linalg: solve

doc/specs/stdlib_linalg.md

@@ -600,6 +600,107 @@ Specifically, upper Hessenberg matrices satisfy `a_ij = 0` when `j < i-1`, and l
 {!example/linalg/example_is_hessenberg.f90!}
 ```
 
+## `solve` - Solves a linear matrix equation or a linear system of equations. 
+
+### Status
+
+Experimental
+
+### Description
+
+This function computes the solution to a linear matrix equation \( A \cdot x = b \), where \( A \) is a square, full-rank, `real` or `complex` matrix.
+
+Result vector or array `x` returns the exact solution to within numerical precision, provided that the matrix is not ill-conditioned. 
+An error is returned if the matrix is rank-deficient or singular to working precision. 
+The solver is based on LAPACK's `*GESV` backends.
+
+### Syntax
+
+`Pure` interface:
+
+`x = ` [[stdlib_linalg(module):solve(interface)]] `(a, b)`
+
+Expert interface:
+
+`x = ` [[stdlib_linalg(module):solve(interface)]] `(a, b [, overwrite_a], err)`
+
+### Arguments
+
+`a`: Shall be a rank-2 `real` or `complex` square array containing the coefficient matrix. It is normally an `intent(in)` argument. If `overwrite_a=.true.`, it is an `intent(inout)` argument and is destroyed by the call. 
+
+`b`: Shall be a rank-1 or rank-2 array of the same kind as `a`, containing the right-hand-side vector(s). It is an `intent(in)` argument.
+
+`overwrite_a` (optional): Shall be an input logical flag. if `.true.`, input matrix `a` will be used as temporary storage and overwritten. This avoids internal data allocation. This is an `intent(in)` argument.
+
+`err` (optional): Shall be a `type(linalg_state_type)` value. This is an `intent(out)` argument. The function is not `pure` if this argument is provided.
+
+### Return value
+
+For a full-rank matrix, returns an array value that represents the solution to the linear system of equations.
+
+Raises `LINALG_ERROR` if the matrix is singular to working precision.
+Raises `LINALG_VALUE_ERROR` if the matrix and rhs vectors have invalid/incompatible sizes.
+If `err` is not present, exceptions trigger an `error stop`.
+
+### Example
+
+```fortran
+{!example/linalg/example_solve1.f90!}
+
+{!example/linalg/example_solve2.f90!}
+```
+
+## `solve_lu` - Solves a linear matrix equation or a linear system of equations (subroutine interface). 
+
+### Status
+
+Experimental
+
+### Description
+
+This subroutine computes the solution to a linear matrix equation \( A \cdot x = b \), where \( A \) is a square, full-rank, `real` or `complex` matrix.
+
+Result vector or array `x` returns the exact solution to within numerical precision, provided that the matrix is not ill-conditioned. 
+An error is returned if the matrix is rank-deficient or singular to working precision. 
+If all optional arrays are provided by the user, no internal allocations take place.
+The solver is based on LAPACK's `*GESV` backends.
+
+### Syntax
+
+Simple (`Pure`) interface:
+
+`call ` [[stdlib_linalg(module):solve_lu(interface)]] `(a, b, x)`
+
+Expert (`Pure`) interface:
+
+`call ` [[stdlib_linalg(module):solve_lu(interface)]] `(a, b, x [, pivot, overwrite_a, err])`
+
+### Arguments
+
+`a`: Shall be a rank-2 `real` or `complex` square array containing the coefficient matrix. It is normally an `intent(in)` argument. If `overwrite_a=.true.`, it is an `intent(inout)` argument and is destroyed by the call. 
+
+`b`: Shall be a rank-1 or rank-2 array of the same kind as `a`, containing the right-hand-side vector(s). It is an `intent(in)` argument.
+
+`x`: Shall be a rank-1 or rank-2 array of the same kind and size as `b`, that returns the solution(s) to the system. It is an `intent(inout)` argument, and must have the `contiguous` property. 
+
+`pivot` (optional): Shall be a rank-1 array of the same kind and matrix dimension as `a`, providing storage for the diagonal pivot indices. It is an `intent(inout)` arguments, and returns the diagonal pivot indices. 
+
+`overwrite_a` (optional): Shall be an input logical flag. if `.true.`, input matrix `a` will be used as temporary storage and overwritten. This avoids internal data allocation. This is an `intent(in)` argument.
+
+### Return value
+
+For a full-rank matrix, returns an array value that represents the solution to the linear system of equations.
+
+Raises `LINALG_ERROR` if the matrix is singular to working precision.
+Raises `LINALG_VALUE_ERROR` if the matrix and rhs vectors have invalid/incompatible sizes.
+If `err` is not present, exceptions trigger an `error stop`.
+
+### Example
+
+```fortran
+{!example/linalg/example_solve3.f90!}
+```
+
 ## `lstsq` - Computes the least squares solution to a linear matrix equation. 
 
 ### Status

example/linalg/CMakeLists.txt

@@ -20,5 +20,8 @@ ADD_EXAMPLE(blas_gemv)
 ADD_EXAMPLE(lapack_getrf)
 ADD_EXAMPLE(lstsq1)
 ADD_EXAMPLE(lstsq2)
+ADD_EXAMPLE(solve1)
+ADD_EXAMPLE(solve2)
+ADD_EXAMPLE(solve3)
 ADD_EXAMPLE(determinant)
 ADD_EXAMPLE(determinant2)

example/linalg/example_solve1.f90

@@ -0,0 +1,26 @@
+program example_solve1
+  use stdlib_linalg_constants, only: sp
+  use stdlib_linalg, only: solve, linalg_state_type 
+  implicit none
+
+  real(sp), allocatable :: A(:,:),b(:),x(:)
+
+  ! Solve a system of 3 linear equations: 
+  !  4x + 3y + 2z =  25
+  ! -2x + 2y + 3z = -10
+  !  3x - 5y + 2z =  -4
+
+  ! Note: Fortran is column-major! -> transpose 
+  A = transpose(reshape([ 4, 3, 2, &
+                         -2, 2, 3, &
+                          3,-5, 2], [3,3])) 
+  b = [25,-10,-4]
+
+  ! Get coefficients of y = coef(1) + x*coef(2) + x^2*coef(3)
+  x = solve(A,b) 
+
+  print *, 'solution: ',x
+  ! 5.0, 3.0, -2.0
+
+end program example_solve1
+

example/linalg/example_solve2.f90

@@ -0,0 +1,26 @@
+program example_solve2
+  use stdlib_linalg_constants, only: sp
+  use stdlib_linalg, only: solve, linalg_state_type 
+  implicit none
+
+  complex(sp), allocatable :: A(:,:),b(:),x(:)
+
+  ! Solve a system of 3 complex linear equations: 
+  !  2x +      iy + 2z = (5-i)
+  ! -ix + (4-3i)y + 6z = i
+  !  4x +      3y +  z = 1
+
+  ! Note: Fortran is column-major! -> transpose 
+  A = transpose(reshape([(2.0, 0.0),(0.0, 1.0),(2.0,0.0), &
+                         (0.0,-1.0),(4.0,-3.0),(6.0,0.0), &
+                         (4.0, 0.0),(3.0, 0.0),(1.0,0.0)] , [3,3])) 
+  b = [(5.0,-1.0),(0.0,1.0),(1.0,0.0)]
+
+  ! Get coefficients of y = coef(1) + x*coef(2) + x^2*coef(3)
+  x = solve(A,b) 
+
+  print *, 'solution: ',x
+  !   (1.0947,0.3674) (-1.519,-0.4539) (1.1784,-0.1078)
+
+end program example_solve2
+

example/linalg/example_solve3.f90

@@ -0,0 +1,32 @@
+program example_solve3
+  use stdlib_linalg_constants, only: sp,ilp
+  use stdlib_linalg, only: solve_lu, linalg_state_type 
+  implicit none
+
+  integer(ilp) :: test
+  integer(ilp), allocatable :: pivot(:)
+  complex(sp), allocatable :: A(:,:),b(:),x(:)
+
+  ! Solve a system of 3 complex linear equations: 
+  !  2x +      iy + 2z = (5-i)
+  ! -ix + (4-3i)y + 6z = i
+  !  4x +      3y +  z = 1
+
+  ! Note: Fortran is column-major! -> transpose 
+  A = transpose(reshape([(2.0, 0.0),(0.0, 1.0),(2.0,0.0), &
+                         (0.0,-1.0),(4.0,-3.0),(6.0,0.0), &
+                         (4.0, 0.0),(3.0, 0.0),(1.0,0.0)] , [3,3])) 
+
+  ! Pre-allocate x
+  allocate(b(size(A,2)),pivot(size(A,2)))
+  allocate(x,mold=b)
+
+  ! Call system many times avoiding reallocation 
+  do test=1,100
+     b = test*[(5.0,-1.0),(0.0,1.0),(1.0,0.0)]
+     call solve_lu(A,b,x,pivot)
+     print "(i3,'-th solution: ',*(1x,f12.6))", test,x
+  end do
+
+end program example_solve3
+

src/CMakeLists.txt

@@ -25,6 +25,7 @@ set(fppFiles
     stdlib_linalg_outer_product.fypp
     stdlib_linalg_kronecker.fypp
     stdlib_linalg_cross_product.fypp
+    stdlib_linalg_solve.fypp    
     stdlib_linalg_determinant.fypp
     stdlib_linalg_state.fypp 
     stdlib_optval.fypp

src/stdlib_linalg.fypp

@@ -22,6 +22,8 @@ module stdlib_linalg
   public :: eye
   public :: lstsq
   public :: lstsq_space
+  public :: solve
+  public :: solve_lu  
   public :: solve_lstsq
   public :: trace
   public :: outer_product
@@ -228,6 +230,100 @@ module stdlib_linalg
     #:endfor
   end interface is_hessenberg
 
+  ! Solve linear system system Ax=b.
+  interface solve
+     !! version: experimental 
+     !!
+     !! Solves the linear system \( A \cdot x = b \) for the unknown vector \( x \) from a square matrix \( A \). 
+     !! ([Specification](../page/specs/stdlib_linalg.html#solve-solves-a-linear-matrix-equation-or-a-linear-system-of-equations))
+     !!
+     !!### Summary 
+     !! Interface for solving a linear system arising from a general matrix.
+     !!
+     !!### Description
+     !! 
+     !! This interface provides methods for computing the solution of a linear matrix system.
+     !! Supported data types include `real` and `complex`. No assumption is made on the matrix 
+     !! structure. 
+     !! The function can solve simultaneously either one (from a 1-d right-hand-side vector `b(:)`) 
+     !! or several (from a 2-d right-hand-side vector `b(:,:)`) systems.
+     !! 
+     !!@note The solution is based on LAPACK's generic LU decomposition based solvers `*GESV`.
+     !!@note BLAS/LAPACK backends do not currently support extended precision (``xdp``).
+     !!    
+     #:for nd,ndsuf,nde in ALL_RHS
+     #:for rk,rt,ri in RC_KINDS_TYPES
+     #:if rk!="xdp"
+     module function stdlib_linalg_${ri}$_solve_${ndsuf}$(a,b,overwrite_a,err) result(x)
+         !> Input matrix a[n,n]
+         ${rt}$, intent(inout), target :: a(:,:)
+         !> Right hand side vector or array, b[n] or b[n,nrhs]
+         ${rt}$, intent(in) :: b${nd}$     
+         !> [optional] Can A data be overwritten and destroyed?
+         logical(lk), optional, intent(in) :: overwrite_a
+         !> [optional] state return flag. On error if not requested, the code will stop
+         type(linalg_state_type), intent(out) :: err
+         !> Result array/matrix x[n] or x[n,nrhs]
+         ${rt}$, allocatable, target :: x${nd}$
+     end function stdlib_linalg_${ri}$_solve_${ndsuf}$
+     pure module function stdlib_linalg_${ri}$_pure_solve_${ndsuf}$(a,b) result(x)
+         !> Input matrix a[n,n]
+         ${rt}$, intent(in) :: a(:,:)
+         !> Right hand side vector or array, b[n] or b[n,nrhs]
+         ${rt}$, intent(in) :: b${nd}$
+         !> Result array/matrix x[n] or x[n,nrhs]
+         ${rt}$, allocatable, target :: x${nd}$
+     end function stdlib_linalg_${ri}$_pure_solve_${ndsuf}$
+     #:endif
+     #:endfor
+     #:endfor    
+  end interface solve
+
+  ! Solve linear system Ax = b using LU decomposition (subroutine interface).
+  interface solve_lu
+     !! version: experimental 
+     !!
+     !! Solves the linear system \( A \cdot x = b \) for the unknown vector \( x \) from a square matrix \( A \). 
+     !! ([Specification](../page/specs/stdlib_linalg.html#solve-lu-solves-a-linear-matrix-equation-or-a-linear-system-of-equations-subroutine-interface))
+     !!
+     !!### Summary 
+     !! Subroutine interface for solving a linear system using LU decomposition.
+     !!
+     !!### Description
+     !! 
+     !! This interface provides methods for computing the solution of a linear matrix system using
+     !! a subroutine. Supported data types include `real` and `complex`. No assumption is made on the matrix 
+     !! structure. Preallocated space for the solution vector `x` is user-provided, and it may be provided
+     !! for the array of pivot indices, `pivot`. If all pre-allocated work spaces are provided, no internal 
+     !! memory allocations take place when using this interface.     
+     !! The function can solve simultaneously either one (from a 1-d right-hand-side vector `b(:)`) 
+     !! or several (from a 2-d right-hand-side vector `b(:,:)`) systems.
+     !! 
+     !!@note The solution is based on LAPACK's generic LU decomposition based solvers `*GESV`.
+     !!@note BLAS/LAPACK backends do not currently support extended precision (``xdp``).
+     !!        
+     #:for nd,ndsuf,nde in ALL_RHS
+     #:for rk,rt,ri in RC_KINDS_TYPES
+     #:if rk!="xdp"
+     pure module subroutine stdlib_linalg_${ri}$_solve_lu_${ndsuf}$(a,b,x,pivot,overwrite_a,err)     
+         !> Input matrix a[n,n]
+         ${rt}$, intent(inout), target :: a(:,:)
+         !> Right hand side vector or array, b[n] or b[n,nrhs]
+         ${rt}$, intent(in) :: b${nd}$
+         !> Result array/matrix x[n] or x[n,nrhs]     
+         ${rt}$, intent(inout), contiguous, target :: x${nd}$
+         !> [optional] Storage array for the diagonal pivot indices
+         integer(ilp), optional, intent(inout), target :: pivot(:)
+         !> [optional] Can A data be overwritten and destroyed?
+         logical(lk), optional, intent(in) :: overwrite_a
+         !> [optional] state return flag. On error if not requested, the code will stop
+         type(linalg_state_type), optional, intent(out) :: err
+     end subroutine stdlib_linalg_${ri}$_solve_lu_${ndsuf}$
+     #:endif
+     #:endfor
+     #:endfor    
+  end interface solve_lu     
+
   ! Least squares solution to system Ax=b, i.e. such that the 2-norm abs(b-Ax) is minimized.
   interface lstsq
     !! version: experimental