Question

I have a scatter plot with logarithmic x- and y axis (because I’m mainly interested in the lower values along both).

However, I want the tick labels to be in decimal format, not as 10^x.

I’m using this:

# axis limits:
ax.set_xlim(xmin=0, xmax = 1.2)
ax.set_ylim(ymin=0,ymax=1000)

# log scales:
ax.set_yscale('log')
ax.set_xscale('log')

# set y-ticks:
ax.set_yticks((1,10,100,1000))
ax.set_yticklabels(("1","10","100","1000"))

This works (though introducing ax.set_yscale('log') or ax.set_xscale('log') brings up the following warning (any idea what’s up with that?):

Warning (from warnings module):
  File "C:\Python27\lib\site-packages\numpy\ma\core.py", line 3785
warnings.warn("Warning: converting a masked element to nan.")
UserWarning: Warning: converting a masked element to nan.

But when I try the same for the x-axis, I get a MaskError:

# set x-ticks:
ax.set_xticks((0, 0.2, 0.4, 0.8, 1))
ax.set_xticklabels(("0", "0.2", "0.4", "0.8", "1"))

[snip long long traceback]
File "C:\Python27\lib\site-packages\numpy\ma\core.py", line 3795, in __int__
  raise MaskError, 'Cannot convert masked element to a Python int.'
MaskError: Cannot convert masked element to a Python int.

I think it has something to do with minor vs major ticks. I have tried to play around with ticker, but always run into the same error in the end.

I’d be immensely grateful for any help!

Edit after answer:
Problem solved by replacing

ax.set_yticks((1,10,100,1000))
ax.set_yticklabels(("1","10","100","1000"))
ax.set_xticks((0, 0.2, 0.4, 0.8, 1))
ax.set_xticklabels(("0", "0.2", "0.4", "0.8", "1"))

with

ax.yaxis.set_major_formatter(FormatStrFormatter('%1.0f'))
ax.xaxis.set_major_formatter(FormatStrFormatter('%.1f'))
ax.xaxis.set_minor_formatter(FormatStrFormatter('%.1f'))

Answer 1

You can use ticker as:

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.ticker import FormatStrFormatter

fig = plt.figure(1, [5,4])
ax = fig.add_subplot(111)

ax.plot( range(1,100) , range(1,100) ,  color='#aaaaff')
ax.set_xscale('log')
ax.xaxis.set_major_formatter(FormatStrFormatter('%.03f'))
plt.show()