Wed Sep 12 15:53:12 2018 DASUM_TEST Python version: 3.6.5 DASUM adds the absolute values of elements of a vector. Vector x: 0: -2 1: 4 2: -6 3: 8 4: -10 5: 12 6: -14 7: 16 8: -18 9: 20 DASUM ( NX, X, 1 ) = 110 DASUM ( NX//2, X, 2 ) = 50 DASUM ( 2, X, NX//2 ) = 14 Matrix A: 11 -12 13 -14 -21 22 -23 24 31 -32 33 -34 -41 42 -43 44 51 -52 53 -54 DASUM(MA,A(1:MA,2),1) = 160 DASUM(NA,A(2,1:NA),1) = 90 DASUM_TEST Normal end of execution. DAXPY_TEST Python version: 3.6.5 DAXPY adds a multiple of vector X to vector Y. X: 0: 1 1: 2 2: 3 3: 4 4: 5 5: 6 Y: 0: 100 1: 200 2: 300 3: 400 4: 500 5: 600 z = daxpy ( 6, 1.000000, x, 1, y, 1 ) 0 101.000000 1 202.000000 2 303.000000 3 404.000000 4 505.000000 5 606.000000 z = daxpy ( 6, -2.000000, x, 1, y, 1 ) 0 98.000000 1 196.000000 2 294.000000 3 392.000000 4 490.000000 5 588.000000 z = daxpy ( 3, 3.000000, x, 2, y, 1 ) 0 103.000000 1 209.000000 2 315.000000 z = daxpy ( 3, -4.000000, x, 1, y, 2 ) 0 96.000000 1 292.000000 2 488.000000 DAXPY_TEST Normal end of execution. DCOPY_TEST DCOPY copies one vector into another. X = 0 1.000000 1 2.000000 2 3.000000 3 4.000000 4 5.000000 5 6.000000 6 7.000000 7 8.000000 8 9.000000 9 10.000000 Y = 0 10.000000 1 20.000000 2 30.000000 3 40.000000 4 50.000000 5 60.000000 6 70.000000 7 80.000000 8 90.000000 9 100.000000 A = 11.000000 12.000000 13.000000 14.000000 15.000000 21.000000 22.000000 23.000000 24.000000 25.000000 31.000000 32.000000 33.000000 34.000000 35.000000 41.000000 42.000000 43.000000 44.000000 45.000000 51.000000 52.000000 53.000000 54.000000 55.000000 DCOPY ( 5, X, 1, Y, 1 ) 0 1.000000 1 2.000000 2 3.000000 3 4.000000 4 5.000000 5 60.000000 6 70.000000 7 80.000000 8 90.000000 9 100.000000 DCOPY ( 3, X, 2, Y, 3 ) 0 1.000000 1 20.000000 2 30.000000 3 3.000000 4 50.000000 5 60.000000 6 5.000000 7 80.000000 8 90.000000 9 100.000000 A[0:5,0] = DCOPY ( 5, X, 1, A[0:5,0], 1 ) A = 1.000000 12.000000 13.000000 14.000000 15.000000 2.000000 22.000000 23.000000 24.000000 25.000000 3.000000 32.000000 33.000000 34.000000 35.000000 4.000000 42.000000 43.000000 44.000000 45.000000 5.000000 52.000000 53.000000 54.000000 55.000000 A[0,0:5] = DCOPY ( 5, X, 2, A[0,0:5], 1 ) A = 1.000000 3.000000 5.000000 7.000000 9.000000 21.000000 22.000000 23.000000 24.000000 25.000000 31.000000 32.000000 33.000000 34.000000 35.000000 41.000000 42.000000 43.000000 44.000000 45.000000 51.000000 52.000000 53.000000 54.000000 55.000000 DCOPY_TEST Normal end of execution. DDOT_TEST Python version: 3.6.5 DDOT computes the dot product of vectors. ddot ( n, x, 1, y, 1 ) = -55 ddot ( n, a[1,0:n], 1, x, 1 ) = 85 ddot ( n, a[0:n,1], 1, x, 1 ) = 85 Matrix product computed with c[i,j] = ddot ( n, a[i,0:n], 1, b[0:n,j), 1 ): 50.000000 30.000000 10.000000 -10.000000 -30.000000 60.000000 35.000000 10.000000 -15.000000 -40.000000 70.000000 40.000000 10.000000 -20.000000 -50.000000 80.000000 45.000000 10.000000 -25.000000 -60.000000 90.000000 50.000000 10.000000 -30.000000 -70.000000 DDOT_TEST Normal end of execution. DMACH_TEST Python version: 3.6.5 DMACH returns some approximate machine numbers. dmach(1) = eps = 2.22045e-16 dmach(2) = tiny = 8.9003e-306 dmach(3) = huge = 1.12356e+305 DMACH_TEST Normal end of execution. DNRM2_TEST Python version: 3.6.5 DNRM2 computes the Euclidean norm of a vector. x: 0: 1 1: 2 2: 3 3: 4 4: 5 dnrm2 ( n, x, incx ) = 7.4162 dnrm2 ( n, a[1,0:n], incx ) = 11.619 dnrm2 ( n, a[0:n,1], incx ) = 11.619 DNRM2_TEST Normal end of execution. DROT_TEST Python version: 3.6.5 DROT carries out a Givens rotation. Vectors X and Y 0 1 -11 1 2 -8 2 3 -3 3 4 4 4 5 13 5 6 24 xr, yr = drot ( n, x, 1, y, 1, 0.5, 0.866025 ) Rotated vectors XR and YR 0 -9.02628 -6.36603 1 -5.9282 -5.73205 2 -1.09808 -4.09808 3 5.4641 -1.4641 4 13.7583 2.16987 5 23.7846 6.80385 xr, yr = drot ( n, x, 1, y, 1, 0.0905357, -0.995893 ) Rotated vectors XR and YR 0 11.0454 -8.88178e-16 1 8.14822 1.2675 2 3.25929 2.71607 3 -3.62143 4.34572 4 -12.4939 6.15643 5 -23.3582 8.14822 DROT_TEST Normal end of execution. DROTG_TEST Python version: 3.6.5 DROTG generates a real Givens rotation ( C S ) * ( A ) = ( R ) ( -S C ) ( B ) ( 0 ) A = 0.218418 B = 0.956318 C = 0.222661 S = 0.974896 R = 0.980943 Z = 4.49112 C*A+S*B = 0.980943 -S*A+C*B = 0 A = 0.829509 B = 0.561695 C = 0.828025 S = 0.560691 R = 1.00179 Z = 0.560691 C*A+S*B = 1.00179 -S*A+C*B = 0 A = 0.415307 B = 0.0661187 C = 0.987563 S = 0.157224 R = 0.420537 Z = 0.157224 C*A+S*B = 0.420537 -S*A+C*B = 0 A = 0.257578 B = 0.109957 C = 0.919705 S = 0.392611 R = 0.280066 Z = 0.392611 C*A+S*B = 0.280066 -S*A+C*B = 0 A = 0.043829 B = 0.633966 C = 0.06897 S = 0.997619 R = 0.635479 Z = 14.4991 C*A+S*B = 0.635479 -S*A+C*B = 6.93889e-18 DROTG_TEST Normal end of execution. DSCAL_TEST Python version: 3.6.5 DSCAL multiplies a vector X by a scalar S. x: 0: 1 1: 2 2: 3 3: 4 4: 5 5: 6 y = dscal ( 6, 5.0, x, 1 ) 0: 5 1: 10 2: 15 3: 20 4: 25 5: 30 y = dscal ( 3, -2.0, x, 2 ) 0: -2 1: -6 2: -10 DSCAL_TEST Normal end of execution. IDAMAX_TEST Python version: 3.6.5 IDAMAX returns the index of maximum magnitude The vector X: 0: 2 1: -2 2: 5 3: 1 4: -3 5: 4 6: 0 7: -4 8: 3 9: -1 10: -5 The index of maximum magnitude = 2 IDAMAX_TEST Normal end of execution. Wed Sep 12 15:53:12 2018