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Merge branch 'fortran-lang:master' into sparse_sellc
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doc/specs/stdlib_linalg.md

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@@ -506,6 +506,37 @@ Returns a `logical` scalar that is `.true.` if the input matrix is skew-symmetri
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{!example/linalg/example_is_skew_symmetric.f90!}
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```
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## `hermitian` - Compute the Hermitian version of a rank-2 matrix
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### Status
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Experimental
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### Description
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Compute the Hermitian version of a rank-2 matrix.
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For `complex` matrices, the function returns the conjugate transpose (`conjg(transpose(a))`).
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For `real` or `integer` matrices, the function returns the transpose (`transpose(a)`).
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### Syntax
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`h = ` [[stdlib_linalg(module):hermitian(interface)]] `(a)`
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### Arguments
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`a`: Shall be a rank-2 array of type `integer`, `real`, or `complex`. The input matrix `a` is not modified.
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### Return value
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Returns a rank-2 array of the same shape and type as `a`. If `a` is of type `complex`, the Hermitian matrix is computed as `conjg(transpose(a))`.
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For `real` or `integer` types, it is equivalent to the intrinsic `transpose(a)`.
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### Example
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```fortran
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{!example/linalg/example_hermitian.f90!}
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```
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## `is_hermitian` - Checks if a matrix is Hermitian
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### Status
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{!example/linalg/example_inverse_function.f90!}
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```
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## `pinv` - Moore-Penrose pseudo-inverse of a matrix
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### Status
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Experimental
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### Description
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This function computes the Moore-Penrose pseudo-inverse of a `real` or `complex` matrix.
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The pseudo-inverse, \( A^{+} \), generalizes the matrix inverse and satisfies the conditions:
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- \( A \cdot A^{+} \cdot A = A \)
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- \( A^{+} \cdot A \cdot A^{+} = A^{+} \)
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- \( (A \cdot A^{+})^T = A \cdot A^{+} \)
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- \( (A^{+} \cdot A)^T = A^{+} \cdot A \)
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The computation is based on singular value decomposition (SVD). Singular values below a relative
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tolerance threshold \( \text{rtol} \cdot \sigma_{\max} \), where \( \sigma_{\max} \) is the largest
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singular value, are treated as zero.
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### Syntax
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`b =` [[stdlib_linalg(module):pinv(interface)]] `(a, [, rtol, err])`
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### Arguments
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`a`: Shall be a rank-2, `real` or `complex` array of shape `[m, n]` containing the coefficient matrix.
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It is an `intent(in)` argument.
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`rtol` (optional): Shall be a scalar `real` value specifying the relative tolerance for singular value cutoff.
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If `rtol` is not provided, the default relative tolerance is \( \text{rtol} = \text{max}(m, n) \cdot \epsilon \),
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where \( \epsilon \) is the machine precision for the element type of `a`. It is an `intent(in)` argument.
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`err` (optional): Shall be a `type(linalg_state_type)` value. It is an `intent(out)` argument.
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### Return value
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Returns an array value of the same type, kind, and rank as `a` with shape `[n, m]`, that contains the pseudo-inverse matrix \( A^{+} \).
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Raises `LINALG_ERROR` if the underlying SVD did not converge.
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Raises `LINALG_VALUE_ERROR` if `a` has invalid size.
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If `err` is not present, exceptions trigger an `error stop`.
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### Example
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```fortran
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{!example/linalg/example_pseudoinverse.f90!}
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```
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## `pseudoinvert` - Moore-Penrose pseudo-inverse of a matrix
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### Status
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Experimental
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### Description
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This subroutine computes the Moore-Penrose pseudo-inverse of a `real` or `complex` matrix.
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The pseudo-inverse \( A^{+} \) is a generalization of the matrix inverse and satisfies the following properties:
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- \( A \cdot A^{+} \cdot A = A \)
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- \( A^{+} \cdot A \cdot A^{+} = A^{+} \)
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- \( (A \cdot A^{+})^T = A \cdot A^{+} \)
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- \( (A^{+} \cdot A)^T = A^{+} \cdot A \)
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The computation is based on singular value decomposition (SVD). Singular values below a relative
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tolerance threshold \( \text{rtol} \cdot \sigma_{\max} \), where \( \sigma_{\max} \) is the largest
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singular value, are treated as zero.
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On return, matrix `pinva` `[n, m]` will store the pseudo-inverse of `a` `[m, n]`.
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### Syntax
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`call ` [[stdlib_linalg(module):pseudoinvert(interface)]] `(a, pinva [, rtol] [, err])`
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### Arguments
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`a`: Shall be a rank-2, `real` or `complex` array containing the coefficient matrix.
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It is an `intent(in)` argument.
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`pinva`: Shall be a rank-2 array of the same kind as `a`, and size equal to that of `transpose(a)`.
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On output, it contains the Moore-Penrose pseudo-inverse of `a`.
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`rtol` (optional): Shall be a scalar `real` value specifying the relative tolerance for singular value cutoff.
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If not provided, the default threshold is \( \text{max}(m, n) \cdot \epsilon \), where \( \epsilon \) is the
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machine precision for the element type of `a`.
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`err` (optional): Shall be a `type(linalg_state_type)` value. It is an `intent(out)` argument.
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### Return value
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Computes the Moore-Penrose pseudo-inverse of the matrix \( A \), \( A^{+} \), and returns it in matrix `pinva`.
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Raises `LINALG_ERROR` if the underlying SVD did not converge.
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Raises `LINALG_VALUE_ERROR` if `pinva` and `a` have degenerate or incompatible sizes.
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If `err` is not present, exceptions trigger an `error stop`.
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### Example
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```fortran
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{!example/linalg/example_pseudoinverse.f90!}
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```
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## `.pinv.` - Moore-Penrose Pseudo-Inverse operator
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### Status
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Experimental
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### Description
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This operator returns the Moore-Penrose pseudo-inverse of a `real` or `complex` matrix \( A \).
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The pseudo-inverse \( A^{+} \) is computed using Singular Value Decomposition (SVD), and singular values
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below a given threshold are treated as zero.
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This interface is equivalent to the function [[stdlib_linalg(module):pinv(interface)]].
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### Syntax
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`b = ` [[stdlib_linalg(module):operator(.pinv.)(interface)]] `a`
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### Arguments
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`a`: Shall be a rank-2 array of any `real` or `complex` kinds, with arbitrary dimensions \( m \times n \). It is an `intent(in)` argument.
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### Return value
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Returns a rank-2 array with the same type, kind, and rank as `a`, that contains the Moore-Penrose pseudo-inverse of `a`.
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If an exception occurs, or if the input matrix is degenerate (e.g., rank-deficient), the returned matrix will contain `NaN`s.
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For more detailed error handling, it is recommended to use the `subroutine` or `function` interfaces.
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### Example
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```fortran
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{!example/linalg/example_pseudoinverse.f90!}
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```
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## `get_norm` - Computes the vector norm of a generic-rank array.
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### Status

example/linalg/CMakeLists.txt

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@@ -6,6 +6,7 @@ ADD_EXAMPLE(diag5)
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ADD_EXAMPLE(eye1)
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ADD_EXAMPLE(eye2)
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ADD_EXAMPLE(is_diagonal)
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ADD_EXAMPLE(hermitian)
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ADD_EXAMPLE(is_hermitian)
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ADD_EXAMPLE(is_hessenberg)
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ADD_EXAMPLE(is_skew_symmetric)
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ADD_EXAMPLE(inverse_function)
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ADD_EXAMPLE(inverse_inplace)
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ADD_EXAMPLE(inverse_subroutine)
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ADD_EXAMPLE(pseudoinverse)
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ADD_EXAMPLE(outer_product)
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ADD_EXAMPLE(eig)
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ADD_EXAMPLE(eigh)

example/linalg/example_hermitian.f90

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! Example program demonstrating the usage of hermitian
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program example_hermitian
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use stdlib_linalg, only: hermitian
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implicit none
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complex, dimension(2, 2) :: A, AT
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! Define input matrices
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A = reshape([(1,2),(3,4),(5,6),(7,8)],[2,2])
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! Compute Hermitian matrices
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AT = hermitian(A)
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print *, "Original Complex Matrix:"
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print *, A
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print *, "Hermitian Complex Matrix:"
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print *, AT
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end program example_hermitian
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! Matrix pseudo-inversion example: function, subroutine, and operator interfaces
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program example_pseudoinverse
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use stdlib_linalg, only: pinv, pseudoinvert, operator(.pinv.), linalg_state_type
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implicit none(type,external)
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real :: A(15,5), Am1(5,15)
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type(linalg_state_type) :: state
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integer :: i, j
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real, parameter :: tol = sqrt(epsilon(0.0))
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! Generate random matrix A (15x15)
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call random_number(A)
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! Pseudo-inverse: Function interfcae
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Am1 = pinv(A, err=state)
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print *, 'Max error (function) : ', maxval(abs(A-matmul(A, matmul(Am1,A))))
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! User threshold
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Am1 = pinv(A, rtol=0.001, err=state)
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print *, 'Max error (rtol=0.001): ', maxval(abs(A-matmul(A, matmul(Am1,A))))
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! Pseudo-inverse: Subroutine interface
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call pseudoinvert(A, Am1, err=state)
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print *, 'Max error (subroutine): ', maxval(abs(A-matmul(A, matmul(Am1,A))))
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! Operator interface
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Am1 = .pinv.A
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print *, 'Max error (operator) : ', maxval(abs(A-matmul(A, matmul(Am1,A))))
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end program example_pseudoinverse

src/CMakeLists.txt

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stdlib_linalg_determinant.fypp
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stdlib_linalg_qr.fypp
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stdlib_linalg_inverse.fypp
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stdlib_linalg_pinv.fypp
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stdlib_linalg_norms.fypp
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stdlib_linalg_state.fypp
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stdlib_linalg_svd.fypp

src/stdlib_io.fypp

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read (s,*,iostat=ios,iomsg=iomsg) d(i, :)
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if (ios/=0) then
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write(msgout,1) trim(iomsg),i,trim(filename)
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write(msgout,1) trim(iomsg),size(d,2),i,trim(filename)
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call error_stop(msg=trim(msgout))
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end if
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write(msgout,1) trim(iomsg),size(d,2),i,trim(filename)
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call error_stop(msg=trim(msgout))
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end if
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close(s)
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1 format('loadtxt: error <',a,'> reading line ',i0,' of ',a,'.')
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1 format('loadtxt: error <',a,'> reading ',i0,' values from line ',i0,' of ',a,'.')
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end subroutine loadtxt_${t1[0]}$${k1}$
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#:endfor
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iostat=ios,iomsg=iomsg) d(i, :)
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close(s)
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1 format('savetxt: error <',a,'> writing line ',i0,' of ',a,'.')
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1 format('savetxt: error <',a,'> writing ',i0,' values to line ',i0,' of ',a,'.')
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end subroutine savetxt_${t1[0]}$${k1}$
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#:endfor

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