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testrandom.C File Reference

Detailed Description

View in nbviewer Open in SWAN Performance test of all the ROOT random generator (TRandom, TRandom1, TRandom2 and TRandom3) Tests the generator TRandom3 against some ref values and creates a timing table against TRandom, TRandom1 and TRandom2.

E.g. on an an Intel Xeon Quad-core Harpertown (E5410) 2.33 GHz running Linux SLC4 64 bit and compiled with gcc 3.4

Distribution nanoseconds/call
Rndm.............. 5.000 105.000 7.000 10.000
RndmArray......... 4.000 104.000 6.000 9.000
Gaus.............. 36.000 180.000 40.000 48.000
Rannor............ 118.000 220.000 120.000 124.000
Landau............ 22.000 123.000 26.000 31.000
Exponential....... 93.000 198.000 98.000 104.000
Binomial(5,0.5)... 30.000 548.000 46.000 65.000
Binomial(15,0.5).. 75.000 1615.000 125.000 178.000
Poisson(3)........ 96.000 494.000 109.000 125.000
Poisson(10)....... 138.000 1236.000 165.000 203.000
Poisson(70)....... 818.000 1195.000 835.000 844.000
Poisson(100)...... 837.000 1218.000 849.000 864.000
GausTF1........... 83.000 180.000 87.000 88.000
LandauTF1......... 80.000 180.000 83.000 86.000
GausUNURAN........ 40.000 139.000 41.000 44.000
PoissonUNURAN(10). 85.000 271.000 92.000 102.000
PoissonUNURAN(100) 62.000 256.000 69.000 78.000
The Ranlux Random number generator class.
Definition TRandom1.h:27
Random number generator class based on the maximally quidistributed combined Tausworthe generator by ...
Definition TRandom2.h:27
Random number generator class based on M.
Definition TRandom3.h:27
This is the base class for the ROOT Random number generators.
Definition TRandom.h:27

Note that this tutorial can be executed in interpreted or compiled mode

Root > .x testrandom.C
Root > .x testrandom.C++
Distribution nanoseconds/call
TRandom TRandom1 TRandom2 TRandom3 MixMax240 MixMax17 Mixmax256_0 MixMax256_2 MixMax256_4 MT_64 Ranlux48
Rndm.............. 5.000 100.000 5.000 5.000 10.000 15.000 10.000 30.000 35.000 25.000 200.000
RndmArray......... 0.000 100.000 5.000 5.000 5.000 10.000 10.000 25.000 35.000 20.000 200.000
Gaus.............. 25.000 150.000 25.000 35.000 35.000 40.000 40.000 60.000 80.000 40.000
Rannor............ 30.000 100.000 30.000 30.000 30.000 35.000 35.000 55.000 60.000 45.000
Landau............ 15.000 100.000 15.000 20.000
Exponential....... 15.000 100.000 15.000 20.000
Binomial(5,0.5)... 20.000 400.000 30.000 35.000
Binomial(15,0.5).. 60.000 1250.000 80.000 80.000
Poisson(3)........ 45.000 350.000 50.000 50.000
Poisson(10)....... 75.000 900.000 80.000 90.000
Poisson(70)....... 245.000 550.000 260.000 260.000
Poisson(100)...... 245.000 550.000 260.000 260.000
GausTF1........... 50.000 130.000 50.000 55.000
LandauTF1......... 50.000 130.000 50.000 55.000
GausUNURAN........ 20.000 100.000 25.000 20.000
PoissonUNURAN(10). 50.000 195.000 50.000 55.000
PoissonUNURAN(100) 45.000 195.000 50.000 50.000
#include <TRandom1.h>
#include <TRandom2.h>
#include <TRandom3.h>
#include <TRandomGen.h>
#include <TStopwatch.h>
#include <TF1.h>
#include <TUnuran.h>
#include <TFile.h>
void testAll() {
int i, N = 2000000;
float cpn = 1000000000./N;
int N1 = N/10; float cpn1 = cpn*10; // for TRandom1
double x,y;
TRandom *rsave = gRandom;
TRandom *r0 = new TRandom();
TRandom *r1 = new TRandom1();
TRandom *r2 = new TRandom2();
TRandom *r3 = new TRandom3();
TRandom *r4 = new TRandomMixMax();
TRandom *r5 = new TRandomMixMax17();
TRandom *r9 = new TRandomMT64();
TRandom *r10 = new TRandomRanlux48();
printf("Distribution nanoseconds/call\n");
printf(" TRandom TRandom1 TRandom2 TRandom3 MixMax240 MixMax17 Mixmax256_0 MixMax256_2 MixMax256_4 MT_64 Ranlux48\n");
sw.Start();
for (i=0;i<N;i++) {
x = r0->Rndm(i);
}
printf("Rndm.............. %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N1;i++) {
x = r1->Rndm(i);
}
printf(" %8.3f",sw.CpuTime()*cpn1);
sw.Start();
for (i=0;i<N;i++) {
x = r2->Rndm(i);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = r3->Rndm(i);
}
printf(" %8.3f",sw.CpuTime()*cpn);
// new random generators
sw.Start();
for (i=0;i<N;i++) {
x = r4->Rndm(i);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = r5->Rndm(i);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = r6->Rndm(i);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = r7->Rndm(i);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = r8->Rndm(i);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = r9->Rndm(i);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N1;i++) {
x = r10->Rndm(i);
}
printf(" %8.3f",sw.CpuTime()*cpn1);
printf("\n\n");
// RNDMARRAY
const int NR = 1000;
double rn[NR];
sw.Start();
for (i=0;i<N;i+=NR) {
r0->RndmArray(NR,rn);
}
printf("RndmArray......... %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N1;i+=NR) {
r1->RndmArray(NR,rn);
}
printf(" %8.3f",sw.CpuTime()*cpn1);
sw.Start();
for (i=0;i<N;i+=NR) {
r2->RndmArray(NR,rn);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i+=NR) {
r3->RndmArray(NR,rn);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i+=NR) {
r4->RndmArray(NR,rn);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i+=NR) {
r5->RndmArray(NR,rn);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i+=NR) {
r6->RndmArray(NR,rn);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i+=NR) {
r7->RndmArray(NR,rn);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i+=NR) {
r8->RndmArray(NR,rn);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i+=NR) {
r9->RndmArray(NR,rn);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N1;i+=NR) {
r10->RndmArray(NR,rn);
}
printf(" %8.3f\n",sw.CpuTime()*cpn1);
// Gaus
sw.Start();
for (i=0;i<N;i++) {
x = r0->Gaus(0,1);
}
printf("Gaus.............. %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N1;i++) {
x = r1->Gaus(0,1);
}
printf(" %8.3f",sw.CpuTime()*cpn1);
sw.Start();
for (i=0;i<N;i++) {
x = r2->Gaus(0,1);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = r3->Gaus(0,1);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = r4->Gaus(0,1);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = r5->Gaus(0,1);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = r6->Gaus(0,1);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = r7->Gaus(0,1);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = r8->Gaus(0,1);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = r9->Gaus(0,1);
}
printf(" %8.3f\n",sw.CpuTime()*cpn);
// RANNOR
sw.Start();
for (i=0;i<N;i+=2) {
r0->Rannor(x,y);
}
printf("Rannor............ %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N1;i+=2) {
r1->Rannor(x,y);
}
printf(" %8.3f",sw.CpuTime()*cpn1);
sw.Start();
for (i=0;i<N;i+=2) {
r2->Rannor(x,y);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i+=2) {
r3->Rannor(x,y);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i+=2) {
r4->Rannor(x,y);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i+=2) {
r5->Rannor(x,y);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i+=2) {
r6->Rannor(x,y);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i+=2) {
r7->Rannor(x,y);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i+=2) {
r8->Rannor(x,y);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i+=2) {
r9->Rannor(x,y);
}
printf(" %8.3f\n",sw.CpuTime()*cpn);
// Landau
sw.Start();
for (i=0;i<N;i++) {
x = r0->Landau(0,1);
}
printf("Landau............ %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N1;i++) {
x = r1->Landau(0,1);
}
printf(" %8.3f",sw.CpuTime()*cpn1);
sw.Start();
for (i=0;i<N;i++) {
x = r2->Landau(0,1);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = r3->Landau(0,1);
}
printf(" %8.3f\n",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = r0->Exp(1);
}
printf("Exponential....... %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N1;i++) {
x = r1->Exp(1);
}
printf(" %8.3f",sw.CpuTime()*cpn1);
sw.Start();
for (i=0;i<N;i++) {
x = r2->Exp(1);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = r3->Exp(1);
}
printf(" %8.3f\n",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = r0->Binomial(5,0.5);
}
printf("Binomial(5,0.5)... %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N1;i++) {
x = r1->Binomial(5,0.5);
}
printf(" %8.3f",sw.CpuTime()*cpn1);
sw.Start();
for (i=0;i<N;i++) {
x = r2->Binomial(5,0.5);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = r3->Binomial(5,0.5);
}
printf(" %8.3f\n",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = r0->Binomial(15,0.5);
}
printf("Binomial(15,0.5).. %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N1;i++) {
x = r1->Binomial(15,0.5);
}
printf(" %8.3f",sw.CpuTime()*cpn1);
sw.Start();
for (i=0;i<N;i++) {
x = r2->Binomial(15,0.5);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = r3->Binomial(15,0.5);
}
printf(" %8.3f\n",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = r0->Poisson(3);
}
printf("Poisson(3)........ %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N1;i++) {
x = r1->Poisson(3);
}
printf(" %8.3f",sw.CpuTime()*cpn1);
sw.Start();
for (i=0;i<N;i++) {
x = r2->Poisson(3);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = r3->Poisson(3);
}
printf(" %8.3f\n",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = r0->Poisson(10);
}
printf("Poisson(10)....... %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N1;i++) {
x = r1->Poisson(10);
}
printf(" %8.3f",sw.CpuTime()*cpn1);
sw.Start();
for (i=0;i<N;i++) {
x = r2->Poisson(10);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = r3->Poisson(10);
}
printf(" %8.3f\n",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = r0->Poisson(70);
}
printf("Poisson(70)....... %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N1;i++) {
x = r1->Poisson(70);
}
printf(" %8.3f",sw.CpuTime()*cpn1);
sw.Start();
for (i=0;i<N;i++) {
x = r2->Poisson(70);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = r3->Poisson(70);
}
printf(" %8.3f\n",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = r0->Poisson(100);
}
printf("Poisson(100)...... %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N1;i++) {
x = r1->Poisson(100);
}
printf(" %8.3f",sw.CpuTime()*cpn1);
sw.Start();
for (i=0;i<N;i++) {
x = r2->Poisson(100);
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = r3->Poisson(100);
}
printf(" %8.3f\n",sw.CpuTime()*cpn);
TF1 *f1 = new TF1("f1","gaus",-4,4);
f1->SetParameters(1,0,1);
gRandom = r0;
sw.Start();
for (i=0;i<N;i++) {
x = f1->GetRandom();
}
printf("GausTF1........... %8.3f",sw.CpuTime()*cpn);
gRandom = r1;
sw.Start();
for (i=0;i<N;i++) {
x = f1->GetRandom();
}
printf(" %8.3f",sw.CpuTime()*cpn);
gRandom = r2;
sw.Start();
for (i=0;i<N;i++) {
x = f1->GetRandom();
}
printf(" %8.3f",sw.CpuTime()*cpn);
gRandom = r3;
sw.Start();
for (i=0;i<N;i++) {
x = f1->GetRandom();
}
printf(" %8.3f\n",sw.CpuTime()*cpn);
TF1 *f2 = new TF1("f2","landau",-5,15);
f2->SetParameters(1,0,1);
gRandom = r0;
sw.Start();
for (i=0;i<N;i++) {
x = f2->GetRandom();
}
printf("LandauTF1......... %8.3f",sw.CpuTime()*cpn);
gRandom = r1;
sw.Start();
for (i=0;i<N;i++) {
x = f2->GetRandom();
}
printf(" %8.3f",sw.CpuTime()*cpn);
gRandom = r2;
sw.Start();
for (i=0;i<N;i++) {
x = f2->GetRandom();
}
printf(" %8.3f",sw.CpuTime()*cpn);
gRandom = r3;
sw.Start();
for (i=0;i<N;i++) {
x = f2->GetRandom();
}
printf(" %8.3f\n",sw.CpuTime()*cpn);
// test using Unuran
TUnuran unr0(r0);
TUnuran unr1(r1);
TUnuran unr2(r2);
TUnuran unr3(r3);
// continuous distribution (ex. Gaus)
// use arou method (is probably the fastest)
unr0.Init(dist,"arou");
unr1.Init(dist,"arou");
unr2.Init(dist,"arou");
unr3.Init(dist,"arou");
sw.Start();
for (i=0;i<N;i++) {
x = unr0.Sample();
}
printf("GausUNURAN........ %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = unr1.Sample();
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = unr2.Sample();
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = unr3.Sample();
}
printf(" %8.3f\n",sw.CpuTime()*cpn);
// Poisson (nned to initialize before with Poisson mu value)
unr0.InitPoisson(10);
unr1.InitPoisson(10);
unr2.InitPoisson(10);
unr3.InitPoisson(10);
sw.Start();
for (i=0;i<N;i++) {
x = unr0.SampleDiscr();
}
printf("PoissonUNURAN(10). %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = unr1.SampleDiscr();
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = unr2.SampleDiscr();
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = unr3.SampleDiscr();
}
printf(" %8.3f\n",sw.CpuTime()*cpn);
unr0.InitPoisson(100);
unr1.InitPoisson(100);
unr2.InitPoisson(100);
unr3.InitPoisson(100);
sw.Start();
for (i=0;i<N;i++) {
x = unr0.SampleDiscr();
}
printf("PoissonUNURAN(100) %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = unr1.SampleDiscr();
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = unr2.SampleDiscr();
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = unr3.SampleDiscr();
}
printf(" %8.3f\n",sw.CpuTime()*cpn);
delete r0;
delete r1;
delete r2;
delete r3;
gRandom = rsave;
#ifdef LATER
// Binomial
unr0.InitBinomial(15,0.5);
unr1.InitBinomial(15,0.5);
unr2.InitBinomial(15,0.5);
unr3.InitBinomial(15,0.5);
sw.Start();
for (i=0;i<N;i++) {
x = unr0.SampleDiscr();
}
printf("BinomialUN(15,0.5) %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = unr1.SampleDiscr();
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = unr2.SampleDiscr();
}
printf(" %8.3f",sw.CpuTime()*cpn);
sw.Start();
for (i=0;i<N;i++) {
x = unr3.SampleDiscr();
}
printf(" %8.3f\n",sw.CpuTime()*cpn);
#endif
}
int testRandom3() {
Float_t RefValue[] = // running using a seed of 4357 ROOT 5.13.07 and checked with GSL 1.8
{ 0.999741749, 0.162909875, 0.282617805, 0.947201082, 0.231656543, 0.484973614, 0.957476957, 0.744305343,
0.540043658, 0.739952981, 0.759943798, 0.658636614, 0.315637622, 0.804403015, 0.519672115, 0.168572422,
0.47552973, 0.392313994, 0.221667687, 0.213190459,0.0303352042, 0.33353925, 0.194148851, 0.943716781,
0.579931675, 0.898304858, 0.665563931, 0.49861031, 0.560628257, 0.182284646, 0.296525531, 0.117408933,
0.0629176658, 0.648125575, 0.725418529, 0.637131158, 0.713885062,0.0995762432, 0.699267196, 0.10781247,
0.129242751, 0.502403039, 0.207779906, 0.288910306,0.0831747944, 0.128124215, 0.547371411,0.0823195996,
0.292141427, 0.891623737, 0.227117839, 0.431845463, 0.140733001, 0.400392135, 0.686946901, 0.170670911,
0.440820868, 0.045336565, 0.311296414, 0.506181051, 0.18241084, 0.511032015, 0.740788205, 0.365988627,
0.160808837, 0.460106785, 0.627836472, 0.677603688, 0.698196523, 0.478536868,0.0901075942, 0.338728522,
0.0952137967, 0.436541964, 0.474673352, 0.419245926, 0.777536852, 0.624610565, 0.98043655, 0.370430201,
0.830812636, 0.140806447, 0.744085307, 0.82973968, 0.391104318, 0.621956392, 0.346699478,0.0461695245,
0.613066321, 0.567374048, 0.498894026, 0.723802079, 0.144550525,0.0423031633, 0.310787023, 0.121641154,
0.242069671, 0.381058855, 0.440128537, 0.599795902, 0.644574654, 0.432626217, 0.555968262, 0.716841168,
0.642362515, 0.685776725,0.0961581462, 0.122933464,0.0569974151, 0.820072044, 0.125539286, 0.315745071,
0.180566925, 0.142227219, 0.664429613, 0.685189223, 0.191001933, 0.436343019, 0.964459225, 0.86816359,
0.130879965, 0.48444228, 0.374654451, 0.900475122, 0.178656787, 0.679635131, 0.62287431, 0.98365595,
0.44071478, 0.804737277, 0.994845061, 0.541550961, 0.255905455, 0.638945635, 0.57591027, 0.25872142,
0.191593001, 0.445663047, 0.149266509, 0.996723689, 0.121762222, 0.65153928,0.0277950978, 0.389977602,
0.827913044, 0.283813907, 0.610203644, 0.23641275, 0.41082105, 0.677714617, 0.847126588, 0.649256228,
0.0813826511, 0.120830484, 0.479199264, 0.777878358, 0.471977701, 0.943337511, 0.980800992, 0.334554731,
0.202667924, 0.342841234, 0.653544244, 0.682758797, 0.60993614,0.0999271029, 0.766254981, 0.735581528,
0.24113914, 0.263178711, 0.960869899, 0.423395737, 0.336058146,0.000249497825, 0.868841017,0.00375315035,
0.165846311,0.0118208411, 0.606455074, 0.729972019, 0.613824557, 0.965768184, 0.497098261, 0.529885403,
0.461607532, 0.713033701, 0.579959768, 0.682802555, 0.953921514,0.0236552036, 0.280110147, 0.869526353,
0.299333274, 0.319553603, 0.300951709, 0.941111486, 0.848127064, 0.753346129, 0.538244087, 0.408481381,
0.212371316,0.0761404021, 0.289934908,0.0197818337, 0.241247899, 0.384619165, 0.454906886, 0.373982521,
0.440188796, 0.117896808, 0.805429845, 0.164892641, 0.282529936, 0.172685399, 0.93584233, 0.68095306,
0.133696739, 0.254761223, 0.399444876, 0.369235365, 0.726361892, 0.277837459, 0.693569104, 0.500354689,
0.118405538, 0.151303335, 0.681446943, 0.720665918, 0.979646939, 0.696779111, 0.557210072, 0.680821482,
0.95535205, 0.598208956, 0.770453895, 0.913597486, 0.658958649, 0.670974613, 0.578185175, 0.95303929,
0.162923458, 0.335056986, 0.951824704, 0.109661644, 0.619302303, 0.956816742, 0.985243094,0.0707377489,
0.50233039, 0.680721226, 0.553320066, 0.587005581, 0.691620562, 0.46264791, 0.574254294, 0.072890088,
0.638266518, 0.387757288, 0.220960217,0.00223180233, 0.495656775, 0.191316523, 0.022265008, 0.903589021,
0.738628175, 0.44453089, 0.417702243, 0.760861122, 0.437753222, 0.190982861, 0.577112962, 0.132688343,
0.317824347, 0.48691649, 0.939091069, 0.933946281, 0.073660135, 0.612436295, 0.514748724, 0.624663582,
0.130645262, 0.645210441, 0.13414855, 0.652925968, 0.265210009, 0.381805269, 0.59021506, 0.669704082,
0.55433248,0.0195047602, 0.184346962, 0.991180462, 0.573677764, 0.637762085, 0.594857598, 0.515244688,
0.330693509, 0.39674245, 0.88396548, 0.771485266, 0.599075381,0.0247266297,0.0122587895, 0.698452319,
0.265991009, 0.736700721, 0.999972619, 0.749792316, 0.484955589, 0.823700529, 0.62277709, 0.902512094,
0.0565051287, 0.739077389, 0.37617622, 0.036800765, 0.776198219, 0.837354186, 0.34508193,0.0818426476,
0.222621545, 0.152476319, 0.401177195, 0.531612608, 0.811706602,0.0407775661, 0.117889008, 0.575189965,
0.832362208, 0.204641853, 0.238721773, 0.9969287, 0.258590596, 0.892055968, 0.846859788, 0.306583706,
0.0333624918, 0.706420498, 0.193615608, 0.508978138,0.0215451468, 0.672732793, 0.813562444, 0.807284052,
0.481526843, 0.537519095, 0.780848606, 0.335848908, 0.699259371, 0.425855299, 0.825240663, 0.945613692,
0.55484125, 0.710495188, 0.378360366, 0.648338731,0.0456727168, 0.155477323, 0.885353968, 0.721565725,
0.961667201, 0.430300885, 0.132031354, 0.439331209, 0.467187736, 0.410083217, 0.277196711, 0.278509559,
0.954620806, 0.804357491, 0.968510466, 0.999722791, 0.947160283, 0.248551138,0.0067049861, 0.444727315,
0.674048778, 0.496480361,0.0210092501, 0.831763222, 0.108545852,0.0931516394, 0.89020564, 0.445945211,
0.906906768, 0.554039821, 0.759434349, 0.815551384, 0.532968503,0.0551351462,0.0539856541, 0.89918819,
0.146907374, 0.482647314,0.0673029809, 0.281161865, 0.932849165, 0.507317933, 0.564503014, 0.8007132,
0.645887499, 0.309219498,0.0478066066, 0.25196583, 0.713881142, 0.670994017, 0.60528576, 0.148271899,
0.79525035, 0.665277353, 0.854302043, 0.810533677,0.0711439839,0.0687935678, 0.890466573, 0.758045957,
0.0703105873, 0.852094478, 0.775356902, 0.684895203, 0.234552787, 0.461575694, 0.936435457, 0.664946419,
0.45967959, 0.88782351, 0.574622261,0.0301686234, 0.767354721, 0.345478555, 0.609123143, 0.21754287,
0.643760561, 0.571392649, 0.802311049, 0.962335547, 0.401769856, 0.996553418, 0.745945812, 0.448411183,
0.39578428, 0.123389926, 0.532614913, 0.833379602, 0.91767313, 0.825607567, 0.4459154, 0.267136201,
0.6643989, 0.766860694, 0.665968275, 0.503955105, 0.835153702, 0.622405379, 0.457538918, 0.554983278,
0.36581371, 0.656302231, 0.917038669, 0.276054591, 0.121214441, 0.966178254, 0.697439008, 0.443547789,
0.630195824, 0.368346675, 0.238191956, 0.300273821, 0.710332172,0.0474748381, 0.492525443,0.0812539798,
0.122016782, 0.99310218, 0.355091027, 0.764863731, 0.904099543, 0.396109613, 0.817134856, 0.348974222,
0.266193634, 0.367501958, 0.752316213, 0.587800024, 0.489421095, 0.673474061, 0.328296139, 0.853945839,
0.832380736, 0.159588686, 0.322411022, 0.950173707, 0.095376712, 0.231019855, 0.860607752, 0.359627192,
0.984843699,0.0319756679, 0.828649914, 0.51680949, 0.489407924, 0.963977298, 0.960131739, 0.681816791,
0.860788169, 0.455829282, 0.332390656,0.0591498043, 0.452245977, 0.217354216, 0.34560744, 0.549971993,
0.317622252, 0.892976443, 0.49004545, 0.25647901, 0.968998638, 0.910636465, 0.226717598, 0.327828572,
0.28670209, 0.142515054,0.0992817392, 0.192332409, 0.308376869, 0.871415959, 0.391148786, 0.788660882,
0.200816041, 0.986475959, 0.882862126, 0.109862451, 0.354283255, 0.555742682, 0.690698458, 0.643815752,
0.363104285,0.0788627111, 0.200820414, 0.71697353, 0.744353746, 0.76763643, 0.245442451, 0.668009119,
0.886989377, 0.366849931, 0.531556628, 0.502843979, 0.31454367, 0.622541364,0.0199038582, 0.676355134,
0.429818622, 0.232835212, 0.987619457, 0.306572135, 0.494637038, 0.748614893, 0.891843561,0.0452854959,
0.427561072, 0.226978442, 0.484072985, 0.16464563,0.0898074883, 0.384263737,0.0238354723, 0.329734547,
0.531230736, 0.476683361, 0.877482474, 0.455501628, 0.497302495, 0.396184301, 0.886124728, 0.736070092,
0.108917595, 0.397921902, 0.842575021, 0.82620032, 0.936655165, 0.24558961, 0.639688616, 0.493335031,
0.0734495069, 0.780138101,0.0421121232, 0.701116477, 0.940523267, 0.70054817, 0.776760272, 0.192742581,
0.0069252688, 0.842983626, 0.919324176, 0.242083269, 0.190100674, 0.735084639, 0.164522319, 0.99030645,
0.98284794, 0.657169539,0.0187736442, 0.759596482, 0.357567611, 0.509016344, 0.738899681, 0.567923164,
0.289056634, 0.41501714, 0.981054561, 0.365884479, 0.517878261, 0.844209022, 0.968122653, 0.258894528,
0.478310441, 0.437340986, 0.379398001, 0.203081884, 0.550820748, 0.255542723, 0.550098031, 0.870477939,
0.241230214, 0.157108238, 0.218260827, 0.116277737, 0.749018275, 0.158290659, 0.476353907, 0.545327323,
0.878978121,0.0171442169, 0.542981987, 0.318018082, 0.788805343, 0.871721374, 0.738490409,0.0923330146,
0.301398643, 0.637103286, 0.571564271, 0.712810342, 0.644289242, 0.230476008, 0.971695586, 0.966159428,
0.291883909, 0.175285818, 0.312882552, 0.98465128, 0.568391354, 0.844468564, 0.144433908, 0.45994061,
0.607897905, 0.184122705, 0.342805493, 0.606432998, 0.838196585, 0.186188518,0.0302744689, 0.307391858,
0.125286029, 0.270394965, 0.874161481, 0.370509557, 0.89423337, 0.407995674, 0.881878469, 0.647951238,
0.236986727, 0.528807336, 0.293731542,0.0943204253, 0.934538626, 0.121679332, 0.34968176,0.0670268578,
0.642196769, 0.692447138, 0.334926733, 0.374244194, 0.313885051, 0.538738295, 0.098592523, 0.490514225,
0.32873567, 0.709725794, 0.88169803, 0.393000481, 0.854243273, 0.463776593, 0.52705639, 0.493309892,
0.267784336, 0.583077476,0.0573514167, 0.959336368, 0.771417173,0.0427184631, 0.498433369,0.0522942701,
0.56155145, 0.960361909, 0.619817314, 0.528628368, 0.698235179, 0.186162042, 0.553998168, 0.666120292,
0.152731049, 0.948750157, 0.186825789, 0.580512664, 0.851024442, 0.106865844, 0.675861737, 0.79604524,
0.657646103,0.00934952381, 0.206267588, 0.636420368,0.0382564603, 0.67771025, 0.677917925, 0.671684269,
0.396317716, 0.661597047, 0.633360383, 0.962124239, 0.992711418,0.0993448263,0.0678932741, 0.426013152,
0.947045502, 0.708326009, 0.466817846,0.0448362886, 0.748580922, 0.678370694, 0.210921343, 0.398490306,
0.953675585,0.0289022848, 0.935766569, 0.846930474, 0.662760176, 0.867910903, 0.652359324, 0.45280494,
0.305228982, 0.352034987, 0.279643402, 0.236045594,0.0270034608, 0.652062389, 0.712000227, 0.619930867,
0.125439078, 0.452789963, 0.92233151, 0.120844359, 0.403808975, 0.260290446, 0.778843638, 0.6678412,
0.0267894373, 0.491332301, 0.915060888, 0.704025347, 0.628200853, 0.578338467, 0.629156416, 0.730410649,
0.641318334, 0.463709335, 0.614291239, 0.254470656, 0.808682692, 0.22898373, 0.450477996, 0.874235142,
0.202773906, 0.523711192, 0.126518266, 0.579402899, 0.26188467, 0.207769057, 0.55283816, 0.851395364,
0.513594437, 0.558259845, 0.666148535, 0.998974657, 0.178274074, 0.116739636,0.0684255431, 0.622713377,
0.31448295, 0.889827933, 0.80647766, 0.429916949, 0.524695458, 0.45267553, 0.630743121, 0.566594485,
0.958860663, 0.908052286, 0.700898262, 0.377025384, 0.683796226, 0.198088462, 0.617400699, 0.413726158,
0.823588417, 0.755577948, 0.703097317, 0.364294278, 0.819786986, 0.751581763, 0.048769509, 0.528569003,
0.616748192, 0.270942831, 0.800841747, 0.235174223, 0.903786552, 0.258801569, 0.191336412, 0.012410342,
0.853413998, 0.621008712, 0.855861931, 0.140106201, 0.872687964, 0.708839735,0.0926409892,0.0207504195,
0.782636518,0.0300825236, 0.504610632,0.0816221782, 0.773493745, 0.872577282, 0.880031248, 0.883524299,
0.872427328, 0.458722225, 0.902298841, 0.547904952,0.0559884352, 0.591179888, 0.563941709, 0.776130076,
0.295569778,0.0408536533, 0.398567183, 0.28227462, 0.806716321, 0.507159362, 0.688150965, 0.49466404,
0.45454604, 0.421480091,0.0392517329,0.0911962031, 0.393815309, 0.135373195, 0.968650583, 0.811676111,
0.325965411, 0.961999178, 0.100281202, 0.102924612, 0.30725909, 0.33368206, 0.857966134, 0.522921736,
0.615500041, 0.981558684, 0.797484739, 0.198809674, 0.45670419, 0.570970797, 0.214908696, 0.686433314,
0.278602115, 0.179739848, 0.397497946, 0.162858935, 0.802621762,0.0836459133, 0.638270752, 0.230856518,
0.580094379, 0.864292514, 0.932738287, 0.821393124, 0.480590473, 0.636373016, 0.181508656, 0.469200501,
0.309276441, 0.668810431, 0.722341161, 0.574856669, 0.527854513, 0.809231559, 0.986882661, 0.323860496,
0.606396459, 0.759558966, 0.79096818,0.0699298142, 0.550465414,0.00929828244, 0.784629475, 0.689044114,
0.963588091, 0.516441598, 0.357178305, 0.482336892, 0.429959602, 0.996306147, 0.601176011, 0.785004207,
0.970542121, 0.487854549,0.0949267522, 0.979331773, 0.120877739, 0.630260336, 0.19424754, 0.213081703,
0.0145987798, 0.366671115, 0.340100777, 0.721786347, 0.367533113,0.0210335371, 0.131687992, 0.586759676,
0.73360464, 0.863635151, 0.136994646,0.0524269778, 0.406223408, 0.241656947, 0.472450703, 0.872215979,
0.454719233,0.0715790696, 0.314061244, 0.492823114, 0.741721134, 0.694783663, 0.982867872, 0.319748137,
0.804203704,0.0534678153, 0.746155348, 0.303474931,0.0930815139, 0.934531664, 0.746868186, 0.100048471,
0.720296508, 0.21075374, 0.96309675, 0.749189411, 0.739621932, 0.510072327,0.0872929865, 0.650020469,
0.0823648495, 0.726920745, 0.532618265, 0.749305866, 0.86126694,0.0346994482,0.0931224583, 0.655257095,
0.959517847, 0.487057231, 0.859895745, 0.084794421, 0.718541715, 0.850918328, 0.818884782, 0.71627446,
0.40822393, 0.63658567, 0.523838703, 0.372038872, 0.353426097, 0.598049047,0.0974868746, 0.276353038
};
Int_t rc1 = 0;
Int_t rc2 = 0;
TRandom3 r(4357);
Int_t i;
// check whether the sequence is ok or not
for (i=0;i<1000;i++) {
x = r.Rndm();
// printf("%e ",x-RefValue[i]); if(i%8==7) printf("\n");
if (TMath::Abs(x-RefValue[i]) > 10e-8) {
printf("i=%d x=%.8f but should be %.8f\n",i,x,RefValue[i]);
rc1 += 1;
}
}
// check whether a state can be saved and restored
TFile *file = new TFile("random3.root","RECREATE");
file->SetCompressionLevel(0);
r.Write("r");
delete file;
file = new TFile("random3.root");
TRandom3 *rs = (TRandom3*) file->Get("r");
for (i=0;i<1000;i++) {
if (r.Rndm() - rs->Rndm() != 0) rc2 += 1;
}
if (rc2 != 0) printf("state restoration failed\n");
return rc1 + rc2;
}
void testrandom()
{
testRandom3();
testAll();
}
ROOT::R::TRInterface & r
Definition Object.C:4
#define e(i)
Definition RSha256.hxx:103
int Int_t
Definition RtypesCore.h:45
float Float_t
Definition RtypesCore.h:57
#define N
R__EXTERN TRandom * gRandom
Definition TRandom.h:62
1-Dim function class
Definition TF1.h:213
virtual Double_t GetRandom(TRandom *rng=nullptr, Option_t *opt=nullptr)
Return a random number following this function shape.
Definition TF1.cxx:2186
virtual void SetParameters(const Double_t *params)
Definition TF1.h:644
A ROOT file is a suite of consecutive data records (TKey instances) with a well defined format.
Definition TFile.h:54
virtual Int_t Write(const char *name=0, Int_t option=0, Int_t bufsize=0)
Write this object to the current directory.
Definition TObject.cxx:868
virtual Double_t Rndm()
Machine independent random number generator.
Definition TRandom3.cxx:99
virtual Double_t Rndm()
Machine independent random number generator.
Definition TRandomGen.h:62
virtual void RndmArray(Int_t n, Float_t *array)
Return an array of n random numbers uniformly distributed in ]0,1].
Definition TRandomGen.h:63
virtual Double_t Gaus(Double_t mean=0, Double_t sigma=1)
Samples a random number from the standard Normal (Gaussian) Distribution with the given mean and sigm...
Definition TRandom.cxx:274
virtual void RndmArray(Int_t n, Float_t *array)
Return an array of n random numbers uniformly distributed in ]0,1].
Definition TRandom.cxx:588
virtual Int_t Poisson(Double_t mean)
Generates a random integer N according to a Poisson law.
Definition TRandom.cxx:402
virtual void Rannor(Float_t &a, Float_t &b)
Return 2 numbers distributed following a gaussian with mean=0 and sigma=1.
Definition TRandom.cxx:500
virtual Double_t Exp(Double_t tau)
Returns an exponential deviate.
Definition TRandom.cxx:251
virtual Double_t Landau(Double_t mean=0, Double_t sigma=1)
Generate a random number following a Landau distribution with location parameter mu and scale paramet...
Definition TRandom.cxx:380
virtual Int_t Binomial(Int_t ntot, Double_t prob)
Generates a random integer N according to the binomial law.
Definition TRandom.cxx:211
virtual Double_t Rndm()
Machine independent random number generator.
Definition TRandom.cxx:552
Stopwatch class.
Definition TStopwatch.h:28
void Start(Bool_t reset=kTRUE)
Start the stopwatch.
Double_t CpuTime()
Stop the stopwatch (if it is running) and return the cputime (in seconds) passed between the start an...
TUnuranContDist class describing one dimensional continuous distribution.
TUnuran class.
Definition TUnuran.h:79
TRandomGen< ROOT::Math::MixMaxEngine< 240, 0 > > TRandomMixMax
MIXMAX generator based on a state of N=240.
Definition TRandomGen.h:105
TRandomGen< ROOT::Math::StdEngine< std::mt19937_64 > > TRandomMT64
Generator based on a the Mersenne-Twister generator with 64 bits, using the implementation provided b...
Definition TRandomGen.h:141
TRandomGen< ROOT::Math::MixMaxEngine< 256, 2 > > TRandomMixMax256
MIXMAX generator based on a state of N=256, based on the generator descrived in this paper:
Definition TRandomGen.h:130
TRandomGen< ROOT::Math::MixMaxEngine< 17, 0 > > TRandomMixMax17
MIXMAX generator based on a state of N=17.
Definition TRandomGen.h:116
TRandomGen< ROOT::Math::StdEngine< std::ranlux48 > > TRandomRanlux48
Generator based on a the RanLux generator with 48 bits, using the implementation provided by the stan...
Definition TRandomGen.h:149
Double_t y[n]
Definition legend1.C:17
Double_t x[n]
Definition legend1.C:17
TF1 * f1
Definition legend1.C:11
double dist(Rotation3D const &r1, Rotation3D const &r2)
Short_t Abs(Short_t d)
Definition TMathBase.h:120
Definition file.py:1
Authors
Rene Brun, Lorenzo Moneta

Definition in file testrandom.C.