Matplotlib log scale tick label number formatting

Question

With matplotlib when a log scale is specified for an axis, the default method of labeling that axis is with numbers that are 10 to a power eg. 10^6. Is there an easy way to change all of these labels to be their full numerical representation? eg. 1, 10, 100, etc.

Note that I do not know what the range of powers will be and want to support an arbitrary range (negatives included).

Answer 1

Sure, just change the formatter.

For example, if we have this plot:

import matplotlib.pyplot as plt  fig, ax = plt.subplots() ax.axis([1, 10000, 1, 100000]) ax.loglog()  plt.show() 

You could set the tick labels manually, but then the tick locations and labels would be fixed when you zoom/pan/etc. Therefore, it's best to change the formatter. By default, a logarithmic scale uses a LogFormatter, which will format the values in scientific notation. To change the formatter to the default for linear axes (ScalarFormatter) use e.g.

from matplotlib.ticker import ScalarFormatter for axis in [ax.xaxis, ax.yaxis]:     axis.set_major_formatter(ScalarFormatter()) 

Answer 2

I've found that using ScalarFormatter is great if all your tick values are greater than or equal to 1. However, if you have a tick at a number <1, the ScalarFormatter prints the tick label as 0.

We can use a FuncFormatter from the matplotlib ticker module to fix this issue. The simplest way to do this is with a lambda function and the g format specifier (thanks to @lenz in comments).

import matplotlib.ticker as ticker  ax.yaxis.set_major_formatter(ticker.FuncFormatter(lambda y, _: '{:g}'.format(y))) 

Note in my original answer I didn't use the g format, instead I came up with this lambda function with FuncFormatter to set numbers >= 1 to their integer value, and numbers <1 to their decimal value, with the minimum number of decimal places required (i.e. 0.1, 0.01, 0.001, etc). It assumes that you are only setting ticks on the base10 values.

import matplotlib.ticker as ticker import numpy as np  ax.yaxis.set_major_formatter(ticker.FuncFormatter(lambda y,pos: ('{{:.{:1d}f}}'.format(int(np.maximum(-np.log10(y),0)))).format(y))) 

For clarity, here's that lambda function written out in a more verbose, but also more understandable, way:

def myLogFormat(y,pos):     # Find the number of decimal places required     decimalplaces = int(np.maximum(-np.log10(y),0))     # =0 for numbers >=1     # Insert that number into a format string     formatstring = '{{:.{:1d}f}}'.format(decimalplaces)     # Return the formatted tick label     return formatstring.format(y)  ax.yaxis.set_major_formatter(ticker.FuncFormatter(myLogFormat))