@alisa-kirkinskaia @campospinto Can you remember why we have no class C1PolarProjection_V2?

Even if it should be identical to C0PolarProjection_V2, for consistency I would at least provide an alias for it, e.g.

C1PolarProjection_V2 = C0PolarProjection_V2

A better solution could be to subclass C0PolarProjection_V2, because it allows us to write a dedicated docstring for it:

class C1PolarProjection_V2(C0PolarProjection_V2):
    """
    CONGA Projector P2 from the full spline space S^{p1-1, p2-1} on logical
    domain to U2, the pre-polar 2-forms splines. The associate matrix
    is square, as in the CONGA approach we keep using the tensor B-spline basis,
    instead of the polar basis of Toshniwal. P2 enforces coefficient relations
    to be in U2.

    Parameters:
    -----------

    W2 : TensorFemSpace
         Full tensor product spline space of the 2-forms S^{p1-1, p2-1}

    transposed : Boolean
         Switch between P2 and P2 transposed (default is False)
    """

    def transpose(self, conjugate=False):
        return C1PolarProjection_V2(self.W2, transposed=not self.transposed)

There is no need to override the other methods, given that they are identical to those of the superclass.

Yes, it was because the two projections are the same. I added your suggestion in 5ecf431. Do we also need to add C1PolarProjection_V2 to the unit tests?

@alisa-kirkinskaia @campospinto Can you remember why we have no class C1PolarProjection_V2?
Even if it should be identical to C0PolarProjection_V2, for consistency I would at least provide an alias for it, e.g.

C1PolarProjection_V2 = C0PolarProjection_V2

A better solution could be to subclass C0PolarProjection_V2, because it allows us to write a dedicated docstring for it:

class C1PolarProjection_V2(C0PolarProjection_V2):
    """
    CONGA Projector P2 from the full spline space S^{p1-1, p2-1} on logical
    domain to U2, the pre-polar 2-forms splines. The associate matrix
    is square, as in the CONGA approach we keep using the tensor B-spline basis,
    instead of the polar basis of Toshniwal. P2 enforces coefficient relations
    to be in U2.

    Parameters:
    -----------

    W2 : TensorFemSpace
         Full tensor product spline space of the 2-forms S^{p1-1, p2-1}

    transposed : Boolean
         Switch between P2 and P2 transposed (default is False)
    """

    def transpose(self, conjugate=False):
        return C1PolarProjection_V2(self.W2, transposed=not self.transposed)

There is no need to override the other methods, given that they are identical to those of the superclass.

Yes, it was because the two projections are the same. I added your suggestion in 5ecf431. Do we also need to add C1PolarProjection_V2 to the unit tests?

Yes, in principle we should test the new class, too. This would be an insurance against future changes to the class. I think we could simply add parametrization to test_PolarProjection_V2

Yes, in principle we should test the new class, too. This would be an insurance against future changes to the class. I think we could simply add parametrization to test_PolarProjection_V2

Done in 0c0eae0

Hi there, I would like to reopen this conversation 😉

This is an example script where we choose the manufactured solution, not a situation where the user can choose an arbitrary function. In any case, even if the solution were more oscillatory, a standard approach would be to increase the number of cells and the spline degree.

Please consider that increasing nquads slows down the matrix assembly a lot. Luckily this is only a 2D example which we do not run with a high number of cells.. but in 3D we would notice a big difference.

In conclusion, I feel that the default number of quadrature points per cell (in each direction) of degree + 1 is appropriate in most cases. Here I would not increase nquads unless strictly necessary.

I see, thanks! f99f5e4