### Is there any practical way to be used on Quadrature Projection ?

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Hello everyone,

I'm dealing with a function and I am trying to project it to Quadrature space by using

So that is actually consistent with quadrature points but since there is a very complicated UFL algebra for T_n, kernel cannot handle that projection. Then I tried to use what David suggest previously to be used in complicated UFL variables:

but also it does not work. Both of the project kills the kernel in Jupyter and the code fails. Is there any other method to be applied such a case ?

Best Regards,
This is very vague question. What are you trying to do, what do you expect and what is the problem? Be sure to post an MWE.

I'm dealing with a function and I am trying to project it to Quadrature space by using

`T=project(voigt(T_n), V1, form_compiler_parameters={"quadrature_degree":2})`

So that is actually consistent with quadrature points but since there is a very complicated UFL algebra for T_n, kernel cannot handle that projection. Then I tried to use what David suggest previously to be used in complicated UFL variables:

```
def projectToQuadPts(toProject,VS):
u = TrialFunction(VS)
v = TestFunction(VS)
lhsForm = inner(u,v)*dx
rhsForm = inner(toProject,v)*dx
p = {"representation":"quadrature"}
A = assemble(lhsForm,form_compiler_parameters=p)
B = assemble(rhsForm,form_compiler_parameters=p)
u = Function(VS)
# Because the matrix is diagonal, it should be inverted exactly by the
# Jacobi preconditioner on the first iteration.
PETScKrylovSolver("cg","jacobi").solve(A,u.vector(),B)
return u
```

but also it does not work. Both of the project kills the kernel in Jupyter and the code fails. Is there any other method to be applied such a case ?

Best Regards,

Community: FEniCS Project

written
3 months ago by
Jan Blechta

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