Update secondary_axis tutorial #29073
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…rom the first. In this case the interpolation must be defined outside the bounds of the data that is plotted. Moreover the tutorial in question has been simplified.
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make endpoints large in magnitude Co-authored-by: Jody Klymak <[email protected]>
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Friendly bump @jklymak |
| secax = ax.secondary_xaxis('top', functions=(forward, inverse)) | ||
| secax.xaxis.set_minor_locator(AutoMinorLocator()) | ||
| secax.set_xlabel('$X_{other}$') | ||
| secax.set_xticks([10, 20, 40, 60, 80, 100]) |
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Optional: One could consider using the square numbers to make the relation even more obvious
| secax.set_xticks([10, 20, 40, 60, 80, 100]) | |
| secax.set_xticks([4, 16, 36, 64, 100]) |
On the downside, this is proably slightly less "realistic", i.e. you would likely not find such tick positions in actual diagrams. Choose yourself, what you think is best.
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I might prefer the way it is now? Just since it (maybe) more closely corresponds to what you'd have in a real plot
explicitly label x2 = x1**2 Co-authored-by: Tim Hoffmann <[email protected]>
simplify interpolation Co-authored-by: Tim Hoffmann <[email protected]>
Kill unhelpful comment Co-authored-by: Jody Klymak <[email protected]>
…073-on-v3.10.x Backport PR #29073 on branch v3.10.x (Update secondary_axis tutorial)
PR summary
Closes #29067
Fixes a small issue with the secondary_axis tutorial where the interpolation from one axis to the other needs to be defined outside the bounds of the data that is plotted. This was previously noted in the tutorial but was not implemented correctly. The example in question has been simplified and updated so that the secondary axis is correctly derived from the primary axis.
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