Matplotlib semi-log plot: minor tick marks are gone when range is large

Question

When making a semi-log plot (y is log), the minor tick marks (8 in a decade) on the y axis appear automatically, but it seems that when the axis range exceeds 10**10, they disappear. I tried many ways to force them back in, but to no avail. It might be that they go away for large ranges to avoid overcrowding, but one should have a choice?

Answer 1

solution for matplotlib >= 2.0.2

Let's consider the following example

which is produced by this code:

import matplotlib.pyplot as plt import matplotlib.ticker import numpy as np  y = np.arange(12) x = 10.0**y  fig, ax=plt.subplots() ax.plot(x,y) ax.set_xscale("log") plt.show() 

The minor ticklabels are indeed gone and usual ways to show them (like plt.tick_params(axis='x', which='minor')) fail.

The first step would then be to show all powers of 10 on the axis,

locmaj = matplotlib.ticker.LogLocator(base=10,numticks=12)  ax.xaxis.set_major_locator(locmaj) 

where the trick is to set numticks to a number equal or larger the number of ticks (i.e. 12 or higher in this case).

Then, we can add minor ticklabels as

locmin = matplotlib.ticker.LogLocator(base=10.0,subs=(0.2,0.4,0.6,0.8),numticks=12) ax.xaxis.set_minor_locator(locmin) ax.xaxis.set_minor_formatter(matplotlib.ticker.NullFormatter()) 

Note that I restricted this to include 4 minor ticks per decade (using 8 is equally possible but in this example would overcrowd the axes). Also note that numticks is again (quite unintuitively) 12 or larger.

Finally we need to use a NullFormatter() for the minor ticks, in order not to have any ticklabels appear for them.

solution for matplotlib 2.0.0

The following works in matplotlib 2.0.0 or below, but it does not work in matplotlib 2.0.2.

Let's consider the following example

which is produced by this code:

import matplotlib.pyplot as plt import matplotlib.ticker import numpy as np  y = np.arange(12) x = 10.0**y  fig, ax=plt.subplots() ax.plot(x,y) ax.set_xscale("log") plt.show() 

The minor ticklabels are indeed gone and usual ways to show them (like plt.tick_params(axis='x', which='minor')) fail.

The first step would then be to show all powers of 10 on the axis,

locmaj = matplotlib.ticker.LogLocator(base=10.0, subs=(0.1,1.0, )) ax.xaxis.set_major_locator(locmaj) 

Then, we can add minor ticklabels as

locmin = matplotlib.ticker.LogLocator(base=10.0, subs=(0.1,0.2,0.4,0.6,0.8,1,2,4,6,8,10 ))  ax.xaxis.set_minor_locator(locmin) ax.xaxis.set_minor_formatter(matplotlib.ticker.NullFormatter()) 

Note that I restricted this to include 4 minor ticks per decade (using 8 is equally possible but in this example would overcrowd the axes). Also note - and that may be the key here - that the subs argument, which gives the multiples of integer powers of the base at which to place ticks (see documentation), is given a list ranging over two decades instead of one.

Finally we need to use a NullFormatter() for the minor ticks, in order not to have any ticklabels appear for them.

Answer 2

Major ticks with empty labels will generate ticks but no labels.

ax.set_yticks([1.E-6,1.E-5,1.E-4,1.E-3,1.E-2,1.E-1,1.E0,1.E1,1.E2,1.E3,1.E4,1.E5,])  ax.set_yticklabels(['$10^{-6}$','','','$10^{-3}$','','','$1$','','','$10^{3}$','','']) 

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