Add function to remove (explicit) zero entries from a CSR matrix

### Describe new/missing feature

Explicit zero values can be added to the entries of CSR matrix.
For some types of elements, the element tensor is not dense, but the sparsity pattern doesn't have this information.

Example using scipy:
``` python3
V = dolfinx.fem.FunctionSpace(mesh, element)
u, v = ufl.TrialFunction(V), ufl.TestFunction(V)
a = ufl.inner(ufl.grad(u), ufl.grad(v)) * ufl.dx + ufl.inner(u, v) * ufl.dx
a = dolfinx.fem.form(a, jit_options=jit_options)
A = dolfinx.fem.assemble_matrix(a)

# Convert to scipy sparse matrix
from scipy.sparse import csr_matrix
D = csr_matrix((A.data, A.indices, A.indptr))

print(D.shape, D.nnz, D.nnz/(D.shape[0]*D.shape[1]) * 100, "%")

D.data[np.abs(D.data) < 1e-15] = 0
D.eliminate_zeros()
D.prune()

print(D.shape, D.nnz, D.nnz/(D.shape[0]*D.shape[1]) * 100, "%")
```
Output example:
```
# Before
(64, 64) 512 12.5 %
# After
(64, 64) 256 6.25 %
```

Maybe a similar function should be implemented for `MatrixCSR.h`.

### Suggestion user interface

```c++
class MatrixCSR
{
...
...

void eliminate_zeros(Scalar tol)
}
```