Logo ROOT   6.19/01
Reference Guide
testrandom.C
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1 /// \file
2 /// \ingroup tutorial_math
3 /// \notebook -nodraw
4 /// Performance test of all the ROOT random generator (TRandom, TRandom1, TRandom2 and TRandom3)
5 /// Tests the generator TRandom3 against some ref values
6 /// and creates a timing table against TRandom, TRandom1 and TRandom2.
7 ///
8 /// E.g. on an an Intel Xeon Quad-core Harpertown (E5410) 2.33 GHz running
9 /// Linux SLC4 64 bit and compiled with gcc 3.4
10 ///
11 /// ~~~
12 /// Distribution nanoseconds/call
13 /// TRandom TRandom1 TRandom2 TRandom3
14 /// Rndm.............. 5.000 105.000 7.000 10.000
15 /// RndmArray......... 4.000 104.000 6.000 9.000
16 /// Gaus.............. 36.000 180.000 40.000 48.000
17 /// Rannor............ 118.000 220.000 120.000 124.000
18 /// Landau............ 22.000 123.000 26.000 31.000
19 /// Exponential....... 93.000 198.000 98.000 104.000
20 /// Binomial(5,0.5)... 30.000 548.000 46.000 65.000
21 /// Binomial(15,0.5).. 75.000 1615.000 125.000 178.000
22 /// Poisson(3)........ 96.000 494.000 109.000 125.000
23 /// Poisson(10)....... 138.000 1236.000 165.000 203.000
24 /// Poisson(70)....... 818.000 1195.000 835.000 844.000
25 /// Poisson(100)...... 837.000 1218.000 849.000 864.000
26 /// GausTF1........... 83.000 180.000 87.000 88.000
27 /// LandauTF1......... 80.000 180.000 83.000 86.000
28 /// GausUNURAN........ 40.000 139.000 41.000 44.000
29 /// PoissonUNURAN(10). 85.000 271.000 92.000 102.000
30 /// PoissonUNURAN(100) 62.000 256.000 69.000 78.000
31 /// ~~~
32 ///
33 /// Note that this tutorial can be executed in interpreted or compiled mode
34 ///
35 /// ~~~{.cpp}
36 /// Root > .x testrandom.C
37 /// Root > .x testrandom.C++
38 /// ~~~
39 ///
40 /// \macro_output
41 /// \macro_code
42 ///
43 /// \authors Rene Brun, Lorenzo Moneta
44 
45 #include <TRandom1.h>
46 #include <TRandom2.h>
47 #include <TRandom3.h>
48 #include <TRandomGen.h>
49 #include <TStopwatch.h>
50 #include <TF1.h>
51 #include <TUnuran.h>
52 #include <TUnuranContDist.h>
53 #include <TFile.h>
54 
55 
56 void testAll() {
57  int i, N = 2000000;
58  float cpn = 1000000000./N;
59  int N1 = N/10; float cpn1 = cpn*10; // for TRandom1
60  double x,y;
61  TRandom *rsave = gRandom;
62  TRandom *r0 = new TRandom();
63  TRandom *r1 = new TRandom1();
64  TRandom *r2 = new TRandom2();
65  TRandom *r3 = new TRandom3();
66  TRandom *r4 = new TRandomMixMax();
67  TRandom *r5 = new TRandomMixMax17();
69  TRandom *r7 = new TRandomMixMax256();
71  TRandom *r9 = new TRandomMT64();
72  TRandom *r10 = new TRandomRanlux48();
73 
74 
75  TStopwatch sw;
76  printf("Distribution nanoseconds/call\n");
77  printf(" TRandom TRandom1 TRandom2 TRandom3 MixMax240 MixMax17 Mixmax256_0 MixMax256_2 MixMax256_4 MT_64 Ranlux48\n");
78 
79  sw.Start();
80  for (i=0;i<N;i++) {
81  x = r0->Rndm(i);
82  }
83  printf("Rndm.............. %8.3f",sw.CpuTime()*cpn);
84  sw.Start();
85  for (i=0;i<N1;i++) {
86  x = r1->Rndm(i);
87  }
88  printf(" %8.3f",sw.CpuTime()*cpn1);
89  sw.Start();
90  for (i=0;i<N;i++) {
91  x = r2->Rndm(i);
92  }
93  printf(" %8.3f",sw.CpuTime()*cpn);
94  sw.Start();
95  for (i=0;i<N;i++) {
96  x = r3->Rndm(i);
97  }
98  printf(" %8.3f",sw.CpuTime()*cpn);
99  // new random generators
100 
101  sw.Start();
102  for (i=0;i<N;i++) {
103  x = r4->Rndm(i);
104  }
105  printf(" %8.3f",sw.CpuTime()*cpn);
106 
107  sw.Start();
108  for (i=0;i<N;i++) {
109  x = r5->Rndm(i);
110  }
111  printf(" %8.3f",sw.CpuTime()*cpn);
112 
113  sw.Start();
114  for (i=0;i<N;i++) {
115  x = r6->Rndm(i);
116  }
117  printf(" %8.3f",sw.CpuTime()*cpn);
118 
119  sw.Start();
120  for (i=0;i<N;i++) {
121  x = r7->Rndm(i);
122  }
123  printf(" %8.3f",sw.CpuTime()*cpn);
124 
125  sw.Start();
126  for (i=0;i<N;i++) {
127  x = r8->Rndm(i);
128  }
129  printf(" %8.3f",sw.CpuTime()*cpn);
130 
131  sw.Start();
132  for (i=0;i<N;i++) {
133  x = r9->Rndm(i);
134  }
135  printf(" %8.3f",sw.CpuTime()*cpn);
136 
137  sw.Start();
138  for (i=0;i<N1;i++) {
139  x = r10->Rndm(i);
140  }
141  printf(" %8.3f",sw.CpuTime()*cpn1);
142 
143  printf("\n\n");
144 
145  // RNDMARRAY
146 
147  const int NR = 1000;
148  double rn[NR];
149  sw.Start();
150  for (i=0;i<N;i+=NR) {
151  r0->RndmArray(NR,rn);
152  }
153  printf("RndmArray......... %8.3f",sw.CpuTime()*cpn);
154  sw.Start();
155  for (i=0;i<N1;i+=NR) {
156  r1->RndmArray(NR,rn);
157  }
158  printf(" %8.3f",sw.CpuTime()*cpn1);
159  sw.Start();
160  for (i=0;i<N;i+=NR) {
161  r2->RndmArray(NR,rn);
162  }
163  printf(" %8.3f",sw.CpuTime()*cpn);
164  sw.Start();
165  for (i=0;i<N;i+=NR) {
166  r3->RndmArray(NR,rn);
167  }
168  printf(" %8.3f",sw.CpuTime()*cpn);
169  sw.Start();
170  for (i=0;i<N;i+=NR) {
171  r4->RndmArray(NR,rn);
172  }
173  printf(" %8.3f",sw.CpuTime()*cpn);
174  sw.Start();
175  for (i=0;i<N;i+=NR) {
176  r5->RndmArray(NR,rn);
177  }
178  printf(" %8.3f",sw.CpuTime()*cpn);
179  sw.Start();
180  for (i=0;i<N;i+=NR) {
181  r6->RndmArray(NR,rn);
182  }
183  printf(" %8.3f",sw.CpuTime()*cpn);
184  sw.Start();
185  for (i=0;i<N;i+=NR) {
186  r7->RndmArray(NR,rn);
187  }
188  printf(" %8.3f",sw.CpuTime()*cpn);
189  sw.Start();
190  for (i=0;i<N;i+=NR) {
191  r8->RndmArray(NR,rn);
192  }
193  printf(" %8.3f",sw.CpuTime()*cpn);
194  sw.Start();
195  for (i=0;i<N;i+=NR) {
196  r9->RndmArray(NR,rn);
197  }
198  printf(" %8.3f",sw.CpuTime()*cpn);
199  sw.Start();
200  for (i=0;i<N1;i+=NR) {
201  r10->RndmArray(NR,rn);
202  }
203  printf(" %8.3f\n",sw.CpuTime()*cpn1);
204 
205  // Gaus
206 
207  sw.Start();
208  for (i=0;i<N;i++) {
209  x = r0->Gaus(0,1);
210  }
211  printf("Gaus.............. %8.3f",sw.CpuTime()*cpn);
212  sw.Start();
213  for (i=0;i<N1;i++) {
214  x = r1->Gaus(0,1);
215  }
216  printf(" %8.3f",sw.CpuTime()*cpn1);
217  sw.Start();
218  for (i=0;i<N;i++) {
219  x = r2->Gaus(0,1);
220  }
221  printf(" %8.3f",sw.CpuTime()*cpn);
222  sw.Start();
223  for (i=0;i<N;i++) {
224  x = r3->Gaus(0,1);
225  }
226  printf(" %8.3f",sw.CpuTime()*cpn);
227  sw.Start();
228  for (i=0;i<N;i++) {
229  x = r4->Gaus(0,1);
230  }
231  printf(" %8.3f",sw.CpuTime()*cpn);
232  sw.Start();
233  for (i=0;i<N;i++) {
234  x = r5->Gaus(0,1);
235  }
236  printf(" %8.3f",sw.CpuTime()*cpn);
237  sw.Start();
238  for (i=0;i<N;i++) {
239  x = r6->Gaus(0,1);
240  }
241  printf(" %8.3f",sw.CpuTime()*cpn);
242  sw.Start();
243  for (i=0;i<N;i++) {
244  x = r7->Gaus(0,1);
245  }
246  printf(" %8.3f",sw.CpuTime()*cpn);
247  sw.Start();
248  for (i=0;i<N;i++) {
249  x = r8->Gaus(0,1);
250  }
251  printf(" %8.3f",sw.CpuTime()*cpn);
252  sw.Start();
253  for (i=0;i<N;i++) {
254  x = r9->Gaus(0,1);
255  }
256  printf(" %8.3f\n",sw.CpuTime()*cpn);
257 
258 
259  // RANNOR
260 
261  sw.Start();
262  for (i=0;i<N;i+=2) {
263  r0->Rannor(x,y);
264  }
265  printf("Rannor............ %8.3f",sw.CpuTime()*cpn);
266  sw.Start();
267  for (i=0;i<N1;i+=2) {
268  r1->Rannor(x,y);
269  }
270  printf(" %8.3f",sw.CpuTime()*cpn1);
271  sw.Start();
272  for (i=0;i<N;i+=2) {
273  r2->Rannor(x,y);
274  }
275  printf(" %8.3f",sw.CpuTime()*cpn);
276  sw.Start();
277  for (i=0;i<N;i+=2) {
278  r3->Rannor(x,y);
279  }
280  printf(" %8.3f",sw.CpuTime()*cpn);
281  sw.Start();
282  for (i=0;i<N;i+=2) {
283  r4->Rannor(x,y);
284  }
285  printf(" %8.3f",sw.CpuTime()*cpn);
286  sw.Start();
287  for (i=0;i<N;i+=2) {
288  r5->Rannor(x,y);
289  }
290  printf(" %8.3f",sw.CpuTime()*cpn);
291  sw.Start();
292  for (i=0;i<N;i+=2) {
293  r6->Rannor(x,y);
294  }
295  printf(" %8.3f",sw.CpuTime()*cpn);
296  sw.Start();
297  for (i=0;i<N;i+=2) {
298  r7->Rannor(x,y);
299  }
300  printf(" %8.3f",sw.CpuTime()*cpn);
301  sw.Start();
302  for (i=0;i<N;i+=2) {
303  r8->Rannor(x,y);
304  }
305  printf(" %8.3f",sw.CpuTime()*cpn);
306  sw.Start();
307  for (i=0;i<N;i+=2) {
308  r9->Rannor(x,y);
309  }
310  printf(" %8.3f\n",sw.CpuTime()*cpn);
311 
312  // Landau
313 
314  sw.Start();
315  for (i=0;i<N;i++) {
316  x = r0->Landau(0,1);
317  }
318  printf("Landau............ %8.3f",sw.CpuTime()*cpn);
319  sw.Start();
320  for (i=0;i<N1;i++) {
321  x = r1->Landau(0,1);
322  }
323  printf(" %8.3f",sw.CpuTime()*cpn1);
324  sw.Start();
325  for (i=0;i<N;i++) {
326  x = r2->Landau(0,1);
327  }
328  printf(" %8.3f",sw.CpuTime()*cpn);
329  sw.Start();
330  for (i=0;i<N;i++) {
331  x = r3->Landau(0,1);
332  }
333  printf(" %8.3f\n",sw.CpuTime()*cpn);
334 
335  sw.Start();
336  for (i=0;i<N;i++) {
337  x = r0->Exp(1);
338  }
339  printf("Exponential....... %8.3f",sw.CpuTime()*cpn);
340  sw.Start();
341  for (i=0;i<N1;i++) {
342  x = r1->Exp(1);
343  }
344  printf(" %8.3f",sw.CpuTime()*cpn1);
345  sw.Start();
346  for (i=0;i<N;i++) {
347  x = r2->Exp(1);
348  }
349  printf(" %8.3f",sw.CpuTime()*cpn);
350  sw.Start();
351  for (i=0;i<N;i++) {
352  x = r3->Exp(1);
353  }
354  printf(" %8.3f\n",sw.CpuTime()*cpn);
355 
356  sw.Start();
357  for (i=0;i<N;i++) {
358  x = r0->Binomial(5,0.5);
359  }
360  printf("Binomial(5,0.5)... %8.3f",sw.CpuTime()*cpn);
361  sw.Start();
362  for (i=0;i<N1;i++) {
363  x = r1->Binomial(5,0.5);
364  }
365  printf(" %8.3f",sw.CpuTime()*cpn1);
366  sw.Start();
367  for (i=0;i<N;i++) {
368  x = r2->Binomial(5,0.5);
369  }
370  printf(" %8.3f",sw.CpuTime()*cpn);
371  sw.Start();
372  for (i=0;i<N;i++) {
373  x = r3->Binomial(5,0.5);
374  }
375  printf(" %8.3f\n",sw.CpuTime()*cpn);
376 
377  sw.Start();
378  for (i=0;i<N;i++) {
379  x = r0->Binomial(15,0.5);
380  }
381  printf("Binomial(15,0.5).. %8.3f",sw.CpuTime()*cpn);
382  sw.Start();
383  for (i=0;i<N1;i++) {
384  x = r1->Binomial(15,0.5);
385  }
386  printf(" %8.3f",sw.CpuTime()*cpn1);
387  sw.Start();
388  for (i=0;i<N;i++) {
389  x = r2->Binomial(15,0.5);
390  }
391  printf(" %8.3f",sw.CpuTime()*cpn);
392  sw.Start();
393  for (i=0;i<N;i++) {
394  x = r3->Binomial(15,0.5);
395  }
396  printf(" %8.3f\n",sw.CpuTime()*cpn);
397 
398  sw.Start();
399  for (i=0;i<N;i++) {
400  x = r0->Poisson(3);
401  }
402  printf("Poisson(3)........ %8.3f",sw.CpuTime()*cpn);
403  sw.Start();
404  for (i=0;i<N1;i++) {
405  x = r1->Poisson(3);
406  }
407  printf(" %8.3f",sw.CpuTime()*cpn1);
408  sw.Start();
409  for (i=0;i<N;i++) {
410  x = r2->Poisson(3);
411  }
412  printf(" %8.3f",sw.CpuTime()*cpn);
413  sw.Start();
414  for (i=0;i<N;i++) {
415  x = r3->Poisson(3);
416  }
417  printf(" %8.3f\n",sw.CpuTime()*cpn);
418 
419  sw.Start();
420  for (i=0;i<N;i++) {
421  x = r0->Poisson(10);
422  }
423  printf("Poisson(10)....... %8.3f",sw.CpuTime()*cpn);
424  sw.Start();
425  for (i=0;i<N1;i++) {
426  x = r1->Poisson(10);
427  }
428  printf(" %8.3f",sw.CpuTime()*cpn1);
429  sw.Start();
430  for (i=0;i<N;i++) {
431  x = r2->Poisson(10);
432  }
433  printf(" %8.3f",sw.CpuTime()*cpn);
434  sw.Start();
435  for (i=0;i<N;i++) {
436  x = r3->Poisson(10);
437  }
438  printf(" %8.3f\n",sw.CpuTime()*cpn);
439 
440  sw.Start();
441  for (i=0;i<N;i++) {
442  x = r0->Poisson(70);
443  }
444  printf("Poisson(70)....... %8.3f",sw.CpuTime()*cpn);
445  sw.Start();
446  for (i=0;i<N1;i++) {
447  x = r1->Poisson(70);
448  }
449  printf(" %8.3f",sw.CpuTime()*cpn1);
450  sw.Start();
451  for (i=0;i<N;i++) {
452  x = r2->Poisson(70);
453  }
454  printf(" %8.3f",sw.CpuTime()*cpn);
455  sw.Start();
456  for (i=0;i<N;i++) {
457  x = r3->Poisson(70);
458  }
459  printf(" %8.3f\n",sw.CpuTime()*cpn);
460 
461  sw.Start();
462  for (i=0;i<N;i++) {
463  x = r0->Poisson(100);
464  }
465  printf("Poisson(100)...... %8.3f",sw.CpuTime()*cpn);
466  sw.Start();
467  for (i=0;i<N1;i++) {
468  x = r1->Poisson(100);
469  }
470  printf(" %8.3f",sw.CpuTime()*cpn1);
471  sw.Start();
472  for (i=0;i<N;i++) {
473  x = r2->Poisson(100);
474  }
475  printf(" %8.3f",sw.CpuTime()*cpn);
476  sw.Start();
477  for (i=0;i<N;i++) {
478  x = r3->Poisson(100);
479  }
480  printf(" %8.3f\n",sw.CpuTime()*cpn);
481 
482  TF1 *f1 = new TF1("f1","gaus",-4,4);
483  f1->SetParameters(1,0,1);
484  gRandom = r0;
485  sw.Start();
486  for (i=0;i<N;i++) {
487  x = f1->GetRandom();
488  }
489  printf("GausTF1........... %8.3f",sw.CpuTime()*cpn);
490  gRandom = r1;
491  sw.Start();
492  for (i=0;i<N;i++) {
493  x = f1->GetRandom();
494  }
495  printf(" %8.3f",sw.CpuTime()*cpn);
496  gRandom = r2;
497  sw.Start();
498  for (i=0;i<N;i++) {
499  x = f1->GetRandom();
500  }
501  printf(" %8.3f",sw.CpuTime()*cpn);
502  gRandom = r3;
503  sw.Start();
504  for (i=0;i<N;i++) {
505  x = f1->GetRandom();
506  }
507  printf(" %8.3f\n",sw.CpuTime()*cpn);
508 
509  TF1 *f2 = new TF1("f2","landau",-5,15);
510  f2->SetParameters(1,0,1);
511 
512  gRandom = r0;
513  sw.Start();
514  for (i=0;i<N;i++) {
515  x = f2->GetRandom();
516  }
517  printf("LandauTF1......... %8.3f",sw.CpuTime()*cpn);
518  gRandom = r1;
519  sw.Start();
520  for (i=0;i<N;i++) {
521  x = f2->GetRandom();
522  }
523  printf(" %8.3f",sw.CpuTime()*cpn);
524  gRandom = r2;
525  sw.Start();
526  for (i=0;i<N;i++) {
527  x = f2->GetRandom();
528  }
529  printf(" %8.3f",sw.CpuTime()*cpn);
530  gRandom = r3;
531  sw.Start();
532  for (i=0;i<N;i++) {
533  x = f2->GetRandom();
534  }
535  printf(" %8.3f\n",sw.CpuTime()*cpn);
536 
537  // test using Unuran
538  TUnuran unr0(r0);
539  TUnuran unr1(r1);
540  TUnuran unr2(r2);
541  TUnuran unr3(r3);
542 
543  // continuous distribution (ex. Gaus)
545  // use arou method (is probably the fastest)
546  unr0.Init(dist,"arou");
547  unr1.Init(dist,"arou");
548  unr2.Init(dist,"arou");
549  unr3.Init(dist,"arou");
550 
551  sw.Start();
552  for (i=0;i<N;i++) {
553  x = unr0.Sample();
554  }
555  printf("GausUNURAN........ %8.3f",sw.CpuTime()*cpn);
556  sw.Start();
557  for (i=0;i<N;i++) {
558  x = unr1.Sample();
559  }
560  printf(" %8.3f",sw.CpuTime()*cpn);
561  sw.Start();
562  for (i=0;i<N;i++) {
563  x = unr2.Sample();
564  }
565  printf(" %8.3f",sw.CpuTime()*cpn);
566  sw.Start();
567  for (i=0;i<N;i++) {
568  x = unr3.Sample();
569  }
570  printf(" %8.3f\n",sw.CpuTime()*cpn);
571 
572  // Poisson (nned to initialize before with Poisson mu value)
573 
574  unr0.InitPoisson(10);
575  unr1.InitPoisson(10);
576  unr2.InitPoisson(10);
577  unr3.InitPoisson(10);
578 
579  sw.Start();
580  for (i=0;i<N;i++) {
581  x = unr0.SampleDiscr();
582  }
583  printf("PoissonUNURAN(10). %8.3f",sw.CpuTime()*cpn);
584  sw.Start();
585  for (i=0;i<N;i++) {
586  x = unr1.SampleDiscr();
587  }
588  printf(" %8.3f",sw.CpuTime()*cpn);
589  sw.Start();
590  for (i=0;i<N;i++) {
591  x = unr2.SampleDiscr();
592  }
593  printf(" %8.3f",sw.CpuTime()*cpn);
594  sw.Start();
595  for (i=0;i<N;i++) {
596  x = unr3.SampleDiscr();
597  }
598  printf(" %8.3f\n",sw.CpuTime()*cpn);
599 
600  unr0.InitPoisson(100);
601  unr1.InitPoisson(100);
602  unr2.InitPoisson(100);
603  unr3.InitPoisson(100);
604 
605  sw.Start();
606  for (i=0;i<N;i++) {
607  x = unr0.SampleDiscr();
608  }
609  printf("PoissonUNURAN(100) %8.3f",sw.CpuTime()*cpn);
610  sw.Start();
611  for (i=0;i<N;i++) {
612  x = unr1.SampleDiscr();
613  }
614  printf(" %8.3f",sw.CpuTime()*cpn);
615  sw.Start();
616  for (i=0;i<N;i++) {
617  x = unr2.SampleDiscr();
618  }
619  printf(" %8.3f",sw.CpuTime()*cpn);
620  sw.Start();
621  for (i=0;i<N;i++) {
622  x = unr3.SampleDiscr();
623  }
624  printf(" %8.3f\n",sw.CpuTime()*cpn);
625 
626 
627  delete r0;
628  delete r1;
629  delete r2;
630  delete r3;
631  gRandom = rsave;
632 
633 #ifdef LATER
634  // Binomial
635  unr0.InitBinomial(15,0.5);
636  unr1.InitBinomial(15,0.5);
637  unr2.InitBinomial(15,0.5);
638  unr3.InitBinomial(15,0.5);
639 
640  sw.Start();
641  for (i=0;i<N;i++) {
642  x = unr0.SampleDiscr();
643  }
644  printf("BinomialUN(15,0.5) %8.3f",sw.CpuTime()*cpn);
645  sw.Start();
646  for (i=0;i<N;i++) {
647  x = unr1.SampleDiscr();
648  }
649  printf(" %8.3f",sw.CpuTime()*cpn);
650  sw.Start();
651  for (i=0;i<N;i++) {
652  x = unr2.SampleDiscr();
653  }
654  printf(" %8.3f",sw.CpuTime()*cpn);
655  sw.Start();
656  for (i=0;i<N;i++) {
657  x = unr3.SampleDiscr();
658  }
659  printf(" %8.3f\n",sw.CpuTime()*cpn);
660 #endif
661 
662 }
663 
664 int testRandom3() {
665 
666  Float_t RefValue[] = // running using a seed of 4357 ROOT 5.13.07 and checked with GSL 1.8
667  { 0.999741749, 0.162909875, 0.282617805, 0.947201082, 0.231656543, 0.484973614, 0.957476957, 0.744305343,
668  0.540043658, 0.739952981, 0.759943798, 0.658636614, 0.315637622, 0.804403015, 0.519672115, 0.168572422,
669  0.47552973, 0.392313994, 0.221667687, 0.213190459,0.0303352042, 0.33353925, 0.194148851, 0.943716781,
670  0.579931675, 0.898304858, 0.665563931, 0.49861031, 0.560628257, 0.182284646, 0.296525531, 0.117408933,
671  0.0629176658, 0.648125575, 0.725418529, 0.637131158, 0.713885062,0.0995762432, 0.699267196, 0.10781247,
672  0.129242751, 0.502403039, 0.207779906, 0.288910306,0.0831747944, 0.128124215, 0.547371411,0.0823195996,
673  0.292141427, 0.891623737, 0.227117839, 0.431845463, 0.140733001, 0.400392135, 0.686946901, 0.170670911,
674  0.440820868, 0.045336565, 0.311296414, 0.506181051, 0.18241084, 0.511032015, 0.740788205, 0.365988627,
675  0.160808837, 0.460106785, 0.627836472, 0.677603688, 0.698196523, 0.478536868,0.0901075942, 0.338728522,
676  0.0952137967, 0.436541964, 0.474673352, 0.419245926, 0.777536852, 0.624610565, 0.98043655, 0.370430201,
677  0.830812636, 0.140806447, 0.744085307, 0.82973968, 0.391104318, 0.621956392, 0.346699478,0.0461695245,
678  0.613066321, 0.567374048, 0.498894026, 0.723802079, 0.144550525,0.0423031633, 0.310787023, 0.121641154,
679  0.242069671, 0.381058855, 0.440128537, 0.599795902, 0.644574654, 0.432626217, 0.555968262, 0.716841168,
680  0.642362515, 0.685776725,0.0961581462, 0.122933464,0.0569974151, 0.820072044, 0.125539286, 0.315745071,
681  0.180566925, 0.142227219, 0.664429613, 0.685189223, 0.191001933, 0.436343019, 0.964459225, 0.86816359,
682  0.130879965, 0.48444228, 0.374654451, 0.900475122, 0.178656787, 0.679635131, 0.62287431, 0.98365595,
683  0.44071478, 0.804737277, 0.994845061, 0.541550961, 0.255905455, 0.638945635, 0.57591027, 0.25872142,
684  0.191593001, 0.445663047, 0.149266509, 0.996723689, 0.121762222, 0.65153928,0.0277950978, 0.389977602,
685  0.827913044, 0.283813907, 0.610203644, 0.23641275, 0.41082105, 0.677714617, 0.847126588, 0.649256228,
686  0.0813826511, 0.120830484, 0.479199264, 0.777878358, 0.471977701, 0.943337511, 0.980800992, 0.334554731,
687  0.202667924, 0.342841234, 0.653544244, 0.682758797, 0.60993614,0.0999271029, 0.766254981, 0.735581528,
688  0.24113914, 0.263178711, 0.960869899, 0.423395737, 0.336058146,0.000249497825, 0.868841017,0.00375315035,
689  0.165846311,0.0118208411, 0.606455074, 0.729972019, 0.613824557, 0.965768184, 0.497098261, 0.529885403,
690  0.461607532, 0.713033701, 0.579959768, 0.682802555, 0.953921514,0.0236552036, 0.280110147, 0.869526353,
691  0.299333274, 0.319553603, 0.300951709, 0.941111486, 0.848127064, 0.753346129, 0.538244087, 0.408481381,
692  0.212371316,0.0761404021, 0.289934908,0.0197818337, 0.241247899, 0.384619165, 0.454906886, 0.373982521,
693  0.440188796, 0.117896808, 0.805429845, 0.164892641, 0.282529936, 0.172685399, 0.93584233, 0.68095306,
694  0.133696739, 0.254761223, 0.399444876, 0.369235365, 0.726361892, 0.277837459, 0.693569104, 0.500354689,
695  0.118405538, 0.151303335, 0.681446943, 0.720665918, 0.979646939, 0.696779111, 0.557210072, 0.680821482,
696  0.95535205, 0.598208956, 0.770453895, 0.913597486, 0.658958649, 0.670974613, 0.578185175, 0.95303929,
697  0.162923458, 0.335056986, 0.951824704, 0.109661644, 0.619302303, 0.956816742, 0.985243094,0.0707377489,
698  0.50233039, 0.680721226, 0.553320066, 0.587005581, 0.691620562, 0.46264791, 0.574254294, 0.072890088,
699  0.638266518, 0.387757288, 0.220960217,0.00223180233, 0.495656775, 0.191316523, 0.022265008, 0.903589021,
700  0.738628175, 0.44453089, 0.417702243, 0.760861122, 0.437753222, 0.190982861, 0.577112962, 0.132688343,
701  0.317824347, 0.48691649, 0.939091069, 0.933946281, 0.073660135, 0.612436295, 0.514748724, 0.624663582,
702  0.130645262, 0.645210441, 0.13414855, 0.652925968, 0.265210009, 0.381805269, 0.59021506, 0.669704082,
703  0.55433248,0.0195047602, 0.184346962, 0.991180462, 0.573677764, 0.637762085, 0.594857598, 0.515244688,
704  0.330693509, 0.39674245, 0.88396548, 0.771485266, 0.599075381,0.0247266297,0.0122587895, 0.698452319,
705  0.265991009, 0.736700721, 0.999972619, 0.749792316, 0.484955589, 0.823700529, 0.62277709, 0.902512094,
706  0.0565051287, 0.739077389, 0.37617622, 0.036800765, 0.776198219, 0.837354186, 0.34508193,0.0818426476,
707  0.222621545, 0.152476319, 0.401177195, 0.531612608, 0.811706602,0.0407775661, 0.117889008, 0.575189965,
708  0.832362208, 0.204641853, 0.238721773, 0.9969287, 0.258590596, 0.892055968, 0.846859788, 0.306583706,
709  0.0333624918, 0.706420498, 0.193615608, 0.508978138,0.0215451468, 0.672732793, 0.813562444, 0.807284052,
710  0.481526843, 0.537519095, 0.780848606, 0.335848908, 0.699259371, 0.425855299, 0.825240663, 0.945613692,
711  0.55484125, 0.710495188, 0.378360366, 0.648338731,0.0456727168, 0.155477323, 0.885353968, 0.721565725,
712  0.961667201, 0.430300885, 0.132031354, 0.439331209, 0.467187736, 0.410083217, 0.277196711, 0.278509559,
713  0.954620806, 0.804357491, 0.968510466, 0.999722791, 0.947160283, 0.248551138,0.0067049861, 0.444727315,
714  0.674048778, 0.496480361,0.0210092501, 0.831763222, 0.108545852,0.0931516394, 0.89020564, 0.445945211,
715  0.906906768, 0.554039821, 0.759434349, 0.815551384, 0.532968503,0.0551351462,0.0539856541, 0.89918819,
716  0.146907374, 0.482647314,0.0673029809, 0.281161865, 0.932849165, 0.507317933, 0.564503014, 0.8007132,
717  0.645887499, 0.309219498,0.0478066066, 0.25196583, 0.713881142, 0.670994017, 0.60528576, 0.148271899,
718  0.79525035, 0.665277353, 0.854302043, 0.810533677,0.0711439839,0.0687935678, 0.890466573, 0.758045957,
719  0.0703105873, 0.852094478, 0.775356902, 0.684895203, 0.234552787, 0.461575694, 0.936435457, 0.664946419,
720  0.45967959, 0.88782351, 0.574622261,0.0301686234, 0.767354721, 0.345478555, 0.609123143, 0.21754287,
721  0.643760561, 0.571392649, 0.802311049, 0.962335547, 0.401769856, 0.996553418, 0.745945812, 0.448411183,
722  0.39578428, 0.123389926, 0.532614913, 0.833379602, 0.91767313, 0.825607567, 0.4459154, 0.267136201,
723  0.6643989, 0.766860694, 0.665968275, 0.503955105, 0.835153702, 0.622405379, 0.457538918, 0.554983278,
724  0.36581371, 0.656302231, 0.917038669, 0.276054591, 0.121214441, 0.966178254, 0.697439008, 0.443547789,
725  0.630195824, 0.368346675, 0.238191956, 0.300273821, 0.710332172,0.0474748381, 0.492525443,0.0812539798,
726  0.122016782, 0.99310218, 0.355091027, 0.764863731, 0.904099543, 0.396109613, 0.817134856, 0.348974222,
727  0.266193634, 0.367501958, 0.752316213, 0.587800024, 0.489421095, 0.673474061, 0.328296139, 0.853945839,
728  0.832380736, 0.159588686, 0.322411022, 0.950173707, 0.095376712, 0.231019855, 0.860607752, 0.359627192,
729  0.984843699,0.0319756679, 0.828649914, 0.51680949, 0.489407924, 0.963977298, 0.960131739, 0.681816791,
730  0.860788169, 0.455829282, 0.332390656,0.0591498043, 0.452245977, 0.217354216, 0.34560744, 0.549971993,
731  0.317622252, 0.892976443, 0.49004545, 0.25647901, 0.968998638, 0.910636465, 0.226717598, 0.327828572,
732  0.28670209, 0.142515054,0.0992817392, 0.192332409, 0.308376869, 0.871415959, 0.391148786, 0.788660882,
733  0.200816041, 0.986475959, 0.882862126, 0.109862451, 0.354283255, 0.555742682, 0.690698458, 0.643815752,
734  0.363104285,0.0788627111, 0.200820414, 0.71697353, 0.744353746, 0.76763643, 0.245442451, 0.668009119,
735  0.886989377, 0.366849931, 0.531556628, 0.502843979, 0.31454367, 0.622541364,0.0199038582, 0.676355134,
736  0.429818622, 0.232835212, 0.987619457, 0.306572135, 0.494637038, 0.748614893, 0.891843561,0.0452854959,
737  0.427561072, 0.226978442, 0.484072985, 0.16464563,0.0898074883, 0.384263737,0.0238354723, 0.329734547,
738  0.531230736, 0.476683361, 0.877482474, 0.455501628, 0.497302495, 0.396184301, 0.886124728, 0.736070092,
739  0.108917595, 0.397921902, 0.842575021, 0.82620032, 0.936655165, 0.24558961, 0.639688616, 0.493335031,
740  0.0734495069, 0.780138101,0.0421121232, 0.701116477, 0.940523267, 0.70054817, 0.776760272, 0.192742581,
741  0.0069252688, 0.842983626, 0.919324176, 0.242083269, 0.190100674, 0.735084639, 0.164522319, 0.99030645,
742  0.98284794, 0.657169539,0.0187736442, 0.759596482, 0.357567611, 0.509016344, 0.738899681, 0.567923164,
743  0.289056634, 0.41501714, 0.981054561, 0.365884479, 0.517878261, 0.844209022, 0.968122653, 0.258894528,
744  0.478310441, 0.437340986, 0.379398001, 0.203081884, 0.550820748, 0.255542723, 0.550098031, 0.870477939,
745  0.241230214, 0.157108238, 0.218260827, 0.116277737, 0.749018275, 0.158290659, 0.476353907, 0.545327323,
746  0.878978121,0.0171442169, 0.542981987, 0.318018082, 0.788805343, 0.871721374, 0.738490409,0.0923330146,
747  0.301398643, 0.637103286, 0.571564271, 0.712810342, 0.644289242, 0.230476008, 0.971695586, 0.966159428,
748  0.291883909, 0.175285818, 0.312882552, 0.98465128, 0.568391354, 0.844468564, 0.144433908, 0.45994061,
749  0.607897905, 0.184122705, 0.342805493, 0.606432998, 0.838196585, 0.186188518,0.0302744689, 0.307391858,
750  0.125286029, 0.270394965, 0.874161481, 0.370509557, 0.89423337, 0.407995674, 0.881878469, 0.647951238,
751  0.236986727, 0.528807336, 0.293731542,0.0943204253, 0.934538626, 0.121679332, 0.34968176,0.0670268578,
752  0.642196769, 0.692447138, 0.334926733, 0.374244194, 0.313885051, 0.538738295, 0.098592523, 0.490514225,
753  0.32873567, 0.709725794, 0.88169803, 0.393000481, 0.854243273, 0.463776593, 0.52705639, 0.493309892,
754  0.267784336, 0.583077476,0.0573514167, 0.959336368, 0.771417173,0.0427184631, 0.498433369,0.0522942701,
755  0.56155145, 0.960361909, 0.619817314, 0.528628368, 0.698235179, 0.186162042, 0.553998168, 0.666120292,
756  0.152731049, 0.948750157, 0.186825789, 0.580512664, 0.851024442, 0.106865844, 0.675861737, 0.79604524,
757  0.657646103,0.00934952381, 0.206267588, 0.636420368,0.0382564603, 0.67771025, 0.677917925, 0.671684269,
758  0.396317716, 0.661597047, 0.633360383, 0.962124239, 0.992711418,0.0993448263,0.0678932741, 0.426013152,
759  0.947045502, 0.708326009, 0.466817846,0.0448362886, 0.748580922, 0.678370694, 0.210921343, 0.398490306,
760  0.953675585,0.0289022848, 0.935766569, 0.846930474, 0.662760176, 0.867910903, 0.652359324, 0.45280494,
761  0.305228982, 0.352034987, 0.279643402, 0.236045594,0.0270034608, 0.652062389, 0.712000227, 0.619930867,
762  0.125439078, 0.452789963, 0.92233151, 0.120844359, 0.403808975, 0.260290446, 0.778843638, 0.6678412,
763  0.0267894373, 0.491332301, 0.915060888, 0.704025347, 0.628200853, 0.578338467, 0.629156416, 0.730410649,
764  0.641318334, 0.463709335, 0.614291239, 0.254470656, 0.808682692, 0.22898373, 0.450477996, 0.874235142,
765  0.202773906, 0.523711192, 0.126518266, 0.579402899, 0.26188467, 0.207769057, 0.55283816, 0.851395364,
766  0.513594437, 0.558259845, 0.666148535, 0.998974657, 0.178274074, 0.116739636,0.0684255431, 0.622713377,
767  0.31448295, 0.889827933, 0.80647766, 0.429916949, 0.524695458, 0.45267553, 0.630743121, 0.566594485,
768  0.958860663, 0.908052286, 0.700898262, 0.377025384, 0.683796226, 0.198088462, 0.617400699, 0.413726158,
769  0.823588417, 0.755577948, 0.703097317, 0.364294278, 0.819786986, 0.751581763, 0.048769509, 0.528569003,
770  0.616748192, 0.270942831, 0.800841747, 0.235174223, 0.903786552, 0.258801569, 0.191336412, 0.012410342,
771  0.853413998, 0.621008712, 0.855861931, 0.140106201, 0.872687964, 0.708839735,0.0926409892,0.0207504195,
772  0.782636518,0.0300825236, 0.504610632,0.0816221782, 0.773493745, 0.872577282, 0.880031248, 0.883524299,
773  0.872427328, 0.458722225, 0.902298841, 0.547904952,0.0559884352, 0.591179888, 0.563941709, 0.776130076,
774  0.295569778,0.0408536533, 0.398567183, 0.28227462, 0.806716321, 0.507159362, 0.688150965, 0.49466404,
775  0.45454604, 0.421480091,0.0392517329,0.0911962031, 0.393815309, 0.135373195, 0.968650583, 0.811676111,
776  0.325965411, 0.961999178, 0.100281202, 0.102924612, 0.30725909, 0.33368206, 0.857966134, 0.522921736,
777  0.615500041, 0.981558684, 0.797484739, 0.198809674, 0.45670419, 0.570970797, 0.214908696, 0.686433314,
778  0.278602115, 0.179739848, 0.397497946, 0.162858935, 0.802621762,0.0836459133, 0.638270752, 0.230856518,
779  0.580094379, 0.864292514, 0.932738287, 0.821393124, 0.480590473, 0.636373016, 0.181508656, 0.469200501,
780  0.309276441, 0.668810431, 0.722341161, 0.574856669, 0.527854513, 0.809231559, 0.986882661, 0.323860496,
781  0.606396459, 0.759558966, 0.79096818,0.0699298142, 0.550465414,0.00929828244, 0.784629475, 0.689044114,
782  0.963588091, 0.516441598, 0.357178305, 0.482336892, 0.429959602, 0.996306147, 0.601176011, 0.785004207,
783  0.970542121, 0.487854549,0.0949267522, 0.979331773, 0.120877739, 0.630260336, 0.19424754, 0.213081703,
784  0.0145987798, 0.366671115, 0.340100777, 0.721786347, 0.367533113,0.0210335371, 0.131687992, 0.586759676,
785  0.73360464, 0.863635151, 0.136994646,0.0524269778, 0.406223408, 0.241656947, 0.472450703, 0.872215979,
786  0.454719233,0.0715790696, 0.314061244, 0.492823114, 0.741721134, 0.694783663, 0.982867872, 0.319748137,
787  0.804203704,0.0534678153, 0.746155348, 0.303474931,0.0930815139, 0.934531664, 0.746868186, 0.100048471,
788  0.720296508, 0.21075374, 0.96309675, 0.749189411, 0.739621932, 0.510072327,0.0872929865, 0.650020469,
789  0.0823648495, 0.726920745, 0.532618265, 0.749305866, 0.86126694,0.0346994482,0.0931224583, 0.655257095,
790  0.959517847, 0.487057231, 0.859895745, 0.084794421, 0.718541715, 0.850918328, 0.818884782, 0.71627446,
791  0.40822393, 0.63658567, 0.523838703, 0.372038872, 0.353426097, 0.598049047,0.0974868746, 0.276353038
792  };
793 
794  Int_t rc1 = 0;
795  Int_t rc2 = 0;
796  TRandom3 r(4357);
797  Float_t x;
798  Int_t i;
799 
800  // check whether the sequence is ok or not
801  for (i=0;i<1000;i++) {
802  x = r.Rndm();
803  // printf("%e ",x-RefValue[i]); if(i%8==7) printf("\n");
804  if (TMath::Abs(x-RefValue[i]) > 10e-8) {
805  printf("i=%d x=%.8f but should be %.8f\n",i,x,RefValue[i]);
806  rc1 += 1;
807  }
808  }
809 
810  // check whether a state can be saved and restored
811  TFile *file = new TFile("random3.root","RECREATE");
812  file->SetCompressionLevel(0);
813  r.Write("r");
814  delete file;
815  file = new TFile("random3.root");
816  TRandom3 *rs = (TRandom3*) file->Get("r");
817  for (i=0;i<1000;i++) {
818  if (r.Rndm() - rs->Rndm() != 0) rc2 += 1;
819  }
820  if (rc2 != 0) printf("state restoration failed\n");
821 
822  return rc1 + rc2;
823 }
824 
825 
826 void testrandom()
827 {
828  testRandom3();
829  testAll();
830 }
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:785
double dist(Rotation3D const &r1, Rotation3D const &r2)
Definition: 3DDistances.cxx:48
virtual void SetParameters(const Double_t *params)
Definition: TF1.h:638
virtual Double_t GetRandom()
Return a random number following this function shape.
Definition: TF1.cxx:2074
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:489
Random number generator class based on M.
Definition: TRandom3.h:27
void Start(Bool_t reset=kTRUE)
Start the stopwatch.
Definition: TStopwatch.cxx:58
virtual Double_t Rndm()
Machine independent random number generator.
Definition: TRandom3.cxx:100
float Float_t
Definition: RtypesCore.h:53
virtual Int_t Binomial(Int_t ntot, Double_t prob)
Generates a random integer N according to the binomial law.
Definition: TRandom.cxx:200
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:263
Random number generator class based on the maximally quidistributed combined Tausworthe generator b...
Definition: TRandom2.h:27
virtual void RndmArray(Int_t n, Float_t *array)
Return an array of n random numbers uniformly distributed in ]0,1].
Definition: TRandom.cxx:577
A ROOT file is a suite of consecutive data records (TKey instances) with a well defined format...
Definition: TFile.h:48
#define N
Double_t CpuTime()
Stop the stopwatch (if it is running) and return the cputime (in seconds) passed between the start an...
Definition: TStopwatch.cxx:125
TRandomGen< ROOT::Math::MixMaxEngine< 240, 0 > > TRandomMixMax
MIXMAX generator based on a state of N=240.
Definition: TRandomGen.h:100
int Int_t
Definition: RtypesCore.h:41
Short_t Abs(Short_t d)
Definition: TMathBase.h:120
Double_t x[n]
Definition: legend1.C:17
The Ranlux Random number generator class
Definition: TRandom1.h:27
This is the base class for the ROOT Random number generators.
Definition: TRandom.h:27
virtual void RndmArray(Int_t n, Float_t *array)
Return an array of n random numbers uniformly distributed in ]0,1].
Definition: TRandomGen.h:61
TRandomGen< ROOT::Math::MixMaxEngine< 17, 0 > > TRandomMixMax17
MIXMAX generator based on a state of N=17.
Definition: TRandomGen.h:111
virtual Double_t Rndm()
Machine independent random number generator.
Definition: TRandom.cxx:541
virtual Double_t Rndm()
Machine independent random number generator.
Definition: TRandomGen.h:60
ROOT::R::TRInterface & r
Definition: Object.C:4
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:133
R__EXTERN TRandom * gRandom
Definition: TRandom.h:62
TUnuran class.
Definition: TUnuran.h:79
Double_t y[n]
Definition: legend1.C:17
you should not use this method at all Int_t Int_t Double_t Double_t Double_t e
Definition: TRolke.cxx:630
TUnuranContDist class describing one dimensional continuous distribution.
Definition: file.py:1
1-Dim function class
Definition: TF1.h:211
TF1 * f1
Definition: legend1.C:11
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:125
virtual Int_t Poisson(Double_t mean)
Generates a random integer N according to a Poisson law.
Definition: TRandom.cxx:391
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:369
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:141
virtual Double_t Exp(Double_t tau)
Returns an exponential deviate.
Definition: TRandom.cxx:240
Stopwatch class.
Definition: TStopwatch.h:28