21 November 2024 8:35:38.079 AM SGMGA_VCN_COEF_TEST: FORTRAN90 version Test the SGMA_VCN_COEF function. SGMGA_VCN_COEF_TESTS calls SGMGA_VCN_COEF_TEST. SGMGA_VCN_COEF_TEST For anisotropic problems, each product grid in a sparse grid has an associated "combinatorial coefficient". SGMGA_VCN_COEF_NAIVE uses a naive algorithm. SGMGA_VCN_COEF attempts a more efficient method. Here, we simply compare COEF1 and COEF2, the same coefficient computed by the naive and efficient ways. IMPORTANCE: 1.00000 1.00000 LEVEL_WEIGHT: 1.00000 1.00000 I Q Coef1 Coef2 X MIN -2.00000 0 0 1 0.00000 1.0 1.0 0 0 MAX 0.00000 0 0 SUM 1.0 1.0 I Q Coef1 Coef2 X MIN -1.00000 0 0 1 0.00000 -1.0 -1.0 0 0 2 1.00000 1.0 1.0 1 0 3 1.00000 1.0 1.0 0 1 MAX 1.00000 1 1 SUM 1.0 1.0 I Q Coef1 Coef2 X MIN 0.00000 0 0 1 1.00000 -1.0 -1.0 1 0 2 1.00000 -1.0 -1.0 0 1 3 2.00000 1.0 1.0 2 0 4 2.00000 1.0 1.0 1 1 5 2.00000 1.0 1.0 0 2 MAX 2.00000 2 2 SUM 1.0 1.0 I Q Coef1 Coef2 X MIN 1.00000 0 0 1 2.00000 -1.0 -1.0 2 0 2 2.00000 -1.0 -1.0 1 1 3 2.00000 -1.0 -1.0 0 2 4 3.00000 1.0 1.0 3 0 5 3.00000 1.0 1.0 2 1 6 3.00000 1.0 1.0 1 2 7 3.00000 1.0 1.0 0 3 MAX 3.00000 3 3 SUM 1.0 1.0 I Q Coef1 Coef2 X MIN 2.00000 0 0 1 3.00000 -1.0 -1.0 3 0 2 3.00000 -1.0 -1.0 2 1 3 3.00000 -1.0 -1.0 1 2 4 3.00000 -1.0 -1.0 0 3 5 4.00000 1.0 1.0 4 0 6 4.00000 1.0 1.0 3 1 7 4.00000 1.0 1.0 2 2 8 4.00000 1.0 1.0 1 3 9 4.00000 1.0 1.0 0 4 MAX 4.00000 4 4 SUM 1.0 1.0 SGMGA_VCN_COEF_TEST For anisotropic problems, each product grid in a sparse grid has an associated "combinatorial coefficient". SGMGA_VCN_COEF_NAIVE uses a naive algorithm. SGMGA_VCN_COEF attempts a more efficient method. Here, we simply compare COEF1 and COEF2, the same coefficient computed by the naive and efficient ways. IMPORTANCE: 2.00000 1.00000 LEVEL_WEIGHT: 0.500000 1.00000 I Q Coef1 Coef2 X MIN -1.50000 0 0 1 0.00000 1.0 1.0 0 0 MAX 0.00000 0 0 SUM 1.0 1.0 I Q Coef1 Coef2 X MIN -1.00000 0 0 1 0.00000 0.0 0.0 0 0 2 0.500000 1.0 1.0 1 0 MAX 0.500000 1 1 SUM 1.0 1.0 I Q Coef1 Coef2 X MIN -0.500000 0 0 1 0.00000 -1.0 -1.0 0 0 2 0.500000 0.0 0.0 1 0 3 1.00000 1.0 1.0 2 0 4 1.00000 1.0 1.0 0 1 MAX 1.00000 2 1 SUM 1.0 1.0 I Q Coef1 Coef2 X MIN 0.00000 0 0 1 0.500000 -1.0 -1.0 1 0 2 1.00000 0.0 0.0 2 0 3 1.00000 0.0 0.0 0 1 4 1.50000 1.0 1.0 3 0 5 1.50000 1.0 1.0 1 1 MAX 1.50000 3 2 SUM 1.0 1.0 I Q Coef1 Coef2 X MIN 0.500000 0 0 1 1.00000 -1.0 -1.0 2 0 2 1.50000 0.0 0.0 3 0 3 1.00000 -1.0 -1.0 0 1 4 1.50000 0.0 0.0 1 1 5 2.00000 1.0 1.0 4 0 6 2.00000 1.0 1.0 2 1 7 2.00000 1.0 1.0 0 2 MAX 2.00000 4 2 SUM 1.0 1.0 I Q Coef1 Coef2 X MIN 1.00000 0 0 1 1.50000 -1.0 -1.0 3 0 2 2.00000 0.0 0.0 4 0 3 1.50000 -1.0 -1.0 1 1 4 2.00000 0.0 0.0 2 1 5 2.00000 0.0 0.0 0 2 6 2.50000 1.0 1.0 5 0 7 2.50000 1.0 1.0 3 1 8 2.50000 1.0 1.0 1 2 MAX 2.50000 5 3 SUM 1.0 1.0 I Q Coef1 Coef2 X MIN 1.50000 0 0 1 2.00000 -1.0 -1.0 4 0 2 2.50000 0.0 0.0 5 0 3 2.00000 -1.0 -1.0 2 1 4 2.50000 0.0 0.0 3 1 5 2.00000 -1.0 -1.0 0 2 6 2.50000 0.0 0.0 1 2 7 3.00000 1.0 1.0 6 0 8 3.00000 1.0 1.0 4 1 9 3.00000 1.0 1.0 2 2 10 3.00000 1.0 1.0 0 3 MAX 3.00000 6 3 SUM 1.0 1.0 I Q Coef1 Coef2 X MIN 2.00000 0 0 1 2.50000 -1.0 -1.0 5 0 2 3.00000 0.0 0.0 6 0 3 2.50000 -1.0 -1.0 3 1 4 3.00000 0.0 0.0 4 1 5 2.50000 -1.0 -1.0 1 2 6 3.00000 0.0 0.0 2 2 7 3.00000 0.0 0.0 0 3 8 3.50000 1.0 1.0 7 0 9 3.50000 1.0 1.0 5 1 10 3.50000 1.0 1.0 3 2 11 3.50000 1.0 1.0 1 3 MAX 3.50000 7 4 SUM 1.0 1.0 I Q Coef1 Coef2 X MIN 2.50000 0 0 1 3.00000 -1.0 -1.0 6 0 2 3.50000 0.0 0.0 7 0 3 3.00000 -1.0 -1.0 4 1 4 3.50000 0.0 0.0 5 1 5 3.00000 -1.0 -1.0 2 2 6 3.50000 0.0 0.0 3 2 7 3.00000 -1.0 -1.0 0 3 8 3.50000 0.0 0.0 1 3 9 4.00000 1.0 1.0 8 0 10 4.00000 1.0 1.0 6 1 11 4.00000 1.0 1.0 4 2 12 4.00000 1.0 1.0 2 3 13 4.00000 1.0 1.0 0 4 MAX 4.00000 8 4 SUM 1.0 1.0 SGMGA_VCN_COEF_TEST For anisotropic problems, each product grid in a sparse grid has an associated "combinatorial coefficient". SGMGA_VCN_COEF_NAIVE uses a naive algorithm. SGMGA_VCN_COEF attempts a more efficient method. Here, we simply compare COEF1 and COEF2, the same coefficient computed by the naive and efficient ways. IMPORTANCE: 1.00000 1.00000 1.00000 LEVEL_WEIGHT: 1.00000 1.00000 1.00000 I Q Coef1 Coef2 X MIN -3.00000 0 0 0 1 0.00000 1.0 1.0 0 0 0 MAX 0.00000 0 0 0 SUM 1.0 1.0 I Q Coef1 Coef2 X MIN -2.00000 0 0 0 1 0.00000 -2.0 -2.0 0 0 0 2 1.00000 1.0 1.0 1 0 0 3 1.00000 1.0 1.0 0 1 0 4 1.00000 1.0 1.0 0 0 1 MAX 1.00000 1 1 1 SUM 1.0 1.0 I Q Coef1 Coef2 X MIN -1.00000 0 0 0 1 0.00000 1.0 1.0 0 0 0 2 1.00000 -2.0 -2.0 1 0 0 3 1.00000 -2.0 -2.0 0 1 0 4 1.00000 -2.0 -2.0 0 0 1 5 2.00000 1.0 1.0 2 0 0 6 2.00000 1.0 1.0 1 1 0 7 2.00000 1.0 1.0 0 2 0 8 2.00000 1.0 1.0 1 0 1 9 2.00000 1.0 1.0 0 1 1 10 2.00000 1.0 1.0 0 0 2 MAX 2.00000 2 2 2 SUM 1.0 1.0 I Q Coef1 Coef2 X MIN 0.00000 0 0 0 1 1.00000 1.0 1.0 1 0 0 2 1.00000 1.0 1.0 0 1 0 3 1.00000 1.0 1.0 0 0 1 4 2.00000 -2.0 -2.0 2 0 0 5 2.00000 -2.0 -2.0 1 1 0 6 2.00000 -2.0 -2.0 0 2 0 7 2.00000 -2.0 -2.0 1 0 1 8 2.00000 -2.0 -2.0 0 1 1 9 2.00000 -2.0 -2.0 0 0 2 10 3.00000 1.0 1.0 3 0 0 11 3.00000 1.0 1.0 2 1 0 12 3.00000 1.0 1.0 1 2 0 13 3.00000 1.0 1.0 0 3 0 14 3.00000 1.0 1.0 2 0 1 15 3.00000 1.0 1.0 1 1 1 16 3.00000 1.0 1.0 0 2 1 17 3.00000 1.0 1.0 1 0 2 18 3.00000 1.0 1.0 0 1 2 19 3.00000 1.0 1.0 0 0 3 MAX 3.00000 3 3 3 SUM 1.0 1.0 I Q Coef1 Coef2 X MIN 1.00000 0 0 0 1 2.00000 1.0 1.0 2 0 0 2 2.00000 1.0 1.0 1 1 0 3 2.00000 1.0 1.0 0 2 0 4 2.00000 1.0 1.0 1 0 1 5 2.00000 1.0 1.0 0 1 1 6 2.00000 1.0 1.0 0 0 2 7 3.00000 -2.0 -2.0 3 0 0 8 3.00000 -2.0 -2.0 2 1 0 9 3.00000 -2.0 -2.0 1 2 0 10 3.00000 -2.0 -2.0 0 3 0 11 3.00000 -2.0 -2.0 2 0 1 12 3.00000 -2.0 -2.0 1 1 1 13 3.00000 -2.0 -2.0 0 2 1 14 3.00000 -2.0 -2.0 1 0 2 15 3.00000 -2.0 -2.0 0 1 2 16 3.00000 -2.0 -2.0 0 0 3 17 4.00000 1.0 1.0 4 0 0 18 4.00000 1.0 1.0 3 1 0 19 4.00000 1.0 1.0 2 2 0 20 4.00000 1.0 1.0 1 3 0 21 4.00000 1.0 1.0 0 4 0 22 4.00000 1.0 1.0 3 0 1 23 4.00000 1.0 1.0 2 1 1 24 4.00000 1.0 1.0 1 2 1 25 4.00000 1.0 1.0 0 3 1 26 4.00000 1.0 1.0 2 0 2 27 4.00000 1.0 1.0 1 1 2 28 4.00000 1.0 1.0 0 2 2 29 4.00000 1.0 1.0 1 0 3 30 4.00000 1.0 1.0 0 1 3 31 4.00000 1.0 1.0 0 0 4 MAX 4.00000 4 4 4 SUM 1.0 1.0 SGMGA_VCN_COEF_TEST For anisotropic problems, each product grid in a sparse grid has an associated "combinatorial coefficient". SGMGA_VCN_COEF_NAIVE uses a naive algorithm. SGMGA_VCN_COEF attempts a more efficient method. Here, we simply compare COEF1 and COEF2, the same coefficient computed by the naive and efficient ways. IMPORTANCE: 1.00000 2.00000 3.00000 LEVEL_WEIGHT: 1.00000 0.500000 0.333333 I Q Coef1 Coef2 X MIN -1.83333 0 0 0 1 0.00000 1.0 1.0 0 0 0 MAX 0.00000 0 0 0 SUM 1.0 1.0 I Q Coef1 Coef2 X MIN -1.50000 0 0 0 1 0.00000 0.0 0.0 0 0 0 2 0.333333 1.0 1.0 0 0 1 MAX 0.333333 1 1 1 SUM 1.0 1.0 I Q Coef1 Coef2 X MIN -1.16667 0 0 0 1 0.00000 -1.0 -1.0 0 0 0 2 0.500000 1.0 1.0 0 1 0 3 0.333333 0.0 0.0 0 0 1 4 0.666667 1.0 1.0 0 0 2 MAX 0.666667 1 2 2 SUM 1.0 1.0 I Q Coef1 Coef2 X MIN -0.833333 0 0 0 1 0.00000 -1.0 -1.0 0 0 0 2 1.00000 1.0 1.0 1 0 0 3 0.500000 -1.0 -1.0 0 1 0 4 1.00000 1.0 1.0 0 2 0 5 0.333333 -1.0 -1.0 0 0 1 6 0.833333 1.0 1.0 0 1 1 7 0.666667 0.0 0.0 0 0 2 8 1.00000 1.0 1.0 0 0 3 MAX 1.00000 1 2 3 SUM 1.0 1.0 I Q Coef1 Coef2 X MIN -0.500000 0 0 0 1 0.00000 0.0 0.0 0 0 0 2 0.500000 0.0 0.0 0 1 0 3 0.333333 -1.0 -1.0 0 0 1 4 1.00000 0.0 0.0 1 0 0 5 1.00000 0.0 0.0 0 2 0 6 1.33333 1.0 1.0 1 0 1 7 0.833333 -1.0 -1.0 0 1 1 8 1.33333 1.0 1.0 0 2 1 9 0.666667 -1.0 -1.0 0 0 2 10 1.16667 1.0 1.0 0 1 2 11 1.00000 0.0 0.0 0 0 3 12 1.33333 1.0 1.0 0 0 4 MAX 1.33333 2 3 4 SUM 1.0 1.0 SGMGA_VCN_COEF_TEST For anisotropic problems, each product grid in a sparse grid has an associated "combinatorial coefficient". SGMGA_VCN_COEF_NAIVE uses a naive algorithm. SGMGA_VCN_COEF attempts a more efficient method. Here, we simply compare COEF1 and COEF2, the same coefficient computed by the naive and efficient ways. IMPORTANCE: 1.00000 2.00000 3.00000 4.00000 LEVEL_WEIGHT: 1.00000 0.500000 0.333333 0.250000 I Q Coef1 Coef2 X MIN -2.08333 0 0 0 0 1 0.00000 1.0 1.0 0 0 0 0 MAX 0.00000 0 0 0 0 SUM 1.0 1.0 I Q Coef1 Coef2 X MIN -1.83333 0 0 0 0 1 0.00000 0.0 0.0 0 0 0 0 2 0.250000 1.0 1.0 0 0 0 1 MAX 0.250000 1 1 1 1 SUM 1.0 1.0 I Q Coef1 Coef2 X MIN -1.58333 0 0 0 0 1 0.00000 -2.0 -2.0 0 0 0 0 2 0.333333 1.0 1.0 0 0 1 0 3 0.250000 0.0 0.0 0 0 0 1 4 0.500000 1.0 1.0 0 1 0 0 5 0.500000 1.0 1.0 0 0 0 2 MAX 0.500000 1 1 2 2 SUM 1.0 1.0 I Q Coef1 Coef2 X MIN -1.33333 0 0 0 0 1 0.00000 0.0 0.0 0 0 0 0 2 0.500000 0.0 0.0 0 1 0 0 3 0.333333 -1.0 -1.0 0 0 1 0 4 0.666667 1.0 1.0 0 0 2 0 5 0.250000 -2.0 -2.0 0 0 0 1 6 0.583333 1.0 1.0 0 0 1 1 7 0.500000 0.0 0.0 0 0 0 2 8 0.750000 1.0 1.0 0 1 0 1 9 0.750000 1.0 1.0 0 0 0 3 MAX 0.750000 1 2 3 3 SUM 1.0 1.0 SGMGA_VCN_COEF_TEST For anisotropic problems, each product grid in a sparse grid has an associated "combinatorial coefficient". SGMGA_VCN_COEF_NAIVE uses a naive algorithm. SGMGA_VCN_COEF attempts a more efficient method. Here, we simply compare COEF1 and COEF2, the same coefficient computed by the naive and efficient ways. IMPORTANCE: 1.00000 0.00000 1.00000 LEVEL_WEIGHT: 1.00000 0.00000 1.00000 I Q Coef1 Coef2 X MIN -2.00000 0 0 0 1 0.00000 1.0 1.0 0 0 0 MAX 0.00000 0 0 0 SUM 1.0 1.0 I Q Coef1 Coef2 X MIN -1.00000 0 0 0 1 0.00000 -1.0 -1.0 0 0 0 2 1.00000 1.0 1.0 1 0 0 3 1.00000 1.0 1.0 0 0 1 MAX 1.00000 1 0 1 SUM 1.0 1.0 I Q Coef1 Coef2 X MIN 0.00000 0 0 0 1 1.00000 -1.0 -1.0 1 0 0 2 1.00000 -1.0 -1.0 0 0 1 3 2.00000 1.0 1.0 2 0 0 4 2.00000 1.0 1.0 1 0 1 5 2.00000 1.0 1.0 0 0 2 MAX 2.00000 2 0 2 SUM 1.0 1.0 I Q Coef1 Coef2 X MIN 1.00000 0 0 0 1 2.00000 -1.0 -1.0 2 0 0 2 2.00000 -1.0 -1.0 1 0 1 3 2.00000 -1.0 -1.0 0 0 2 4 3.00000 1.0 1.0 3 0 0 5 3.00000 1.0 1.0 2 0 1 6 3.00000 1.0 1.0 1 0 2 7 3.00000 1.0 1.0 0 0 3 MAX 3.00000 3 0 3 SUM 1.0 1.0 SGMGA_VCN_COEF_TEST: Normal end of execution. 21 November 2024 8:35:38.079 AM