Thu Sep 13 09:31:37 2018 GRID_TEST Python version: 3.6.5 Test the GRID library. GRID_GENERATE_TESTS: GRID_GENERATE_TEST generates a specific grid. GRID_GENERATE_TEST Python version: 3.6.5 GRID_GENERATE randomly chooses a given number of points on a uniform grid. Spatial dimension = 2 Number of points = 10 Random number SEED = 123456789 Centering option = 1 Grid points: Row: 0 1 Col 0 : 0 0 1 : 0 1 2 : 0.333333 0 3 : 0.333333 0.333333 4 : 0.333333 0.666667 5 : 0.333333 1 6 : 0.666667 0 7 : 0.666667 0.666667 8 : 1 0 9 : 1 1 GRID_GENERATE_TEST: Normal end of execution. Repeat with a different seed from the first run. GRID_GENERATE_TEST Python version: 3.6.5 GRID_GENERATE randomly chooses a given number of points on a uniform grid. Spatial dimension = 2 Number of points = 10 Random number SEED = 987654321 Centering option = 1 Grid points: Row: 0 1 Col 0 : 0 0.666667 1 : 0 1 2 : 0.333333 0 3 : 0.333333 0.333333 4 : 0.333333 0.666667 5 : 0.666667 0 6 : 0.666667 0.333333 7 : 0.666667 1 8 : 1 0.333333 9 : 1 1 GRID_GENERATE_TEST: Normal end of execution. Repeat with the same seed as the first run. GRID_GENERATE_TEST Python version: 3.6.5 GRID_GENERATE randomly chooses a given number of points on a uniform grid. Spatial dimension = 2 Number of points = 10 Random number SEED = 123456789 Centering option = 1 Grid points: Row: 0 1 Col 0 : 0 0 1 : 0 1 2 : 0.333333 0 3 : 0.333333 0.333333 4 : 0.333333 0.666667 5 : 0.333333 1 6 : 0.666667 0 7 : 0.666667 0.666667 8 : 1 0 9 : 1 1 GRID_GENERATE_TEST: Normal end of execution. Repeat with different centering values. GRID_GENERATE_TEST Python version: 3.6.5 GRID_GENERATE randomly chooses a given number of points on a uniform grid. Spatial dimension = 2 Number of points = 10 Random number SEED = 123456789 Centering option = 1 Grid points: Row: 0 1 Col 0 : 0 0 1 : 0 1 2 : 0.333333 0 3 : 0.333333 0.333333 4 : 0.333333 0.666667 5 : 0.333333 1 6 : 0.666667 0 7 : 0.666667 0.666667 8 : 1 0 9 : 1 1 GRID_GENERATE_TEST: Normal end of execution. GRID_GENERATE_TEST Python version: 3.6.5 GRID_GENERATE randomly chooses a given number of points on a uniform grid. Spatial dimension = 2 Number of points = 10 Random number SEED = 123456789 Centering option = 2 Grid points: Row: 0 1 Col 0 : 0.2 0.2 1 : 0.2 0.8 2 : 0.4 0.2 3 : 0.4 0.4 4 : 0.4 0.6 5 : 0.4 0.8 6 : 0.6 0.2 7 : 0.6 0.6 8 : 0.8 0.2 9 : 0.8 0.8 GRID_GENERATE_TEST: Normal end of execution. GRID_GENERATE_TEST Python version: 3.6.5 GRID_GENERATE randomly chooses a given number of points on a uniform grid. Spatial dimension = 2 Number of points = 10 Random number SEED = 123456789 Centering option = 3 Grid points: Row: 0 1 Col 0 : 0 0 1 : 0 0.75 2 : 0.25 0 3 : 0.25 0.25 4 : 0.25 0.5 5 : 0.25 0.75 6 : 0.5 0 7 : 0.5 0.5 8 : 0.75 0 9 : 0.75 0.75 GRID_GENERATE_TEST: Normal end of execution. GRID_GENERATE_TEST Python version: 3.6.5 GRID_GENERATE randomly chooses a given number of points on a uniform grid. Spatial dimension = 2 Number of points = 10 Random number SEED = 123456789 Centering option = 4 Grid points: Row: 0 1 Col 0 : 0.25 0.25 1 : 0.25 1 2 : 0.5 0.25 3 : 0.5 0.5 4 : 0.5 0.75 5 : 0.5 1 6 : 0.75 0.25 7 : 0.75 0.75 8 : 1 0.25 9 : 1 1 GRID_GENERATE_TEST: Normal end of execution. GRID_GENERATE_TEST Python version: 3.6.5 GRID_GENERATE randomly chooses a given number of points on a uniform grid. Spatial dimension = 2 Number of points = 10 Random number SEED = 123456789 Centering option = 5 Grid points: Row: 0 1 Col 0 : 0.125 0.125 1 : 0.125 0.875 2 : 0.375 0.125 3 : 0.375 0.375 4 : 0.375 0.625 5 : 0.375 0.875 6 : 0.625 0.125 7 : 0.625 0.625 8 : 0.875 0.125 9 : 0.875 0.875 GRID_GENERATE_TEST: Normal end of execution. GRID_GENERATE_TESTS: Normal end of execution. GRID_SIDE_TEST Python version: 3.6.5 GRID_SIDE returns the smallest N_SIDE, such that N <= NSIDE^M M N NSIDE NSIDE^M 2 10 4 16 2 100 10 100 2 1000 32 1024 2 10000 100 10000 3 10 3 27 3 100 5 125 3 1000 10 1000 3 10000 22 10648 4 10 2 16 4 100 4 256 4 1000 6 1296 4 10000 10 10000 GRID_SIDE_TEST: Normal end of execution. TUPLE_NEXT_FAST_TEST Python version: 3.6.5 TUPLE_NEXT_FAST returns the next "tuple", that is, a vector of N integers, each between 1 and M. M = 3 N = 2 0 1 1 1 1 2 2 1 3 3 2 1 4 2 2 5 2 3 6 3 1 7 3 2 8 3 3 TUPLE_NEXT_FAST_TEST: Normal end of execution. GRID_TEST: Normal end of execution. Thu Sep 13 09:31:37 2018