Exponential of a matrix

doc/specs/stdlib_linalg.md

@@ -1884,3 +1884,38 @@ If `err` is not present, exceptions trigger an `error stop`.
 {!example/linalg/example_mnorm.f90!}
 ```
 
+## `expm` - Computes the matrix exponential {#expm}
+
+### Status
+
+Experimental
+
+### Description
+
+Given a matrix \(A\), this function compute its matrix exponential \(E = \exp(A)\) using a Pade approximation.
+
+### Syntax
+
+`E = ` [[stdlib_linalg(module):expm(interface)]] `(a [, order, err])`
+
+### Arguments
+
+`a`: Shall be a rank-2 `real` or `complex` array containing the data. It is an `intent(in)` argument.
+
+`order` (optional): Shall be a non-negative `integer` value specifying the order of the Pade approximation. By default `order=10`. It is an `intent(in)` argument. 
+
+`err` (optional): Shall be a `type(linalg_state_type)` value. This is an `intent(out)` argument. 
+
+### Return value
+
+The returned array `E` contains the Pade approximation of \(\exp(A)\).
+
+If `A` is non-square or `order` is negative, it raise a `LINALG_VALUE_ERROR`.
+If `err` is not present, exceptions trigger an `error stop`.
+
+### Example
+
+```fortran
+{!example/linalg/example_expm.f90!}
+```
+

example/linalg/CMakeLists.txt

@@ -52,3 +52,4 @@ ADD_EXAMPLE(qr)
 ADD_EXAMPLE(qr_space)
 ADD_EXAMPLE(cholesky)
 ADD_EXAMPLE(chol)
+ADD_EXAMPLE(expm)

example/linalg/example_expm.f90

@@ -0,0 +1,7 @@
+program example_expm
+   use stdlib_linalg, only: expm
+   implicit none
+   real :: A(3, 3), E(3, 3)
+   A = reshape([1, 2, 3, 4, 5, 6, 7, 8, 9], [3, 3])
+   E = expm(A)
+end program example_expm

src/CMakeLists.txt

@@ -32,16 +32,17 @@ set(fppFiles
     stdlib_linalg_kronecker.fypp
     stdlib_linalg_cross_product.fypp
     stdlib_linalg_eigenvalues.fypp
-    stdlib_linalg_solve.fypp    
+    stdlib_linalg_solve.fypp
     stdlib_linalg_determinant.fypp
     stdlib_linalg_qr.fypp
     stdlib_linalg_inverse.fypp
     stdlib_linalg_pinv.fypp
     stdlib_linalg_norms.fypp
     stdlib_linalg_state.fypp
-    stdlib_linalg_svd.fypp 
+    stdlib_linalg_svd.fypp
     stdlib_linalg_cholesky.fypp
     stdlib_linalg_schur.fypp
+    stdlib_linalg_matrix_functions.fypp
     stdlib_optval.fypp
     stdlib_selection.fypp
     stdlib_sorting.fypp

src/stdlib_linalg.fypp

@@ -28,6 +28,7 @@ module stdlib_linalg
   public :: eigh
   public :: eigvals
   public :: eigvalsh
+  public :: expm
   public :: eye
   public :: inv
   public :: invert
@@ -1678,6 +1679,53 @@ module stdlib_linalg
       #:endfor            
   end interface mnorm
 
+  !> Matrix exponential: function interface
+  interface expm
+    !! version : experimental
+    !!
+    !! Computes the exponential of a matrix using a rational Pade approximation.
+    !! ([Specification](../page/specs/stdlib_linalg.html#expm))
+    !!
+    !! ### Description
+    !!
+    !! This interface provides methods for computing the exponential of a matrix
+    !! represented as a standard Fortran rank-2 array. Supported data types include
+    !! `real` and `complex`.
+    !!
+    !! By default, the order of the Pade approximation is set to 10. It can be changed
+    !! via the `order` argument which must be non-negative.
+    !!
+    !! If the input matrix is non-square or the order of the Pade approximation is
+    !! negative, the function returns an error state.
+    !!
+    !! ### Example
+    !!
+    !! ```fortran
+    !!  real(dp) :: A(3, 3), E(3, 3)
+    !!
+    !!  A = reshape([1, 2, 3, 4, 5, 6, 7, 8, 9], [3, 3])
+    !!
+    !!  ! Default Pade approximation of the matrix exponential.
+    !!  E = expm(A)
+    !!
+    !!  ! Pade approximation with specified order.
+    !!  E = expm(A, order=12)
+    !! ```
+    !!
+    #:for rk,rt,ri in RC_KINDS_TYPES
+    module function stdlib_expm_${ri}$(A, order, err) result(E)
+        !> Input matrix a(n, n).
+        ${rt}$, intent(in) :: A(:, :)
+        !> [optional] Order of the Pade approximation (default `order=10`)
+        integer(ilp), optional, intent(in) :: order
+        !> [optional] State return flag. On error, if not requested, the code will stop.
+        type(linalg_state_type), optional, intent(out) :: err
+        !> Exponential of the input matrix E = exp(A).
+        ${rt}$, allocatable :: E(:, :)
+    end function stdlib_expm_${ri}$
+    #:endfor
+  end interface expm
+
 contains
 
 

src/stdlib_linalg_matrix_functions.fypp

@@ -0,0 +1,141 @@
+#:include "common.fypp"
+#:set RC_KINDS_TYPES = REAL_KINDS_TYPES + CMPLX_KINDS_TYPES
+submodule (stdlib_linalg) stdlib_linalg_matrix_functions
+    use stdlib_constants
+    use stdlib_linalg_constants
+    use stdlib_linalg_blas, only: gemm
+    use stdlib_linalg_lapack, only: gesv
+    use stdlib_linalg_state, only: linalg_state_type, linalg_error_handling, LINALG_ERROR, &
+         LINALG_INTERNAL_ERROR, LINALG_VALUE_ERROR
+    implicit none
+
+contains
+
+    #:for rk,rt,ri in RC_KINDS_TYPES 
+    module function stdlib_expm_${ri}$(A, order, err) result(E)
+        !> Input matrix A(n, n).
+        ${rt}$, intent(in) :: A(:, :)
+        !> [optional] Order of the Pade approximation.
+        integer(ilp), optional, intent(in) :: order
+        !> [optional] State return flag.
+        type(linalg_state_type), optional, intent(out) :: err
+        !> Exponential of the input matrix E = exp(A).
+        ${rt}$, allocatable :: E(:, :)
+
+        ! Internal variables.
+        ${rt}$, allocatable :: A2(:, :), Q(:, :), X(:, :)
+        real(${rk}$)        :: a_norm, c
+        integer(ilp)        :: m, n, ee, k, s, order_, i, j
+        logical(lk)         :: p
+        character(len=*), parameter :: this = "expm"
+        type(linalg_state_type)     :: err0
+
+        ! Deal with optional args.
+        order_ = 10 ; if (present(order)) order_ = order
+
+        ! Problem's dimension.
+        m = size(A, 1) ; n = size(A, 2)
+
+        if (m /= n) then
+            err0 = linalg_state_type(this,LINALG_VALUE_ERROR,'Invalid matrix size A=',[m, n])
+            call linalg_error_handling(err0, err)
+            return
+        else if (order_ < 0) then
+            err0 = linalg_state_type(this, LINALG_VALUE_ERROR, 'Order of Pade approximation &
+                                    needs to be positive, order=', order_)
+            call linalg_error_handling(err0, err)
+            return
+        endif
+
+        ! Compute the L-infinity norm.
+        a_norm = mnorm(A, "inf")
+
+        ! Determine scaling factor for the matrix.
+        ee = int(log(a_norm) / log(2.0_${rk}$)) + 1
+        s  = max(0, ee+1)
+
+        ! Scale the input matrix & initialize polynomial.
+        A2 = A/2.0_${rk}$**s ; X = A2
+
+        ! First step of the Pade approximation.
+        c = 0.5_${rk}$
+        allocate (E, source=A2) ; allocate (Q, source=A2)
+        do concurrent(i=1:n, j=1:n)
+            E(i, j) =  c*E(i, j) ; if (i == j) E(i, j) = 1.0_${rk}$ + E(i, j) ! E = I + c*A2
+            Q(i, j) = -c*Q(i, j) ; if (i == j) Q(i, j) = 1.0_${rk}$ + Q(i, j) ! Q = I - c*A2
+        enddo
+
+        ! Iteratively compute the Pade approximation.
+        block
+            ${rt}$ :: X_tmp(n, n)
+            p = .true.
+            do k = 2, order_
+                c = c * (order_ - k + 1) / (k * (2*order_ - k + 1))
+                X_tmp = X
+                #:if rt.startswith('complex')
+                call gemm("N", "N", n, n, n, one_c${rk}$, A2, n, X_tmp, n, zero_c${rk}$, X, n)
+                #:else
+                call gemm("N", "N", n, n, n, one_${rk}$, A2, n, X_tmp, n, zero_${rk}$, X, n)
+                #:endif
+                do concurrent(i=1:n, j=1:n)
+                    E(i, j) = E(i, j) + c*X(i, j)       ! E = E + c*X
+                enddo
+                if (p) then
+                    do concurrent(i=1:n, j=1:n)
+                        Q(i, j) = Q(i, j) + c*X(i, j)   ! Q = Q + c*X
+                    enddo
+                else
+                    do concurrent(i=1:n, j=1:n)
+                        Q(i, j) = Q(i, j) - c*X(i, j)   ! Q = Q - c*X
+                    enddo
+                endif
+                p = .not. p
+            enddo
+        end block
+
+        block
+            integer(ilp) :: ipiv(n), info
+            call gesv(n, n, Q, n, ipiv, E, n, info) ! E = inv(Q) @ E
+            call handle_gesv_info(info, n, n, n, err0)
+            call linalg_error_handling(err0, err)
+        end block
+
+        ! Matrix squaring.
+        block
+            ${rt}$ :: E_tmp(n, n)
+            do k = 1, s
+                E_tmp = E
+                #:if rt.startswith('complex')
+                call gemm("N", "N", n, n, n, one_c${rk}$, E_tmp, n, E_tmp, n, zero_c${rk}$, E, n)
+                #:else
+                call gemm("N", "N", n, n, n, one_${rk}$, E_tmp, n, E_tmp, n, zero_${rk}$, E, n)
+                #:endif
+            enddo
+        end block
+        return
+    contains
+        elemental subroutine handle_gesv_info(info,lda,n,nrhs,err)
+            integer(ilp), intent(in) :: info,lda,n,nrhs
+            type(linalg_state_type), intent(out) :: err
+            ! Process output
+            select case (info)
+            case (0)
+            ! Success
+            case (-1)
+                err = linalg_state_type(this,LINALG_VALUE_ERROR,'invalid problem size n=',n)
+            case (-2)
+                err = linalg_state_type(this,LINALG_VALUE_ERROR,'invalid rhs size n=',nrhs)
+            case (-4)
+                err = linalg_state_type(this,LINALG_VALUE_ERROR,'invalid matrix size a=',[lda,n])
+            case (-7)
+                err = linalg_state_type(this,LINALG_ERROR,'invalid matrix size a=',[lda,n])
+            case (1:)
+                err = linalg_state_type(this,LINALG_ERROR,'singular matrix')
+            case default
+                err = linalg_state_type(this,LINALG_INTERNAL_ERROR,'catastrophic error')
+            end select
+        end subroutine handle_gesv_info
+    end function stdlib_expm_${ri}$
+    #:endfor
+
+end submodule stdlib_linalg_matrix_functions

test/linalg/CMakeLists.txt

@@ -15,6 +15,7 @@ set(
   "test_linalg_matrix_property_checks.fypp"
   "test_linalg_sparse.fypp"
   "test_linalg_cholesky.fypp"
+  "test_linalg_expm.fypp"
 )
 
 # Preprocessed files to contain preprocessor directives -> .F90
@@ -41,4 +42,5 @@ ADDTEST(linalg_qr)
 ADDTEST(linalg_schur)
 ADDTEST(linalg_svd)
 ADDTEST(linalg_sparse)
-ADDTESTPP(blas_lapack)
+ADDTEST(linalg_expm)
+ADDTESTPP(blas_lapack)