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The current implementation does not allow for variable-coefficient PDOs. Discretizing with the ultraspherical spectral method yields a multiplication operator for variable coefficients which is banded…
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DiffEq's first PDE attempt (which started the package) was a failure. The issue was that it was tied directly to an FEM subpackage I made internally, but then it couldn't scale to all of the problems …
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The following code segment worked sometime ago, but now with the current version of ApproxFun with Julia v1.0.1, I got the ```DimensionMismatch``` error as follows. Something must have been changed.
…
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I keep giving talks and have to explain that the numbers are actually in the superdiagonal:
```julia
ConcreteDerivative:Chebyshev(【-1.0,1.0】)→Ultraspherical(1,【-1.0,1.0】)
1.0 …
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I'm experiencing a surprising SEGFAULT on `precompile`. Here is the setup:
```julia
Pkg.add("ApproxFun")
Pkg.clone("https://github.com/daanhb/Domains.jl")
Pkg.checkout("ApproxFun","domains-support…
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Isn’t a FunctionSpace (almost by definition) just a Space with evaluation defined (that respects the linearity of the space)?
It almost feels like `Fun` is misnomer, as the space could be something…
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I observed that the accuracy of the derivative of interpolated data degenerates with increasing number of sampling points. This becomes evident even for interpolating a linear function. Please see the…
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I get the following error. I couldn't find an open issue #265, so I'm not sure what it's referring too.
If the issue isn't already known, I can try to make a branch to reproduce it.
``` julia
Julia…
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Yet another ApproxFun segfault, that only appears when running all the tests (so hard to isolate).
There's some bizarre behaviour when running the line in question, but does not immediately cause t…
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ChebyshevDirichlet