TDSData.plot_data(xdata, ydata, *, xheader=None, yheader=None, xlabel=None, ylabel=None, linestyles=None, left=None, right=None, ymin=None, ymax=None, legend=None, grid=False, fig=None, ax=None, latex=True, dpi=None, line_width=1.0, font_size=12, greyscale=False, savefig=None, save_format=None, show=True, title=None, hline1=None, hline2=None, vline1=None, hline=None, vline=None, vline2=None, set_xlim=True, set_ylim=True, autoscale=False, figsize=None, legend_bbox=None, legend_loc=None, legend_ncol=1, mask=True, color=None, style='default', **kwargs)[source]#

Plot lines for the supplied data and options.

This functions takes xdata and ydata values. If you provide variable indices instead of values, use plot().

See the argument lists of plot() for more.


An array-like object containing the values for the x-axis variable


An array containing the values of each variables for the y-axis variable. The row of ydata must match the row of xdata. Each column correspondings to a variable.


If enabled (1), when specifying axis limits, only data in the limits will be used for plotting to optimize for autoscaling. It is done through an index mask.

(fig, ax)

The figure and axis handles


To plot the results of arithmetic calculation of variables, retrieve the values, do the calculation, and plot with plot_data.

>>> v = ss.dae.ts.y[:, ss.PVD1.v.a]
>>> Ipcmd = ss.dae.ts.y[:, ss.PVD1.Ipcmd_y.a]
>>> t = ss.dae.ts.t
>>> ss.TDS.plt.plot_data(t, v * Ipcmd,
>>>                      xlabel='Time [s]',
>>>                      ylabel='Ipcmd [pu]')