I want to plot a graph with one logarithmic axis using matplotlib.
I've been reading the docs, but can't figure out the syntax. I know that it's probably something simple like 'scale=linear'
in the plot arguments, but I can't seem to get it right
Sample program:
import pylab
import matplotlib.pyplot as plt
a = [pow(10, i) for i in range(10)]
fig = plt.figure()
ax = fig.add_subplot(2, 1, 1)
line, = ax.plot(a, color='blue', lw=2)
pylab.show()
You can use the Axes.set_yscale
method. That allows you to change the scale after the Axes
object is created. That would also allow you to build a control to let the user pick the scale if you needed to.
The relevant line to add is:
ax.set_yscale('log')
You can use 'linear'
to switch back to a linear scale. Here's what your code would look like:
import pylab
import matplotlib.pyplot as plt
a = [pow(10, i) for i in range(10)]
fig = plt.figure()
ax = fig.add_subplot(2, 1, 1)
line, = ax.plot(a, color='blue', lw=2)
ax.set_yscale('log')
pylab.show()
https://i.stack.imgur.com/CmQwl.png
First of all, it's not very tidy to mix pylab
and pyplot
code. What's more, pyplot style is preferred over using pylab.
Here is a slightly cleaned up code, using only pyplot
functions:
from matplotlib import pyplot
a = [ pow(10,i) for i in range(10) ]
pyplot.subplot(2,1,1)
pyplot.plot(a, color='blue', lw=2)
pyplot.yscale('log')
pyplot.show()
The relevant function is pyplot.yscale()
. If you use the object-oriented version, replace it by the method Axes.set_yscale()
. Remember that you can also change the scale of X axis, using pyplot.xscale()
(or Axes.set_xscale()
).
Check my question What is the difference between ‘log’ and ‘symlog’? to see a few examples of the graph scales that matplotlib offers.
pyplot.semilogy()
is more direct.
if you want to change the base of logarithm, just add:
plt.yscale('log',base=2)
Before Matplotlib 3.3, you would have to use basex/basey as the bases of log
You simply need to use semilogy instead of plot:
from pylab import *
import matplotlib.pyplot as pyplot
a = [ pow(10,i) for i in range(10) ]
fig = pyplot.figure()
ax = fig.add_subplot(2,1,1)
line, = ax.semilogy(a, color='blue', lw=2)
show()
I know this is slightly off-topic, since some comments mentioned the ax.set_yscale('log')
to be "nicest" solution I thought a rebuttal could be due. I would not recommend using ax.set_yscale('log')
for histograms and bar plots. In my version (0.99.1.1) i run into some rendering problems - not sure how general this issue is. However both bar and hist has optional arguments to set the y-scale to log, which work fine.
references: http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.bar
http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.hist
So if you are simply using the unsophisticated API, like I often am (I use it in ipython a lot), then this is simply
yscale('log')
plot(...)
Hope this helps someone looking for a simple answer! :).
Success story sharing
semilogy()
. Furthermore, it is easier to directly usepyplot.yscale()
than to useax.set_yscale('log')
, as there is no need to get theax
object (which is not always immediately available).loglog()
or on x-axis only trysemilogx()
ax
object that to usepyplot
which only might apply to the Axes you want it to.