reduce PR scope

Author: jalvesz

doc/specs/stdlib_linalg_iterative_solvers.md

@@ -167,7 +167,7 @@ Subroutine
 
 #### Description
 
-Implements the Preconditionned Conjugate Gradient (PCG) method for solving the linear system \( Ax = b \), where \( A \) is a symmetric positive-definite linear operator defined via the `linop` type. This is the core implementation, allowing flexibility for custom matrix types or parallel environments.
+Implements the Preconditioned Conjugate Gradient (PCG) method for solving the linear system \( Ax = b \), where \( A \) is a symmetric positive-definite linear operator defined via the `linop` type. This is the core implementation, allowing flexibility for custom matrix types or parallel environments.
 
 #### Syntax
 
@@ -185,7 +185,7 @@ Subroutine
 
 `A`: `class(linop_<kind>_type)` defining the linear operator. This argument is `intent(in)`.
 
-`M`: `class(linop_<kind>_type)` defining the preconditionner linear operator. This argument is `intent(in)`.
+`M`: `class(linop_<kind>_type)` defining the preconditioner linear operator. This argument is `intent(in)`.
 
 `b`: 1-D array of `real(<kind>)` defining the loading conditions of the linear system. This argument is `intent(in)`.
 
@@ -236,9 +236,9 @@ Subroutine
 
 `maxiter` (optional): scalar of type `integer` defining the maximum allowed number of iterations. If no value is given, a default of `N` is set, where `N = size(b)`. This argument is `intent(in)`.
 
-`precond` (optional): scalar of type `integer` enabling to switch among the default preconditionners available. If no value is given, no preconditionning will be applied. This argument is `intent(in)`.
+`precond` (optional): scalar of type `integer` enabling to switch among the default preconditioners available. If no value is given, no preconditionning will be applied. This argument is `intent(in)`.
 
-`M` (optional): `class(linop_<kind>_type)` defining a custom preconditionner linear operator. If given, `precond` will have no effect, a pointer is set to this custom preconditionner.
+`M` (optional): `class(linop_<kind>_type)` defining a custom preconditioner linear operator. If given, `precond` will have no effect, a pointer is set to this custom preconditioner.
 
 `workspace` (optional): `type(solver_workspace_<kind>_type)` holding the work temporal array for the solver. If the user passes its own `workspace`, then internally a pointer is set to it, otherwise, memory will be internally allocated and deallocated before exiting the procedure. This argument is `intent(inout)`.
 

example/linalg/example_solve_custom.f90

@@ -36,7 +36,7 @@ subroutine solve_pcg_custom(A,b,x,di,tol,maxiter,restart,workspace)
         ! internal memory setup
         op%apply => my_apply
         op%inner_product => my_dot
-        M%apply => my_jacobi_preconditionner
+        M%apply => my_jacobi_preconditioner
         if(present(di))then
             di_ => di
         else 
@@ -51,7 +51,7 @@ subroutine solve_pcg_custom(A,b,x,di,tol,maxiter,restart,workspace)
         if(.not.allocated(workspace_%tmp)) allocate( workspace_%tmp(n,size_wksp_pcg) , source = 0.d0 )
         workspace_%callback => my_logger
         !-------------------------
-        ! Jacobi preconditionner factorization
+        ! Jacobi preconditioner factorization
         call diag(A,diagonal)
         where(abs(diagonal)>epsilon(0.d0)) diagonal = 1._dp/diagonal
         !-------------------------
@@ -78,7 +78,7 @@ subroutine my_apply(x,y,alpha,beta)
             call spmv( A , x, y , alpha, beta )
             y = merge( 0._dp, y, di_ )
         end subroutine
-        subroutine my_jacobi_preconditionner(x,y,alpha,beta)
+        subroutine my_jacobi_preconditioner(x,y,alpha,beta)
             real(dp), intent(in)  :: x(:)
             real(dp), intent(inout) :: y(:)
             real(dp), intent(in) :: alpha

src/CMakeLists.txt

@@ -94,7 +94,6 @@ set(cppFiles
 
     stdlib_linalg_blas.fypp
     stdlib_linalg_lapack.fypp
-    stdlib_linalg_iterative_aux.fypp
     stdlib_linalg_iterative_solvers.fypp
     stdlib_linalg_iterative_solvers_cg.fypp
     stdlib_linalg_iterative_solvers_pcg.fypp