diff --git a/integerValues/test b/integerValues/test
deleted file mode 100755
index 001b8d9e5e3dba8ab754bfb0d0bc2c5466e30ad2..0000000000000000000000000000000000000000
Binary files a/integerValues/test and /dev/null differ
diff --git a/realValues/test.txt b/realValues/test.txt
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/result-Csv/failedTests.csv b/result-Csv/failedTests.csv
deleted file mode 100644
index f8629eb7b52174ca6fd5d088d16e6d02b663ea70..0000000000000000000000000000000000000000
--- a/result-Csv/failedTests.csv
+++ /dev/null
@@ -1,10 +0,0 @@
-Generator,Number of Failed Tests,Failed Tests
-pcgReal,0,
-tensorflowReal,0,
-MRG32k3aReal,0,
-wellReal,2,"80 LinearComp, 81 LinearComp,"
-numpyReal,0,
-mtReal,2,"80 LinearComp, 81 LinearComp,"
-numpyPhiloxReal,1,"21 BirthdaySpacings,"
-pythonReal,2,"80 LinearComp, 81 LinearComp,"
-numpyMtReal,2,"80 LinearComp, 81 LinearComp,"
diff --git a/result-Csv/results.csv b/result-Csv/results.csv
deleted file mode 100644
index 26125b0d72ad6a4914d0350c0e6a7ae359d99df1..0000000000000000000000000000000000000000
--- a/result-Csv/results.csv
+++ /dev/null
@@ -1,28 +0,0 @@
-Generator,Real time (s),Real time variance,User time (s),User time variance,Difference (Real - User time),Energy consumption (J/min),Energy consumption during real time (J)
-mrg32k3aO2,31.46596666666667,0.49491024022988495,31.462766666666667,0.4947381160919544,0.0032000000000032003,2750.7950000000005,1442.6070629472226
-mrg32k3aO3,19.965866666666674,0.2272254988505746,19.964000000000002,0.2270607586206895,0.0018666666666717902,3000.865,998.5811745777781
-mrg32k3aR,43.1265,0.20636770689655226,43.12336666666667,0.206296791954023,0.003133333333330768,2783.585,2000.7713083750002
-mt19937arO2,4.503133333333334,0.21657274022988496,4.501466666666667,0.21569949885057468,0.0016666666666669272,3179.1649999999995,238.60339806111114
-mt19937arO3,4.197433333333333,0.15405777126436782,4.195966666666667,0.15353389540229886,0.001466666666665617,3226.824999999999,225.7397135972221
-mt19937arR,7.4846,0.23828914482758615,7.482766666666666,0.237718116091954,0.0018333333333346857,3186.49,397.49338423333336
-numpyMt_numpyMtRandomGenerationAtOnce,13.082566666666668,18.089264460919544,7.268966666666667,0.09162589540229887,5.813600000000002,4358.065,950.2445983361112
-numpyMt_numpyMtRandomGenerationOneByOne,319.89383333333325,26.484203660919537,320.8309,26.49299429999996,-0.9370666666667375,37375.55172413793,199270.1418997126
-numpyPhilox_numpyPhiloxRandomGenerationAtOnce,13.255833333333332,3.4810100057471263,12.000133333333336,0.0920814988505747,1.2556999999999956,5033.005,1111.9445907638888
-numpyPhilox_numpyPhiloxRandomGenerationOneByOne,323.06210000000004,24.89505278275862,323.9827333333333,24.71960661609191,-0.9206333333332282,37590.444827586194,202400.8007655689
-numpyR_numpyRandomGenerationAtOnce,5.773,8.520403655172414,5.754666666666666,8.441070505747126,0.018333333333333535,5906.645,568.3176930833333
-numpyR_numpyRandomGenerationOneByOne,330.97513333333336,162.89779818850576,331.8779333333333,162.6530534436781,-0.9027999999999565,5935.288965517241,32740.55094556552
-numpyTaskset_numpyTasksetRandomGenerationAtOnce,4.354899999999999,0.008284920689655164,3.562033333333334,0.01548003333333333,0.792866666666665,4550.28,330.2669061999999
-pcg64O2,11.073166666666669,0.19433441954022995,11.071966666666667,0.19419824022988502,0.0012000000000025324,3925.1749999999993,724.4019495138889
-pcg64O3,10.9984,0.22081838620689676,10.996300000000003,0.2202073896551725,0.002099999999996882,3882.5499999999997,711.6972986666666
-pcg64R,13.180333333333333,0.12721698850574706,13.179233333333334,0.12687735747126433,0.0010999999999992127,4473.06724137931,982.6086210632183
-pythonR_pythonRandomGenerationAtOnce,75.4612,90.25866609655172,48.47893333333333,12.18376565057471,26.982266666666675,6521.71,8202.267710866668
-pythonR_pythonRandomGenerationOneByOne,36.86926666666667,3.180715719540231,36.8575,3.182281913793104,0.011766666666666481,3865.7082758620686,2375.4304879716474
-pythonTaskset_pythonTasksetRandomGenerationAtOnce,69.5241,2.023144575862068,43.88626666666667,0.41396227126436735,25.637833333333333,3994.8950000000004,4629.024657825001
-pytorchR_pytorchRandomGenerationAtOnce,6.9013,0.16385980344827578,7.010666666666667,0.09930485057471261,-0.10936666666666728,7141.5,821.4272325
-pytorchR_pytorchRandomGenerationOneByOne,2388.4092333333333,385.8636750126419,2388.8528666666666,388.14882956781724,-0.44363333333330957,5630.9,224148.22586627776
-pytorchTaskset_pytorchTasksetRandomGenerationAtOnce,6.020233333333334,0.056457771264367844,5.3053,0.02500014827586207,0.7149333333333345,4348.024137931035,436.26866415517253
-tensorflowR_tensorflowRandomGenerationAtOnce,3.3758,0.06826740689655171,32.3289,1.463164851724137,-28.9531,5131.120000000001,288.69391493333336
-tensorflowTaskset_tensorflowTasksetRandomGenerationAtOnce,8.180733333333333,0.02550523678160922,6.674499999999998,0.01418743103448277,1.5062333333333342,4762.630000000001,649.3634332555557
-well19937O2a,4.974933333333334,0.1644335126436781,4.9732666666666665,0.16416151264367818,0.0016666666666678154,2979.4150000000004,247.03984995555564
-well19937O3a,4.963066666666665,0.10090089195402302,4.9612,0.10049961379310347,0.001866666666665573,2991.035,247.41176845555546
-well19937aR,13.082866666666668,0.00039618850574712724,13.080633333333333,0.00042961954022987576,0.0022333333333346417,3040.6600000000003,663.0091559777778
diff --git a/result-Csv/results_sorted_by_energy_per_minute.csv b/result-Csv/results_sorted_by_energy_per_minute.csv
deleted file mode 100644
index 0e0c6300c92f1e4c88a17c2ec8222410ec0c4050..0000000000000000000000000000000000000000
--- a/result-Csv/results_sorted_by_energy_per_minute.csv
+++ /dev/null
@@ -1,28 +0,0 @@
-Generator,Real time (s),Real time variance,Real time 95% CI,User time (s),User time variance,User time 95% CI,Difference (Real - User time),Energy consumption (J/min),Energy consumption 95% CI,Energy consumption during real time (J),Energy consumption during real time 95% CI
-mrg32k3aO2,31.466,0.4949,[31.21; 31.72],31.4628,0.4947,[31.21; 31.71],0.0032,2750.795,[2744.56; 2757.03],1442.6071,[1439.33; 1445.88]
-mrg32k3aR,43.1265,0.2064,[42.96; 43.29],43.1234,0.2063,[42.96; 43.29],0.0031,2783.585,[2744.86; 2822.31],2000.7713,[1972.93; 2028.61]
-well19937O2a,4.9749,0.1644,[4.83; 5.12],4.9733,0.1642,[4.83; 5.12],0.0017,2979.415,[2970.81; 2988.02],247.0398,[246.33; 247.75]
-well19937O3a,4.9631,0.1009,[4.85; 5.08],4.9612,0.1005,[4.85; 5.07],0.0019,2991.035,[2981.97; 3000.10],247.4118,[246.66; 248.16]
-mrg32k3aO3,19.9659,0.2272,[19.80; 20.14],19.964,0.2271,[19.79; 20.13],0.0019,3000.865,[2941.58; 3060.15],998.5812,[978.85; 1018.31]
-well19937aR,13.0829,0.0004,[13.08; 13.09],13.0806,0.0004,[13.07; 13.09],0.0022,3040.66,[3008.42; 3072.90],663.0092,[655.98; 670.04]
-mt19937arO2,4.5031,0.2166,[4.34; 4.67],4.5015,0.2157,[4.34; 4.67],0.0017,3179.165,[3168.29; 3190.04],238.6034,[237.79; 239.42]
-mt19937arR,7.4846,0.2383,[7.31; 7.66],7.4828,0.2377,[7.31; 7.66],0.0018,3186.49,[3172.36; 3200.62],397.4934,[395.73; 399.26]
-mt19937arO3,4.1974,0.1541,[4.06; 4.34],4.196,0.1535,[4.06; 4.34],0.0015,3226.825,[3159.98; 3293.67],225.7397,[221.06; 230.42]
-pythonR_pythonRandomGenerationOneByOne,36.8693,3.1807,[36.23; 37.51],36.8575,3.1823,[36.22; 37.50],0.0118,3865.7083,[3806.83; 3924.59],2375.4305,[2339.25; 2411.61]
-pcg64O3,10.9984,0.2208,[10.83; 11.17],10.9963,0.2202,[10.83; 11.16],0.0021,3882.55,[3812.37; 3952.73],711.6973,[698.83; 724.56]
-pcg64O2,11.0732,0.1943,[10.92; 11.23],11.072,0.1942,[10.91; 11.23],0.0012,3925.175,[3872.56; 3977.79],724.4019,[714.69; 734.11]
-pythonTaskset_pythonTasksetRandomGenerationAtOnce,69.5241,2.0231,[69.02; 70.03],43.8863,0.4140,[43.66; 44.12],25.6378,3994.895,[3871.83; 4117.96],4629.0247,[4486.43; 4771.62]
-pytorchTaskset_pytorchTasksetRandomGenerationAtOnce,6.0202,0.0565,[5.94; 6.11],5.3053,0.0250,[5.25; 5.36],0.7149,4348.0241,[4306.74; 4389.30],436.2687,[432.13; 440.41]
-numpyMt_numpyMtRandomGenerationAtOnce,13.0826,18.0893,[11.56; 14.60],7.269,0.0916,[7.16; 7.38],5.8136,4358.065,[4168.48; 4547.65],950.2446,[908.91; 991.58]
-pcg64R,13.1803,0.1272,[13.05; 13.31],13.1792,0.1269,[13.05; 13.31],0.0011,4473.0672,[4459.61; 4486.52],982.6086,[979.65; 985.56]
-numpyTaskset_numpyTasksetRandomGenerationAtOnce,4.3549,0.0083,[4.32; 4.39],3.562,0.0155,[3.52; 3.61],0.7929,4550.28,[4530.53; 4570.03],330.2669,[328.83; 331.70]
-tensorflowTaskset_tensorflowTasksetRandomGenerationAtOnce,8.1807,0.0255,[8.12; 8.24],6.6745,0.0142,[6.63; 6.72],1.5062,4762.63,[4750.04; 4775.22],649.3634,[647.65; 651.08]
-numpyPhilox_numpyPhiloxRandomGenerationAtOnce,13.2558,3.4810,[12.59; 13.92],12.0001,0.0921,[11.89; 12.11],1.2557,5033.005,[4875.79; 5190.22],1111.9446,[1077.21; 1146.68]
-tensorflowR_tensorflowRandomGenerationAtOnce,3.3758,0.0683,[3.28; 3.47],32.3289,1.4632,[31.90; 32.76],-28.9531,5131.12,[5100.87; 5161.37],288.6939,[286.99; 290.40]
-pytorchR_pytorchRandomGenerationOneByOne,2388.4092,385.8637,[2381.38; 2395.44],2388.8529,388.1488,[2381.80; 2395.90],-0.4436,5630.9,[5233.18; 6028.62],224148.2259,[208316.06; 239980.39]
-numpyR_numpyRandomGenerationAtOnce,5.773,8.5204,[4.73; 6.82],5.7547,8.4411,[4.71; 6.79],0.0183,5906.645,[5670.16; 6143.13],568.3177,[545.56; 591.07]
-numpyR_numpyRandomGenerationOneByOne,330.9751,162.8978,[326.41; 335.54],331.8779,162.6531,[327.31; 336.44],-0.9028,5935.289,[5772.42; 6098.16],32740.5509,[31842.13; 33638.98]
-pythonR_pythonRandomGenerationAtOnce,75.4612,90.2587,[72.06; 78.86],48.4789,12.1838,[47.23; 49.73],26.9823,6521.71,[6078.98; 6964.44],8202.2677,[7645.45; 8759.08]
-pytorchR_pytorchRandomGenerationAtOnce,6.9013,0.1639,[6.76; 7.05],7.0107,0.0993,[6.90; 7.12],-0.1094,7141.5,[6891.12; 7391.88],821.4272,[792.63; 850.23]
-numpyMt_numpyMtRandomGenerationOneByOne,319.8938,26.4842,[318.05; 321.74],320.8309,26.4930,[318.99; 322.67],-0.9371,37375.5517,[36671.35; 38079.75],199270.1419,[195515.66; 203024.62]
-numpyPhilox_numpyPhiloxRandomGenerationOneByOne,323.0621,24.8951,[321.28; 324.85],323.9827,24.7196,[322.20; 325.76],-0.9206,37590.4448,[36613.97; 38566.92],202400.8008,[197143.08; 207658.52]
diff --git a/result-Csv/results_sorted_by_energy_real_time.csv b/result-Csv/results_sorted_by_energy_real_time.csv
deleted file mode 100644
index a1b83f2e632c2be9216736a7e1951baa05e71de7..0000000000000000000000000000000000000000
--- a/result-Csv/results_sorted_by_energy_real_time.csv
+++ /dev/null
@@ -1,28 +0,0 @@
-Generator,Real time (s),Real time variance,Real time 95% CI,User time (s),User time variance,User time 95% CI,Difference (Real - User time),Energy consumption (J/min),Energy consumption 95% CI,Energy consumption during real time (J),Energy consumption during real time 95% CI
-mt19937arO3,4.1974,0.1541,[4.06; 4.34],4.196,0.1535,[4.06; 4.34],0.0015,3226.825,[3159.98; 3293.67],225.7397,[221.06; 230.42]
-mt19937arO2,4.5031,0.2166,[4.34; 4.67],4.5015,0.2157,[4.34; 4.67],0.0017,3179.165,[3168.29; 3190.04],238.6034,[237.79; 239.42]
-well19937O2a,4.9749,0.1644,[4.83; 5.12],4.9733,0.1642,[4.83; 5.12],0.0017,2979.415,[2970.81; 2988.02],247.0398,[246.33; 247.75]
-well19937O3a,4.9631,0.1009,[4.85; 5.08],4.9612,0.1005,[4.85; 5.07],0.0019,2991.035,[2981.97; 3000.10],247.4118,[246.66; 248.16]
-tensorflowR_tensorflowRandomGenerationAtOnce,3.3758,0.0683,[3.28; 3.47],32.3289,1.4632,[31.90; 32.76],-28.9531,5131.12,[5100.87; 5161.37],288.6939,[286.99; 290.40]
-numpyTaskset_numpyTasksetRandomGenerationAtOnce,4.3549,0.0083,[4.32; 4.39],3.562,0.0155,[3.52; 3.61],0.7929,4550.28,[4530.53; 4570.03],330.2669,[328.83; 331.70]
-mt19937arR,7.4846,0.2383,[7.31; 7.66],7.4828,0.2377,[7.31; 7.66],0.0018,3186.49,[3172.36; 3200.62],397.4934,[395.73; 399.26]
-pytorchTaskset_pytorchTasksetRandomGenerationAtOnce,6.0202,0.0565,[5.94; 6.11],5.3053,0.0250,[5.25; 5.36],0.7149,4348.0241,[4306.74; 4389.30],436.2687,[432.13; 440.41]
-numpyR_numpyRandomGenerationAtOnce,5.773,8.5204,[4.73; 6.82],5.7547,8.4411,[4.71; 6.79],0.0183,5906.645,[5670.16; 6143.13],568.3177,[545.56; 591.07]
-tensorflowTaskset_tensorflowTasksetRandomGenerationAtOnce,8.1807,0.0255,[8.12; 8.24],6.6745,0.0142,[6.63; 6.72],1.5062,4762.63,[4750.04; 4775.22],649.3634,[647.65; 651.08]
-well19937aR,13.0829,0.0004,[13.08; 13.09],13.0806,0.0004,[13.07; 13.09],0.0022,3040.66,[3008.42; 3072.90],663.0092,[655.98; 670.04]
-pcg64O3,10.9984,0.2208,[10.83; 11.17],10.9963,0.2202,[10.83; 11.16],0.0021,3882.55,[3812.37; 3952.73],711.6973,[698.83; 724.56]
-pcg64O2,11.0732,0.1943,[10.92; 11.23],11.072,0.1942,[10.91; 11.23],0.0012,3925.175,[3872.56; 3977.79],724.4019,[714.69; 734.11]
-pytorchR_pytorchRandomGenerationAtOnce,6.9013,0.1639,[6.76; 7.05],7.0107,0.0993,[6.90; 7.12],-0.1094,7141.5,[6891.12; 7391.88],821.4272,[792.63; 850.23]
-numpyMt_numpyMtRandomGenerationAtOnce,13.0826,18.0893,[11.56; 14.60],7.269,0.0916,[7.16; 7.38],5.8136,4358.065,[4168.48; 4547.65],950.2446,[908.91; 991.58]
-pcg64R,13.1803,0.1272,[13.05; 13.31],13.1792,0.1269,[13.05; 13.31],0.0011,4473.0672,[4459.61; 4486.52],982.6086,[979.65; 985.56]
-mrg32k3aO3,19.9659,0.2272,[19.80; 20.14],19.964,0.2271,[19.79; 20.13],0.0019,3000.865,[2941.58; 3060.15],998.5812,[978.85; 1018.31]
-numpyPhilox_numpyPhiloxRandomGenerationAtOnce,13.2558,3.4810,[12.59; 13.92],12.0001,0.0921,[11.89; 12.11],1.2557,5033.005,[4875.79; 5190.22],1111.9446,[1077.21; 1146.68]
-mrg32k3aO2,31.466,0.4949,[31.21; 31.72],31.4628,0.4947,[31.21; 31.71],0.0032,2750.795,[2744.56; 2757.03],1442.6071,[1439.33; 1445.88]
-mrg32k3aR,43.1265,0.2064,[42.96; 43.29],43.1234,0.2063,[42.96; 43.29],0.0031,2783.585,[2744.86; 2822.31],2000.7713,[1972.93; 2028.61]
-pythonR_pythonRandomGenerationOneByOne,36.8693,3.1807,[36.23; 37.51],36.8575,3.1823,[36.22; 37.50],0.0118,3865.7083,[3806.83; 3924.59],2375.4305,[2339.25; 2411.61]
-pythonTaskset_pythonTasksetRandomGenerationAtOnce,69.5241,2.0231,[69.02; 70.03],43.8863,0.4140,[43.66; 44.12],25.6378,3994.895,[3871.83; 4117.96],4629.0247,[4486.43; 4771.62]
-pythonR_pythonRandomGenerationAtOnce,75.4612,90.2587,[72.06; 78.86],48.4789,12.1838,[47.23; 49.73],26.9823,6521.71,[6078.98; 6964.44],8202.2677,[7645.45; 8759.08]
-numpyR_numpyRandomGenerationOneByOne,330.9751,162.8978,[326.41; 335.54],331.8779,162.6531,[327.31; 336.44],-0.9028,5935.289,[5772.42; 6098.16],32740.5509,[31842.13; 33638.98]
-numpyMt_numpyMtRandomGenerationOneByOne,319.8938,26.4842,[318.05; 321.74],320.8309,26.4930,[318.99; 322.67],-0.9371,37375.5517,[36671.35; 38079.75],199270.1419,[195515.66; 203024.62]
-numpyPhilox_numpyPhiloxRandomGenerationOneByOne,323.0621,24.8951,[321.28; 324.85],323.9827,24.7196,[322.20; 325.76],-0.9206,37590.4448,[36613.97; 38566.92],202400.8008,[197143.08; 207658.52]
-pytorchR_pytorchRandomGenerationOneByOne,2388.4092,385.8637,[2381.38; 2395.44],2388.8529,388.1488,[2381.80; 2395.90],-0.4436,5630.9,[5233.18; 6028.62],224148.2259,[208316.06; 239980.39]
diff --git a/result-Csv/results_sorted_by_real_time.csv b/result-Csv/results_sorted_by_real_time.csv
deleted file mode 100644
index 63b5639cd91fe637b0f8b30d71482df74428c1ed..0000000000000000000000000000000000000000
--- a/result-Csv/results_sorted_by_real_time.csv
+++ /dev/null
@@ -1,28 +0,0 @@
-Generator,Real time (s),Real time variance,Real time 95% CI,User time (s),User time variance,User time 95% CI,Difference (Real - User time),Energy consumption (J/min),Energy consumption 95% CI,Energy consumption during real time (J),Energy consumption during real time 95% CI
-tensorflowR_tensorflowRandomGenerationAtOnce,3.3758,0.0683,[3.28; 3.47],32.3289,1.4632,[31.90; 32.76],-28.9531,5131.12,[5100.87; 5161.37],288.6939,[286.99; 290.40]
-mt19937arO3,4.1974,0.1541,[4.06; 4.34],4.196,0.1535,[4.06; 4.34],0.0015,3226.825,[3159.98; 3293.67],225.7397,[221.06; 230.42]
-numpyTaskset_numpyTasksetRandomGenerationAtOnce,4.3549,0.0083,[4.32; 4.39],3.562,0.0155,[3.52; 3.61],0.7929,4550.28,[4530.53; 4570.03],330.2669,[328.83; 331.70]
-mt19937arO2,4.5031,0.2166,[4.34; 4.67],4.5015,0.2157,[4.34; 4.67],0.0017,3179.165,[3168.29; 3190.04],238.6034,[237.79; 239.42]
-well19937O3a,4.9631,0.1009,[4.85; 5.08],4.9612,0.1005,[4.85; 5.07],0.0019,2991.035,[2981.97; 3000.10],247.4118,[246.66; 248.16]
-well19937O2a,4.9749,0.1644,[4.83; 5.12],4.9733,0.1642,[4.83; 5.12],0.0017,2979.415,[2970.81; 2988.02],247.0398,[246.33; 247.75]
-numpyR_numpyRandomGenerationAtOnce,5.773,8.5204,[4.73; 6.82],5.7547,8.4411,[4.71; 6.79],0.0183,5906.645,[5670.16; 6143.13],568.3177,[545.56; 591.07]
-pytorchTaskset_pytorchTasksetRandomGenerationAtOnce,6.0202,0.0565,[5.94; 6.11],5.3053,0.0250,[5.25; 5.36],0.7149,4348.0241,[4306.74; 4389.30],436.2687,[432.13; 440.41]
-pytorchR_pytorchRandomGenerationAtOnce,6.9013,0.1639,[6.76; 7.05],7.0107,0.0993,[6.90; 7.12],-0.1094,7141.5,[6891.12; 7391.88],821.4272,[792.63; 850.23]
-mt19937arR,7.4846,0.2383,[7.31; 7.66],7.4828,0.2377,[7.31; 7.66],0.0018,3186.49,[3172.36; 3200.62],397.4934,[395.73; 399.26]
-tensorflowTaskset_tensorflowTasksetRandomGenerationAtOnce,8.1807,0.0255,[8.12; 8.24],6.6745,0.0142,[6.63; 6.72],1.5062,4762.63,[4750.04; 4775.22],649.3634,[647.65; 651.08]
-pcg64O3,10.9984,0.2208,[10.83; 11.17],10.9963,0.2202,[10.83; 11.16],0.0021,3882.55,[3812.37; 3952.73],711.6973,[698.83; 724.56]
-pcg64O2,11.0732,0.1943,[10.92; 11.23],11.072,0.1942,[10.91; 11.23],0.0012,3925.175,[3872.56; 3977.79],724.4019,[714.69; 734.11]
-numpyMt_numpyMtRandomGenerationAtOnce,13.0826,18.0893,[11.56; 14.60],7.269,0.0916,[7.16; 7.38],5.8136,4358.065,[4168.48; 4547.65],950.2446,[908.91; 991.58]
-well19937aR,13.0829,0.0004,[13.08; 13.09],13.0806,0.0004,[13.07; 13.09],0.0022,3040.66,[3008.42; 3072.90],663.0092,[655.98; 670.04]
-pcg64R,13.1803,0.1272,[13.05; 13.31],13.1792,0.1269,[13.05; 13.31],0.0011,4473.0672,[4459.61; 4486.52],982.6086,[979.65; 985.56]
-numpyPhilox_numpyPhiloxRandomGenerationAtOnce,13.2558,3.4810,[12.59; 13.92],12.0001,0.0921,[11.89; 12.11],1.2557,5033.005,[4875.79; 5190.22],1111.9446,[1077.21; 1146.68]
-mrg32k3aO3,19.9659,0.2272,[19.80; 20.14],19.964,0.2271,[19.79; 20.13],0.0019,3000.865,[2941.58; 3060.15],998.5812,[978.85; 1018.31]
-mrg32k3aO2,31.466,0.4949,[31.21; 31.72],31.4628,0.4947,[31.21; 31.71],0.0032,2750.795,[2744.56; 2757.03],1442.6071,[1439.33; 1445.88]
-pythonR_pythonRandomGenerationOneByOne,36.8693,3.1807,[36.23; 37.51],36.8575,3.1823,[36.22; 37.50],0.0118,3865.7083,[3806.83; 3924.59],2375.4305,[2339.25; 2411.61]
-mrg32k3aR,43.1265,0.2064,[42.96; 43.29],43.1234,0.2063,[42.96; 43.29],0.0031,2783.585,[2744.86; 2822.31],2000.7713,[1972.93; 2028.61]
-pythonTaskset_pythonTasksetRandomGenerationAtOnce,69.5241,2.0231,[69.02; 70.03],43.8863,0.4140,[43.66; 44.12],25.6378,3994.895,[3871.83; 4117.96],4629.0247,[4486.43; 4771.62]
-pythonR_pythonRandomGenerationAtOnce,75.4612,90.2587,[72.06; 78.86],48.4789,12.1838,[47.23; 49.73],26.9823,6521.71,[6078.98; 6964.44],8202.2677,[7645.45; 8759.08]
-numpyMt_numpyMtRandomGenerationOneByOne,319.8938,26.4842,[318.05; 321.74],320.8309,26.4930,[318.99; 322.67],-0.9371,37375.5517,[36671.35; 38079.75],199270.1419,[195515.66; 203024.62]
-numpyPhilox_numpyPhiloxRandomGenerationOneByOne,323.0621,24.8951,[321.28; 324.85],323.9827,24.7196,[322.20; 325.76],-0.9206,37590.4448,[36613.97; 38566.92],202400.8008,[197143.08; 207658.52]
-numpyR_numpyRandomGenerationOneByOne,330.9751,162.8978,[326.41; 335.54],331.8779,162.6531,[327.31; 336.44],-0.9028,5935.289,[5772.42; 6098.16],32740.5509,[31842.13; 33638.98]
-pytorchR_pytorchRandomGenerationOneByOne,2388.4092,385.8637,[2381.38; 2395.44],2388.8529,388.1488,[2381.80; 2395.90],-0.4436,5630.9,[5233.18; 6028.62],224148.2259,[208316.06; 239980.39]
diff --git a/result-Csv/results_sorted_by_user_time.csv b/result-Csv/results_sorted_by_user_time.csv
deleted file mode 100644
index d3feadedc054d178ae8fec3c5d45d4f4ef8501d1..0000000000000000000000000000000000000000
--- a/result-Csv/results_sorted_by_user_time.csv
+++ /dev/null
@@ -1,28 +0,0 @@
-Generator,Real time (s),Real time variance,Real time 95% CI,User time (s),User time variance,User time 95% CI,Difference (Real - User time),Energy consumption (J/min),Energy consumption 95% CI,Energy consumption during real time (J),Energy consumption during real time 95% CI
-numpyTaskset_numpyTasksetRandomGenerationAtOnce,4.3549,0.0083,[4.32; 4.39],3.562,0.0155,[3.52; 3.61],0.7929,4550.28,[4530.53; 4570.03],330.2669,[328.83; 331.70]
-mt19937arO3,4.1974,0.1541,[4.06; 4.34],4.196,0.1535,[4.06; 4.34],0.0015,3226.825,[3159.98; 3293.67],225.7397,[221.06; 230.42]
-mt19937arO2,4.5031,0.2166,[4.34; 4.67],4.5015,0.2157,[4.34; 4.67],0.0017,3179.165,[3168.29; 3190.04],238.6034,[237.79; 239.42]
-well19937O3a,4.9631,0.1009,[4.85; 5.08],4.9612,0.1005,[4.85; 5.07],0.0019,2991.035,[2981.97; 3000.10],247.4118,[246.66; 248.16]
-well19937O2a,4.9749,0.1644,[4.83; 5.12],4.9733,0.1642,[4.83; 5.12],0.0017,2979.415,[2970.81; 2988.02],247.0398,[246.33; 247.75]
-pytorchTaskset_pytorchTasksetRandomGenerationAtOnce,6.0202,0.0565,[5.94; 6.11],5.3053,0.0250,[5.25; 5.36],0.7149,4348.0241,[4306.74; 4389.30],436.2687,[432.13; 440.41]
-numpyR_numpyRandomGenerationAtOnce,5.773,8.5204,[4.73; 6.82],5.7547,8.4411,[4.71; 6.79],0.0183,5906.645,[5670.16; 6143.13],568.3177,[545.56; 591.07]
-tensorflowTaskset_tensorflowTasksetRandomGenerationAtOnce,8.1807,0.0255,[8.12; 8.24],6.6745,0.0142,[6.63; 6.72],1.5062,4762.63,[4750.04; 4775.22],649.3634,[647.65; 651.08]
-pytorchR_pytorchRandomGenerationAtOnce,6.9013,0.1639,[6.76; 7.05],7.0107,0.0993,[6.90; 7.12],-0.1094,7141.5,[6891.12; 7391.88],821.4272,[792.63; 850.23]
-numpyMt_numpyMtRandomGenerationAtOnce,13.0826,18.0893,[11.56; 14.60],7.269,0.0916,[7.16; 7.38],5.8136,4358.065,[4168.48; 4547.65],950.2446,[908.91; 991.58]
-mt19937arR,7.4846,0.2383,[7.31; 7.66],7.4828,0.2377,[7.31; 7.66],0.0018,3186.49,[3172.36; 3200.62],397.4934,[395.73; 399.26]
-pcg64O3,10.9984,0.2208,[10.83; 11.17],10.9963,0.2202,[10.83; 11.16],0.0021,3882.55,[3812.37; 3952.73],711.6973,[698.83; 724.56]
-pcg64O2,11.0732,0.1943,[10.92; 11.23],11.072,0.1942,[10.91; 11.23],0.0012,3925.175,[3872.56; 3977.79],724.4019,[714.69; 734.11]
-numpyPhilox_numpyPhiloxRandomGenerationAtOnce,13.2558,3.4810,[12.59; 13.92],12.0001,0.0921,[11.89; 12.11],1.2557,5033.005,[4875.79; 5190.22],1111.9446,[1077.21; 1146.68]
-well19937aR,13.0829,0.0004,[13.08; 13.09],13.0806,0.0004,[13.07; 13.09],0.0022,3040.66,[3008.42; 3072.90],663.0092,[655.98; 670.04]
-pcg64R,13.1803,0.1272,[13.05; 13.31],13.1792,0.1269,[13.05; 13.31],0.0011,4473.0672,[4459.61; 4486.52],982.6086,[979.65; 985.56]
-mrg32k3aO3,19.9659,0.2272,[19.80; 20.14],19.964,0.2271,[19.79; 20.13],0.0019,3000.865,[2941.58; 3060.15],998.5812,[978.85; 1018.31]
-mrg32k3aO2,31.466,0.4949,[31.21; 31.72],31.4628,0.4947,[31.21; 31.71],0.0032,2750.795,[2744.56; 2757.03],1442.6071,[1439.33; 1445.88]
-tensorflowR_tensorflowRandomGenerationAtOnce,3.3758,0.0683,[3.28; 3.47],32.3289,1.4632,[31.90; 32.76],-28.9531,5131.12,[5100.87; 5161.37],288.6939,[286.99; 290.40]
-pythonR_pythonRandomGenerationOneByOne,36.8693,3.1807,[36.23; 37.51],36.8575,3.1823,[36.22; 37.50],0.0118,3865.7083,[3806.83; 3924.59],2375.4305,[2339.25; 2411.61]
-mrg32k3aR,43.1265,0.2064,[42.96; 43.29],43.1234,0.2063,[42.96; 43.29],0.0031,2783.585,[2744.86; 2822.31],2000.7713,[1972.93; 2028.61]
-pythonTaskset_pythonTasksetRandomGenerationAtOnce,69.5241,2.0231,[69.02; 70.03],43.8863,0.4140,[43.66; 44.12],25.6378,3994.895,[3871.83; 4117.96],4629.0247,[4486.43; 4771.62]
-pythonR_pythonRandomGenerationAtOnce,75.4612,90.2587,[72.06; 78.86],48.4789,12.1838,[47.23; 49.73],26.9823,6521.71,[6078.98; 6964.44],8202.2677,[7645.45; 8759.08]
-numpyMt_numpyMtRandomGenerationOneByOne,319.8938,26.4842,[318.05; 321.74],320.8309,26.4930,[318.99; 322.67],-0.9371,37375.5517,[36671.35; 38079.75],199270.1419,[195515.66; 203024.62]
-numpyPhilox_numpyPhiloxRandomGenerationOneByOne,323.0621,24.8951,[321.28; 324.85],323.9827,24.7196,[322.20; 325.76],-0.9206,37590.4448,[36613.97; 38566.92],202400.8008,[197143.08; 207658.52]
-numpyR_numpyRandomGenerationOneByOne,330.9751,162.8978,[326.41; 335.54],331.8779,162.6531,[327.31; 336.44],-0.9028,5935.289,[5772.42; 6098.16],32740.5509,[31842.13; 33638.98]
-pytorchR_pytorchRandomGenerationOneByOne,2388.4092,385.8637,[2381.38; 2395.44],2388.8529,388.1488,[2381.80; 2395.90],-0.4436,5630.9,[5233.18; 6028.62],224148.2259,[208316.06; 239980.39]
diff --git a/result-Csv/results_with_all_confidence_intervals.csv b/result-Csv/results_with_all_confidence_intervals.csv
deleted file mode 100644
index bae21bf92ff829e1b1fc53b822468410df9a684c..0000000000000000000000000000000000000000
--- a/result-Csv/results_with_all_confidence_intervals.csv
+++ /dev/null
@@ -1,28 +0,0 @@
-Generator,Real time (s),Real time variance,Real time 95% CI,User time (s),User time variance,User time 95% CI,Difference (Real - User time),Energy consumption (J/min),Energy consumption 95% CI,Energy consumption during real time (J),Energy consumption during real time 95% CI
-mrg32k3aO2,31.46596666666667,0.49491024022988495,[31.21; 31.72],31.462766666666667,0.4947381160919544,[31.21; 31.71],0.0032000000000032003,2750.7950000000005,[2744.56; 2757.03],1442.6070629472226,[1439.33; 1445.88]
-mrg32k3aO3,19.965866666666674,0.2272254988505746,[19.80; 20.14],19.964000000000002,0.2270607586206895,[19.79; 20.13],0.0018666666666717902,3000.865,[2941.58; 3060.15],998.5811745777781,[978.85; 1018.31]
-mrg32k3aR,43.1265,0.20636770689655226,[42.96; 43.29],43.12336666666667,0.206296791954023,[42.96; 43.29],0.003133333333330768,2783.585,[2744.86; 2822.31],2000.7713083750002,[1972.93; 2028.61]
-mt19937arO2,4.503133333333334,0.21657274022988496,[4.34; 4.67],4.501466666666667,0.21569949885057468,[4.34; 4.67],0.0016666666666669272,3179.1649999999995,[3168.29; 3190.04],238.60339806111114,[237.79; 239.42]
-mt19937arO3,4.197433333333333,0.15405777126436782,[4.06; 4.34],4.195966666666667,0.15353389540229886,[4.06; 4.34],0.001466666666665617,3226.824999999999,[3159.98; 3293.67],225.7397135972221,[221.06; 230.42]
-mt19937arR,7.4846,0.23828914482758615,[7.31; 7.66],7.482766666666666,0.237718116091954,[7.31; 7.66],0.0018333333333346857,3186.49,[3172.36; 3200.62],397.49338423333336,[395.73; 399.26]
-numpyMt_numpyMtRandomGenerationAtOnce,13.082566666666668,18.089264460919544,[11.56; 14.60],7.268966666666667,0.09162589540229887,[7.16; 7.38],5.813600000000002,4358.065,[4168.48; 4547.65],950.2445983361112,[908.91; 991.58]
-numpyMt_numpyMtRandomGenerationOneByOne,319.89383333333325,26.484203660919537,[318.05; 321.74],320.8309,26.49299429999996,[318.99; 322.67],-0.9370666666667375,37375.55172413793,[36671.35; 38079.75],199270.1418997126,[195515.66; 203024.62]
-numpyPhilox_numpyPhiloxRandomGenerationAtOnce,13.255833333333332,3.4810100057471263,[12.59; 13.92],12.000133333333336,0.0920814988505747,[11.89; 12.11],1.2556999999999956,5033.005,[4875.79; 5190.22],1111.9445907638888,[1077.21; 1146.68]
-numpyPhilox_numpyPhiloxRandomGenerationOneByOne,323.06210000000004,24.89505278275862,[321.28; 324.85],323.9827333333333,24.71960661609191,[322.20; 325.76],-0.9206333333332282,37590.444827586194,[36613.97; 38566.92],202400.8007655689,[197143.08; 207658.52]
-numpyR_numpyRandomGenerationAtOnce,5.773,8.520403655172414,[4.73; 6.82],5.754666666666666,8.441070505747126,[4.71; 6.79],0.018333333333333535,5906.645,[5670.16; 6143.13],568.3176930833333,[545.56; 591.07]
-numpyR_numpyRandomGenerationOneByOne,330.97513333333336,162.89779818850576,[326.41; 335.54],331.8779333333333,162.6530534436781,[327.31; 336.44],-0.9027999999999565,5935.288965517241,[5772.42; 6098.16],32740.55094556552,[31842.13; 33638.98]
-numpyTaskset_numpyTasksetRandomGenerationAtOnce,4.354899999999999,0.008284920689655164,[4.32; 4.39],3.562033333333334,0.01548003333333333,[3.52; 3.61],0.792866666666665,4550.28,[4530.53; 4570.03],330.2669061999999,[328.83; 331.70]
-pcg64O2,11.073166666666669,0.19433441954022995,[10.92; 11.23],11.071966666666667,0.19419824022988502,[10.91; 11.23],0.0012000000000025324,3925.1749999999993,[3872.56; 3977.79],724.4019495138889,[714.69; 734.11]
-pcg64O3,10.9984,0.22081838620689676,[10.83; 11.17],10.996300000000003,0.2202073896551725,[10.83; 11.16],0.002099999999996882,3882.5499999999997,[3812.37; 3952.73],711.6972986666666,[698.83; 724.56]
-pcg64R,13.180333333333333,0.12721698850574706,[13.05; 13.31],13.179233333333334,0.12687735747126433,[13.05; 13.31],0.0010999999999992127,4473.06724137931,[4459.61; 4486.52],982.6086210632183,[979.65; 985.56]
-pythonR_pythonRandomGenerationAtOnce,75.4612,90.25866609655172,[72.06; 78.86],48.47893333333333,12.18376565057471,[47.23; 49.73],26.982266666666675,6521.71,[6078.98; 6964.44],8202.267710866668,[7645.45; 8759.08]
-pythonR_pythonRandomGenerationOneByOne,36.86926666666667,3.180715719540231,[36.23; 37.51],36.8575,3.182281913793104,[36.22; 37.50],0.011766666666666481,3865.7082758620686,[3806.83; 3924.59],2375.4304879716474,[2339.25; 2411.61]
-pythonTaskset_pythonTasksetRandomGenerationAtOnce,69.5241,2.023144575862068,[69.02; 70.03],43.88626666666667,0.41396227126436735,[43.66; 44.12],25.637833333333333,3994.8950000000004,[3871.83; 4117.96],4629.024657825001,[4486.43; 4771.62]
-pytorchR_pytorchRandomGenerationAtOnce,6.9013,0.16385980344827578,[6.76; 7.05],7.010666666666667,0.09930485057471261,[6.90; 7.12],-0.10936666666666728,7141.5,[6891.12; 7391.88],821.4272325,[792.63; 850.23]
-pytorchR_pytorchRandomGenerationOneByOne,2388.4092333333333,385.8636750126419,[2381.38; 2395.44],2388.8528666666666,388.14882956781724,[2381.80; 2395.90],-0.44363333333330957,5630.9,[5233.18; 6028.62],224148.22586627776,[208316.06; 239980.39]
-pytorchTaskset_pytorchTasksetRandomGenerationAtOnce,6.020233333333334,0.056457771264367844,[5.94; 6.11],5.3053,0.02500014827586207,[5.25; 5.36],0.7149333333333345,4348.024137931035,[4306.74; 4389.30],436.26866415517253,[432.13; 440.41]
-tensorflowR_tensorflowRandomGenerationAtOnce,3.3758,0.06826740689655171,[3.28; 3.47],32.3289,1.463164851724137,[31.90; 32.76],-28.9531,5131.120000000001,[5100.87; 5161.37],288.69391493333336,[286.99; 290.40]
-tensorflowTaskset_tensorflowTasksetRandomGenerationAtOnce,8.180733333333333,0.02550523678160922,[8.12; 8.24],6.674499999999998,0.01418743103448277,[6.63; 6.72],1.5062333333333342,4762.630000000001,[4750.04; 4775.22],649.3634332555557,[647.65; 651.08]
-well19937O2a,4.974933333333334,0.1644335126436781,[4.83; 5.12],4.9732666666666665,0.16416151264367818,[4.83; 5.12],0.0016666666666678154,2979.4150000000004,[2970.81; 2988.02],247.03984995555564,[246.33; 247.75]
-well19937O3a,4.963066666666665,0.10090089195402302,[4.85; 5.08],4.9612,0.10049961379310347,[4.85; 5.07],0.001866666666665573,2991.035,[2981.97; 3000.10],247.41176845555546,[246.66; 248.16]
-well19937aR,13.082866666666668,0.00039618850574712724,[13.08; 13.09],13.080633333333333,0.00042961954022987576,[13.07; 13.09],0.0022333333333346417,3040.6600000000003,[3008.42; 3072.90],663.0091559777778,[655.98; 670.04]
diff --git a/result-Csv/results_with_formatted_confidence_intervals.csv b/result-Csv/results_with_formatted_confidence_intervals.csv
deleted file mode 100644
index b28b716c244180a6c05721456d405170a192f34c..0000000000000000000000000000000000000000
--- a/result-Csv/results_with_formatted_confidence_intervals.csv
+++ /dev/null
@@ -1,21 +0,0 @@
-Generator,Real time (s),Real time variance,Real time 95% CI,User time (s),User time variance,User time 95% CI,Difference (Real - User time),Energy consumption (J/min),Energy consumption 95% CI,Energy consumption during real time (J)
-mt19937arIntegerO2,4.743366666666668,0.03560927471264366,[4.68; 4.81],4.7386,0.03539273103448277,[4.67; 4.81],0.004766666666667696,3323.89,[3226.38; 3421.40],262.7738171611112
-mt19937arIntegerO3,4.292333333333333,0.11800464367816095,[4.17; 4.42],4.290366666666667,0.11791086091954024,[4.17; 4.41],0.00196666666666534,3607.7349999999997,[3476.79; 3738.68],258.09335330555547
-mt19937arIntegerR,7.101000000000001,0.16065758620689644,[6.96; 7.24],7.097499999999998,0.15948515517241377,[6.95; 7.24],0.003500000000002501,3419.125,[3285.98; 3552.27],404.65344375000006
-numpyIntegerMt_numpyIntegerMtRandomGenerationAtOnce,4.551866666666666,0.1308721885057471,[4.42; 4.68],5.146533333333333,0.11990411954022988,[5.02; 5.27],-0.5946666666666669,4847.665,[4828.75; 4866.58],367.76541207777774
-numpyIntegerMt_numpyIntegerMtRandomGenerationOneByOne,6327.762666666665,77323.71811471261,[6228.26; 6427.27],6328.496200000002,77348.20327120001,[6228.97; 6428.02],-0.7335333333376184,45223.56206896552,[42623.11; 47824.02],4769399.4618947115
-numpyIntegerPhilox_numpyIntegerPhiloxRandomGenerationAtOnce,6.772866666666665,0.15895742988505743,[6.63; 6.92],7.369800000000001,0.16249402758620698,[7.23; 7.51],-0.596933333333336,4849.215,[4829.80; 4868.63],547.3847772166665
-numpyIntegerPhilox_numpyIntegerPhiloxRandomGenerationOneByOne,6552.208433333333,49609.537693771235,[6472.50; 6631.91],6553.128133333333,49627.2739763954,[6473.41; 6632.85],-0.919699999999466,64212.808928571416,[61111.12; 67314.50],7012261.80316346
-numpyIntegerR_numpyIntegerRandomGenerationAtOnce,3.4213333333333336,0.2778338850574712,[3.23; 3.61],3.9793333333333334,0.24018078160919537,[3.80; 4.15],-0.5579999999999998,4688.14,[4669.67; 4706.61],267.32816088888893
-numpyIntegerR_numpyIntegerRandomGenerationOneByOne,6458.611266666666,29731.226886891945,[6396.91; 6520.31],6459.4995,29756.44412901723,[6397.77; 6521.23],-0.8882333333340284,5925.941379310343,[5579.41; 6272.47],637889.1959669997
-numpyIntegerTaskset_numpyIntegerTasksetRandomGenerationAtOnce,2.598366666666666,0.00010134367816091952,[2.59; 2.60],2.2034333333333334,0.0023462540229885033,[2.19; 2.22],0.39493333333333247,4766.348275862068,[4747.59; 4785.10],206.4120080287355
-pcg32IntegerR,2.452033333333333,0.2623192057471264,[2.27; 2.64],2.4505,0.2614450172413793,[2.27; 2.63],0.0015333333333331645,3209.7,[3185.35; 3234.05],131.17152316666665
-philoxIntegerR,90.06043333333334,0.8233662540229879,[89.74; 90.39],90.0577666666667,0.8211610816091908,[89.73; 90.38],0.002666666666641504,4845.4800000000005,[4824.15; 4866.81],7273.100475133334
-pythonIntegerR_pythonIntegerRandomGenerationAtOnce,489.0244666666667,23.150945222988522,[487.30; 490.75],453.2894333333334,15.438946047126404,[451.88; 454.70],35.73503333333326,4375.205,[4110.53; 4639.88],35659.70486137222
-pythonIntegerR_pythonIntegerRandomGenerationOneByOne,425.9194333333333,21.97728259885056,[424.24; 427.60],425.9053666666667,21.98476644712646,[424.23; 427.58],0.01406666666662204,5410.519310344826,[5185.95; 5635.09],38407.4219783521
-pythonIntegerTaskset_pythonIntegerTasksetRandomGenerationAtOnce,486.1138333333333,30.353489867816105,[484.14; 488.09],452.9372333333333,20.35909349540229,[451.32; 454.55],33.17659999999995,4298.715,[4260.00; 4337.43],34827.747117625004
-pytorchIntegerR_pytorchIntegerRandomGenerationAtOnce,9.086766666666668,0.07867397816091957,[8.99; 9.19],8.931566666666665,0.04828694367816087,[8.85; 9.01],0.15520000000000245,4812.527586206897,[4775.33; 4849.73],728.838587545977
-pytorchIntegerR_pytorchIntegerRandomGenerationOneByOne,2281.7916,8409.516744662069,[2248.98; 2314.61],2282.3334000000004,8415.962512386206,[2249.51; 2315.16],-0.5418000000004213,8846.437142857145,[8492.64; 9200.24],336428.7660416572
-pytorchIntegerTaskset_pytorchIntegerTasksetRandomGenerationAtOnce,8.062233333333332,0.031242254022988518,[8.00; 8.13],7.119666666666666,0.02589919540229886,[7.06; 7.18],0.9425666666666652,4766.960000000002,[4748.06; 4785.86],640.5390635111112
-tensorflowIntegerR_tensorflowIntegerRandomGenerationAtOnce,3.2186333333333335,0.00778065402298851,[3.19; 3.25],17.890566666666665,0.2898039091954021,[17.70; 18.08],-14.671933333333332,4893.7241379310335,[4862.41; 4925.04],262.51839390804594
-tensorflowIntegerTaskset_tensorflowIntegerTasksetRandomGenerationAtOnce,7.082533333333333,0.014976671264367818,[7.04; 7.13],6.230566666666666,0.009662047126436776,[6.20; 6.27],0.8519666666666668,4800.250000000001,[4784.14; 4816.36],566.6321772222223
diff --git a/result-Csv/sorted_by_Real_Time.csv b/result-Csv/sorted_by_Real_Time.csv
deleted file mode 100644
index 8a062e98d6a440edc6580bbdd598599134f80b0f..0000000000000000000000000000000000000000
--- a/result-Csv/sorted_by_Real_Time.csv
+++ /dev/null
@@ -1,11 +0,0 @@
-File,Real Time,User Time,Sys Time
-timeNumpySaving.txt,170.6,33.1,137.3
-timePytorchSaving.txt,176.2,43.2,132.5
-timeNumpyMtSaving.txt,177.5,48.4,128.6
-timeNumpyPhiloxSaving.txt,231.9,96.7,135.0
-timeMtSaving.txt,281.8,126.0,154.4
-timeWellSaving.txt,283.0,127.4,155.2
-timeTensorflowSaving.txt,288.8,1893.2,393.4
-timePcgSaving.txt,346.8,185.8,160.6
-timeMrgSaving.txt,449.9,307.2,142.2
-timePythonSaving.txt,1355.8,1218.5,136.7
diff --git a/result-Csv/sorted_by_Sys_Time.csv b/result-Csv/sorted_by_Sys_Time.csv
deleted file mode 100644
index 6016e366620e70cc518ad28a3646a270035ae294..0000000000000000000000000000000000000000
--- a/result-Csv/sorted_by_Sys_Time.csv
+++ /dev/null
@@ -1,11 +0,0 @@
-File,Real Time,User Time,Sys Time
-timeNumpyMtSaving.txt,177.5,48.4,128.6
-timePytorchSaving.txt,176.2,43.2,132.5
-timeNumpyPhiloxSaving.txt,231.9,96.7,135.0
-timePythonSaving.txt,1355.8,1218.5,136.7
-timeNumpySaving.txt,170.6,33.1,137.3
-timeMrgSaving.txt,449.9,307.2,142.2
-timeMtSaving.txt,281.8,126.0,154.4
-timeWellSaving.txt,283.0,127.4,155.2
-timePcgSaving.txt,346.8,185.8,160.6
-timeTensorflowSaving.txt,288.8,1893.2,393.4
diff --git a/result-Csv/sorted_by_User_Time.csv b/result-Csv/sorted_by_User_Time.csv
deleted file mode 100644
index 2c4d671fdd0c687cc02bd42098052b1c66fc6d21..0000000000000000000000000000000000000000
--- a/result-Csv/sorted_by_User_Time.csv
+++ /dev/null
@@ -1,11 +0,0 @@
-File,Real Time,User Time,Sys Time
-timeNumpySaving.txt,170.6,33.1,137.3
-timePytorchSaving.txt,176.2,43.2,132.5
-timeNumpyMtSaving.txt,177.5,48.4,128.6
-timeNumpyPhiloxSaving.txt,231.9,96.7,135.0
-timeMtSaving.txt,281.8,126.0,154.4
-timeWellSaving.txt,283.0,127.4,155.2
-timePcgSaving.txt,346.8,185.8,160.6
-timeMrgSaving.txt,449.9,307.2,142.2
-timePythonSaving.txt,1355.8,1218.5,136.7
-timeTensorflowSaving.txt,288.8,1893.2,393.4