When a type is immutable, that means you can't modify the data in the type. If a field of a type is mutable, a reference to it is stored in the type, and you cannot modify that reference. In the case of SparseMatrixCSC, that means you can't make A.colptr point to a different array, for example. You are still free to change the values in A.colptr, because that does not require modifying the reference. If the field is immutable, then the value itself is stored in the type, not a reference to the value, and you cannot modify the value. That's why you get the error in the example.
The best solution I can think of for your rmCol example is to create a new SparseMatrixCSC that uses the same arrays as the old one (to avoid increasing memory usage) and return it. Replacing the last line of rmCol with: SparseMatrixCSC(m, n-1, A.colptr, A.rowval, A.nzval) should do the trick. The only sticky point is that the original A now contains invalid data, so you'll have to make sure only the the matrix returned from rmCol is used in the future, not the original A. Jared Crean On Saturday, November 5, 2016 at 5:07:45 PM UTC-4, Corbin Foucart wrote: > > The SparseMatrixCSC type is immutable, which I understand to mean that I > must respect the types of the attributes of SparseMatrixCSC types, as well > as not changing the attributes themselves. > > The following gives a loadError (type is immutable). I am confused that I > can modify the colptr and rowval attributes of A, but not the A.n > attribute. Why is this? I am trying to change the size of a sparse matrix > after removing the data from a row and column. > > I have checked that both A.n and A.n - 1 are type Int. > > function rmCol(A::SparseMatrixCSC, rmCol::Int) > colRmRange = A.colptr[rmCol]:(A.colptr[rmCol+1]-1) > filter!(e -> e != rmCol, A.colptr) > > deleteat!(A.rowval, rowval[colRmRange]) > deleteat!(A.nzval, colRmRange) > A.n -= 1 # inclusion of this line throws error > > end >
