bool) – plot push peaks, default is True

Returns

axes – an array containing an axis for the left, right and mean side

Return type

np.array

worklab.plots.rot_vel_plot(time, rot_vel, name='')[source]#

Plot rotational velocity versus time

Parameters

  • time (np.array, pd.Series) – time structure

  • rot_vel (np.array, pd.Series) – rotational velocity structure

  • name (str) – name of a session

Returns

ax

Return type

axis object

worklab.plots.set_axes_equal_3d(axes)[source]#

Set 3D plot axes to equal scale and size

Parameters

axes (matplotlib.axes._subplots.Axes3DSubplot) – axes containing 3D plotted data

worklab.plots.vel_peak_dist_plot(time, vel, dist, name='')[source]#

Plot velocity and distance against time

Parameters

  • time (np.array, pd.Series) – time structure

  • vel (np.array, pd.Series) – velocity structure

  • dist (np.array, pd.Series) – distance structure

  • name (str) – name of a session

Returns

ax

Return type

axis object

worklab.plots.vel_peak_plot(time, vel, name='')[source]#

Plot velocity versus time, with vel_peak

Parameters

  • time (np.array, pd.Series) – time structure

  • vel (np.array, pd.Series) – velocity structure

  • name (str) – name of a session

Returns

ax

Return type

axis object

worklab.plots.vel_plot(time, vel, name='')[source]#

Plot velocity versus time

Parameters

  • time (np.array, pd.Series) – time structure

  • vel (np.array, pd.Series) – velocity structure

  • name (str) – name of a session

Returns

ax

Return type

axis object