plot§

typed_lisa_toolkit.plot(obj, /, fig=None, ax=None, *, plot_mode=None, set_legend=True, **kwargs)[source]§

Plot a single object with customizable visualization options.

This function provides a unified interface for plotting various types The function automatically handles axis creation, unit normalization, and label formatting.

Parameters:

obj – The object to plot. Can be a representation, a data, or a waveform. Positional-only.
fig (matplotlib.figure.Figure, optional) – The figure to plot into. If not provided a new figure will be created.
ax (matplotlib.axes.Axes, optional) – The axes to plot into. If provided, fig must also be provided. Can not be specified when plotting multi-channel objects.
plot_mode ({'loglog', 'semilogx', 'semilogy', 'plot', 'imshow'}, optional) – The plotting mode to use. If not specified, a default mode is selected based on the object type.
set_legend (bool, default True) – Whether to display a legend on the plot.
**kwargs –
Additional keyword arguments passed to matplotlib or figure creation. Common options include:
- Figure kwargs: figsize, dpi, constrained_layout
- Subplot kwargs: sharex, sharey, wspace, hspace
- Line kwargs: color, linewidth, linestyle, label
- Image kwargs: cmap, vmin, vmax

Returns:

fig (matplotlib.figure.Figure) – The figure containing the plot.
axs (list[list[matplotlib.axes.Axes]]) – The axes containing the plot, organized as a list of rows of axes, where a row is itself a list of axes.

Raises:

TypeError – If obj is not a plottable type.
ValueError – If the object has an unsupported shape or if ax is provided without fig.
NotImplementedError – If obj has a sparse grid or other configuration yet to be supported.

Notes

Units are automatically normalized across all data in the plot for consistency and readability.
For TimeSeries, the time unit is automatically selected based on the duration (seconds, hours, or days).
For FrequencySeries and Phasor, the frequency unit is automatically selected based on the maximum frequency (Hz, kHz, or mHz).
When plotting multi-channel objects, subplots are created with shared axes.