Why does matplotlib choose the wrong range in y using log scale?

Question

Using matplotlib version 1.5.1 and python 2.7.11 I noticed that I need to specify the limits in y manually or else only the largest y-value point is plotted. Arrays behave the same way.

If I remove the first point, I get a few more points, but not all of them.

I don't recall ever having to manually set limits like this before - why here?

import matplotlib.pyplot as plt

X = [0.997, 2.643, 0.354, 0.075, 1.0, 0.03, 2.39, 0.364, 0.221, 0.437]
Y = [15.487507, 2.320735, 0.085742, 0.303032, 1.0, 0.025435, 4.436435,
     0.025435, 0.000503, 2.320735]

plt.figure()

plt.subplot(1,2,1)
plt.scatter(X, Y)
plt.xscale('log')
plt.yscale('log')


plt.subplot(1,2,2)
plt.scatter(X, Y)
plt.xscale('log')
plt.yscale('log')
plt.ylim(0.5*min(Y), 2.0*max(Y))  # why is this line necessary?
plt.title('added plt.ylim()')

plt.show()

potential-at-infinity · Accepted Answer · 2016-08-06 02:25:09Z

4

The problem arises because you have first drawn the scatter plot and then set the scales as logarithmic which results in a zooming in effect. This removes the problem:

plt.xscale('log')
plt.yscale('log')
plt.scatter(X, Y)

This produces the intended result. (2nd subplot in your question.)

answered Aug 6, 2016 at 2:25

potential-at-infinity

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2 Comments

uhoh Over a year ago

OK that's a fix, but is that the way it's supposed to work? It only affects the y scale, the x scale does not need this.

uhoh Over a year ago

I guess I must have always been doing it in the 'right' order without realizing it. Thanks!

Kartik · Accepted Answer · 2016-08-06 02:56:33Z

1

It seems like matplotlib is creating the y-axis ticks before converting to a log scale, and then not recreating the ticks based on the change. The y-axis on your first subplot starts at 10e1, not 10e-3. So change the scales before you plot.

plt.xscale('log')
plt.yscale('log')
plt.scatter(X, Y)

I think if you plot the original scale beside the log scale, you might be able to figure out the answer to the partial treatment of the axes by matplotlib. In a log scale, there is no true 0 -- because log(0) is undefined. So the coordinate has to start somewhere above 0, and that causes the problems. Your x axis ranges from 0 to 3, but y from 0 to 16. When converted to log, matplotlib correctly scales x axis, but since y has a factor of 10, it misses the scaling.

edited Aug 6, 2016 at 2:56

answered Aug 6, 2016 at 2:30

Kartik

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4 Comments

uhoh Over a year ago

y, but not x? I use log constantly, sometimes x, or y, or both axes. I've never seen this happen before.

uhoh Over a year ago

hmm... like I said in the other answer, possibly I've always been doing it in that order without actually realizing that it was the 'right' order.

uhoh Over a year ago

Thanks! I looked back at some examples of my plots and I found that 90% of the time I use plt.plot() where the 'wrong' order works just fine. It seems it's 'wrong' for plt.scatter(). A lot of my scatter plots that use log scales seemed to have worked 'by accident' due to limited range - like this one just for a random example. And possibly this has happened occasionally before and I just fiddled with it, got it working, and moved on.

uhoh Over a year ago

I've linked your helpful answer in this question.

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