Fix/restore secondary axis support for Transform-type functions#27267
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| self._functions = functions | ||
| elif isinstance(functions, Transform): | ||
| self._functions = ( | ||
| functions.transform, functions.inverted().transform) |
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This is dangerous, as Transform.inverted returns a copy with a snapshot of the transform, and thus won't be in sync if the input transform changes. Instead, you'd probably want (identity - input).
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I agree, but is it preferable to implicitly allow arguments to be mutated after the fact as a side effect at all? I.e., would a better way to ensure consistency be to simply copy the passed transform to begin with? Let me know which way to go (not sure if there's precedent here)
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Yes, we tend to be lazily evaluated, e.g., if we had Axes.transData here, it might change depending on limits (though of course that specific transform won't work here, being 2D, and as you've noted above this argument is 1D.)
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Actually, I'm not finding that to be the case (that subtraction avoids inconsistency upon mutation), at least with the Translation class I defined:
import matplotlib.pyplot as plt
import matplotlib.transforms as mtransforms
class Translation(mtransforms.Transform):
input_dims = 1
output_dims = 1
def __init__(self, dx):
self.dx = dx
def transform(self, values):
return values + self.dx
def inverted(self):
return Translation(-self.dx)
forward = Translation(1)
backward = mtransforms.IdentityTransform() - forward
print(forward.transform(1), backward.transform(1))
forward.dx = 2
print(forward.transform(1), backward.transform(1))prints
2 0
3 0
Reviewing Transform.__sub__, I can't actually say I understand how lazy inversion ever occurs... let me know what you think.
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But your test is wrong? The second printout should be 3 -1, if backward and forward are linked (which is what we want here, since the user only supplied the forward transform.)
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That's my point - forward and IdentityTransform() - forward are not linked, and I don't see any mechanism for that operation being lazy in Transform.__sub__.
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Oh, I see what you're saying now. Yes, I misremembered what happened there. What you will have to do is put a lambda in that calculates the inverse when it's called.
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The coverage drop is because it is missing some of the uploads (it is only seeing 5, should be atlesat 9). |
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Thank you for you work @zachjweiner and congratulations on your first merged PR to Matplotlib 🎉 We hope to hear from you again. |
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Cheers, thanks! (and thanks @QuLogic for iterating on this!) |
PR summary
Closes #25691 and adds a test.
First contribution to matplotlib, so please let me know if I've missed anything.
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