04 November 2014 04:37:43 PM IHS_PRB C++ version Test the IHS library. TEST01 IHS implements the IHS Algorithm (Improved Distributed Hypercube Sampling) Demonstrate the code for a fixed number of points and an increasing dimension. Random number seed = 17 Spatial dimension = 1 Number of points = 10 Duplication factor = 5 Desired minimum distance = 1 Average minimum distance 1 Standard deviation: 0 Covariance: 0 X: Row: 0 Col 0: 10 1: 9 2: 8 3: 7 4: 6 5: 5 6: 4 7: 3 8: 2 9: 1 Random number seed = 17 Spatial dimension = 2 Number of points = 10 Duplication factor = 5 Desired minimum distance = 3.16228 Average minimum distance 2.61235 Standard deviation: 0.646017 Covariance: 0.247293 X: Row: 0 1 Col 0: 10 8 1: 8 2 2: 7 5 3: 9 9 4: 6 10 5: 5 7 6: 2 6 7: 4 4 8: 3 1 9: 1 3 Random number seed = 17 Spatial dimension = 3 Number of points = 10 Duplication factor = 5 Desired minimum distance = 4.64159 Average minimum distance 4.25073 Standard deviation: 0.381952 Covariance: 0.0898556 X: Row: 0 1 2 Col 0: 8 7 6 1: 9 8 2 2: 2 5 3 3: 3 9 10 4: 10 2 1 5: 7 4 4 6: 6 10 5 7: 4 6 7 8: 5 1 8 9: 1 3 9 Random number seed = 17 Spatial dimension = 4 Number of points = 10 Duplication factor = 5 Desired minimum distance = 5.62341 Average minimum distance 5.16627 Standard deviation: 0.823054 Covariance: 0.159313 X: Row: 0 1 2 3 Col 0: 9 7 8 2 1: 10 6 3 5 2: 7 9 6 1 3: 4 2 1 10 4: 8 1 7 3 5: 3 10 5 9 6: 5 8 2 4 7: 2 5 4 7 8: 6 4 10 6 9: 1 3 9 8 TEST02 IHS implements the IHS Algorithm (Improved Distributed Hypercube Sampling) Demonstrate the code for a fixed number of points and dimension, but vary the duplication value. Spatial dimension = 2 Number of points = 10 Desired minimum distance = 3.16228 Random number seed = 17 Duplication factor = 1 Average minimum distance 2.75287 Standard deviation: 0.831132 Covariance: 0.301915 X: Row: 0 1 Col 0: 5 7 1: 10 4 2: 8 2 3: 7 5 4: 2 9 5: 9 10 6: 6 8 7: 3 6 8: 4 1 9: 1 3 Random number seed = 17 Duplication factor = 2 Average minimum distance 2.59148 Standard deviation: 0.305893 Covariance: 0.118038 X: Row: 0 1 Col 0: 9 7 1: 8 4 2: 6 2 3: 10 9 4: 7 10 5: 5 8 6: 4 5 7: 2 6 8: 3 1 9: 1 3 Random number seed = 17 Duplication factor = 3 Average minimum distance 2.96197 Standard deviation: 0.1724 Covariance: 0.0582044 X: Row: 0 1 Col 0: 3 9 1: 6 4 2: 10 10 3: 9 5 4: 8 8 5: 7 1 6: 4 2 7: 5 7 8: 2 6 9: 1 3 Random number seed = 17 Duplication factor = 4 Average minimum distance 2.61235 Standard deviation: 0.646017 Covariance: 0.247293 X: Row: 0 1 Col 0: 2 10 1: 3 9 2: 9 1 3: 6 2 4: 10 6 5: 7 5 6: 8 8 7: 5 7 8: 4 4 9: 1 3 Random number seed = 17 Duplication factor = 5 Average minimum distance 2.61235 Standard deviation: 0.646017 Covariance: 0.247293 X: Row: 0 1 Col 0: 10 8 1: 8 2 2: 7 5 3: 9 9 4: 6 10 5: 5 7 6: 2 6 7: 4 4 8: 3 1 9: 1 3 TEST03 IHS implements the IHS Algorithm (Improved Distributed Hypercube Sampling) Demonstrate the code for a fixed dimension and duplication value, and increasing number of points. Spatial dimension = 2 Duplication factor = 5 Random number seed = 17 Number of points = 10 Desired minimum distance = 3.16228 Average minimum distance 2.61235 Standard deviation: 0.646017 Covariance: 0.247293 1 10 8 2 8 2 3 7 5 4 9 9 5 6 10 6 5 7 7 2 6 8 4 4 9 3 1 10 1 3 Random number seed = 17 Number of points = 20 Desired minimum distance = 4.47214 Average minimum distance 3.93991 Standard deviation: 0.431761 Covariance: 0.109586 1 7 15 2 17 20 3 9 17 4 13 19 5 19 8 6 3 14 7 20 18 8 16 16 9 15 4 10 18 12 11 10 13 12 14 10 13 11 7 14 12 1 15 6 11 16 8 3 17 5 6 18 4 2 19 2 9 20 1 5 Random number seed = 17 Number of points = 40 Desired minimum distance = 6.32456 Average minimum distance 5.41626 Standard deviation: 1.21491 Covariance: 0.224307 1 29 18 2 23 22 3 5 35 4 7 29 5 40 6 6 34 12 7 35 2 8 32 8 9 13 28 10 37 16 11 9 34 .... ........ 31 21 13 32 25 5 33 19 7 34 4 20 35 18 1 36 12 3 37 10 9 38 6 14 39 3 4 40 1 10 Random number seed = 17 Number of points = 80 Desired minimum distance = 8.94427 Average minimum distance 7.62952 Standard deviation: 1.50205 Covariance: 0.196873 1 51 49 2 8 37 3 28 29 4 17 73 5 46 10 6 64 14 7 43 59 8 60 26 9 32 57 10 69 70 11 4 61 .... ........ 71 12 40 72 11 60 73 7 52 74 13 31 75 3 44 76 2 35 77 18 18 78 5 27 79 9 15 80 1 19 Random number seed = 17 Number of points = 160 Desired minimum distance = 12.6491 Average minimum distance 11.0375 Standard deviation: 2.04303 Covariance: 0.185099 1 85 65 2 123 60 3 42 111 4 145 145 5 77 46 6 99 101 7 144 75 8 118 31 9 27 122 10 92 53 11 130 89 .... ........ 151 16 66 152 34 16 153 21 54 154 9 48 155 23 10 156 25 42 157 17 21 158 14 36 159 6 26 160 1 38 TEST04 IHS implements the IHS Algorithm (Improved Distributed Hypercube Sampling) Demonstrate the code for a fixed number of points, dimension, and duplication factor, but with a varying random number seed. Spatial dimension = 2 Number of points = 10 Duplication factor = 5 Desired minimum distance = 3.16228 Random number seed = 17 Average minimum distance 2.61235 Standard deviation: 0.646017 Covariance: 0.247293 X: Row: 0 1 Col 0: 10 8 1: 8 2 2: 7 5 3: 9 9 4: 6 10 5: 5 7 6: 2 6 7: 4 4 8: 3 1 9: 1 3 Random number seed = 1207526547 Average minimum distance 2.71251 Standard deviation: 0.701024 Covariance: 0.258441 X: Row: 0 1 Col 0: 4 8 1: 8 10 2: 7 7 3: 3 9 4: 1 3 5: 2 6 6: 5 5 7: 10 4 8: 9 1 9: 6 2 Random number seed = 1136848141 Average minimum distance 3.16228 Standard deviation: 4.68111e-16 Covariance: 1.4803e-16 X: Row: 0 1 Col 0: 3 3 1: 8 8 2: 2 6 3: 1 9 4: 9 5 5: 10 2 6: 7 1 7: 6 4 8: 5 7 9: 4 10 Random number seed = 1231916218 Average minimum distance 3.09551 Standard deviation: 0.140764 Covariance: 0.0454736 X: Row: 0 1 Col 0: 10 8 1: 7 7 2: 1 3 3: 9 1 4: 4 2 5: 6 10 6: 3 9 7: 8 4 8: 2 6 9: 5 5 IHS_PRB Normal end of execution. 04 November 2014 04:37:43 PM