seed =Menu
0. Exit
1. Run with class 1. Loops over each element
2. Run with class 2. Fills (row*col*prob) elements.
3. Run with different fills
4. Run with 3 functions using class 2 matrix.
5. Run with graph matrix. Vary size.
6. Run with graph matrix. Vary prob.
7. Run ge vs origional ge vs new sge with different sizes.
8. Same as 7 but with edges and diag. of the range of matrix sizes

  type >> StartRow = startCol = endRow = endCol = Density (< 1) = stepSize = 100000
200000
SGE: 11.01 VS. SGE_original: 12.24 VS. GE: 18.98  Stats: [80000,80000]  fill=256015 prob=4e-05
true
100000
200000
SGE: 20.24 VS. SGE_original: 23.51 VS. GE: 36.35  Stats: [80000,82000]  fill=262414 prob=4e-05
true
100000
200000
SGE: 26.93 VS. SGE_original: 31.96 VS. GE: 49.4  Stats: [80000,84000]  fill=268813 prob=4e-05
true
100000
200000
SGE: 34.59 VS. SGE_original: 39.26 VS. GE: 63.06  Stats: [80000,86000]  fill=275215 prob=4e-05
true
100000
200000
SGE: 42.73 VS. SGE_original: 47.84 VS. GE: 77.23  Stats: [80000,88000]  fill=281617 prob=4e-05
true
100000
200000
SGE: 51.71 VS. SGE_original: 58.63 VS. GE: 96.35  Stats: [80000,90000]  fill=288016 prob=4e-05
true
100000
200000
SGE: 59.16 VS. SGE_original: 71.24 VS. GE: 118.84  Stats: [80000,92000]  fill=294410 prob=4e-05
true
100000
200000
300000
SGE: 66.14 VS. SGE_original: 74.23 VS. GE: 134.37  Stats: [80000,94000]  fill=300813 prob=4e-05
true
100000
200000
300000
SGE: 83.61 VS. SGE_original: 96.74 VS. GE: 170.72  Stats: [80000,96000]  fill=307216 prob=4e-05
true
100000
200000
300000
SGE: 86.04 VS. SGE_original: 99.9 VS. GE: 163.14  Stats: [80000,98000]  fill=313618 prob=4e-05
true
100000
200000
300000
SGE: 95.53 VS. SGE_original: 112.32 VS. GE: 170.16  Stats: [80000,100000]  fill=320022 prob=4e-05
true
100000
200000
SGE: 12.1 VS. SGE_original: 13.28 VS. GE: 20.59  Stats: [80000,80000]  fill=256011 prob=4e-05
true
100000
200000
SGE: 20.3 VS. SGE_original: 22.45 VS. GE: 33.65  Stats: [82000,82000]  fill=268978 prob=4e-05
true
100000
200000
SGE: 36.63 VS. SGE_original: 43.85 VS. GE: 68.83  Stats: [84000,84000]  fill=282254 prob=4e-05
true
100000
200000
SGE: 57.2 VS. SGE_original: 66.64 VS. GE: 114.58  Stats: [86000,86000]  fill=295856 prob=4e-05
true
100000
200000
300000
SGE: 93.71 VS. SGE_original: 114.8 VS. GE: 185.6  Stats: [88000,88000]  fill=309777 prob=4e-05
true
100000
200000
300000
SGE: 124.53 VS. SGE_original: 163.73 VS. GE: 277.78  Stats: [90000,90000]  fill=324013 prob=4e-05
true
100000
200000
300000
SGE: 183.14 VS. SGE_original: 255.71 VS. GE: 418.1  Stats: [92000,92000]  fill=338571 prob=4e-05
true
100000
200000
300000
SGE: 262.21 VS. SGE_original: 375.54 VS. GE: 638.53  Stats: [94000,94000]  fill=353456 prob=4e-05
true
100000
200000
300000
SGE: 368.69 VS. SGE_original: 550.27 VS. GE: 937.36  Stats: [96000,96000]  fill=368657 prob=4e-05
true
100000
200000
300000
SGE: 493.69 VS. SGE_original: 772.33 VS. GE: 1309.5  Stats: [98000,98000]  fill=384177 prob=4e-05
true
100000
200000
300000
400000
SGE: 692.73 VS. SGE_original: 1082.39 VS. GE: 1755.62  Stats: [100000,100000]  fill=400020 prob=4e-05
true
100000
200000
SGE: 11.48 VS. SGE_original: 11.91 VS. GE: 18.03  Stats: [80000,80000]  fill=256012 prob=4e-05
true
100000
200000
SGE: 9.22 VS. SGE_original: 8.97 VS. GE: 14.11  Stats: [82000,80000]  fill=262424 prob=4e-05
true
100000
200000
SGE: 8.19 VS. SGE_original: 7.48 VS. GE: 10.77  Stats: [84000,80000]  fill=268819 prob=4e-05
true
100000
200000
SGE: 4.73 VS. SGE_original: 4.37 VS. GE: 4.96  Stats: [86000,80000]  fill=275218 prob=4e-05
true
100000
200000
SGE: 3.42 VS. SGE_original: 3.26 VS. GE: 2.16  Stats: [88000,80000]  fill=281609 prob=4e-05
true
100000
200000
SGE: 2.47 VS. SGE_original: 2.31 VS. GE: 1.12  Stats: [90000,80000]  fill=288006 prob=4e-05
true
100000
200000
SGE: 1.78 VS. SGE_original: 1.72 VS. GE: 0.75  Stats: [92000,80000]  fill=294419 prob=4e-05
true
100000
200000
300000
SGE: 1.52 VS. SGE_original: 1.46 VS. GE: 0.64  Stats: [94000,80000]  fill=300819 prob=4e-05
true
100000
200000
300000
SGE: 1.17 VS. SGE_original: 1.14 VS. GE: 0.53  Stats: [96000,80000]  fill=307216 prob=4e-05
true
100000
200000
300000
SGE: 1.12 VS. SGE_original: 1.09 VS. GE: 0.5  Stats: [98000,80000]  fill=313615 prob=4e-05
true
100000
200000
300000
SGE: 0.99 VS. SGE_original: 0.95 VS. GE: 0.48  Stats: [100000,80000]  fill=320021 prob=4e-05
true
Menu
0. Exit
1. Run with class 1. Loops over each element
2. Run with class 2. Fills (row*col*prob) elements.
3. Run with different fills
4. Run with 3 functions using class 2 matrix.
5. Run with graph matrix. Vary size.
6. Run with graph matrix. Vary prob.
7. Run ge vs origional ge vs new sge with different sizes.
8. Same as 7 but with edges and diag. of the range of matrix sizes

  type >> TOTAL TIME: 14065.8
