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cmbant opened this issue Oct 3, 2019 · 3 comments · Fixed by #17590
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ScalarFormatter.set_powerlimits documentation seems inconsistent #15376

cmbant opened this issue Oct 3, 2019 · 3 comments · Fixed by #17590
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Documentation
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v3.3.0

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@cmbant
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cmbant commented Oct 3, 2019

Bug report

Documentation says:

set_powerlimits(self, lims)[source]
Sets size thresholds for scientific notation.
(min_exp, max_exp)
A tuple containing the powers of 10 that determine the switchover threshold. Numbers below 10**min_exp and above 10**max_exp will be displayed in scientific notation.

However

    sFormatter = matplotlib.ticker.ScalarFormatter(useOffset=False, useMathText=True)
    sFormatter.set_powerlimits((-2, 2))
    plt.plot([120,130,140],[0.03,0.05,0.08])
    plt.gca().xaxis.set_major_formatter(sFormatter)
    plt.gca().yaxis.set_major_formatter(sFormatter)

does use scientific notation on the y axis but not the x axis. The the correct description of the actual behaviour seems to be

A tuple containing the powers of 10 that determine the switchover threshold. Numbers with absolute values below 10**(min_exp+1) and above 10**(max_exp+1) will be displayed in scientific notation.

Or it is a bug (would make more sense if the original description were correct).
@ImportanceOfBeingErnest
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A confusing bit is that you are using the same formatter for both axes. If using a dedicated formatter per axis it would give

import matplotlib.ticker
import matplotlib.pyplot as plt

sFormatter1 = matplotlib.ticker.ScalarFormatter(useOffset=False, useMathText=True)
sFormatter1.set_powerlimits((-2, 2))

sFormatter2 = matplotlib.ticker.ScalarFormatter(useOffset=False, useMathText=True)
sFormatter2.set_powerlimits((-2, 2))

plt.plot([120,130,140],[0.03,0.05,0.08])
plt.gca().xaxis.set_major_formatter(sFormatter1)
plt.gca().yaxis.set_major_formatter(sFormatter2)

plt.show()

image

Still, the sentence in the documentation remains incorrect (or at least not detailed enough), as seen from the y axis.

@anntzer
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anntzer commented Oct 4, 2019

As a general rule a single formatter instance cannot be used across multiple axises --- though #13482 fixes that :)

@ImportanceOfBeingErnest ImportanceOfBeingErnest added this to the v3.3.0 milestone Oct 5, 2019
@timhoffm timhoffm mentioned this issue Jun 8, 2020
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@timhoffm
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timhoffm commented Jun 8, 2020

Reusing formatters is off-topic.

The actual issue is a documentation issue. IMHO it's not a bug, but one has to think about the limits in the right way, see #17590.

@Samreay Samreay mentioned this issue Oct 30, 2020
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Clarify docs of set_powerlimits() timhoffm/matplotlib
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@anntzer @timhoffm @cmbant @ImportanceOfBeingErnest