["python","numpy","matplotlib","graphing"]
Matplotlib log scale tick label number formatting

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).
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())