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Given a plot of signal in time representation, how to draw lines marking corresponding time index?

Specifically, given a signal plot with time index ranging from 0 to 2.6(s), I want to draw vertical red lines indicating corresponding time index for the list [0.22058956, 0.33088437, 2.20589566], how can I do it?

The standard way to add vertical lines that will cover your entire plot window without you having to specify their actual height is plt.axvline

import matplotlib.pyplot as plt



plt.axvline(x=0.22058956)

plt.axvline(x=0.33088437)

plt.axvline(x=2.20589566)

OR

xcoords = [0.22058956, 0.33088437, 2.20589566]

for xc in xcoords:

    plt.axvline(x=xc)

You can use many of the keywords available for other plot commands (e.g. color, linestyle, linewidth ...). You can pass in keyword arguments ymin and ymax if you like in axes corrdinates (e.g. ymin=0.25, ymax=0.75 will cover the middle half of the plot). There are corresponding functions for horizontal lines (axhline) and rectangles (axvspan).

For multiple lines

xposition = [0.3, 0.4, 0.45]

for xc in xposition:

    plt.axvline(x=xc, color='k', linestyle='--')

Calling axvline in a loop, as others have suggested, works, but can be inconvenient because

1. Each line is a separate plot object, which causes things to be very slow when you have many lines.


2. When you create the legend each line has a new entry, which may not be what you want.

Instead you can use the following convenience functions which create all the lines as a single plot object:

import matplotlib.pyplot as plt

import numpy as np





def axhlines(ys, ax=None, **plot_kwargs):

    """

    Draw horizontal lines across plot

    :param ys: A scalar, list, or 1D array of vertical offsets

    :param ax: The axis (or none to use gca)

    :param plot_kwargs: Keyword arguments to be passed to plot

    :return: The plot object corresponding to the lines.

    """

    if ax is None:

        ax = plt.gca()

    ys = np.array((ys, ) if np.isscalar(ys) else ys, copy=False)

    lims = ax.get_xlim()

    y_points = np.repeat(ys[:, None], repeats=3, axis=1).flatten()

    x_points = np.repeat(np.array(lims + (np.nan, ))[None, :], repeats=len(ys), axis=0).flatten()

    plot = ax.plot(x_points, y_points, scalex = False, **plot_kwargs)

    return plot





def axvlines(xs, ax=None, **plot_kwargs):

    """

    Draw vertical lines on plot

    :param xs: A scalar, list, or 1D array of horizontal offsets

    :param ax: The axis (or none to use gca)

    :param plot_kwargs: Keyword arguments to be passed to plot

    :return: The plot object corresponding to the lines.

    """

    if ax is None:

        ax = plt.gca()

    xs = np.array((xs, ) if np.isscalar(xs) else xs, copy=False)

    lims = ax.get_ylim()

    x_points = np.repeat(xs[:, None], repeats=3, axis=1).flatten()

    y_points = np.repeat(np.array(lims + (np.nan, ))[None, :], repeats=len(xs), axis=0).flatten()

    plot = ax.plot(x_points, y_points, scaley = False, **plot_kwargs)

    return plot

If someone wants to add a legend and/or colors to some vertical lines, then use this:

import matplotlib.pyplot as plt



xcoords = [0.1, 0.3, 0.5]

colors = ['r','k','b']



for xc,c in zip(xcoords,colors):

    plt.axvline(x=xc, label='line at x = {}'.format(xc), c=c)



plt.legend()

plt.show()

Results:

In addition to the plt.axvline and plt.plot((x1, x2), (y1, y2)) OR plt.plot([x1, x2], [y1, y2]) as provided in the answers above, one can also use

plt.vlines(x_pos, ymin=y1, ymax=y2)

to plot a vertical line at x_pos spanning from y1 to y2 where the values y1 and y2 are in absolute data coordinates.