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akhikolla / RcppDeepState

RcppDeepState, a simple way to fuzz test code in Rcpp packages
https://akhikolla.github.io./
8 stars 2 forks source link

generate only finite values? (sometimes?) #36

Closed tdhock closed 3 years ago

tdhock commented 4 years ago

Hi @akhikolla is it true that the random generation functions (RcppDeepState_NumericVector etc) always have some nan/inf values? It seems so from the log output. e.g.

x values: -inf -4.30039e-277 nan -inf 3.91522e-233 inf inf -inf nan nan inf inf -inf -inf nan nan -inf -inf 4.04417e-245 -inf inf -inf nan nan nan -inf -inf nan nan inf -inf 1.5147e-111 -inf -inf inf inf nan -3.53791e-266 nan nan inf -3.56549e+204 nan -4.78404e+198 inf nan nan -6.90744e-23 -inf -5.38333e-174 nan nan inf -2.37436e+189 inf nan nan nan 3.09255e-187 nan -inf -inf -5.36873e+129 nan -inf inf -inf nan -4.80468e+291 -inf nan -inf -2.73599e+74 inf 5.22581e+45 nan nan -inf nan 0
y values: -inf nan nan -inf nan nan 1.54621e+305 nan -inf inf inf nan -inf -1.83297e+20 nan nan -3.12058e-208 inf nan nan inf -3.08838e-57 -9.50095e+291 1.91111e-282 -inf -inf inf inf nan inf inf inf nan inf -inf nan nan inf nan nan -inf nan nan -inf -3.49774e-124 inf nan nan nan inf nan nan 3.43469e+86 -inf nan -inf nan 1.09457e+26 inf -inf inf inf -1.07381e-204 1.21151e-120 -inf nan 3.7042e+112 -6.39816e+138 -2.69118e+237 nan nan nan -inf nan inf nan nan -2.92753e+127 inf nan -inf -inf inf -4.31656e-305 nan inf nan -1.22806e-155 0
z values: nan -inf -inf nan nan -1.25067e-210 2.40212e-95 6.74738e+155 inf nan inf nan inf inf -inf inf inf nan -2.9391e+141 -6.084e-207 -7.66514e-224 inf 3.76915e+120 1.23003e+98 -inf -4.48158e-05 -2.80807e+95 inf nan nan nan nan inf -3.80109e-230 nan -5.9527e-35 nan inf nan 4.73542e-126 3.71801e-152 -inf inf -inf inf nan -inf -3.80151e+231 -2.54146e+99 nan 6.20522e+35 -1.29686e-111 nan inf nan inf nan nan inf inf inf -inf nan 1.95989e+231 nan inf -inf nan nan 4.92815e+305 inf 0

If so can you modify them so that they sometimes include all finite (non-inf, non-nan) values?

akhikolla commented 4 years ago

I am using OneOf a lambda function to choose the inputs. When I specify OneOf(DeepState_Double, NA, NaN) - It chooses one of those values. It's the system that decides what to choose depending upon the functionality and input types.

tdhock commented 4 years ago

sure but maybe it would be interesting to use OneOf(all finite values, some finite + some Inf, some finite + some NaN, some finite + some NA, combination of all types) ?

tdhock commented 4 years ago

I am still seeing this behavior in current master...

input starts
input_data values: -inf inf -inf inf -inf -inf 2.6957e+201 -inf -inf -3.76545e-206 -inf -inf inf -1.60672e+214 -4.04269e-27 2.7096e-223 -inf nan -3.13255e-88 nan nan nan inf nan -1.4945e-144 -inf inf nan -1.30679e-21 inf inf 7.26356e-114 nan -2.67732e-99 inf nan -4.90542e+69 nan nan nan 6.31779e+72 nan nan 7.40867e-167 nan nan -2.19165e+12 1.67924e-253 -inf inf inf -inf -inf nan nan nan nan -inf inf inf nan -inf nan -inf -4.79359e-172 -1.91429e+26 nan inf inf nan inf inf inf inf -inf -inf nan nan nan -1.01917e+99 nan inf 5.03847e-187 -1.96586e-267 -inf nan -1.57985e-67 nan nan 0
input_label_start values: 1781847365 -316588954 -2147483648 -1625011973 1352603066 -413586220 -2147483648 -2147483648 -369137004 -2147483648 -2147483648 -2147483648 1621835030 -2147483648 681908452 -2147483648 -2147483648 -2147483648 174867464 -2147483648 -2147483648 -2147483648 -2147483648 -2147483648 -2100309363 -865445717 798948727 -2147483648 -2147483648 -2093104706 -1064055750 493416855
input_label_end values: -2147483648 -1132419056 1996345537 -2147483648 2010204752 -2147483648 -2147483648 1641776856 -1831539402 -2147483648
input_label_changes values: 1026839640 -640684879 1509093209 -2147483648 -2147483648 110088377 -407300339 -2147483648 -2147483648 1469250962 -925228202 -1445664793 -2147483648 -2147483648 -793438156 -2147483648 -1295398820 1573031360 -2147483648 1778249303 -2147483648 -2147483648 -2103373601 -2147483648 -2147483648 -2147483648 -2147483648 957922078 -1162786019 -2147483648 2059308111 -2147483648 -2147483648 -2147483648 -2147483648 -182630021 -690189966 -2147483648 -1238312628 -2147483648 624628709 -2147483648 1964304018 938561560 -2147483648 -2147483648 -2147483648 -962777029 -2147483648 -2147483648 -2147483648 290344343 1752357423 557367102 385897303 769159250 -2147483648 -1759173704 -1517654340 -2147483648 -2147483648 -2147483648 -2147483648 72592993 -2147483648 -2147483648
n_updates values: 212535981
penalty_unlabeled values: 2.28402e+45
penalty_labeled values: 5.38818e+167
input ends
tdhock commented 3 years ago

hi any progress?

akhikolla commented 3 years ago

Modified the input generation functions to generate finite values most of the time.

> rd <- deepstate_analyze_fun("~/extdata/LOPART/inst/testfiles/LOPART_interface")
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> rd
                                                                                                                           binaryfile
1: /home/akolla/extdata/LOPART/inst/testfiles/LOPART_interface/LOPART_interface_output/001310115c35c0b174b6d980baf72b13b36c37d8.crash
2: /home/akolla/extdata/LOPART/inst/testfiles/LOPART_interface/LOPART_interface_output/00cf8e258d7c931bfab621a336a217c1780f624f.crash
3: /home/akolla/extdata/LOPART/inst/testfiles/LOPART_interface/LOPART_interface_output/01a4f00e9091eec347d237ea4571e4be56346320.crash
      inputs              logtable
1: <list[7]> No source trace found
2: <list[7]> No source trace found
3: <list[7]> No source trace found
> rd$inputs
[[1]]
[[1]]$input_data
 [1]  -5.445125e+42  1.034473e+195  -2.194624e-39   3.202240e-95  7.144787e-295
 [6] -1.045352e+121 -4.635202e-259 -4.813551e-238  5.200153e+117   9.653992e-50
[11]  -1.692591e+55  6.423121e+102 -1.632870e+239  -7.904699e-98             NA
[16] -5.415249e+128 -9.496334e-115  -1.375819e-69   3.652437e-86  -4.199826e+95
[21] -8.584922e+195  1.822307e+149  -1.668400e-58  6.771657e-143  2.482182e+264
[26]             NA  -7.014959e-42  -1.497959e+23  5.023092e-209  6.047984e-240
[31]  3.125316e+232 -7.075239e-307  -1.253349e+40   5.924565e+71 -1.190799e+141
[36]  -4.435186e-57  6.033721e-110   1.986062e+00   8.456582e+52  1.745875e-143
[41]  6.895263e-127  -7.303105e+74   3.811473e+32   4.218756e-94  3.502579e+124
[46]  1.310714e-200             NA -5.479759e+231  8.822581e+268 -2.706878e+253
[51]  2.149976e-129             NA  -6.116944e+70  9.323646e-172  -1.125342e+93
[56]   6.490314e-35 -2.902425e-214 -3.215296e-226 -1.257669e-190  -1.114852e+57
[61] -3.033473e+205   3.099160e+11  5.761635e-139  7.967479e+150  8.453417e-185
[66] -1.086020e+164  1.478179e-254  4.670239e-284             NA

[[1]]$input_label_changes
 [1]  -293942560  1002105073  -642388841   179198938  1405186103   298036921
 [7]   757070054   941444390 -1743255853  -756103764 -1531886674  1604225202
[13]  1610148208 -1130944023 -1239298066  1058870487   890939911   158315437
[19]   553016191 -1797049612  -602184552 -1282506391 -1353623314  1852622243
[25] -2022659440  -547472128  1419280361  2075254103  -851316864  -814618241
[31] -1035899600 -1372335307 -1552038526 -1206311577 -1711138539 -1275695744
[37]   928776199  -840268145   737394649   647106249   282283243  -707912849
[43]  -801864316   720503906  1308977436  -269505766  -496241655   -50146803
[49]  -702613077  -317449283  1235239283 -1840851488  1262419002   766006288
[55]   323492112  1273699873   169331959   736605300 -2013861863  1019083399
[61]   -50937559 -1642776143  1582482089  1054919240  -141148382  2129893125
[67]  -377544923  1008315448   258826926 -2086969375  -299791828 -1206311577
[73]  -357360792 -1498255728   831370605 -1503484235  -821533870 -1547488367
[79]  -457327130   288481020  -453417845 -1412293668  1607485957   854637314
[85]  -132229989  -511169082  1173007447   478827264 -2068346065 -1968829207
[91]  2002186153  1185590078  -939468374 -2012843827  -249814003 -1502147286
[97]   798579385

[[1]]$input_label_end
integer(0)

[[1]]$input_label_start
 [1]  2108727583   812894892   -74462682   765787896  2092363075  -218404115
 [7]  1167902587  1381767119   230223421   733604134  1219710325  1464561108
[13]    22747124  1451352475   497555311   917935515  -433238511  -432523474
[19]  -343628733  -820963375  1815004611 -1331274035  1316306258 -1552128887
[25] -1447912816  -355287338  1449269542  1949366240  1589420814  1644354736
[31]  1998127643 -1788435394   423611907   294508903   917935515   579093633
[37]  1088917410  -378842527 -2074772455 -1155508012  1596381296 -1280190301
[43] -1536883002  -364230870   853003547  1109359815  1962467376   423101560
[49]  1608313106 -1899907790   649918480   104872760   386421849   667951260
[55]  -922628894   969955992 -1388074181    73428267   476396323 -1518969924
[61]  2125403814 -2143927735   923675505  -561706613  -910899507   355727409
[67] -1724623810 -1431241943  1595002847  1192306815   525594877  -637957726
[73] -1370525757 -2090273764 -1672914362  -111841448  1715353774  1331703150
[79] -1273140083   385167300  1151240135

[[1]]$n_updates
[1] 538861841

[[1]]$penalty_labeled
[1] -1.96168e-271

[[1]]$penalty_unlabeled
[1] 1.59012e-96

[[2]]
[[2]]$input_data
 [1]  3.360693e+261  -1.089856e-92  1.543337e+289  1.990277e-257  8.587880e-262
 [6]  4.818347e+120 -1.903377e-193   3.449134e-47 -1.966630e-113  7.104489e-161
[11]   3.825352e+92 -2.495372e-172  1.007209e+211   3.741694e+32  6.400233e+243
[16] -1.756817e+218   1.361804e-91   1.020744e-41 -1.946769e+274 -1.189234e+193
[21]   1.929945e-03   1.407549e+48  1.433971e+281             NA  -4.193934e+75
[26] -4.670272e+219             NA  6.717120e+227 -7.104779e-163  4.138449e-211
[31] -4.374785e-191  5.033827e-292   2.863688e-48  1.344791e-275   1.360465e+34
[36]  4.281253e+262   1.629459e-53 -3.558040e-153   5.384918e+88  4.514698e+223
[41]  1.784057e-125 -7.829707e+142             NA  -1.052090e+33             NA
[46]   1.700721e-51 -6.357185e-201  6.992089e-208  -1.512619e+85  -5.863417e-05
[51]             NA  -4.630504e-98 -1.195067e-227 -2.832050e+284  2.300159e-212
[56] -5.493617e-242 -6.817255e+258   0.000000e+00

[[2]]$input_label_changes
 [1]  1879903991  1225534453  1447306710  1061428111  -792946811   636261923
 [7]   126346744  1435853510 -1552892436  2095636946   755411052  1254357786
[13]          NA

[[2]]$input_label_end
[1] -1869590697 -1869590697

[[2]]$input_label_start
 [1]  -357692300 -1002379694  1918036506  1833045632 -1743402670  -734150396
 [7] -1984042709  1206600241 -1722898851 -1886605567  -543614132  -618017677
[13]  1050002962  -746121380  1157662604  -339100028   392487334  -258955057
[19]   700652292  -303531989  2101231184  -984241142  1429444417   -61487852
[25] -1180190039   929200481   647259411  2094874362   461130465  -772281561
[31]   713189415  -684901488  -722126324  1488153982  1204982212 -1328562485
[37]  1275636765    -6798294   447500786  -628325714 -2118337831  1864849335
[43]   -85427286 -1204194044  1092755777 -1167692844   314361580  1212783561
[49]    89498485  2113547383  -475586149 -1568014057 -1195351438 -1568014057
[55] -1995627055  1455463260   373215635   956107291 -1540639100 -1051351686
[61]   369683516  -718047905  1100689559  1540092785   163841090 -1056023195
[67]   957671931  1771009407 -1755202452 -1791898666  -855872216  -949904943
[73]   631116775

[[2]]$n_updates
[1] -981570062

[[2]]$penalty_labeled
[1] -1.73255e+16

[[2]]$penalty_unlabeled
[1] 1.34088e+125

[[3]]
[[3]]$input_data
 [1]             NA  6.122407e+141 -8.065526e-252  3.165869e+287             NA
 [6]   4.612883e-64  3.501353e+198  3.637589e-152  2.358054e+124 -6.165105e-240
[11]   1.797791e+65  -1.310990e+43             NA   0.000000e+00

[[3]]$input_label_changes
 [1]   621594665    44381909   295670277 -1612164227 -1328720802 -1093494440
 [7]   -94688792          NA -1447453013  1590984815  1947366675   -70741845
[13] -1780217517 -1230853200   -36333491  1904853530  1113638561   893784233
[19]  1501936724  1296891874   805844710 -1411279192 -1238436568 -1195949318
[25]   403217229  1336735400   833813631   -17080018    60232878  2041206575
[31]  -666085488    77237020 -1574540815  -765486844   295011087 -1864090220
[37]  2085700341   -73849645  -428055318   384763576   359639784  -834409249
[43]  -646975895  1395391951  -285969656  -639022401

[[3]]$input_label_end
 [1]  1858152314 -1000768995          NA  -702127845  -148926837  -459156209
 [7]   671339166  2006134757  1431723801 -1344719021 -1907174300  2016772208
[13]  1410267961 -1345304361  -753240501 -1364905981   -74441557  1767112440
[19] -1512874978   148672093  -360081767  1507750188  -102271065 -1935103353
[25]   952513185   439458239    83287308

[[3]]$input_label_start
 [1]  1714426738   130315114 -1174317935 -1039851915  -970521966  -385601670
 [7]  -392961878 -1728110593   791900470  -136011343          NA  1173971212
[13]   543464970  1758299217  1634073593  1679554707  1315621445  1315698484
[19]  1614468262   859157075 -1722786558   518148991  1196325035  1769029303
[25]  -620167895  1945394900   775060065  1730982913  2081555354  -195684037
[31] -1533876722    52741598   767690656 -1234864924 -1745992193   452591767
[37]   201535744

[[3]]$n_updates
[1] -155622583

[[3]]$penalty_labeled
[1] 1.05908e+225

[[3]]$penalty_unlabeled
[1] 5.54512e+283

Please let me know if this works or should I modify it more?

Rcpp::NumericVector RcppDeepState_NumericVector(){
  rand_size = DeepState_IntInRange(0,100);
  double missing_values[] = {DeepState_Double(),R_NaN,R_PosInf,R_NegInf,NA_REAL};
  Rcpp::NumericVector rand_numvec(rand_size);
  for(int i = 0 ; i < rand_size - 1 ;i++){      
    rand_numvec[i] = DeepState_Double();  
  }
  for(int i = 0 ; i < 5 ; i++){
    rand_numvec[DeepState_IntInRange(0,rand_size-1)] = NA_REAL;
  }
  return rand_numvec;
}

Rcpp::IntegerVector RcppDeepState_IntegerVector(){
  int rand_size = DeepState_IntInRange(0,100);
  int missing_values[] = {DeepState_Int(),NA_INTEGER};
  Rcpp::IntegerVector rand_intvec(rand_size);
  for(int i = 0 ; i < rand_size ;i++){
        rand_intvec[i] = DeepState_Int();
  }
  for(int i = 0 ; i < 2 ; i++){
    rand_intvec[DeepState_IntInRange(0,rand_size-1)] = OneOf(missing_values);
  }
  return rand_intvec;
}
tdhock commented 3 years ago

that looks reasonable. can you explain "most of the time" ?

tdhock commented 3 years ago

what about NaN values?

akhikolla commented 3 years ago

Yes we have all the missing values here is the output

> rd <- deepstate_analyze_fun("~/extdata/packages/BNSL/inst/testfiles/mi",5)
> rd$inputs
[[1]]
[[1]]$proc
[1] -1525461954

[[1]]$x
 [1]  8.427173e+123  1.117069e-234 -4.515790e-284   2.038697e-77 -1.288984e-151
 [6]   2.649105e+45  1.103804e-134 -3.357048e-153 -1.185950e+138 -1.882493e-113
[11] -4.308517e+232   7.435494e-38   8.583160e-18  2.245533e+257 -1.613434e+283
[16] -2.666229e+279            NaN  1.386557e+212  -2.972611e+58  7.800572e+133
[21] -1.070369e-230 -6.174936e+184  1.009144e-112   3.947265e+60  -9.824733e+55
[26]   2.087360e+61  5.652771e+212 -1.357260e-250  3.808048e-129  1.418266e+211
[31] -2.717473e+175 -1.144652e-295  7.226323e-161  8.255508e+161 -1.969129e+135
[36]  4.138561e-303 -5.127045e-191  -7.823581e-71 -8.542369e+276  1.201313e-188
[41] -2.968837e-256  9.996111e-213  1.712621e-188   1.222629e-25            Inf
[46]  -3.187003e-63   8.887075e-71  -4.580651e-69 -1.523949e-127  1.927809e+127
[51] -1.801650e+125   1.942710e-75   4.986202e-79  -1.586607e+06   6.109465e+85
[56] -4.351218e-160 -1.904249e-200  -3.812914e+14  2.040737e-112 -5.106116e+223
[61] -4.202567e+151  1.108642e-220            NaN -1.557560e-307            NaN

[[1]]$y
 [1] -5.880240e+204  1.693315e-157  2.185051e-123  2.656044e+158   7.822259e+92
 [6]   4.247718e+22   6.372644e-96   7.672445e-52  7.415374e-198   7.988503e-72
[11]  -3.965002e-78  5.141563e+229  2.500044e+182  8.921874e-263  7.900195e+121
[16] -6.953393e-115   3.880374e-59 -2.051518e+295 -4.940772e-211 -5.971622e+270
[21]   1.531024e+32  1.324421e-299 -1.780382e+168  -9.753420e+65 -5.924136e-299
[26] -5.521087e+251 -8.215041e-252  -5.483912e-10  4.131672e-248 -4.502935e+251
[31] -2.607736e+185  8.431282e+102   5.894052e+21  -7.073661e-48 -5.571354e-229
[36]            NaN  -2.279067e+47  4.453073e-258  -1.066152e+60   1.617854e-83
[41] -3.066955e+144  2.054307e-122  1.401121e+266 -1.718262e+140 -1.160978e+136
[46]   7.795542e+14   1.489523e+51 -4.232476e-138   9.898241e-25  3.035638e-182
[51]  -5.412741e-11  1.131269e-204  -1.973360e-88  6.859663e-216 -2.356559e-143
[56]            NaN  2.256622e+246  5.258403e+291 -1.776727e+102 -3.495783e-146
[61]            NaN  -1.680931e+82  5.837709e+241  9.310119e-175  -5.430260e+73
[66] -1.857219e+302  -3.693950e+59 -7.674413e-119   2.950778e-61  2.694178e+231
[71] -3.610747e-197  1.023516e+298             NA  3.370415e-219  5.257832e-195
[76]   1.152634e-91 -3.853583e-153  -4.781135e-79  1.238762e+105  1.516698e+249
[81]   1.774927e+54 -2.668766e-275 -4.672858e-108 -5.987380e-246 -4.094624e-124
[86]  1.235007e+232   1.853151e-53   1.630905e-77  -9.673466e-30  3.067502e-246
[91]  5.574386e-245   0.000000e+00

[[2]]
[[2]]$proc
[1] -368828245

[[2]]$x
 [1]  -1.211787e+01   5.407487e+74  7.082012e-102            Inf  6.632413e+120
 [6]  2.510300e+283           -Inf  9.520515e+194 -1.583278e+268 -1.187565e-195
[11]   2.135832e-89 -1.131094e-305   2.737299e+09 -6.249565e+164  -8.518762e-41
[16]   5.817285e+91   2.752837e+87  1.072520e+303  -1.165785e-24   8.918899e+60
[21]  9.028907e+223 -1.109461e-192  2.871238e-204  1.614077e-253  5.632332e+116
[26]  3.529462e-213   1.539680e-93  -3.638001e-45  1.867765e+118  4.068157e+241
[31]  3.492486e+167  6.322562e-124           -Inf  4.514349e+236  8.424338e+279
[36]  4.098750e+239 -2.621693e+252 -7.475972e-190  9.987565e-203 -2.110470e+143
[41] -1.065435e+217 -1.171729e+247   3.008855e-44  1.939933e-178  2.289025e+199
[46]  -4.886040e-01  1.946969e+182  -6.360762e-25 -1.086591e+184   4.167361e-39
[51] -8.465239e+251 -2.568850e-145  5.460787e+225  6.879641e+112  2.782136e+294
[56]   2.670047e-71 -1.428912e+104 -1.441694e+237  7.683257e-296 -2.873390e-238
[61]  2.895659e-142  2.959821e+102   1.640421e+93  4.718761e+250  1.392888e+139
[66]  1.316505e+219 -3.365784e-189 -5.947962e+285  1.319526e+154  2.481348e+292
[71]   8.032314e+26   7.175767e-67 -6.521567e-134  1.137452e+261  3.121498e-104
[76] -1.153466e-129 -1.258058e+171 -7.705406e-137  8.035508e+167   5.953329e-52
[81]   3.602742e+14 -5.956779e+227  5.020297e-229            NaN  -5.199513e+42
[86] -6.696721e-167 -5.495423e+168 -2.480449e-239  1.914153e+260 -6.771995e-250
[91]  1.486723e+244             NA -6.520332e-293  5.291521e-296   0.000000e+00

[[2]]$y
 [1] -2.261140e-269  1.692449e-211 -3.871866e+142 -1.467482e-194 -2.238964e+302
 [6]  6.840724e-135 -6.622427e-190            Inf -7.036368e+255  -1.005498e+22
[11]  3.054362e-294  1.291491e-172  4.138621e+254   8.006135e+64   1.676216e+39
[16] -5.822143e-131   1.040997e+30   1.247452e-57  2.417244e-271  1.177781e-277
[21]   6.254519e-23 -4.580717e+122  2.549381e-166  -1.246979e+97 -1.370371e-165
[26] -1.310945e+221           -Inf            NaN  -1.084054e+33            Inf
[31]  3.764579e-104  1.726853e-244 -2.707496e-250  3.086298e+298  -3.887847e+24
[36] -3.224243e-297   1.607582e-20  3.656979e-132  1.200365e+123  2.075321e-170
[41]  3.476313e+190  3.562624e+150 -4.078044e+242  -9.541286e-94   3.476926e-66
[46] -1.407605e+120  4.445942e-107   4.055662e-11  -1.956888e-11  4.452349e-246
[51] -3.695261e+283  1.011808e-217   5.428040e-56 -1.113133e+230   1.834385e+05
[56] -1.152191e-266 -6.987547e+118  1.856654e+261  4.023319e-277  4.632042e-255
[61] -2.926482e-303 -1.967921e-131  2.885778e+269 -1.718178e-158  -2.232720e-57
[66] -3.838186e-231  2.039750e+214   5.345110e+16 -1.302132e+288  -9.694407e+16
[71]  6.302335e-292  7.881451e-147 -3.055507e-107   2.609812e+92 -7.421367e-111
[76] -2.647194e-242 -1.563664e-152 -2.037170e+152 -2.929361e-103  3.564432e+132
[81] -5.883995e-306 -3.626106e-143  1.332677e-141  3.280310e-152 -3.875863e-155
[86]  6.046656e-133   7.549545e-19   0.000000e+00

[[3]]
[[3]]$proc
[1] 442222113

[[3]]$x
 [1]  -1.315603e+76  5.944990e-228  2.524083e+222  -5.526018e+07  -1.827265e-81
 [6]            Inf  4.546164e-182             NA  2.011809e+105 -2.705909e+241
[11] -2.861891e+305 -4.296043e-151   8.119379e+37  9.129424e-150  -9.039184e+92
[16]  -1.749919e-32   9.245392e-33 -5.375967e+277  3.712462e+143  -4.913528e+52
[21]   3.275156e-66 -4.394789e+193 -5.426126e+107   1.858226e+51 -3.601565e-163
[26]  2.256602e+145  -1.375539e+96  -9.644887e-87 -1.817573e-233 -1.762153e-225
[31]  1.172680e-105  1.179222e+298  3.442025e-100  -1.329609e-27 -1.177077e+170
[36]  -1.020693e-22  8.084316e+211   8.114992e-13 -6.933512e-184  1.443038e-136
[41]  -1.429515e-67  1.747878e+108  7.944174e-234 -2.931752e-226 -1.343973e-103
[46]  2.245314e-228  2.114742e+276  1.738680e-183 -8.949129e+279  1.472069e-210
[51]            NaN   2.881122e+78   7.260736e+26  -4.332354e+52  -2.864752e+61
[56] -4.906877e-260   1.443136e-27   2.775031e-58 -2.238503e+191  2.353666e-223
[61]  -2.437488e+21   3.414551e+65  -2.491923e+47  -1.567876e+83  1.822550e+104
[66]  2.346569e+271  5.944990e-228

[[3]]$y
 [1]  5.639270e-301   2.928447e+72  1.413051e+202   1.056599e-75  2.298971e-128
 [6]  2.431211e-286  1.565793e+277  -3.145913e+92  -3.975296e-27   2.578777e-08
[11]  -3.264816e+58 -1.158644e-265 -1.200883e-162  -9.546380e-97   5.115207e+42
[16]  -5.893930e-09 -2.892387e-164            Inf  -5.166389e+29   1.201387e+62
[21]  -2.881889e+90  2.388020e-120  1.169604e-193  -1.726966e+37 -4.420396e-276
[26]  6.062395e-264 -2.573909e+175 -1.303795e-129   2.458644e+66   5.830606e+64
[31] -2.636172e+196 -5.812442e-171 -5.608278e-268 -7.538751e-230   4.919099e+44
[36]  1.082596e+282  4.200943e+154 -2.709955e+246 -1.375406e-275 -1.609230e+190
[41]  3.973021e-249  1.744921e+118   3.621715e-62 -3.414560e-122 -6.211252e+220
[46]  -6.195039e-98  8.881997e+154  2.779266e+232 -1.690471e-166 -3.942104e-193
[51] -8.901118e+155  6.019898e+212  1.308280e+303  2.190714e-159            NaN
[56]   4.278817e+03  -1.800887e-40  2.446226e+188  1.532165e+109 -1.287332e+185
[61] -6.677466e-285  -4.484747e+14  -3.867190e-85   1.551158e+63   8.824668e-69
[66]  9.373674e+117  4.693116e-130           -Inf -5.584207e+200  2.153086e-142
[71] -4.244002e-203  4.808490e-219 -7.787479e-196 -5.913624e+162  1.709622e+128
[76]           -Inf

[[4]]
[[4]]$proc
[1] 1478301630

[[4]]$x
 [1]             NA  3.194010e+207 -2.305993e+233   8.034195e+03  6.934853e+169
 [6]  2.188621e+223  -6.475848e+29  1.130472e+125  -6.710291e-38 -2.627057e+185
[11] -3.020525e+176 -1.821694e-126   9.740703e+14  -7.561862e+90           -Inf
[16]  1.720188e+203  8.442190e+243 -1.882584e-155   2.860324e+50  -2.592647e-42
[21]   2.071251e+06            Inf -3.020525e+176  8.536241e-160 -1.084265e+285
[26]   3.962628e+59  2.793099e-169  -7.172241e-81   0.000000e+00

[[4]]$y
 [1] -3.248099e-159             NA -7.798658e-247   4.043349e+45   4.329796e-66
 [6] -1.552424e-214  -1.159025e-45 -9.968982e-270  1.543822e+265 -6.150174e-208
[11] -3.729425e+166           -Inf           -Inf  2.500269e-269 -1.052623e-222
[16]   3.001243e+53 -2.816485e-205  1.116357e+107 -7.005252e+162   6.817291e-33
[21]  -8.145374e+79   2.385996e-98  -5.099203e+30  1.309476e+265             NA
[26]  2.315403e+288  1.585987e-148 -8.489379e+237   4.708555e-04  -2.445088e+29
[31]  1.071799e+141   7.754382e+64 -6.471852e+193 -4.162778e-200  -7.750785e+33
[36]  1.525921e-254  1.257071e-206 -3.428272e-224  1.145200e-225           -Inf
[41]  1.881102e+238  -3.360492e+55  4.279588e-206  4.748555e-156   0.000000e+00

[[5]]
[[5]]$proc
[1] -459984978

[[5]]$x
 [1]  -2.557793e+29  5.175763e-111  7.685173e-203  4.616428e-304  1.009915e+155
 [6]   1.392813e+69  -1.329716e+58 -2.058268e-298 -3.072541e-304  3.335675e-198
[11]  3.460558e-109  1.482481e+169  -4.723076e-22   4.404118e+15 -9.967777e+116
[16] -1.769662e-196 -2.723953e-164 -7.601377e+108  -8.123718e-53  2.023199e+102
[21]  4.546335e-194  3.725898e+276  1.277559e-290  3.771586e+162  -1.741893e-65
[26]  7.168012e-209  -1.643485e-23  4.527359e-184 -7.156073e-152  4.858251e-132
[31] -4.760591e+164  2.267219e-265   1.896374e+63 -2.847086e-204             NA
[36]   4.633766e-95 -2.655594e+154  -1.314968e+76  3.565396e-128   1.130189e-64
[41] -4.257433e-195  4.052671e-159 -1.435022e-235  7.334623e+272  5.410362e-128
[46]  4.424611e+282   2.746145e+02  1.576415e-141  2.391698e+131   3.346999e+89
[51]  1.520585e+259   4.294880e+74 -9.545783e+145  1.766521e-219  5.441635e+301
[56] -9.117638e+195  -4.624935e-07            Inf  1.463843e+270  -1.775156e+00
[61]   7.471864e-26   5.416977e+22  -8.688201e+94   4.605276e-32   1.129375e-30
[66]            Inf   2.482643e-65            NaN  1.918059e-248   1.919370e+18
[71]   4.500427e+05 -8.678357e-284  -1.509039e-58   0.000000e+00

[[5]]$y
 [1]             NA  3.044519e-260  4.173143e+192   1.584978e+94 -8.542674e+253
 [6] -7.604854e+292             NA            Inf  -7.743403e+18             NA
[11] -2.664826e+246   0.000000e+00

>
tdhock commented 3 years ago

ok but it looks like there are always some elements which are NaN/NA. can you try OneOf(vector with all finite values, vector with some NaN values) instead?

akhikolla commented 3 years ago

I have updated the RcppDeepState_ random generation function to generate vectors that are having either no missing values at all or few missing values.