52 lines
1.6 KiB
Python
Executable file
52 lines
1.6 KiB
Python
Executable file
"""
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You can share the x or y axis limits for one axis with another by
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passing an axes instance as a sharex or sharey kwarg.
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Changing the axis limits on one axes will be reflected automatically
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in the other, and vice-versa, so when you navigate with the toolbar
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the axes will follow each other on their shared axes. Ditto for
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changes in the axis scaling (eg log vs linear). However, it is
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possible to have differences in tick labeling, eg you can selectively
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turn off the tick labels on one axes.
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The example below shows how to customize the tick labels on the
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various axes. Shared axes share the tick locator, tick formatter,
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view limits, and transformation (eg log, linear). But the ticklabels
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themselves do not share properties. This is a feature and not a bug,
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because you may want to make the tick labels smaller on the upper
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axes, eg in the example below.
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If you want to turn off the ticklabels for a given axes (eg on
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subplot(211) or subplot(212), you cannot do the standard trick
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setp(ax2, xticklabels=[])
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because this changes the tick Formatter, which is shared among all
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axes. But you can alter the visibility of the labels, which is a
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property
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setp( ax2.get_xticklabels(), visible=False)
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"""
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from pylab import *
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t = arange(0.01, 5.0, 0.01)
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s1 = sin(2*pi*t)
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s2 = exp(-t)
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s3 = sin(4*pi*t)
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ax1 = subplot(311)
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plot(t,s1)
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setp( ax1.get_xticklabels(), fontsize=6)
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## share x only
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ax2 = subplot(312, sharex=ax1)
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plot(t, s2)
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# make these tick labels invisible
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setp( ax2.get_xticklabels(), visible=False)
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# share x and y
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ax3 = subplot(313, sharex=ax1, sharey=ax1)
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plot(t, s3)
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xlim(0.01,5.0)
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show()
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