Draw connecting line to points with a zero ordinate on a log scale with matplotlib?

Question

Is it possible to plot the connecting line to points whose y value is zero on a log scale in matplotlib?

I have some data that I want to plot with a log scale on the y-axis. The y values for some of the data lie at zero. I realize it's not possible for matplotlib to plot these points on a log scale, but I really wish it would draw the connecting line from the previous point or to the next point (if either are non-zero).

One solution would be to simply replace all zeros with some TINY number. I'd rather not do this.

What matplotlib draws: Log Plot with No Connecting Line

What I'd like it to draw: Log Plot with Connecting Line

timday · Accepted Answer · 2012-04-18 22:01:37Z

3

I'd be looking to solve this by using the 'symlog' option on the y axis instead of 'log'. There's then a linthreshy arg which lets you specify

"The range within which the plot is linear (to avoid having the plot go to infinity around zero).".

In fact it's exactly this sort of issue the option seems designed to deal with. It can look a bit goofy having this weird linear zone along the bottom of your log scale plot, but you can make it pretty small.

answered Apr 18, 2012 at 22:01

timday

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user545424 Over a year ago

Perfect! It works fine if I just use the symlog option, but for some reason if I try to specify an argument to linthresy I get a TypeError: bad operand type for unary -: 'tuple'

Hooked · Accepted Answer · 2012-04-19 13:46:07Z

0

You could always appened an extra point to the bottom of the graph by pulling out the coordinates from your current figure:

import numpy as np
import pylab as plt

# Create some sample data like yours
X = np.linspace(0,3,100)
Y = np.exp(-X)

def semilogy_to_bottom(X,Y):
    # Plot once to move axes and remove plot
    P, = plt.semilogy(X,Y)
    plt.gca().lines.remove(P)

    # Find the bottom of the graph
    y_min = plt.gca().get_ylim()[0]

    # Add a new point
    X2 = np.concatenate((X,[X[-1]]))
    Y2 = np.concatenate((Y,[y_min]))
    plt.semilogy(X2,Y2)

semilogy_to_bottom(X,Y)
plt.xlim(0,5)
plt.show()

enter image description here

answered Apr 19, 2012 at 13:46

Hooked

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