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- ____RRRRAAAATTTTQQQQRRRR((((3333FFFF)))) ____RRRRAAAATTTTQQQQRRRR((((3333FFFF))))
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- NNNNAAAAMMMMEEEE
- RATQR, SRATQR - EISPACK routine. This subroutine finds the
- algebraically smallest or largest eigenvalues of a SYMMETRIC TRIDIAGONAL
- matrix by the rational QR method with Newton corrections.
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- SSSSYYYYNNNNOOOOPPPPSSSSYYYYSSSS
- ssssuuuubbbbrrrroooouuuuttttiiiinnnneeee rrrraaaattttqqqqrrrr((((nnnn,,,,eeeeppppssss1111,,,,dddd,,,,eeee,,,,eeee2222,,,,mmmm,,,,wwww,,,,iiiinnnndddd,,,,bbbbdddd,,,,ttttyyyyppppeeee,,,,iiiiddddeeeeffff,,,,iiiieeeerrrrrrrr))))
- iiiinnnntttteeeeggggeeeerrrr nnnn,,,, mmmm,,,, iiiinnnndddd((((nnnn)))),,,, iiiiddddeeeeffff,,,, iiiieeeerrrrrrrr
- ddddoooouuuubbbblllleeee pppprrrreeeecccciiiissssiiiioooonnnn eeeeppppssss1111
- ddddoooouuuubbbblllleeee pppprrrreeeecccciiiissssiiiioooonnnn dddd((((nnnn)))),,,, eeee((((nnnn)))),,,, eeee2222((((nnnn)))),,,, wwww((((nnnn)))),,,, bbbbdddd((((nnnn))))
- llllooooggggiiiiccccaaaallll ttttyyyyppppeeee
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- ssssuuuubbbbrrrroooouuuuttttiiiinnnneeee ssssrrrraaaattttqqqqrrrr((((nnnn,,,,eeeeppppssss1111,,,,dddd,,,,eeee,,,,eeee2222,,,,mmmm,,,,wwww,,,,iiiinnnndddd,,,,bbbbdddd,,,,ttttyyyyppppeeee,,,,iiiiddddeeeeffff,,,,iiiieeeerrrrrrrr))))
- iiiinnnntttteeeeggggeeeerrrr nnnn,,,, mmmm,,,, iiiinnnndddd((((nnnn)))),,,, iiiiddddeeeeffff,,,, iiiieeeerrrrrrrr
- rrrreeeeaaaallll eeeeppppssss1111
- rrrreeeeaaaallll dddd((((nnnn)))),,,, eeee((((nnnn)))),,,, eeee2222((((nnnn)))),,,, wwww((((nnnn)))),,,, bbbbdddd((((nnnn))))
- llllooooggggiiiiccccaaaallll ttttyyyyppppeeee
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- DDDDEEEESSSSCCCCRRRRIIIIPPPPTTTTIIIIOOOONNNN
- On Input
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- NNNN is the order of the matrix.
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- EEEEPPPPSSSS1111 is a theoretical absolute error tolerance for the computed
- eigenvalues. If the input EPS1 is non-positive, or indeed smaller than
- its default value, it is reset at each iteration to the respective
- default value, namely, the product of the relative machine precision and
- the magnitude of the current eigenvalue iterate. The theoretical
- absolute error in the K-th eigenvalue is usually not greater than K times
- EPS1.
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- DDDD contains the diagonal elements of the input matrix.
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- EEEE contains the subdiagonal elements of the input matrix in its last N-1
- positions. E(1) is arbitrary.
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- EEEE2222 contains the squares of the corresponding elements of E. E2(1) is
- arbitrary.
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- MMMM is the number of eigenvalues to be found.
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- IIIIDDDDEEEEFFFF should be set to 1 if the input matrix is known to be positive
- definite, to -1 if the input matrix is known to be negative definite, and
- to 0 otherwise.
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- TTTTYYYYPPPPEEEE should be set to .TRUE. if the smallest eigenvalues are to be found,
- and to .FALSE. If the largest eigenvalues are to be found. On Output
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- EEEEPPPPSSSS1111 is unaltered unless it has been reset to its (last) default value.
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- PPPPaaaaggggeeee 1111
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- ____RRRRAAAATTTTQQQQRRRR((((3333FFFF)))) ____RRRRAAAATTTTQQQQRRRR((((3333FFFF))))
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- DDDD and E are unaltered (unless W overwrites D). ELEMENTS of E2,
- corresponding to elements of E regarded as negligible, have been replaced
- by zero causing the matrix to split into a direct sum of submatrices.
- E2(1) is set to 0.0e0 if the smallest eigenvalues have been found, and to
- 2.0e0 if the largest eigenvalues have been found. E2 is otherwise
- unaltered (unless overwritten by BD).
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- WWWW contains the M algebraically smallest eigenvalues in ascending order,
- or the M largest eigenvalues in descending order. If an error exit is
- made because of an incorrect specification of IDEF, no eigenvalues are
- found. If the Newton iterates for a particular eigenvalue are not
- monotone, the best estimate obtained is returned and IERR is set. W may
- coincide with D.
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- IIIINNNNDDDD contains in its first M positions the submatrix indices associated
- with the corresponding eigenvalues in W -- 1 for eigenvalues belonging to
- the first submatrix from the top, 2 for those belonging to the second
- submatrix, etc.
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- BBBBDDDD contains refined bounds for the theoretical errors of the
- corresponding eigenvalues in W. These bounds are usually within the
- tolerance specified by EPS1. BD may coincide with E2.
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- IIIIEEEERRRRRRRR is set to Zero for normal return, 6*N+1 if IDEF is set
- to 1 and type to .TRUE.
- when the matrix is NOT positive definite, or
- if IDEF is set to -1 and type to .FALSE.
- when the matrix is NOT negative definite, 5*N+K if successive
- iterates to the K-th eigenvalue
- are NOT monotone increasing, where K refers
- to the last such occurrence. Note that subroutine TRIDIB is generally
- faster and more accurate than RATQR if the eigenvalues are clustered.
- Questions and comments should be directed to B. S. Garbow, APPLIED
- MATHEMATICS DIVISION, ARGONNE NATIONAL LABORATORY
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- PPPPaaaaggggeeee 2222
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