Fix for Cofunction self-assignment via interpolation
#3939
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| a = assemble(TestFunction(V1) * dx) | ||
| b = assemble(TestFunction(V1) * dx) | ||
| a.interpolate(a) | ||
| assert (a.dat.data_ro == b.dat.data_ro).all() |
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Not sure if this should be a np.allclose test
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I think you're right as written. No flops should be performed so that should be an equality.
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I don't think it's actually no flops, it's interpolation which happens to be the identify except for roundoff.
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Changed to np.allclose, I'm pretty sure now that's correct
| a = assemble(TestFunction(V1) * dx) | ||
| b = assemble(TestFunction(V1) * dx) | ||
| a.interpolate(a) | ||
| assert (a.dat.data_ro == b.dat.data_ro).all() |
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I think you're right as written. No flops should be performed so that should be an equality.
| if x.id != out.id: | ||
| mul(x, out) | ||
| else: | ||
| out_ = out.duplicate() |
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Shouldn't a no-op be the right thing?
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I don't think so, e.g.
u = fd.Function(space, name="u")
v = fd.Function(space, name="v")
w = fd.Cofunction(space.dual(), name="w")
...
fd.assemble(fd.action(
fd.adjoint(fd.derivative(interpolate(v * u, space), u)),
w), tensor=w)
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I see, it only is a no-op in the MFE from the issue: assemble(L(w), tensor=w) with L being the identity.
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Maybe it'd be good to add a more complicated test then
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Done. I think there are also be issues with complex here (transpose should be Hermitian for the adjoint actions?).
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@jrmaddison just like #3965 please can you update this branch. It should then pass tests. |
Co-authored-by: David A. Ham <[email protected]>
…s a dependency of the input expression
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Done |
Fixes #3935