bag.data.plot

This module contains utilities to improve waveform plotting in python.

Module Contents

Classes

WaveformPlotter	A custom matplotlib interactive plotting class.
MarkerFigure

Functions

figure(fig_id[, picker])	Create a WaveformPlotter.
plot_waveforms(xvec, panel_list[, fig])	Plot waveforms in vertical panels with shared X axis.
_fpart(x)
_rfpart(x)
draw_line(x0, y0, x1, y1, xmax, grid)	Draws an anti-aliased line in img from p1 to p2 with the given color.
plot_eye_heatmap(fig, tvec, yvec, tper[, tstart, ...])	Plot eye diagram heat map.
plot_eye(fig, tvec, yvec_list, tper[, tstart, tend, ...])	Plot eye diagram.
_find_closest_point(x, y, xvec, yvec, xnorm, ynorm)	Find point on PWL waveform described by xvec, yvec closest to (x, y)

Attributes

color_cycle

bag.data.plot.color_cycle = ['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728', '#9467bd', '#8c564b', '#e377c2', '#7f7f7f',...

bag.data.plot.figure(fig_id, picker=5.0)

Create a WaveformPlotter.

Parameters:

• fig_id (int) – the figure ID.

• picker (float) – picker event pixel tolerance.

Returns:

plotter – a plotter that helps you make interactive matplotlib figures.

Return type:

bag.data.plot.WaveformPlotter

bag.data.plot.plot_waveforms(xvec, panel_list, fig=1)

Plot waveforms in vertical panels with shared X axis.

Parameters:

• xvec (numpy.ndarray) – the X data.

• panel_list (list[list[(str, numpy.ndarray)]]) – list of lists of Y data. Each sub-list is one panel. Each element of the sub-list is a tuple of signal name and signal data.

• fig (int) – the figure ID.

bag.data.plot._fpart(x)

bag.data.plot._rfpart(x)

bag.data.plot.draw_line(x0, y0, x1, y1, xmax, grid)

Draws an anti-aliased line in img from p1 to p2 with the given color.

bag.data.plot.plot_eye_heatmap(fig, tvec, yvec, tper, tstart=None, tend=None, toff=None, tstep=None, vstep=None, cmap=None, vmargin=0.05, interpolation='gaussian', repeat=False)

Plot eye diagram heat map.

Parameters:

• fig (int) – the figure ID.

• tvec (np.ndarray) – the time data.

• yvec (np.ndarray) – waveform data.

• tper (float) – the eye period.

• tstart (float) – starting time. Defaults to first point.

• tend (float) – ending time. Defaults to last point.

• toff (float) – eye offset. Defaults to 0.

• tstep (float or None) – horizontal bin size. Defaults to using 200 bins.

• vstep (float or None) – vertical bin size. Defaults to using 200 bins.

• cmap – the colormap used for coloring the heat map. If None, defaults to cubehelix_r

• vmargin (float) – vertical margin in percentage of maximum/minimum waveform values. Defaults to 5 percent. This is used so that there some room between top/bottom of eye and the plot.

• interpolation (str) – interpolation method. Defaults to ‘gaussian’. Use ‘none’ for no interpolation.

• repeat (bool) – True to repeat the eye diagram once to the right. This is useful if you want to look at edge transistions.

bag.data.plot.plot_eye(fig, tvec, yvec_list, tper, tstart=None, tend=None, toff_list=None, name_list=None, alpha=1.0)

Plot eye diagram.

Parameters:

• fig (int) – the figure ID.

• tvec (np.ndarray) – the time data.

• yvec_list (list[np.ndarray]) – list of waveforms to plot in eye diagram.

• tper (float) – the period.

• tstart (float) – starting time. Defaults to first point.

• tend (float) – ending time. Defaults to last point.

• toff_list (list[float]) – offset to apply to each waveform. Defaults to zeros.

• name_list (list[str] or None) – the name of each waveform. Defaults to numbers.

• alpha (float) – the transparency of each trace. Can be used to mimic heatmap.

bag.data.plot._find_closest_point(x, y, xvec, yvec, xnorm, ynorm)

Find point on PWL waveform described by xvec, yvec closest to (x, y)

class bag.data.plot.WaveformPlotter(fig_idx, picker=5.0, normal_width=1.5, select_width=3.0)

Bases: object

A custom matplotlib interactive plotting class.

This class adds many useful features, such as ability to add/remove markers, ability to toggle waveforms on and off, and so on.

Parameters:

• fig_idx (int) – the figure index.

• picker (float) – picker event pixel tolerance.

• normal_width (float) – normal linewidth.

• select_width (float) – selected linewidth.

plot(*args, **kwargs)

setup()

figure_closed(event)

figure_resized(event)

fix_legend_location(event)

legend_line_picked(artist)

legend_text_picked(artist, draw=True)

class bag.data.plot.MarkerFigure(**kwargs)

Bases: matplotlib.figure.Figure

set_line_visibility(axline, visible)

register_pick_event(artist_set, fun)

on_button_release(event)

Disable data cursor dragging.

on_motion(event)

Move data cursor around.

_get_idx_under_point(event)

Find selected data cursor.

on_pick(event)

_create_marker()

close_figure()

setup_callbacks()