I have a sort -g k9 command on a file that gives me this in the bash standard output:
55.19 645 156 15 9 520 58 702 0.0 661
55.50 636 159 16 9 520 58 693 0.0 654
55.19 645 156 15 9 520 58 702 0.0 658
56.52 644 147 16 9 520 59 701 0.0 669
55.97 645 151 15 9 520 65 709 0.0 672
55.97 645 151 15 9 520 65 709 4e-124 674
28.32 671 301 32 1 507 48 702 3e-49 183
28.32 671 301 32 1 507 47 701 3e-49 183
31.40 516 247 24 86 507 196 698 1e-46 176
31.41 519 243 25 86 507 196 698 5e-46 175
27.72 588 290 26 19 481 98 675 2e-39 154
30.56 337 170 17 101 413 302 598 5e-20 96.3
30.56 337 170 17 101 413 302 598 8e-20 95.5
I would like to cut my data based on the 9th column. The idea would be to compare the value of the 9th column on line i, divide it by the value of the 9th column on line i+1, and if the ratio is 0 OR 0/0 OR > 1e-50, line i and i+1 are kept. As soon as one of these conditions is not filled, stop reading. The desired output would be:
55.19 645 156 15 9 520 58 702 0.0 661
55.50 636 159 16 9 520 58 693 0.0 654
55.19 645 156 15 9 520 58 702 0.0 658
56.52 644 147 16 9 520 59 701 0.0 669
55.97 645 151 15 9 520 65 709 0.0 672
55.97 645 151 15 9 520 65 709 4e-124 674
I can obtain this output with head -n 6 but this is obviously not based on the condition on values in the 9th column. Please note that the values are in 'scientific' format.
I know how to do this in Python (write the standard output to a file, calculate ratios, etc.) but for commodity reasons I'd prefer a shell-based solution (with awk or sort for instance) although I don't know if that's possible. Thanks for your help!
Just exit the script when the condition is not accomplished; otherwise, print the previous line and store the 9th field to compare on the next loop:
$ awk '($9 && prev/$9>1e-50) {exit} {print stored; prev=$9; stored=$0}' file
55.19 645 156 15 9 520 58 702 0.0 661
55.50 636 159 16 9 520 58 693 0.0 654
55.19 645 156 15 9 520 58 702 0.0 658
56.52 644 147 16 9 520 59 701 0.0 669
55.97 645 151 15 9 520 65 709 0.0 672
55.97 645 151 15 9 520 65 709 4e-124 674
Related
Problem
I'm running an executable cp2k installed on HPC cluster using mpich-3.2. The output from the executable is printed in an out file. The problem is, that there is no output in the out file after some steps are printed, but when I see the status of my job on the cluster, it turns out that it is still running. Basically, the problem is that my job is still running, but the output is not getting printed.
Script
I'm using the following job script:
#!/bin/bash
#PBS -N test
#PBS -o test.log
#PBS -j oe
#PBS -l nodes=2:ppn=20
#PBS -q mini
#PBS -l walltime=2:00:00
cd $PBS_O_WORKDIR
echo Master process running on `hostname`
echo Directory is `pwd`
echo PBS has allocated the following nodes:
echo `cat $PBS_NBODEFILE`
NPROCS=`wc -l < $PBS_NODEFILE`
echo This job has allocated $NPROCS nodes
export I_MPI_FABRICS=shm:dapl
export I_MPI_PROVIDER=psm2
export I_MPI_FALLBACK=0
export KMP_AFFINITY=verbose,scatter
export OMP_NUM_THREADS=1
export I_MPI_IFACE=ib0
echo Starting executation at `date`
EXEC="/home/arshil/software/cp2k-5.1.0/exe/local/cp2k.popt"
cp $EXEC ./cp2k
mpiexec -np $NPROCS --machinefile $PBS_NODEFILE ./cp2k -i test.inp >& out
rm cp2k
echo Finished at `date`
Error
The ouput in the out file:
SCF WAVEFUNCTION OPTIMIZATION
----------------------------------- OT ---------------------------------------
Minimizer : DIIS : direct inversion
in the iterative subspace
using 7 DIIS vectors
safer DIIS on
Preconditioner : FULL_SINGLE_INVERSE : inversion of
H + eS - 2*(Sc)(c^T*H*c+const)(Sc)^T
Precond_solver : DEFAULT
stepsize : 0.08000000 energy_gap : 0.08000000
eps_taylor : 0.10000E-15 max_taylor : 4
----------------------------------- OT ---------------------------------------
Step Update method Time Convergence Total energy Change
------------------------------------------------------------------------------
1 OT DIIS 0.80E-01 21.3 0.00002878 -8797.2068024142 -8.80E+03
2 OT DIIS 0.80E-01 10.9 0.00007114 -8797.2061897209 6.13E-04
3 OT DIIS 0.80E-01 10.8 0.00001688 -8797.2073257531 -1.14E-03
As it can be seen, there is no printing after step 3 in the output file, but the job is still running in the background. Even after the walltime is over, the output file remains the same as above. Where is the output going?
The executable cp2k is used to perform quantum chemical calculations and was installed on the cluster along with mpich-3.2. All CP2K needs is an input file with extension .inp. For my case, test.inp is the input file.
&FORCE_EVAL
METHOD Quickstep
&DFT
BASIS_SET_FILE_NAME GTH_BASIS_SETS
POTENTIAL_FILE_NAME GTH_POTENTIALS
&MGRID
NGRIDS 4
CUTOFF 380
REL_CUTOFF 60
&END MGRID
&QS
METHOD GPW
MAP_CONSISTENT
EXTRAPOLATION ASPC
EXTRAPOLATION_ORDER 3
&END QS
&SCF
MAX_SCF 1000
EPS_SCF 1.0E-5
SCF_GUESS ATOMIC
&OT
PRECONDITIONER FULL_SINGLE_INVERSE
MINIMIZER DIIS
N_DIIS 7
&END OT
&PRINT
&RESTART OFF
&END RESTART
&END PRINT
&END SCF
&XC
&XC_FUNCTIONAL PBE
&END XC_FUNCTIONAL
&vdW_POTENTIAL
DISPERSION_FUNCTIONAL PAIR_POTENTIAL
&PAIR_POTENTIAL
PARAMETER_FILE_NAME dftd3.dat
TYPE DFTD3
REFERENCE_FUNCTIONAL PBE
R_CUTOFF [angstrom] 12.3
&END PAIR_POTENTIAL
&END vdW_POTENTIAL
&END XC
&END DFT
&SUBSYS
&CELL
ABC 24.6904 24.6904 24.6904
PERIODIC XYZ
&END CELL
&KIND C
BASIS_SET TZV2P-GTH
POTENTIAL GTH-PBE-q4
&END KIND
&KIND P
BASIS_SET TZV2P-GTH
POTENTIAL GTH-PBE-q5
&END KIND
&KIND H
BASIS_SET TZV2P-GTH
POTENTIAL GTH-PBE-q1
&END KIND
&KIND O
BASIS_SET TZV2P-GTH
POTENTIAL GTH-PBE-q6
&END KIND
&KIND N
BASIS_SET TZV2P-GTH
POTENTIAL GTH-PBE-q5
&END KIND
&KIND Mg
BASIS_SET TZV2P-GTH
POTENTIAL GTH-PBE-q10
&END KIND
&COLVAR
&COORDINATION
ATOMS_FROM 41
ATOMS_TO 38
R_0 [bohr] 4.5
NN 6
ND 12
&END COORDINATION
&END COLVAR
&COLVAR
&COORDINATION
ATOMS_FROM 41
ATOMS_TO 42 44 47 50 53 56 59 62 65 68 71 74 77 80 83 86 89 92 95 98 101 104 107 110 113 116 119 122 125 128 131 134 137 140 143 146 149 152 155 158 161 164 167 170 173 176 179 182 185 188 191 194 197 200 203 206 209 212 215 218 221 224 227 230 233 236 239 242 245 248 251 254 257 260 263 266 269 272 275 278 281 284 287 290 293 296 299 302 305 308 311 314 317 320 323 326 329 332 335 338 341 344 347 350 353 356 359 362 365 368 371 374 377 380 383 386 389 392 395 398 401 404 407 410 413 416 419 422 425 428 431 434 437 440 443 446 449 452 455 458 461 464 467 470 473 476 479 482 485 488 491 494 497 500 503 506 509 512 515 518 521 524 527 530 533 536 539 542 545 548 551 554 557 560 563 566 569 572 575 578 581 584 587 590 593 596 599 602 605 608 611 614 617 620 623 626 629 632 635 638 641 644 647 650 653 656 659 662 665 668 671 674 677 680 683 686 689 692 695 698 701 704 707 710 713 716 719 722 725 728 731 734 737 740 743 746 749 752 755 758 761 764 767 770 773 776 779 782 785 788 791 794 797 800 803 806 809 812 815 818 821 824 827 830 833 836 839 842 845 848 851 854 857 860 863 866 869 872 875 878 881 884 887 890 893 896 899 902 905 908 911 914 917 920 923 926 929 932 935 938 941 944 947 950 953 956 959 962 965 968 971 974 977 980 983 986 989 992 995 998 1001 1004 1007 1010 1013 1016 1019 1022 1025 1028 1031 1034 1037 1040 1043 1046 1049 1052 1055 1058 1061 1064 1067 1070 1073 1076 1079 1082 1085 1088 1091 1094 1097 1100 1103 1106 1109 1112 1115 1118 1121 1124 1127 1130 1133 1136 1139 1142 1145 1148 1151 1154 1157 1160 1163 1166 1169 1172 1175 1178 1181 1184 1187 1190 1193 1196 1199 1202 1205 1208 1211 1214 1217 1220 1223 1226 1229 1232 1235 1238 1241 1244 1247 1250 1253 1256 1259 1262 1265 1268 1271 1274 1277 1280 1283 1286 1289 1292 1295 1298 1301 1304 1307 1310 1313 1316 1319 1322 1325 1328 1331 1334 1337 1340 1343 1346 1349 1352 1355 1358 1361 1364 1367 1370 1373 1376 1379 1382 1385 1388 1391 1394 1397 1400 1403 1406 1409 1412 1415 1418 1421 1424 1427 1430 1433 1436 1439 1442 1445 1448 1451 1454 1457
ATOMS_TO 1460 1463 1466 1469 1472 1475 1478 1481 1484 1487 1490 1493 1496 1499 1502 1505
R_0 [bohr] 4.5
NN 6
ND 12
&END COORDINATION
&END COLVAR
&END SUBSYS
&END FORCE_EVAL
&GLOBAL
PROJECT test
RUN_TYPE MD
PRINT_LEVEL LOW
&END GLOBAL
&MOTION
&MD
ENSEMBLE NVT
STEPS 100000
TIMESTEP 0.5
TEMPERATURE 310
TEMP_TOL 100
&THERMOSTAT
&NOSE
LENGTH 3
YOSHIDA 3
TIMECON 100.0
MTS 2
&END NOSE
&END
&PRINT
&ENERGY
&EACH
MD 10
&END
&END
&PROGRAM_RUN_INFO
&EACH
MD 100
&END
&END
FORCE_LAST
&END PRINT
&END MD
&FREE_ENERGY
&METADYN
DO_HILLS
LAGRANGE .TRUE.
NT_HILLS 40
WW [kcalmol] 1
TEMPERATURE 310
TEMP_TOL 10
&METAVAR
SCALE 0.05
COLVAR 1
MASS 50
LAMBDA 2
&WALL
POSITION 0.0
TYPE QUARTIC
&QUARTIC
DIRECTION WALL_MINUS
K 10.0
&END
&END
&END METAVAR
&METAVAR
SCALE 0.05
COLVAR 2
MASS 50
LAMBDA 2
&WALL
POSITION 0.0
TYPE QUARTIC
&QUARTIC
DIRECTION WALL_MINUS
K 10.0
&END
&END
&END METAVAR
&PRINT
&COLVAR
COMMON_ITERATION_LEVELS 3
&EACH
MD 1
&END
&END
&HILLS
COMMON_ITERATION_LEVELS 3
&EACH
MD 1
&END
&END
&END
&END METADYN
&END
&PRINT
&TRAJECTORY
&EACH
MD 1
&END
&END
&VELOCITIES OFF
&END
&RESTART
&EACH
MD 20
&END
ADD_LAST NUMERIC
&END
&RESTART_HISTORY
&EACH
MD 2000
&END
&END
&END
&END MOTION
&EXT_RESTART
RESTART_FILE_NAME NVT-1.restart
RESTART_COUNTERS .FALSE.
&END
The problem in my opinion is not with the input file. It has got to do something with mpich-3.2. I would really appreciate some help.
This may be something similar going on / solutions that can be used here: Python "print" not working when embedded into MPI program It is not perfect as you are not using python however it may help.
At a basic level MPI launches many processes - but only the command that launches it has access to stdio etc. The redirect at the end of the line starting with mpiexec sends the stdout of mpiexec to a file. The output from your script is buffered by mpiexec until the processes end (either they complete or they are stopped).
Where the output is going is a good question and may require changes in test.np or some other way of shutting down (you mention you were out of wall time). I'm looking to solve the same problem - and will update this (if) I find an answer.
Also the output from different processes started by mpi can arrive in random order. I do not care about this but if you do you may need to pass the messages back to some common thread which sorts their order.
I'm trying to generate a zobrist key for transposition tables in my chess engine.
Here's how I'm generating the 64 bit numbers,
as show here: How to generate 64 bit random numbers?
typedef unsigned long long U64;
std::random_device rd;
std::mt19937_64 mt(rd());
std::uniform_int_distribution<U64> dist(std::llround(std::pow(2,61)),
std::llround(std::pow(2,62)));
rand function:
U64 ZobristH::random64()
{
U64 ranUI = dist(mt);
return ranUI;
}
In order to try and make sure i'm generating random enough numbers I'm using a test distribution function I found online that looks like this (will later input data into excel and look at distribution):
int sampleSize = 2000;
int distArray[sampleSize];
int t = 0;
while (t < 10)
{
for (int i = 0; i < 10000; i++)
{
distArray[(int)(random64() % (sampleSize / 2))]++;
}
t++;
}
for (int i = 0; i < sampleSize; i++)
{
std::cout << distArray[i] << ", ";
}
the results I'm getting look a little something like this:
416763345, 417123246, 7913280, 7914356, 417726722, 417726718, 19, 83886102,
77332499, 14
Are these the decimal representation of binary numbers below 1000? Or am I doing something completely wrong?
Okay I did this to check out the distribution of random numbers; you can run this short program to generate a text file to look to see what values you are getting. Instead of using a function call I just used a lambda within the for loop and instead of setting the values into the array I wrote the values out to the text file before and after the post increment.
#include <iostream>
#include <fstream>
#include <iomanip>
#include <random>
#include <functional> // may not need - included in almost all of my apps
#include <algorithm> // same as above
typedef unsigned long long U64;
int main( int argc, char** argv ) {
std::random_device rd;
std::mt19937_64 mt( rd() );
std::uniform_int_distribution<U64> dist( std::llround( std::pow( 2, 61 ) ),
std::llround( std::pow( 2, 62 ) ) );
auto lambda = [&] { return dist(mt); };
const int sampleSize = 2000;
// int distArray[sampleSize];
int t = 0;
std::ofstream file( "samples.txt" );
while ( t < 10 ) {
file << "Sample: " << (t+1) << "\n";
for ( int i = 0; i < 10000; i++ ) {
auto val = static_cast<int>( (lambda() % (sampleSize / 2)) );
file << std::setw(5) << i << ": " << std::setw(6) << val << "\t"
<< std::setw(6) << val++ << "\n";
// distArray[...]
}
file << "\n\n";
t++;
}
file.close();
/* for ( int i = 0; i < sampleSize; i++ ) {
std::cout << distArray[i] << "\n";
}*/
// Quick & Dirty Way TO Pause The Console
std::cout << "\nPress any key and enter to quit.\n";
char c;
std::cin >> c;
return 0;
}
Then check out the text file that this program generates and if you scroll through the file you will see the distributions. The first column is the value before the post increment and the second column is after. The largest possible value before the post increment that I have seen is 1,000 and after the post increment is 999. I've built and ran this for both 32 & 64 bit platform versions and have seen similar results for the distributions and that they indeed have a uniform distribution.
Sample.txt - Small Version About 1,000 Entries Out The 1st Sample Set
Sample: 1
0: 342 341
1: 517 516
2: 402 401
3: 741 740
4: 238 237
5: 557 556
6: 35 34
7: 572 571
8: 205 204
9: 353 352
10: 301 300
11: 65 64
12: 223 222
13: 647 646
14: 185 184
15: 535 534
16: 97 96
17: 843 842
18: 716 715
19: 294 293
20: 485 484
21: 648 647
22: 406 405
23: 250 249
24: 245 244
25: 915 914
26: 888 887
27: 986 985
28: 345 344
29: 493 492
30: 654 653
31: 860 859
32: 921 920
33: 526 525
34: 793 792
35: 503 502
36: 939 938
37: 802 801
38: 142 141
39: 806 805
40: 540 539
41: 778 777
42: 787 786
43: 884 883
44: 109 108
45: 842 841
46: 794 793
47: 279 278
48: 821 820
49: 112 111
50: 438 437
51: 402 401
52: 69 68
53: 396 395
54: 196 195
55: 655 654
56: 859 858
57: 674 673
58: 417 416
59: 331 330
60: 632 631
61: 210 209
62: 641 640
63: 737 736
64: 838 837
65: 592 591
66: 562 561
67: 883 882
68: 750 749
69: 726 725
70: 253 252
71: 660 659
72: 57 56
73: 401 400
74: 919 918
75: 851 850
76: 345 344
77: 25 24
78: 300 299
79: 781 780
80: 695 694
81: 220 219
82: 378 377
83: 471 470
84: 281 280
85: 945 944
86: 536 535
87: 407 406
88: 431 430
89: 745 744
90: 32 31
91: 389 388
92: 358 357
93: 582 581
94: 820 819
95: 622 621
96: 459 458
97: 233 232
98: 594 593
99: 509 508
100: 260 259
101: 152 151
102: 148 147
103: 137 136
104: 945 944
105: 244 243
106: 968 967
107: 54 53
108: 420 419
109: 58 57
110: 678 677
111: 715 714
112: 780 779
113: 834 833
114: 241 240
115: 669 668
116: 722 721
117: 608 607
118: 805 804
119: 155 154
120: 220 219
121: 520 519
122: 740 739
123: 184 183
124: 198 197
125: 247 246
126: 115 114
127: 520 519
128: 457 456
129: 864 863
130: 659 658
131: 511 510
132: 718 717
133: 119 118
134: 588 587
135: 113 112
136: 518 517
137: 164 163
138: 375 374
139: 866 865
140: 382 381
141: 526 525
142: 621 620
143: 680 679
144: 147 146
145: 712 711
146: 408 407
147: 486 485
148: 7 6
149: 203 202
150: 741 740
151: 290 289
152: 810 809
153: 960 959
154: 449 448
155: 683 682
156: 997 996
157: 454 453
158: 131 130
159: 427 426
160: 157 156
161: 3 2
162: 427 426
163: 554 553
164: 806 805
165: 228 227
166: 431 430
167: 174 173
168: 845 844
169: 121 120
170: 397 396
171: 770 769
172: 17 16
173: 761 760
174: 736 735
175: 629 628
176: 772 771
177: 417 416
178: 739 738
179: 226 225
180: 301 300
181: 217 216
182: 746 745
183: 344 343
184: 607 606
185: 927 926
186: 428 427
187: 385 384
188: 287 286
189: 537 536
190: 705 704
191: 649 648
192: 127 126
193: 252 251
194: 160 159
195: 390 389
196: 282 281
197: 66 65
198: 659 658
199: 844 843
200: 358 357
201: 360 359
202: 872 871
203: 495 494
204: 695 694
205: 988 987
206: 969 968
207: 641 640
208: 799 798
209: 30 29
210: 109 108
211: 675 674
212: 345 344
213: 309 308
214: 807 806
215: 283 282
216: 457 456
217: 193 192
218: 972 971
219: 330 329
220: 914 913
221: 508 507
222: 624 623
223: 254 253
224: 342 341
225: 69 68
226: 918 917
227: 551 550
228: 148 147
229: 645 644
230: 905 904
231: 503 502
232: 980 979
233: 881 880
234: 137 136
235: 202 201
236: 808 807
237: 988 987
238: 497 496
239: 506 505
240: 576 575
241: 671 670
242: 874 873
243: 217 216
244: 808 807
245: 741 740
246: 14 13
247: 206 205
248: 894 893
249: 180 179
250: 4 3
251: 27 26
252: 62 61
253: 203 202
254: 392 391
255: 868 867
256: 673 672
257: 881 880
258: 664 663
259: 831 830
260: 293 292
261: 916 915
262: 860 859
263: 487 486
264: 642 641
265: 161 160
266: 881 880
267: 233 232
268: 423 422
269: 12 11
270: 398 397
271: 993 992
272: 323 322
273: 878 877
274: 114 113
275: 42 41
276: 58 57
277: 398 397
278: 878 877
279: 64 63
280: 873 872
281: 841 840
282: 506 505
283: 412 411
284: 545 544
285: 887 886
286: 17 16
287: 504 503
288: 350 349
289: 772 771
290: 16 15
291: 597 596
292: 553 552
293: 25 24
294: 324 323
295: 242 241
296: 580 579
297: 479 478
298: 702 701
299: 640 639
300: 173 172
301: 918 917
302: 678 677
303: 714 713
304: 258 257
305: 97 96
306: 304 303
307: 80 79
308: 394 393
309: 940 939
310: 985 984
311: 651 650
312: 42 41
313: 179 178
314: 672 671
315: 915 914
316: 160 159
317: 332 331
318: 887 886
319: 370 369
320: 850 849
321: 730 729
322: 395 394
323: 889 888
324: 114 113
325: 505 504
326: 381 380
327: 578 577
328: 762 761
329: 896 895
330: 793 792
331: 295 294
332: 488 487
333: 599 598
334: 182 181
335: 25 24
336: 623 622
337: 396 395
338: 898 897
339: 981 980
340: 645 644
341: 806 805
342: 205 204
343: 404 403
344: 234 233
345: 36 35
346: 659 658
347: 285 284
348: 62 61
349: 608 607
350: 632 631
351: 825 824
352: 585 584
353: 685 684
354: 14 13
355: 828 827
356: 720 719
357: 871 870
358: 88 87
359: 716 715
360: 879 878
361: 650 649
362: 464 463
363: 898 897
364: 930 929
365: 194 193
366: 997 996
367: 105 104
368: 776 775
369: 398 397
370: 962 961
371: 434 433
372: 954 953
373: 548 547
374: 989 988
375: 943 942
376: 229 228
377: 866 865
378: 554 553
379: 567 566
380: 379 378
381: 564 563
382: 738 737
383: 468 467
384: 660 659
385: 693 692
386: 784 783
387: 739 738
388: 662 661
389: 474 473
390: 545 544
391: 958 957
392: 703 702
393: 316 315
394: 571 570
395: 95 94
396: 497 496
397: 672 671
398: 676 675
399: 821 820
400: 368 367
401: 7 6
402: 817 816
403: 221 220
404: 839 838
405: 578 577
406: 635 634
407: 453 452
408: 70 69
409: 764 763
410: 78 77
411: 968 967
412: 295 294
413: 483 482
414: 392 391
415: 23 22
416: 389 388
417: 678 677
418: 150 149
419: 863 862
420: 677 676
421: 676 675
422: 455 454
423: 405 404
424: 126 125
425: 753 752
426: 821 820
427: 328 327
428: 773 772
429: 596 595
430: 645 644
431: 829 828
432: 377 376
433: 444 443
434: 813 812
435: 395 394
436: 794 793
437: 641 640
438: 98 97
439: 827 826
440: 824 823
441: 681 680
442: 736 735
443: 288 287
444: 560 559
445: 781 780
446: 556 555
447: 327 326
448: 820 819
449: 859 858
450: 686 685
451: 919 918
452: 267 266
453: 128 127
454: 583 582
455: 446 445
456: 783 782
457: 712 711
458: 378 377
459: 367 366
460: 52 51
461: 316 315
462: 780 779
463: 398 397
464: 435 434
465: 788 787
466: 380 379
467: 235 234
468: 748 747
469: 429 428
470: 91 90
471: 675 674
472: 853 852
473: 674 673
474: 277 276
475: 179 178
476: 264 263
477: 511 510
478: 514 513
479: 979 978
480: 845 844
481: 728 727
482: 904 903
483: 874 873
484: 750 749
485: 659 658
486: 376 375
487: 713 712
488: 393 392
489: 538 537
490: 896 895
491: 879 878
492: 347 346
493: 819 818
494: 210 209
495: 707 706
496: 869 868
497: 319 318
498: 832 831
499: 498 497
500: 71 70
501: 290 289
502: 861 860
503: 295 294
504: 888 887
505: 515 514
506: 222 221
507: 661 660
508: 813 812
509: 969 968
510: 547 546
511: 900 899
512: 58 57
513: 805 804
514: 428 427
515: 453 452
516: 23 22
517: 969 968
518: 718 717
519: 775 774
520: 395 394
521: 521 520
522: 522 521
523: 465 464
524: 317 316
525: 216 215
526: 254 253
527: 696 695
528: 677 676
529: 21 20
530: 318 317
531: 301 300
532: 142 141
533: 877 876
534: 486 485
535: 981 980
536: 516 515
537: 254 253
538: 328 327
539: 385 384
540: 2 1
541: 405 404
542: 387 386
543: 794 793
544: 48 47
545: 641 640
546: 814 813
547: 981 980
548: 354 353
549: 281 280
550: 561 560
551: 683 682
552: 247 246
553: 739 738
554: 370 369
555: 799 798
556: 680 679
557: 915 914
558: 638 637
559: 254 253
560: 705 704
561: 320 319
562: 640 639
563: 487 486
564: 47 46
565: 852 851
566: 749 748
567: 419 418
568: 300 299
569: 507 506
570: 141 140
571: 972 971
572: 895 894
573: 988 987
574: 279 278
575: 268 267
576: 392 391
577: 530 529
578: 679 678
579: 855 854
580: 246 245
581: 645 644
582: 624 623
583: 417 416
584: 203 202
585: 30 29
586: 9 8
587: 585 584
588: 573 572
589: 471 470
590: 504 503
591: 290 289
592: 588 587
593: 230 229
594: 351 350
595: 651 650
596: 615 614
597: 502 501
598: 352 351
599: 472 471
// 600 - 699 omitted to make space to fit answer
700: 247 246
701: 894 893
702: 809 808
703: 382 381
704: 81 80
705: 574 573
706: 507 506
707: 508 507
708: 569 568
709: 947 946
710: 384 383
711: 14 13
712: 627 626
713: 951 950
714: 825 824
715: 657 656
716: 206 205
717: 598 597
718: 300 299
719: 266 265
720: 909 908
721: 206 205
722: 126 125
723: 841 840
724: 586 585
725: 348 347
726: 100 99
727: 361 360
728: 695 694
729: 556 555
730: 66 65
731: 5 4
732: 686 685
733: 488 487
734: 149 148
735: 622 621
736: 476 475
737: 488 487
738: 371 370
739: 331 330
740: 965 964
741: 141 140
742: 396 395
743: 917 916
744: 31 30
745: 924 923
746: 283 282
747: 369 368
748: 519 518
749: 830 829
750: 688 687
751: 374 373
752: 41 40
753: 418 417
754: 766 765
755: 854 853
756: 453 452
757: 521 520
758: 640 639
759: 185 184
760: 41 40
761: 125 124
762: 723 722
763: 341 340
764: 142 141
765: 754 753
766: 459 458
767: 899 898
768: 166 165
769: 374 373
770: 572 571
771: 304 303
772: 352 351
773: 235 234
774: 879 878
775: 736 735
776: 576 575
777: 56 55
778: 102 101
779: 170 169
780: 208 207
781: 135 134
782: 919 918
783: 599 598
784: 37 36
785: 997 996
786: 922 921
787: 502 501
788: 29 28
789: 173 172
790: 54 53
791: 601 600
792: 535 534
793: 64 63
794: 723 722
795: 491 490
796: 685 684
797: 58 57
798: 272 271
799: 261 260
800: 81 80
801: 149 148
802: 129 128
803: 712 711
804: 377 376
805: 151 150
806: 514 513
807: 14 13
808: 838 837
809: 347 346
810: 517 516
811: 442 441
812: 264 263
813: 883 882
814: 447 446
815: 140 139
816: 195 194
817: 841 840
818: 218 217
819: 858 857
820: 28 27
821: 222 221
822: 223 222
823: 906 905
824: 873 872
825: 492 491
826: 826 825
827: 738 737
828: 307 306
829: 185 184
830: 525 524
831: 449 448
832: 646 645
833: 686 685
834: 942 941
835: 433 432
836: 881 880
837: 824 823
838: 641 640
839: 290 289
840: 897 896
841: 4 3
842: 124 123
843: 679 678
844: 524 523
845: 424 423
846: 282 281
847: 625 624
848: 414 413
849: 647 646
850: 129 128
851: 395 394
852: 720 719
853: 318 317
854: 262 261
855: 402 401
856: 413 412
857: 139 138
858: 549 548
859: 472 471
860: 162 161
861: 605 604
862: 67 66
863: 980 979
864: 465 464
865: 912 911
866: 219 218
867: 648 647
868: 619 618
869: 331 330
870: 625 624
871: 360 359
872: 425 424
873: 935 934
874: 89 88
875: 641 640
876: 535 534
877: 404 403
878: 966 965
879: 27 26
880: 281 280
881: 637 636
882: 57 56
883: 152 151
884: 156 155
885: 813 812
886: 340 339
887: 181 180
888: 921 920
889: 306 305
890: 101 100
891: 178 177
892: 417 416
893: 845 844
894: 904 903
895: 295 294
896: 346 345
897: 654 653
898: 357 356
899: 929 928
900: 195 194
901: 499 498
902: 377 376
903: 727 726
904: 570 569
905: 853 852
906: 71 70
907: 580 579
908: 642 641
909: 889 888
910: 559 558
911: 134 133
912: 324 323
913: 120 119
914: 991 990
915: 6 5
916: 708 707
917: 347 346
918: 929 928
919: 454 453
920: 636 635
921: 218 217
922: 739 738
923: 715 714
924: 87 86
925: 782 781
926: 670 669
927: 845 844
928: 79 78
929: 730 729
930: 58 57
931: 216 215
932: 711 710
933: 898 897
934: 871 870
935: 388 387
936: 389 388
937: 944 943
938: 927 926
939: 88 87
940: 617 616
941: 940 939
942: 948 947
943: 927 926
944: 646 645
945: 125 124
946: 615 614
947: 846 845
948: 705 704
949: 998 997
950: 304 303
951: 346 345
952: 675 674
953: 783 782
954: 129 128
955: 69 68
956: 17 16
957: 646 645
958: 559 558
959: 62 61
960: 807 806
961: 571 570
962: 54 53
963: 297 296
964: 771 770
965: 972 971
966: 829 828
967: 786 785
968: 650 649
969: 101 100
970: 705 704
971: 690 689
972: 365 364
973: 304 303
974: 82 81
975: 776 775
976: 495 494
977: 586 585
978: 556 555
979: 77 76
980: 640 639
981: 161 160
982: 910 909
983: 46 45
984: 43 42
985: 162 161
986: 514 513
987: 654 653
988: 668 667
989: 126 125
990: 254 253
991: 133 132
992: 398 397
993: 993 992
994: 357 356
995: 298 297
996: 519 518
997: 904 903
998: 382 381
999: 28 27
1000: 19 18
1001: 939 938
1002: 868 867
1003: 888 887
1004: 576 575
1005: 183 182
1006: 174 173
1007: 679 678
1008: 831 830
1009: 464 463
1010: 876 875
1011: 738 737
1012: 447 446
1013: 385 384
1014: 271 270
1015: 38 37
1016: 28 27
1017: 451 450
1018: 162 161
1019: 847 846
1020: 430 429
1021: 849 848
1022: 207 206
1023: 196 195
1024: 42 41
1025: 709 708
1026: 557 556
1027: 173 172
1028: 788 787
1029: 160 159
1030: 535 534
1031: 555 554
1032: 252 251
1033: 111 110
1034: 476 475
1035: 780 779
1036: 44 43
1037: 190 189
1038: 443 442
1039: 655 654
1040: 7 6
1041: 845 844
1042: 856 855
1043: 274 273
1044: 933 932
1045: 336 335
1046: 185 184
1047: 580 579
1048: 807 806
1049: 286 285
1050: 409 408
1051: 347 346
1052: 461 460
1053: 624 623
1054: 378 377
1055: 903 902
1056: 483 482
1057: 838 837
1058: 809 808
1059: 919 918
1060: 544 543
1061: 458 457
1062: 121 120
1063: 192 191
1064: 126 125
1065: 843 842
1066: 927 926
1067: 390 389
1068: 567 566
1069: 1000 999
Entry 1069 is the first occurrence in this sample set to reach 1,000. I've ran this about a dozen times both in 32bit and 64bit modes and I did not see any value go above 1,000.
I'm not sure but I think that this line in your code is what is giving you your problem(s):
distArray[(int)(random64() % (sampleSize / 2))]++;
Below is a full section of bytes stream I got from Exchange2013 server after sending activesync command 'itemoperations' from iPhone.
31 139 8 0 0 0 0 0 4 0 237 189 7 96 28 73 150 37 38 47 109 202 123 127 74 245 74 215 224 116 161 8 128 96 19 36 216 144 64 16 236 193 136 205 230 146 236 29 105 71 35 41 171 42 129 202 101 86 101 93 102 22 64 204 237 157 188 247 222 123 239 189 247 222 123 239 189 247 186 59 157 78 39 247 223 255 63 92 102 100 1 108 246 206 74 218 201 158 33 128 170 200 31 63 126 124 31 63 34 126 237 95 243 167 127 141 95 227 183 58 253 226 215 222 253 53 126 205 23 207 248 199 175 241 155 255 196 175 125 255 119 191 151 61 220 167 127 240 247 111 245 123 253 26 191 249 119 127 237 54 127 215 222 93 149 89 177 196 71 207 127 237 215 95 61 124 253 229 79 31 191 251 226 233 233 15 126 234 167 143 175 190 248 233 183 87 95 60 61 198 255 119 190 124 243 19 59 47 62 255 226 7 191 207 155 159 250 233 23 139 223 231 222 139 167 211 221 23 63 248 226 250 167 126 250 247 217 161 191 247 126 234 233 239 115 255 197 226 171 189 159 250 233 239 44 94 252 244 23 244 115 122 253 226 167 207 246 190 120 67 127 63 125 187 67 237 174 95 44 78 247 94 188 249 125 126 240 226 7 63 177 75 144 232 253 179 123 47 126 154 127 18 220 47 222 125 177 248 234 7 218 159 254 255 212 251 221 252 127 26 126 255 6 248 30 95 253 212 27 243 25 193 249 193 219 31 124 241 211 223 41 191 248 193 233 15 8 151 125 134 251 70 254 254 242 233 23 215 95 60 125 50 255 125 246 126 159 61 250 219 194 122 241 148 218 253 128 218 253 244 23 192 237 7 47 8 159 23 63 125 122 77 227 218 37 24 10 231 39 8 206 23 87 244 61 189 251 157 183 47 126 250 43 140 135 218 31 83 59 124 126 76 99 195 223 103 123 47 208 15 141 235 139 31 224 221 51 130 71 125 124 206 116 217 121 241 131 175 238 125 241 131 87 229 139 207 127 31 162 171 224 255 133 197 95 255 14 199 255 238 133 163 129 155 31 249 158 254 254 170 67 163 83 31 30 254 255 217 175 241 107 226 249 127 0 225 220 243 27 28 2 0 0
I don't know why it is not normal and expect it sholud start like this:
3 1 106 0 0 20 69 77 3 49 0 1 78 70 77 3 49 0 1 0 17 81 3 82 103 65 65 65 65 65 117 50 72 120 85 112 65 ..........
I think the response must have been encrypted, but what's the encryption algorithm?
Will be very appreciated for any ideas.
I have got the answer, the stream 31 139 8 0 0 0 0 0 4 0 237 189 7 96 28 73 150 37 ...... has been compressed by Gzip
I am looking at all possible paths through a graph. I have written a DFS algorithm that finds all these paths. I want to make sure that my algorithm works correctly and that no two paths are identical. My algorithm returns a list that looks as follows:
....
[[2770]]
[1] 1 2 3 52 53 54 55 56 57 58 59 60 12 11 10 9 8 78 79 80 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129
[38] 130 131 132 133 134 137 138 139 140 141 142 143 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166
[[2771]]
[1] 1 2 3 52 53 54 55 56 57 58 59 60 12 11 10 9 8 78 79 80 113 114 115 143 144 145 146 147 148 149 150 151 152 153 154 155 156
[38] 157 158 159 160 161 162 163 164 165 166
[[2772]]
[1] 1 2 3 52 53 54 55 56 57 58 59 60 12 11 10 9 8 78 79 80 113 114 115 143 150 151 152 153 154 155 156 157 158 159 160 161 162
[38] 163 164 165 166
As you can see, the list is 2772 elements long. This means there are 2,772 paths through this graph. How can I easily compare all the list elements to make sure there are no duplicates. Just to be clear, the same set of numbers but in a different ordering represents a different path and is not a duplicate!
Thank you for your help!
maybe something like
test<-list(1:2,3:4,5:7,1:10,3:4,4:3)
dups<-duplicated(test)
idups<-seq_along(test)[dups]
Closed. This question does not meet Stack Overflow guidelines. It is not currently accepting answers.
We don’t allow questions seeking recommendations for books, tools, software libraries, and more. You can edit the question so it can be answered with facts and citations.
Closed 2 years ago.
Improve this question
I wrote a simple genetic algorithm that can solve traveling salesman problem with 5 cities. I want to see how it does on a problem with more cities, something like 10, 25, 50, 100, but I can't find a sample date for the problem to try it on. Basically, I am looking for 2D lists or matrices with distances between cities. It would be nice if there is a solution. Where should I look?
Thank You in Advance
A well-known benchmark library for the TSP with instances ranging from as few as 14 to close to 100,000 cities is the TSPLIB. The instances have been solved to optimality, for some instances the optimal solution is also available.
Many of the instances have a real-world background such as travel been cities in Germany, Switzerland, the USA, or in the whole world. Some of the instances represent drilling problems for computer board layout There's also an instance that represents the voyage of Ulysses.
The sources I've found online are quite huge. I might be doing something wrong, but 10 places (cities) take ~0.6s and 11 places take ~7s. The smallest known-solution dataset I could find was 15 places (and considered "small", the "classical" one being 48 places) but perhaps those are for optimized (non-brute force) algorithms. In the end I made my own table with real-world cities:
m
a
a h
s h s u
t a e i g l
r a e t e s
i c r t l e b b a e
c h l a e c o e n o p
h e e r e h n r n h e
t n n d n t n g e e n
maastricht 0 29 20 21 16 31 100 12 4 31 18
aachen 29 0 15 29 28 40 72 21 29 41 12
heerlen 20 15 0 15 14 25 81 9 23 27 13
sittard 21 29 15 0 4 12 92 12 25 13 25
geleen 16 28 14 4 0 16 94 9 20 16 22
echt 31 40 25 12 16 0 95 24 36 3 37
bonn 100 72 81 92 94 95 0 90 101 99 84
hulsberg 12 21 9 12 9 24 90 0 15 25 13
kanne 4 29 23 25 20 36 101 15 0 35 18
ohe 31 41 27 13 16 3 99 25 35 0 38
epen 18 12 13 25 22 37 84 13 18 38 0
Optimal (by program): cities 0-7-4-3-9-5-2-6-1-10-8-0 = 253km
maastricht -> hulsberg -> geleen -> sittard -> ohe -> kanne -> echt
-> heerlen -> bonn -> aachen -> epen -> kanne -> maastricht
The data format readable by the program is a partial table (because it's symmetrical):
29 20 21 16 31 100 12 4 31 18
15 29 28 40 72 21 29 41 12
15 14 25 81 9 23 27 13
4 12 92 12 25 13 25
16 94 9 20 16 22
95 24 36 3 37
90 101 99 84
15 25 13
35 18
38
For me this takes ~6.7 seconds to process on a 3rd gen i7 (i7-3630QM). Program is written in C++, single-threaded and simply brute-forces the possibilities. For testing it might be more practical to remove one place, then it takes ~660ms (0.7s) which is still enough to see if code changes make much of a difference.
For next incomes, i'll paste some more "small" cases:
You can find more tests in here. but the file is ".tsp" extension and you should do a simple parse that translate to the matrix of distances.
(distance in miles)
6 cities, expected: 1248.0
9999 64 378 519 434 200
64 9999 318 455 375 164
378 318 9999 170 265 344
519 455 170 9999 223 428
434 375 265 223 9999 273
200 164 344 428 273 9999
15 cities, expected: 1194.0
-1 141 134 152 173 289 326 329 285 401 388 366 343 305 276
141 -1 152 150 153 312 354 313 249 324 300 272 247 201 176
134 152 -1 24 48 168 210 197 153 280 272 257 237 210 181
152 150 24 -1 24 163 206 182 133 257 248 233 214 187 158
173 153 48 24 -1 160 203 167 114 234 225 210 190 165 137
289 312 168 163 160 -1 43 90 124 250 264 270 264 267 249
326 354 210 206 203 43 -1 108 157 271 290 299 295 303 287
329 313 197 182 167 90 108 -1 70 164 183 195 194 210 201
285 249 153 133 114 124 157 70 -1 141 147 148 140 147 134
401 324 280 257 234 250 271 164 141 -1 36 67 88 134 150
388 300 272 248 225 264 290 183 147 36 -1 33 57 104 124
366 272 257 233 210 270 299 195 148 67 33 -1 26 73 96
343 247 237 214 190 264 295 194 140 88 57 26 -1 48 71
305 201 210 187 165 267 303 210 147 134 104 73 48 -1 30
276 176 181 158 137 249 287 201 134 150 124 96 71 30 -1
Hugeeee 29 cities, expected: 27603
imagem: western sahara
-1 74 4110 3048 2267 974 4190 3302 4758 3044 3095 3986 5093 6407 5904 8436 6963 6694 6576 8009 7399 7267 7425 9639 9230 8320 9300 8103 7799
74 -1 4070 3000 2214 901 4138 3240 4702 2971 3021 3915 5025 6338 5830 8369 6891 6620 6502 7939 7326 7193 7351 9571 9160 8249 9231 8030 7725
4110 4070 -1 1173 1973 3496 892 1816 1417 3674 3778 2997 2877 3905 5057 5442 4991 5151 5316 5596 5728 5811 5857 6675 6466 6061 6523 6165 6164
3048 3000 1173 -1 817 2350 1172 996 1797 2649 2756 2317 2721 3974 4548 5802 4884 4887 4960 5696 5537 5546 5634 7045 6741 6111 6805 6091 5977
2267 2214 1973 817 -1 1533 1924 1189 2498 2209 2312 2325 3089 4401 4558 6342 5175 5072 5075 6094 5755 5712 5828 7573 7222 6471 7289 6374 6187
974 901 3496 2350 1533 -1 3417 2411 3936 2114 2175 3014 4142 5450 4956 7491 5990 5725 5615 7040 6430 6304 6459 8685 8268 7348 8338 7131 6832
4190 4138 892 1172 1924 3417 -1 1233 652 3086 3185 2203 1987 3064 4180 4734 4117 4261 4425 4776 4844 4922 4971 5977 5719 5228 5780 5302 5281
3302 3240 1816 996 1189 2411 1233 -1 1587 1877 1979 1321 1900 3214 3556 5175 4006 3947 3992 4906 4615 4599 4700 6400 6037 5288 6105 5209 5052
4758 4702 1417 1797 2498 3936 652 1587 -1 3286 3374 2178 1576 2491 3884 4088 3601 3818 4029 4180 4356 4469 4497 5331 5084 4645 5143 4761 4787
3044 2971 3674 2649 2209 2114 3086 1877 3286 -1 107 1360 2675 3822 2865 5890 4090 3723 3560 5217 4422 4257 4428 7000 6514 5455 6587 5157 4802
3095 3021 3778 2756 2312 2175 3185 1979 3374 107 -1 1413 2725 3852 2826 5916 4088 3705 3531 5222 4402 4229 4403 7017 6525 5451 6598 5142 4776
3986 3915 2997 2317 2325 3014 2203 1321 2178 1360 1413 -1 1315 2511 2251 4584 2981 2778 2753 4031 3475 3402 3531 5734 5283 4335 5355 4143 3897
5093 5025 2877 2721 3089 4142 1987 1900 1576 2675 2725 1315 -1 1323 2331 3350 2172 2275 2458 3007 2867 2935 2988 4547 4153 3400 4222 3376 3307
6407 6338 3905 3974 4401 5450 3064 3214 2491 3822 3852 2511 1323 -1 2350 2074 1203 1671 2041 1725 1999 2213 2173 3238 2831 2164 2901 2285 2397
5904 5830 5057 4548 4558 4956 4180 3556 3884 2865 2826 2251 2331 2350 -1 3951 1740 1108 772 2880 1702 1450 1650 4779 4197 2931 4270 2470 2010
8436 8369 5442 5802 6342 7491 4734 5175 4088 5890 5916 4584 3350 2074 3951 -1 2222 2898 3325 1276 2652 3019 2838 1244 1089 1643 1130 2252 2774
6963 6891 4991 4884 5175 5990 4117 4006 3601 4090 4088 2981 2172 1203 1740 2222 -1 684 1116 1173 796 1041 974 3064 2505 1368 2578 1208 1201
6694 6620 5151 4887 5072 5725 4261 3947 3818 3723 3705 2778 2275 1671 1108 2898 684 -1 432 1776 706 664 756 3674 3090 1834 3162 1439 1120
6576 6502 5316 4960 5075 5615 4425 3992 4029 3560 3531 2753 2458 2041 772 3325 1116 432 -1 2174 930 699 885 4064 3469 2177 3540 1699 1253
8009 7939 5596 5696 6094 7040 4776 4906 4180 5217 5222 4031 3007 1725 2880 1276 1173 1776 2174 -1 1400 1770 1577 1900 1332 510 1406 1002 1499
7399 7326 5728 5537 5755 6430 4844 4615 4356 4422 4402 3475 2867 1999 1702 2652 796 706 930 1400 -1 371 199 3222 2611 1285 2679 769 440
7267 7193 5811 5546 5712 6304 4922 4599 4469 4257 4229 3402 2935 2213 1450 3019 1041 664 699 1770 371 -1 220 3583 2970 1638 3037 1071 560
7425 7351 5857 5634 5828 6459 4971 4700 4497 4428 4403 3531 2988 2173 1650 2838 974 756 885 1577 199 220 -1 3371 2756 1423 2823 852 375
9639 9571 6675 7045 7573 8685 5977 6400 5331 7000 7017 5734 4547 3238 4779 1244 3064 3674 4064 1900 3222 3583 3371 -1 620 1952 560 2580 3173
9230 9160 6466 6741 7222 8268 5719 6037 5084 6514 6525 5283 4153 2831 4197 1089 2505 3090 3469 1332 2611 2970 2756 620 -1 1334 74 1961 2554
8320 8249 6061 6111 6471 7348 5228 5288 4645 5455 5451 4335 3400 2164 2931 1643 1368 1834 2177 510 1285 1638 1423 1952 1334 -1 1401 648 1231
9300 9231 6523 6805 7289 8338 5780 6105 5143 6587 6598 5355 4222 2901 4270 1130 2578 3162 3540 1406 2679 3037 2823 560 74 1401 -1 2023 2617
8103 8030 6165 6091 6374 7131 5302 5209 4761 5157 5142 4143 3376 2285 2470 2252 1208 1439 1699 1002 769 1071 852 2580 1961 648 2023 -1 594
7799 7725 6164 5977 6187 6832 5281 5052 4787 4802 4776 3897 3307 2397 2010 2774 1201 1120 1253 1499 440 560 375 3173 2554 1231 2617 594 -1