python - Adjust exponent text after setting scientific limits on matplotlib axis

Question

At the moment if I set matplotlib y axis ticklabels to scientific mode it gives me an exponent at the top of the y axis of the form 1e-5

I'd like to adjust this to read r'$mathregular{10^{-5}}$' so that it prints out nicely.

Here's my example code:

# Create a figure and axis
fig, ax = plt.subplots()

# Plot 100 random points 
# the y values of which are very small
ax.scatter(np.random.rand(100), np.random.rand(100)/100000.0)

# Set the y limits appropriately
ax.set_ylim(0, 1/100000.0)

# Change the y ticklabel format to scientific format
ax.ticklabel_format(axis='y', style='sci', scilimits=(-2, 2))

# Get the offset value
offset = ax.yaxis.get_offset_text()

# Print it out
print '1st offset printout: {}'.format(offset)

# Run plt.tight_layout()
plt.tight_layout()

# Print out offset again - you can see the value now!
print '2nd offset printout: {}'.format(offset)

# Change it to latex format
offset.set_text(r'$mathregular{10^{-5}}$')

# Print it out
print '3rd offset printout: {}'.format(offset)

# Add some text to the middle of the figure just to 
# check that it isn't the latex format that's the problem
ax.text(0.5, 0.5/100000.0, r'$mathregular{10^{-2}}$')

# And show the figure
plt.show()

My output looks like this:

1st offset printout: Text(0,0.5,u'')
2nd offset printout: Text(0,636.933,u'1eu22125')
3rd offset printout: Text(0,636.933,u'$\mathregular{10^{-5}}$')

You can find the code and output figure here.

There are two oddities: One is that I can't overwrite the 1e-5 at the top of the y axis (which is the goal), and the other is that I have to run plt.tight_layout() in order to even see that unicode value as the offset.

Can anyone tell me where I'm going wrong?

Thank you

EDIT: The original question didn't make clear that I'd like to automatically detect the exponent as is currently calculated by ticklabel_format. So instead of passing a set string to the offset text it should automatically detect that value and adjust the latex string accordingly.

Answer 1

Building on @edsmith's answer one possible work around which does what I'd like is to get the offset text, convert it to a latex string, turn off the offset and add in that string at the top of the axis.

def format_exponent(ax, axis='y'):

    # Change the ticklabel format to scientific format
    ax.ticklabel_format(axis=axis, style='sci', scilimits=(-2, 2))

    # Get the appropriate axis
    if axis == 'y':
        ax_axis = ax.yaxis
        x_pos = 0.0
        y_pos = 1.0
        horizontalalignment='left'
        verticalalignment='bottom'
    else:
        ax_axis = ax.xaxis
        x_pos = 1.0
        y_pos = -0.05
        horizontalalignment='right'
        verticalalignment='top'

    # Run plt.tight_layout() because otherwise the offset text doesn't update
    plt.tight_layout()
    ##### THIS IS A BUG 
    ##### Well, at least it's sub-optimal because you might not
    ##### want to use tight_layout(). If anyone has a better way of 
    ##### ensuring the offset text is updated appropriately
    ##### please comment!

    # Get the offset value
    offset = ax_axis.get_offset_text().get_text()

    if len(offset) > 0:
        # Get that exponent value and change it into latex format
        minus_sign = u'u2212'
        expo = np.float(offset.replace(minus_sign, '-').split('e')[-1])
        offset_text = r'x$mathregular{10^{%d}}$' %expo

        # Turn off the offset text that's calculated automatically
        ax_axis.offsetText.set_visible(False)

        # Add in a text box at the top of the y axis
        ax.text(x_pos, y_pos, offset_text, transform=ax.transAxes,
               horizontalalignment=horizontalalignment,
               verticalalignment=verticalalignment)
    return ax

Note that you should be able to use the position of the offset text by calling pos = ax_axis.get_offset_text().get_position() but these values are not in axis units (they're likely pixel units - thanks @EdSmith - and thus not very helpful). Therefore I've just set the x_pos and y_pos values according to whichever axis we're looking at.

I also wrote a little function to automatically detect appropriate x and y limits (even though I know that matplotlib has lots of fancy ways of doing this).

def get_min_max(x, pad=0.05):
    '''
    Find min and max values such that
    all the data lies within 90% of
    of the axis range
    '''
    r = np.max(x) - np.min(x)
    x_min = np.min(x) - pad * r
    x_max = np.max(x) + pad * r
    return x_min, x_max

So, to update my example from the question (with a slight change to make both axes need the exponent):

import matplotlib.pylab as plt
import numpy as np

# Create a figure and axis
fig, ax = plt.subplots()

# Plot 100 random points that are very small
x = np.random.rand(100)/100000.0
y = np.random.rand(100)/100000.0
ax.scatter(x, y)

# Set the x and y limits
x_min, x_max = get_min_max(x)
ax.set_xlim(x_min, x_max)
y_min, y_max = get_min_max(y)    
ax.set_ylim(y_min, y_max)

# Format the exponents nicely
ax = format_exponent(ax, axis='x')
ax = format_exponent(ax, axis='y')

# And show the figure
plt.show()

A gist with an ipython notebook showing the output of the code is available here.

I hope that helps!