Annotating ranges of data in matplotlib

Question

How can I annotate a range of my data? E.g., say the data from x = 5 to x = 10 is larger than some cut-off, how could I indicate that on the graph. If I was annotating by hand, I would just draw a large bracket above the range and write my annotation above the bracket.

The closest I've seen is using arrowstyle='<->' and connectionstyle='bar', to make two arrows pointing to the edges of your data with a line connecting their tails. But that doesn't quite do the right thing; the text that you enter for the annotation will end up under one of the arrows, rather than above the bar.

Here is my attempt, along with it's results:

annotate(' ', xy=(1,.5),  xycoords='data',
            xytext=(190, .5), textcoords='data',
            arrowprops=dict(arrowstyle="<->",
                            connectionstyle="bar",
                            ec="k",
                            shrinkA=5, shrinkB=5,
                            )
            )

Another problem with my attempted solution is that the squared shape of the annotating bracket does not really make it clear that I am highlighting a range (unlike, e.g., a curly brace). But I suppose that's just being nitpicky at this point.

Answer 1

As mentioned in this answer, you can construct curly brackets with sigmoidal functions. Below is a function that adds curly brackets just above the x-axis. The curly brackets it produces should look the same regardless of the axes limits, as long as the figure width and height don't vary.

import numpy as np
import matplotlib.pyplot as plt

def draw_brace(ax, xspan, text):
    """Draws an annotated brace on the axes."""
    xmin, xmax = xspan
    xspan = xmax - xmin
    ax_xmin, ax_xmax = ax.get_xlim()
    xax_span = ax_xmax - ax_xmin
    ymin, ymax = ax.get_ylim()
    yspan = ymax - ymin
    resolution = int(xspan/xax_span*100)*2+1 # guaranteed uneven
    beta = 300./xax_span # the higher this is, the smaller the radius

    x = np.linspace(xmin, xmax, resolution)
    x_half = x[:resolution//2+1]
    y_half_brace = (1/(1.+np.exp(-beta*(x_half-x_half[0])))
                    + 1/(1.+np.exp(-beta*(x_half-x_half[-1]))))
    y = np.concatenate((y_half_brace, y_half_brace[-2::-1]))
    y = ymin + (.05*y - .01)*yspan # adjust vertical position

    ax.autoscale(False)
    ax.plot(x, y, color='black', lw=1)

    ax.text((xmax+xmin)/2., ymin+.07*yspan, text, ha='center', va='bottom')

ax = plt.gca()
ax.plot(range(10))
draw_brace(ax, (0, 8), 'large brace')
draw_brace(ax, (8, 9), 'small brace')

Output:

Answer 2

I modified Joooeey's answer to allow to change the vertical position of braces:

def draw_brace(ax, xspan, yy, text):
    """Draws an annotated brace on the axes."""
    xmin, xmax = xspan
    xspan = xmax - xmin
    ax_xmin, ax_xmax = ax.get_xlim()
    xax_span = ax_xmax - ax_xmin

    ymin, ymax = ax.get_ylim()
    yspan = ymax - ymin
    resolution = int(xspan/xax_span*100)*2+1 # guaranteed uneven
    beta = 300./xax_span # the higher this is, the smaller the radius

    x = np.linspace(xmin, xmax, resolution)
    x_half = x[:int(resolution/2)+1]
    y_half_brace = (1/(1.+np.exp(-beta*(x_half-x_half[0])))
                    + 1/(1.+np.exp(-beta*(x_half-x_half[-1]))))
    y = np.concatenate((y_half_brace, y_half_brace[-2::-1]))
    y = yy + (.05*y - .01)*yspan # adjust vertical position

    ax.autoscale(False)
    ax.plot(x, y, color='black', lw=1)

    ax.text((xmax+xmin)/2., yy+.07*yspan, text, ha='center', va='bottom')

ax = plt.gca()
ax.plot(range(10))
draw_brace(ax, (0, 8), -0.5, 'large brace')
draw_brace(ax, (8, 9), 3, 'small brace')

Output:

Also note that in Joooeey's answer, line

x_half = x[:resolution/2+1]

should be

x_half = x[:int(resolution/2)+1]

Otherwise, the number that the script tries to use as index here is a float.

Finally, note that right now the brace will not show up if you move it out of bounds. You need to add parameter clip_on=False, like this:

ax.plot(x, y, color='black', lw=1, clip_on=False)