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# SparseSolve(_:_:_:_:)

Solve `AX=B` using the specified iterative method for complex double values.

```
func SparseSolve(_ method: SparseIterativeMethod, _ ApplyOperator: @escaping (Bool, CBLAS_TRANSPOSE, DenseMatrix_Complex_Double, DenseMatrix_Complex_Double) -> Void, _ B: DenseMatrix_Complex_Double, _ X: DenseMatrix_Complex_Double) -> SparseIterativeStatus_t
```

## Parameters

`method`

(input) Iterative method specification, eg return value of
`SparseConjugateGradient()`.

`ApplyOperator`

`ApplyOperator(accumulate, trans, X, Y)`
should perform the operation `Y = op(A)X` if `accumulate` is `false`,
or `Y += op(A)X` if `accumulate` is `true`.

- `accumulate` : (input) Indicates whether to perform `Y += op(A)X` (if
  true) or `Y = op(A)X` (if false).
- `trans`: (input) Indicates whether `op(A)` is the application of `A`
  (`trans=CblasNoTrans`) or `A^T` (`trans=CblasTrans`).
-  `X`: The matrix to multiply.
-  `Y`: The matrix in which to accumulate or store the result.

`B`

The right-hand sides `B` to solve for. If `A` has dimension `m x n`, then
`B` must have dimension `m x nrhs`, where nrhs is the number of
right-hand sides to find solutions for.

`X`

On entry, initial guess for solution, on return the solution. If `A`
has dimension `m x n`, and `B` has dimension `m x nrhs`, then `X` must have
dimension `n x nrhs`. If no good initial estimate is available, user
should set the initial guess to be the zero vector.

---

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