making square axes plot with log2 scales in matplotlib

Question

I'd like to make a square axis scatter plot with matplotlib. Normally using set_scale("log") works great, but it limits me to log10. I'd like to make the plot in log2. I saw the solution here: How to produce an exponentially scaled axis?

but it is quite complicated and does not work if you have 0 values in your arrays, which I do. I'd like to simply ignore those like other numpy functions do.

For example:

log2scatter(data1, data2)

where data1 and data2 contain 0s should have a logarithmic scale on the x and y axis, with logarithmic spaced ticks. Just like log10, except log2...

Thanks.

Logs are only defined for positive arguments. This holds irrespective of the base, i.e. it holds for natural logs, log base 10, log base 2 etc. Hence you just can't plot something which has zeros in a logscale, unless you do something to these zero values. — ev-br
Use the answer from that question but filter out the y-values that are 0 and their corresponding x values first (that's how numpy ignores them anyway). — mathematical.coffee
What's an elegant way to do that in numpy? The filtering complicates the code since now I have to have a copy of the array unfiltered, and a copy filtered... — user248237

Joe Kington Joe Kington · Accepted Answer · 2012-01-17T00:15:08

Just specify basex=2 or basey=2.

import matplotlib.pyplot as plt

fig, ax = plt.subplots()
ax.set_xscale('log', basex=2)
ax.set_yscale('log', basey=2)

ax.plot(range(1024))
plt.show()

enter image description here

For the zero-crossing behavior, what you're referring to is a "Symmetric Log" plot (a.k.a. "symlog"). For whatever it's worth, data isn't filtered out, it's just a linear plot near 0 and a log plot everywhere else. It's the scale that changes, not the data.

Normally you'd just do ax.set_xscale('symlog', basex=2) but using a non-10 base appears to be buggy at the moment for symlog plots.

Edit: Heh! The bug appears to be due to a classic mistake: using a mutable default argument.
I've filed a bug report, but if you feel like fixing it, you'll need to make a minor edit to lib/matplotlib/ticker.py, around line 1376, in the __init__ method of SymmetricalLogLocator.

Instead of

def __init__(self, transform, subs=[1.0]):
    self._transform = transform
    self._subs = subs
    ...

Change it to something similar to:

def __init__(self, transform, subs=None):
    self._transform = transform
    if subs is None:
        self._subs = [1.0]
    else:
        self._subs = subs
    ....

With that change made, it behaves as expected...

import matplotlib.pyplot as plt
import numpy as np

fig, ax = plt.subplots()
ax.set_xscale('symlog', basex=2)
ax.set_yscale('symlog', basey=2)

x = np.arange(-1024, 1024)
ax.plot(x, x)

plt.show()

enter image description here

making square axes plot with log2 scales in matplotlib

2 Answers