Matplotlib – Adding an arbitrary line to a matplotlib plot in ipython notebook

ipythonmatplotlib

I'm rather new to both python/matplotlib and using it through the ipython notebook. I'm trying to add some annotation lines to an existing graph and I can't figure out how to render the lines on a graph. So, for example, if I plot the following:

import numpy as np
np.random.seed(5)
x = arange(1, 101)
y = 20 + 3 * x + np.random.normal(0, 60, 100)
p =  plot(x, y, "o")

I get the following graph:

beautiful scatter plot

So how would I add a vertical line from (70,100) up to (70,250)? What about a diagonal line from (70,100) to (90,200)?

I've tried a few things with Line2D() resulting in nothing but confusion on my part. In R I would simply use the segments() function which would add line segments. Is there an equivalent in matplotlib?

Best Answer

You can directly plot the lines you want by feeding the plot command with the corresponding data (boundaries of the segments):

plot([x1, x2], [y1, y2], color='k', linestyle='-', linewidth=2)

(of course you can choose the color, line width, line style, etc.)

From your example:

import numpy as np
import matplotlib.pyplot as plt

np.random.seed(5)
x = np.arange(1, 101)
y = 20 + 3 * x + np.random.normal(0, 60, 100)
plt.plot(x, y, "o")


# draw vertical line from (70,100) to (70, 250)
plt.plot([70, 70], [100, 250], 'k-', lw=2)

# draw diagonal line from (70, 90) to (90, 200)
plt.plot([70, 90], [90, 200], 'k-')

plt.show()

new chart

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From the matplotlib documentation,

font = {'family' : 'normal',
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matplotlib.rc('font', **font)

This sets the font of all items to the font specified by the kwargs object, font.

Alternatively, you could also use the rcParams update method as suggested in this answer:

matplotlib.rcParams.update({'font.size': 22})

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Matplotlib – When to use cla(), clf() or close() for clearing a plot in matplotlib

They all do different things, since matplotlib uses a hierarchical order in which a figure window contains a figure which may consist of many axes. Additionally, there are functions from the pyplot interface and there are methods on the Figure class. I will discuss both cases below.

pyplot interface

pyplot is a module that collects a couple of functions that allow matplotlib to be used in a functional manner. I here assume that pyplot has been imported as import matplotlib.pyplot as plt. In this case, there are three different commands that remove stuff:

See matplotlib.pyplot Functions:

plt.cla() clears an axes, i.e. the currently active axes in the current figure. It leaves the other axes untouched.

plt.clf() clears the entire current figure with all its axes, but leaves the window opened, such that it may be reused for other plots.

plt.close() closes a window, which will be the current window, if not specified otherwise.

Which functions suits you best depends thus on your use-case.

The close() function furthermore allows one to specify which window should be closed. The argument can either be a number or name given to a window when it was created using figure(number_or_name) or it can be a figure instance fig obtained, i.e., usingfig = figure(). If no argument is given to close(), the currently active window will be closed. Furthermore, there is the syntax close('all'), which closes all figures.

methods of the Figure class

Additionally, the Figure class provides methods for clearing figures. I'll assume in the following that fig is an instance of a Figure:

fig.clf() clears the entire figure. This call is equivalent to plt.clf() only if fig is the current figure.

fig.clear() is a synonym for fig.clf()

Note that even del fig will not close the associated figure window. As far as I know the only way to close a figure window is using plt.close(fig) as described above.