1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
1001
1002
1003
1004
1005
1006
1007
1008
1009
1010
1011
1012
1013
1014
1015
1016
1017
1018
1019
1020
1021
1022
1023
1024
1025
1026
1027
1028
1029
1030
1031
1032
1033
1034
1035
1036
1037
1038
1039
1040
1041
1042
1043
1044
1045
1046
1047
1048
1049
1050
1051
1052
1053
1054
1055
1056
1057
1058
1059
1060
1061
1062
1063
1064
1065
1066
1067
1068
1069
1070
1071
1072
1073
1074
1075
1076
1077
1078
1079
1080
1081
1082
1083
1084
1085
1086
1087
1088
1089
1090
1091
1092
1093
1094
1095
1096
1097
1098
1099
1100
1101
1102
1103
1104
1105
1106
1107
1108
1109
1110
1111
1112
|
//
// getmetacommunitycommand.cpp
// Mothur
//
// Created by SarahsWork on 4/9/13.
// Copyright (c) 2013 Schloss Lab. All rights reserved.
//
#include "getmetacommunitycommand.h"
#include "communitytype.h"
#include "kmeans.h"
#include "validcalculator.h"
#include "subsample.h"
//**********************************************************************************************************************
vector<string> GetMetaCommunityCommand::setParameters(){
try {
CommandParameter pshared("shared", "InputTypes", "", "", "none", "none", "none","outputType",false,true); parameters.push_back(pshared);
CommandParameter pgroups("groups", "String", "", "", "", "", "","",false,false); parameters.push_back(pgroups);
CommandParameter plabel("label", "String", "", "", "", "", "","",false,false); parameters.push_back(plabel);
CommandParameter pcalc("calc", "Multiple", "sharedsobs-sharedchao-sharedace-jabund-sorabund-jclass-sorclass-jest-sorest-thetayc-thetan-kstest-sharednseqs-ochiai-anderberg-kulczynski-kulczynskicody-lennon-morisitahorn-braycurtis-whittaker-odum-canberra-structeuclidean-structchord-hellinger-manhattan-structpearson-soergel-spearman-structkulczynski-speciesprofile-hamming-structchi2-gower-memchi2-memchord-memeuclidean-mempearson-jsd-rjsd", "rjsd", "", "", "","",false,false,true); parameters.push_back(pcalc);
CommandParameter psubsample("subsample", "String", "", "", "", "", "","",false,false); parameters.push_back(psubsample);
CommandParameter piters("iters", "Number", "", "1000", "", "", "","",false,false); parameters.push_back(piters);
CommandParameter pminpartitions("minpartitions", "Number", "", "5", "", "", "","",false,false,true); parameters.push_back(pminpartitions);
CommandParameter pmaxpartitions("maxpartitions", "Number", "", "100", "", "", "","",false,false,true); parameters.push_back(pmaxpartitions);
CommandParameter poptimizegap("optimizegap", "Number", "", "3", "", "", "","",false,false,true); parameters.push_back(poptimizegap);
CommandParameter pprocessors("processors", "Number", "", "1", "", "", "","",false,false,true); parameters.push_back(pprocessors);
CommandParameter pinputdir("inputdir", "String", "", "", "", "", "","",false,false); parameters.push_back(pinputdir);
CommandParameter poutputdir("outputdir", "String", "", "", "", "", "","",false,false); parameters.push_back(poutputdir);
CommandParameter pmethod("method", "Multiple", "dmm-kmeans-pam", "dmm", "", "", "","",false,false,true); parameters.push_back(pmethod);
vector<string> myArray;
for (int i = 0; i < parameters.size(); i++) { myArray.push_back(parameters[i].name); }
return myArray;
}
catch(exception& e) {
m->errorOut(e, "NewCommand", "setParameters");
exit(1);
}
}
//**********************************************************************************************************************
string GetMetaCommunityCommand::getHelpString(){
try {
string helpString = "";
helpString += "The get.communitytype command parameters are shared, method, label, groups, minpartitions, maxpartitions, optimizegap and processors. The shared file is required. \n";
helpString += "The label parameter is used to analyze specific labels in your input. labels are separated by dashes.\n";
helpString += "The groups parameter allows you to specify which of the groups in your shared file you would like analyzed. Group names are separated by dashes.\n";
helpString += "The method parameter allows to select the method you would like to use. Options are dmm, kmeans and pam. Default=dmm.\n";
helpString += "The calc parameter allows to select the calculator you would like to use to calculate the distance matrix used by the pam and kmeans method. By default the rjsd calculator is used.\n";
helpString += "The iters parameter allows you to choose the number of times you would like to run the subsample while calculating the distance matrix for the pam and kmeans method.\n";
helpString += "The subsample parameter allows you to enter the size pergroup of the sample or you can set subsample=T and mothur will use the size of your smallest group while calculating the distance matrix for the pam and kmeans methods.\n";
helpString += "The minpartitions parameter is used to .... Default=5.\n";
helpString += "The maxpartitions parameter is used to .... Default=10.\n";
helpString += "The optimizegap parameter is used to .... Default=3.\n";
helpString += "The processors parameter allows you to specify number of processors to use. The default is 1.\n";
helpString += "The get.communitytype command should be in the following format: get.communitytype(shared=yourSharedFile).\n";
return helpString;
}
catch(exception& e) {
m->errorOut(e, "GetMetaCommunityCommand", "getHelpString");
exit(1);
}
}
//**********************************************************************************************************************
string GetMetaCommunityCommand::getOutputPattern(string type) {
try {
string pattern = "";
if (type == "fit") { pattern = "[filename],[distance],[method],mix.fit"; }
else if (type == "relabund") { pattern = "[filename],[distance],[method],[tag],mix.relabund"; }
else if (type == "design") { pattern = "[filename],[distance],[method],mix.design"; }
else if (type == "matrix") { pattern = "[filename],[distance],[method],[tag],mix.posterior"; }
else if (type == "parameters") { pattern = "[filename],[distance],[method],mix.parameters"; }
else if (type == "summary") { pattern = "[filename],[distance],[method],mix.summary"; }
else { m->mothurOut("[ERROR]: No definition for type " + type + " output pattern.\n"); m->control_pressed = true; }
return pattern;
}
catch(exception& e) {
m->errorOut(e, "GetMetaCommunityCommand", "getOutputPattern");
exit(1);
}
}
//**********************************************************************************************************************
GetMetaCommunityCommand::GetMetaCommunityCommand(){
try {
abort = true; calledHelp = true;
setParameters();
vector<string> tempOutNames;
outputTypes["fit"] = tempOutNames;
outputTypes["relabund"] = tempOutNames;
outputTypes["matrix"] = tempOutNames;
outputTypes["design"] = tempOutNames;
outputTypes["parameters"] = tempOutNames;
outputTypes["summary"] = tempOutNames;
}
catch(exception& e) {
m->errorOut(e, "GetMetaCommunityCommand", "GetMetaCommunityCommand");
exit(1);
}
}
//**********************************************************************************************************************
GetMetaCommunityCommand::GetMetaCommunityCommand(string option) {
try {
abort = false; calledHelp = false;
allLines=true;
//allow user to run help
if(option == "help") { help(); abort = true; calledHelp = true; }
else if(option == "citation") { citation(); abort = true; calledHelp = true;}
else {
//valid paramters for this command
vector<string> myArray = setParameters();
OptionParser parser(option);
map<string,string> parameters = parser.getParameters();
ValidParameters validParameter;
map<string,string>::iterator it;
//check to make sure all parameters are valid for command
for (it = parameters.begin(); it != parameters.end(); it++) {
if (validParameter.isValidParameter(it->first, myArray, it->second) != true) { abort = true; }
}
vector<string> tempOutNames;
outputTypes["fit"] = tempOutNames;
outputTypes["relabund"] = tempOutNames;
outputTypes["matrix"] = tempOutNames;
outputTypes["design"] = tempOutNames;
outputTypes["parameters"] = tempOutNames;
outputTypes["summary"] = tempOutNames;
//if the user changes the input directory command factory will send this info to us in the output parameter
string inputDir = validParameter.validFile(parameters, "inputdir", false);
if (inputDir == "not found"){ inputDir = ""; }
else {
string path;
it = parameters.find("shared");
if(it != parameters.end()){
path = m->hasPath(it->second);
if (path == "") { parameters["shared"] = inputDir + it->second; }
}
}
//get shared file, it is required
sharedfile = validParameter.validFile(parameters, "shared", true);
if (sharedfile == "not open") { sharedfile = ""; abort = true; }
else if (sharedfile == "not found") {
//if there is a current shared file, use it
sharedfile = m->getSharedFile();
if (sharedfile != "") { m->mothurOut("Using " + sharedfile + " as input file for the shared parameter."); m->mothurOutEndLine(); }
else { m->mothurOut("You have no current sharedfile and the shared parameter is required."); m->mothurOutEndLine(); abort = true; }
}else { m->setSharedFile(sharedfile); }
//if the user changes the output directory command factory will send this info to us in the output parameter
outputDir = validParameter.validFile(parameters, "outputdir", false); if (outputDir == "not found"){
outputDir = m->hasPath(sharedfile); //if user entered a file with a path then preserve it
}
string temp = validParameter.validFile(parameters, "minpartitions", false); if (temp == "not found"){ temp = "5"; }
m->mothurConvert(temp, minpartitions);
temp = validParameter.validFile(parameters, "maxpartitions", false); if (temp == "not found"){ temp = "10"; }
m->mothurConvert(temp, maxpartitions);
temp = validParameter.validFile(parameters, "optimizegap", false); if (temp == "not found"){ temp = "3"; }
m->mothurConvert(temp, optimizegap);
temp = validParameter.validFile(parameters, "processors", false); if (temp == "not found"){ temp = m->getProcessors(); }
m->setProcessors(temp);
m->mothurConvert(temp, processors);
string groups = validParameter.validFile(parameters, "groups", false);
if (groups == "not found") { groups = ""; }
else { m->splitAtDash(groups, Groups); }
m->setGroups(Groups);
string label = validParameter.validFile(parameters, "label", false);
if (label == "not found") { label = ""; }
else {
if(label != "all") { m->splitAtDash(label, labels); allLines = 0; }
else { allLines = 1; }
}
method = validParameter.validFile(parameters, "method", false);
if (method == "not found") { method = "dmm"; }
if ((method == "dmm") || (method == "kmeans") || (method == "pam")) { }
else { m->mothurOut("[ERROR]: " + method + " is not a valid method. Valid algorithms are dmm, kmeans and pam."); m->mothurOutEndLine(); abort = true; }
calc = validParameter.validFile(parameters, "calc", false);
if (calc == "not found") { calc = "rjsd"; }
else {
if (calc == "default") { calc = "rjsd"; }
}
m->splitAtDash(calc, Estimators);
if (m->inUsersGroups("citation", Estimators)) {
ValidCalculators validCalc; validCalc.printCitations(Estimators);
//remove citation from list of calcs
for (int i = 0; i < Estimators.size(); i++) { if (Estimators[i] == "citation") { Estimators.erase(Estimators.begin()+i); break; } }
}
if (Estimators.size() != 1) { abort = true; m->mothurOut("[ERROR]: only one calculator is allowed.\n"); }
temp = validParameter.validFile(parameters, "iters", false); if (temp == "not found") { temp = "1000"; }
m->mothurConvert(temp, iters);
temp = validParameter.validFile(parameters, "subsample", false); if (temp == "not found") { temp = "F"; }
if (m->isNumeric1(temp)) { m->mothurConvert(temp, subsampleSize); subsample = true; }
else {
if (m->isTrue(temp)) { subsample = true; subsampleSize = -1; } //we will set it to smallest group later
else { subsample = false; }
}
if (subsample == false) { iters = 0; }
}
}
catch(exception& e) {
m->errorOut(e, "GetMetaCommunityCommand", "GetMetaCommunityCommand");
exit(1);
}
}
//**********************************************************************************************************************
int GetMetaCommunityCommand::execute(){
try {
if (abort == true) { if (calledHelp) { return 0; } return 2; }
InputData input(sharedfile, "sharedfile");
vector<SharedRAbundVector*> lookup = input.getSharedRAbundVectors();
string lastLabel = lookup[0]->getLabel();
//if the users enters label "0.06" and there is no "0.06" in their file use the next lowest label.
set<string> processedLabels;
set<string> userLabels = labels;
if (subsample) {
if (subsampleSize == -1) { //user has not set size, set size = smallest samples size
subsampleSize = lookup[0]->getNumSeqs();
for (int i = 1; i < lookup.size(); i++) {
int thisSize = lookup[i]->getNumSeqs();
if (thisSize < subsampleSize) { subsampleSize = thisSize; }
}
}else {
m->clearGroups();
Groups.clear();
vector<SharedRAbundVector*> temp;
for (int i = 0; i < lookup.size(); i++) {
if (lookup[i]->getNumSeqs() < subsampleSize) {
m->mothurOut(lookup[i]->getGroup() + " contains " + toString(lookup[i]->getNumSeqs()) + ". Eliminating."); m->mothurOutEndLine();
delete lookup[i];
}else {
Groups.push_back(lookup[i]->getGroup());
temp.push_back(lookup[i]);
}
}
lookup = temp;
m->setGroups(Groups);
}
if (lookup.size() < 2) { m->mothurOut("You have not provided enough valid groups. I cannot run the command."); m->mothurOutEndLine(); m->control_pressed = true; return 0; }
}
//as long as you are not at the end of the file or done wih the lines you want
while((lookup[0] != NULL) && ((allLines == 1) || (userLabels.size() != 0))) {
if (m->control_pressed) { for (int i = 0; i < lookup.size(); i++) { delete lookup[i]; } return 0; }
if(allLines == 1 || labels.count(lookup[0]->getLabel()) == 1){
m->mothurOut(lookup[0]->getLabel()); m->mothurOutEndLine();
createProcesses(lookup);
processedLabels.insert(lookup[0]->getLabel());
userLabels.erase(lookup[0]->getLabel());
}
if ((m->anyLabelsToProcess(lookup[0]->getLabel(), userLabels, "") == true) && (processedLabels.count(lastLabel) != 1)) {
string saveLabel = lookup[0]->getLabel();
for (int i = 0; i < lookup.size(); i++) { delete lookup[i]; }
lookup = input.getSharedRAbundVectors(lastLabel);
m->mothurOut(lookup[0]->getLabel()); m->mothurOutEndLine();
createProcesses(lookup);
processedLabels.insert(lookup[0]->getLabel());
userLabels.erase(lookup[0]->getLabel());
//restore real lastlabel to save below
lookup[0]->setLabel(saveLabel);
}
lastLabel = lookup[0]->getLabel();
//prevent memory leak
for (int i = 0; i < lookup.size(); i++) { delete lookup[i]; lookup[i] = NULL; }
if (m->control_pressed) { return 0; }
//get next line to process
lookup = input.getSharedRAbundVectors();
}
if (m->control_pressed) { return 0; }
//output error messages about any remaining user labels
set<string>::iterator it;
bool needToRun = false;
for (it = userLabels.begin(); it != userLabels.end(); it++) {
m->mothurOut("Your file does not include the label " + *it);
if (processedLabels.count(lastLabel) != 1) {
m->mothurOut(". I will use " + lastLabel + "."); m->mothurOutEndLine();
needToRun = true;
}else {
m->mothurOut(". Please refer to " + lastLabel + "."); m->mothurOutEndLine();
}
}
//run last label if you need to
if (needToRun == true) {
for (int i = 0; i < lookup.size(); i++) { if (lookup[i] != NULL) { delete lookup[i]; } }
lookup = input.getSharedRAbundVectors(lastLabel);
m->mothurOut(lookup[0]->getLabel()); m->mothurOutEndLine();
createProcesses(lookup);
for (int i = 0; i < lookup.size(); i++) { delete lookup[i]; }
}
//output files created by command
m->mothurOutEndLine();
m->mothurOut("Output File Names: "); m->mothurOutEndLine();
for (int i = 0; i < outputNames.size(); i++) { m->mothurOut(outputNames[i]); m->mothurOutEndLine(); }
m->mothurOutEndLine();
return 0;
}
catch(exception& e) {
m->errorOut(e, "GetMetaCommunityCommand", "execute");
exit(1);
}
}
//**********************************************************************************************************************
int GetMetaCommunityCommand::createProcesses(vector<SharedRAbundVector*>& thislookup){
try {
#if defined (__APPLE__) || (__MACH__) || (linux) || (__linux) || (__linux__) || (__unix__) || (__unix)
#else
processors=1; //qFinderDMM not thread safe
#endif
vector<int> processIDS;
int process = 1;
int num = 0;
int minPartition = 0;
//sanity check
if (maxpartitions < processors) { processors = maxpartitions; }
map<string, string> variables;
variables["[filename]"] = outputDir + m->getRootName(m->getSimpleName(sharedfile));
variables["[distance]"] = thislookup[0]->getLabel();
variables["[method]"] = method;
string outputFileName = getOutputFileName("fit", variables);
outputNames.push_back(outputFileName); outputTypes["fit"].push_back(outputFileName);
//divide the partitions between the processors
vector< vector<int> > dividedPartitions;
vector< vector<string> > rels, matrix;
vector<string> doneFlags;
dividedPartitions.resize(processors);
rels.resize(processors);
matrix.resize(processors);
//for each file group figure out which process will complete it
//want to divide the load intelligently so the big files are spread between processes
for (int i=1; i<=maxpartitions; i++) {
//cout << i << endl;
int processToAssign = (i+1) % processors;
if (processToAssign == 0) { processToAssign = processors; }
if (m->debug) { m->mothurOut("[DEBUG]: assigning " + toString(i) + " to process " + toString(processToAssign-1) + "\n"); }
dividedPartitions[(processToAssign-1)].push_back(i);
variables["[tag]"] = toString(i);
string relName = getOutputFileName("relabund", variables);
string mName = getOutputFileName("matrix", variables);
rels[(processToAssign-1)].push_back(relName);
matrix[(processToAssign-1)].push_back(mName);
}
for (int i = 0; i < processors; i++) { //read from everyone elses, just write to yours
string tempDoneFile = m->getRootName(m->getSimpleName(sharedfile)) + toString(i) + ".done.temp";
doneFlags.push_back(tempDoneFile);
ofstream out;
m->openOutputFile(tempDoneFile, out); //clear out
out.close();
}
#if defined (__APPLE__) || (__MACH__) || (linux) || (__linux) || (__linux__) || (__unix__) || (__unix)
//loop through and create all the processes you want
while (process != processors) {
int pid = fork();
if (pid > 0) {
processIDS.push_back(pid); //create map from line number to pid so you can append files in correct order later
process++;
}else if (pid == 0){
outputNames.clear();
num = processDriver(thislookup, dividedPartitions[process], (outputFileName + toString(getpid())), rels[process], matrix[process], doneFlags, process);
//pass numSeqs to parent
ofstream out;
string tempFile = toString(getpid()) + ".outputNames.temp";
m->openOutputFile(tempFile, out);
out << num << endl;
out << outputNames.size() << endl;
for (int i = 0; i < outputNames.size(); i++) { out << outputNames[i] << endl; }
out.close();
exit(0);
}else {
m->mothurOut("[ERROR]: unable to spawn the necessary processes."); m->mothurOutEndLine();
for (int i = 0; i < processIDS.size(); i++) { kill (processIDS[i], SIGINT); }
exit(0);
}
}
//do my part
if (method == "dmm") { m->mothurOut("K\tNLE\t\tlogDet\tBIC\t\tAIC\t\tLaplace\n"); }
else {
m->mothurOut("K\tCH\t");
for (int i = 0; i < thislookup.size(); i++) { m->mothurOut(thislookup[i]->getGroup() + '\t'); }
m->mothurOut("\n");
}
minPartition = processDriver(thislookup, dividedPartitions[0], outputFileName, rels[0], matrix[0], doneFlags, 0);
//force parent to wait until all the processes are done
for (int i=0;i<processIDS.size();i++) {
int temp = processIDS[i];
wait(&temp);
}
vector<string> tempOutputNames = outputNames;
for (int i=0;i<processIDS.size();i++) {
ifstream in;
string tempFile = toString(processIDS[i]) + ".outputNames.temp";
m->openInputFile(tempFile, in);
if (!in.eof()) {
int tempNum = 0;
in >> tempNum; m->gobble(in);
if (tempNum < minPartition) { minPartition = tempNum; }
in >> tempNum; m->gobble(in);
for (int i = 0; i < tempNum; i++) {
string tempName = "";
in >> tempName; m->gobble(in);
tempOutputNames.push_back(tempName);
}
}
in.close(); m->mothurRemove(tempFile);
m->appendFilesWithoutHeaders(outputFileName + toString(processIDS[i]), outputFileName);
m->mothurRemove(outputFileName + toString(processIDS[i]));
}
if (processors > 1) {
outputNames.clear();
for (int i = 0; i < tempOutputNames.size(); i++) { //remove files if needed
string name = tempOutputNames[i];
vector<string> parts;
m->splitAtChar(name, parts, '.');
bool keep = true;
if (((parts[parts.size()-1] == "relabund") || (parts[parts.size()-1] == "posterior")) && (parts[parts.size()-2] == "mix")) {
string tempNum = parts[parts.size()-3];
int num; m->mothurConvert(tempNum, num);
//if (num > minPartition) {
// m->mothurRemove(tempOutputNames[i]);
// keep = false; if (m->debug) { m->mothurOut("[DEBUG]: removing " + tempOutputNames[i] + ".\n"); }
//}
}
if (keep) { outputNames.push_back(tempOutputNames[i]); }
}
//reorder fit file
ifstream in;
m->openInputFile(outputFileName, in);
string headers = m->getline(in); m->gobble(in);
map<int, string> file;
while (!in.eof()) {
string numString, line;
int num;
in >> numString; line = m->getline(in); m->gobble(in);
m->mothurConvert(numString, num);
file[num] = line;
}
in.close();
ofstream out;
m->openOutputFile(outputFileName, out);
out << headers << endl;
for (map<int, string>::iterator it = file.begin(); it != file.end(); it++) {
out << it->first << '\t' << it->second << endl;
if (m->debug) { m->mothurOut("[DEBUG]: printing: " + toString(it->first) + '\t' + it->second + ".\n"); }
}
out.close();
}
#else
m->mothurOut("K\tNLE\t\tlogDet\tBIC\t\tAIC\t\tLaplace\n");
minPartition = processDriver(thislookup, dividedPartitions[0], outputFileName, rels[0], matrix[0], doneFlags, 0);
#endif
for (int i = 0; i < processors; i++) { //read from everyone elses, just write to yours
string tempDoneFile = m->getRootName(m->getSimpleName(sharedfile)) + toString(i) + ".done.temp";
m->mothurRemove(tempDoneFile);
}
if (m->control_pressed) { return 0; }
if (m->debug) { m->mothurOut("[DEBUG]: minPartition = " + toString(minPartition) + "\n"); }
//run generate Summary function for smallest minPartition
variables["[tag]"] = toString(minPartition);
vector<double> piValues = generateDesignFile(minPartition, variables);
if (method == "dmm") { generateSummaryFile(minPartition, variables, piValues); } //pam doesn't make a relabund file
return 0;
}
catch(exception& e) {
m->errorOut(e, "GetMetaCommunityCommand", "createProcesses");
exit(1);
}
}
//**********************************************************************************************************************
int GetMetaCommunityCommand::processDriver(vector<SharedRAbundVector*>& thislookup, vector<int>& parts, string outputFileName, vector<string> relabunds, vector<string> matrix, vector<string> doneFlags, int processID){
try {
double minLaplace = 1e10;
int minPartition = 1;
vector<double> minSilhouettes; minSilhouettes.resize(thislookup.size(), 0);
ofstream fitData, silData;
if (method == "dmm") {
m->openOutputFile(outputFileName, fitData);
fitData.setf(ios::fixed, ios::floatfield);
fitData.setf(ios::showpoint);
fitData << "K\tNLE\tlogDet\tBIC\tAIC\tLaplace" << endl;
}else if((method == "pam") || (method == "kmeans")) { //because ch is looking of maximal value
minLaplace = 0;
m->openOutputFile(outputFileName, silData);
silData.setf(ios::fixed, ios::floatfield);
silData.setf(ios::showpoint);
silData << "K\tCH\t";
for (int i = 0; i < thislookup.size(); i++) { silData << thislookup[i]->getGroup() << '\t'; }
silData << endl;
}
cout.setf(ios::fixed, ios::floatfield);
cout.setf(ios::showpoint);
vector< vector<int> > sharedMatrix;
vector<string> thisGroups;
for (int i = 0; i < thislookup.size(); i++) { sharedMatrix.push_back(thislookup[i]->getAbundances()); thisGroups.push_back(thislookup[i]->getGroup()); }
vector< vector<double> > dists; //do we want to output this matrix??
if ((method == "pam") || (method == "kmeans")) { dists = generateDistanceMatrix(thislookup); }
if (m->debug) {
m->mothurOut("[DEBUG]: dists = \n");
for (int i = 0; i < dists.size(); i++) {
if (m->control_pressed) { break; }
m->mothurOut("[DEBUG]: i = " + toString(i) + '\t');
for (int j = 0; j < i; j++) { m->mothurOut(toString(dists[i][j]) +"\t"); }
m->mothurOut("\n");
}
}
for(int i=0;i<parts.size();i++){
int numPartitions = parts[i];
if (m->debug) { m->mothurOut("[DEBUG]: running partition " + toString(numPartitions) + "\n"); }
if (m->control_pressed) { break; }
//check to see if anyone else is done
for (int j = 0; j < doneFlags.size(); j++) {
if (!m->isBlank(doneFlags[j])) { //another process has finished
//are they done at a lower partition?
ifstream in;
m->openInputFile(doneFlags[j], in);
int tempNum;
in >> tempNum; in.close();
if (tempNum < numPartitions) { break; } //quit, because someone else has finished
}
}
CommunityTypeFinder* finder = NULL;
if (method == "dmm") { finder = new qFinderDMM(sharedMatrix, numPartitions); }
else if (method == "kmeans") { finder = new KMeans(sharedMatrix, numPartitions); }
else if (method == "pam") { finder = new Pam(sharedMatrix, dists, numPartitions); }
else {
if (i == 0) { m->mothurOut(method + " is not a valid method option. I will run the command using dmm.\n"); }
finder = new qFinderDMM(sharedMatrix, numPartitions);
}
string relabund = relabunds[i];
string matrixName = matrix[i];
outputNames.push_back(matrixName); outputTypes["matrix"].push_back(matrixName);
finder->printZMatrix(matrixName, thisGroups);
double chi; vector<double> silhouettes;
if (method == "dmm") {
double laplace = finder->getLaplace();
if(laplace < minLaplace){
minPartition = numPartitions;
minLaplace = laplace;
}
}else {
chi = finder->calcCHIndex(dists);
silhouettes = finder->calcSilhouettes(dists);
if (chi > minLaplace) { //save partition with maximum ch index score
minPartition = numPartitions;
minLaplace = chi;
minSilhouettes = silhouettes;
}
}
if (method == "dmm") {
finder->printFitData(cout, minLaplace);
finder->printFitData(fitData);
finder->printRelAbund(relabund, m->currentSharedBinLabels);
outputNames.push_back(relabund); outputTypes["relabund"].push_back(relabund);
}else if ((method == "pam") || (method == "kmeans")) { //print silouettes and ch values
finder->printSilData(cout, chi, silhouettes);
finder->printSilData(silData, chi, silhouettes);
if (method == "kmeans") {
finder->printRelAbund(relabund, m->currentSharedBinLabels);
outputNames.push_back(relabund); outputTypes["relabund"].push_back(relabund);
}
}
delete finder;
if(optimizegap != -1 && (numPartitions - minPartition) >= optimizegap && numPartitions >= minpartitions){
string tempDoneFile = m->getRootName(m->getSimpleName(sharedfile)) + toString(processID) + ".done.temp";
ofstream outDone;
m->openOutputFile(tempDoneFile, outDone);
outDone << minPartition << endl;
outDone.close();
break;
}
}
if (method == "dmm") { fitData.close(); }
if (m->control_pressed) { return 0; }
return minPartition;
}
catch(exception& e) {
m->errorOut(e, "GetMetaCommunityCommand", "processDriver");
exit(1);
}
}
/**************************************************************************************************/
vector<double> GetMetaCommunityCommand::generateDesignFile(int numPartitions, map<string,string> variables){
try {
vector<double> piValues(numPartitions, 0);
ifstream postFile;
variables["[tag]"] = toString(numPartitions);
string input = getOutputFileName("matrix", variables);
m->openInputFile(input, postFile);//((fileRoot + toString(numPartitions) + "mix.posterior").c_str()); //matrix file
variables.erase("[tag]");
string outputFileName = getOutputFileName("design", variables);
ofstream designFile;
m->openOutputFile(outputFileName, designFile);
outputNames.push_back(outputFileName); outputTypes["design"].push_back(outputFileName);
vector<string> titles(numPartitions);
for(int i=0;i<numPartitions;i++){ postFile >> titles[i]; }
double posterior;
string sampleName;
int numSamples = 0;
while(postFile){
if (m->control_pressed) { break; }
double maxPosterior = 0.0000;
int maxPartition = -1;
postFile >> sampleName;
for(int i=0;i<numPartitions;i++){
postFile >> posterior;
if(posterior > maxPosterior){
maxPosterior = posterior;
maxPartition = i;
}
piValues[i] += posterior;
}
designFile << sampleName << '\t' << titles[maxPartition] << endl;
numSamples++;
m->gobble(postFile);
}
for(int i=0;i<numPartitions;i++){
piValues[i] /= (double)numSamples;
}
postFile.close();
designFile.close();
return piValues;
}
catch(exception& e) {
m->errorOut(e, "GetMetaCommunityCommand", "generateDesignFile");
exit(1);
}
}
/**************************************************************************************************/
inline bool summaryFunction(summaryData i, summaryData j){ return i.difference > j.difference; }
/**************************************************************************************************/
int GetMetaCommunityCommand::generateSummaryFile(int numPartitions, map<string,string> v, vector<double> piValues){
try {
vector<summaryData> summary;
vector<double> pMean(numPartitions, 0);
vector<double> pLCI(numPartitions, 0);
vector<double> pUCI(numPartitions, 0);
string name, header;
double mean, lci, uci;
ifstream referenceFile;
map<string, string> variables;
variables["[filename]"] = v["[filename]"];
variables["[distance]"] = v["[distance]"];
variables["[method]"] = method;
variables["[tag]"] = "1";
string reference = getOutputFileName("relabund", variables);
m->openInputFile(reference, referenceFile); //((fileRoot + label + ".1mix.relabund").c_str());
variables["[tag]"] = toString(numPartitions);
string partFile = getOutputFileName("relabund", variables);
ifstream partitionFile;
m->openInputFile(partFile, partitionFile); //((fileRoot + toString(numPartitions) + "mix.relabund").c_str());
header = m->getline(referenceFile);
header = m->getline(partitionFile);
stringstream head(header);
string dummy, label;
head >> dummy;
vector<string> thetaValues(numPartitions, "");
for(int i=0;i<numPartitions;i++){
head >> label >> dummy >> dummy;
thetaValues[i] = label.substr(label.find_last_of('_')+1);
}
vector<double> partitionDiff(numPartitions, 0.0000);
while(referenceFile){
if (m->control_pressed) { break; }
referenceFile >> name >> mean >> lci >> uci;
summaryData tempData;
tempData.name = name;
tempData.refMean = mean;
double difference = 0.0000;
partitionFile >> name;
for(int j=0;j<numPartitions;j++){
partitionFile >> pMean[j] >> pLCI[j] >> pUCI[j];
difference += abs(mean - pMean[j]);
partitionDiff[j] += abs(mean - pMean[j]);;
}
tempData.partMean = pMean;
tempData.partLCI = pLCI;
tempData.partUCI = pUCI;
tempData.difference = difference;
summary.push_back(tempData);
m->gobble(referenceFile);
m->gobble(partitionFile);
}
referenceFile.close();
partitionFile.close();
if (m->control_pressed) { return 0; }
int numOTUs = (int)summary.size();
sort(summary.begin(), summary.end(), summaryFunction);
variables.erase("[tag]");
string outputFileName = getOutputFileName("parameters", variables);
outputNames.push_back(outputFileName); outputTypes["parameters"].push_back(outputFileName);
ofstream parameterFile;
m->openOutputFile(outputFileName, parameterFile); //((fileRoot + "mix.parameters").c_str());
parameterFile.setf(ios::fixed, ios::floatfield);
parameterFile.setf(ios::showpoint);
double totalDifference = 0.0000;
parameterFile << "Part\tDif2Ref_i\ttheta_i\tpi_i\n";
for(int i=0;i<numPartitions;i++){
if (m->control_pressed) { break; }
parameterFile << i+1 << '\t' << setprecision(2) << partitionDiff[i] << '\t' << thetaValues[i] << '\t' << piValues[i] << endl;
totalDifference += partitionDiff[i];
}
parameterFile.close();
if (m->control_pressed) { return 0; }
string summaryFileName = getOutputFileName("summary", variables);
outputNames.push_back(summaryFileName); outputTypes["summary"].push_back(summaryFileName);
ofstream summaryFile;
m->openOutputFile(summaryFileName, summaryFile); //((fileRoot + "mix.summary").c_str());
summaryFile.setf(ios::fixed, ios::floatfield);
summaryFile.setf(ios::showpoint);
summaryFile << "OTU\tP0.mean";
for(int i=0;i<numPartitions;i++){
summaryFile << "\tP" << i+1 << ".mean\tP" << i+1 << ".lci\tP" << i+1 << ".uci";
}
summaryFile << "\tDifference\tCumFraction" << endl;
double cumDiff = 0.0000;
for(int i=0;i<numOTUs;i++){
if (m->control_pressed) { break; }
summaryFile << summary[i].name << setprecision(2) << '\t' << summary[i].refMean;
for(int j=0;j<numPartitions;j++){
summaryFile << '\t' << summary[i].partMean[j] << '\t' << summary[i].partLCI[j] << '\t' << summary[i].partUCI[j];
}
cumDiff += summary[i].difference/totalDifference;
summaryFile << '\t' << summary[i].difference << '\t' << cumDiff << endl;
}
summaryFile.close();
return 0;
}
catch(exception& e) {
m->errorOut(e, "GetMetaCommunityCommand", "generateSummaryFile");
exit(1);
}
}
//**********************************************************************************************************************
vector<vector<double> > GetMetaCommunityCommand::generateDistanceMatrix(vector<SharedRAbundVector*>& thisLookup){
try {
vector<vector<double> > results;
Calculator* matrixCalculator;
ValidCalculators validCalculator;
int i = 0;
if (validCalculator.isValidCalculator("matrix", Estimators[i]) == true) {
if (Estimators[i] == "sharedsobs") {
matrixCalculator = new SharedSobsCS();
}else if (Estimators[i] == "sharedchao") {
matrixCalculator = new SharedChao1();
}else if (Estimators[i] == "sharedace") {
matrixCalculator = new SharedAce();
}else if (Estimators[i] == "jabund") {
matrixCalculator = new JAbund();
}else if (Estimators[i] == "sorabund") {
matrixCalculator = new SorAbund();
}else if (Estimators[i] == "jclass") {
matrixCalculator = new Jclass();
}else if (Estimators[i] == "sorclass") {
matrixCalculator = new SorClass();
}else if (Estimators[i] == "jest") {
matrixCalculator = new Jest();
}else if (Estimators[i] == "sorest") {
matrixCalculator = new SorEst();
}else if (Estimators[i] == "thetayc") {
matrixCalculator = new ThetaYC();
}else if (Estimators[i] == "thetan") {
matrixCalculator = new ThetaN();
}else if (Estimators[i] == "kstest") {
matrixCalculator = new KSTest();
}else if (Estimators[i] == "sharednseqs") {
matrixCalculator = new SharedNSeqs();
}else if (Estimators[i] == "ochiai") {
matrixCalculator = new Ochiai();
}else if (Estimators[i] == "anderberg") {
matrixCalculator = new Anderberg();
}else if (Estimators[i] == "kulczynski") {
matrixCalculator = new Kulczynski();
}else if (Estimators[i] == "kulczynskicody") {
matrixCalculator = new KulczynskiCody();
}else if (Estimators[i] == "lennon") {
matrixCalculator = new Lennon();
}else if (Estimators[i] == "morisitahorn") {
matrixCalculator = new MorHorn();
}else if (Estimators[i] == "braycurtis") {
matrixCalculator = new BrayCurtis();
}else if (Estimators[i] == "whittaker") {
matrixCalculator = new Whittaker();
}else if (Estimators[i] == "odum") {
matrixCalculator = new Odum();
}else if (Estimators[i] == "canberra") {
matrixCalculator = new Canberra();
}else if (Estimators[i] == "structeuclidean") {
matrixCalculator = new StructEuclidean();
}else if (Estimators[i] == "structchord") {
matrixCalculator = new StructChord();
}else if (Estimators[i] == "hellinger") {
matrixCalculator = new Hellinger();
}else if (Estimators[i] == "manhattan") {
matrixCalculator = new Manhattan();
}else if (Estimators[i] == "structpearson") {
matrixCalculator = new StructPearson();
}else if (Estimators[i] == "soergel") {
matrixCalculator = new Soergel();
}else if (Estimators[i] == "spearman") {
matrixCalculator = new Spearman();
}else if (Estimators[i] == "structkulczynski") {
matrixCalculator = new StructKulczynski();
}else if (Estimators[i] == "speciesprofile") {
matrixCalculator = new SpeciesProfile();
}else if (Estimators[i] == "hamming") {
matrixCalculator = new Hamming();
}else if (Estimators[i] == "structchi2") {
matrixCalculator = new StructChi2();
}else if (Estimators[i] == "gower") {
matrixCalculator = new Gower();
}else if (Estimators[i] == "memchi2") {
matrixCalculator = new MemChi2();
}else if (Estimators[i] == "memchord") {
matrixCalculator = new MemChord();
}else if (Estimators[i] == "memeuclidean") {
matrixCalculator = new MemEuclidean();
}else if (Estimators[i] == "mempearson") {
matrixCalculator = new MemPearson();
}else if (Estimators[i] == "jsd") {
matrixCalculator = new JSD();
}else if (Estimators[i] == "rjsd") {
matrixCalculator = new RJSD();
}else {
m->mothurOut("[ERROR]: " + Estimators[i] + " is not a valid calculator, please correct.\n"); m->control_pressed = true; return results;
}
}
//calc distances
vector< vector< vector<seqDist> > > calcDistsTotals; //each iter, then each groupCombos dists. this will be used to make .dist files
vector< vector<seqDist> > calcDists; calcDists.resize(1);
for (int thisIter = 0; thisIter < iters+1; thisIter++) {
vector<SharedRAbundVector*> thisItersLookup = thisLookup;
if (subsample && (thisIter != 0)) {
SubSample sample;
vector<string> tempLabels; //dont need since we arent printing the sampled sharedRabunds
//make copy of lookup so we don't get access violations
vector<SharedRAbundVector*> newLookup;
for (int k = 0; k < thisItersLookup.size(); k++) {
SharedRAbundVector* temp = new SharedRAbundVector();
temp->setLabel(thisItersLookup[k]->getLabel());
temp->setGroup(thisItersLookup[k]->getGroup());
newLookup.push_back(temp);
}
//for each bin
for (int k = 0; k < thisItersLookup[0]->getNumBins(); k++) {
if (m->control_pressed) { for (int j = 0; j < newLookup.size(); j++) { delete newLookup[j]; } return results; }
for (int j = 0; j < thisItersLookup.size(); j++) { newLookup[j]->push_back(thisItersLookup[j]->getAbundance(k), thisItersLookup[j]->getGroup()); }
}
tempLabels = sample.getSample(newLookup, subsampleSize);
thisItersLookup = newLookup;
}
driver(thisItersLookup, calcDists, matrixCalculator);
if (subsample && (thisIter != 0)) {
if((thisIter) % 100 == 0){ m->mothurOutJustToScreen(toString(thisIter)+"\n"); }
calcDistsTotals.push_back(calcDists);
for (int i = 0; i < calcDists.size(); i++) {
for (int j = 0; j < calcDists[i].size(); j++) {
if (m->debug) { m->mothurOut("[DEBUG]: Results: iter = " + toString(thisIter) + ", " + thisLookup[calcDists[i][j].seq1]->getGroup() + " - " + thisLookup[calcDists[i][j].seq2]->getGroup() + " distance = " + toString(calcDists[i][j].dist) + ".\n"); }
}
}
//clean up memory
for (int i = 0; i < thisItersLookup.size(); i++) { delete thisItersLookup[i]; }
thisItersLookup.clear();
}else { //print results for whole dataset
for (int i = 0; i < calcDists.size(); i++) {
if (m->control_pressed) { break; }
//initialize matrix
results.resize(thisLookup.size());
for (int k = 0; k < thisLookup.size(); k++) { results[k].resize(thisLookup.size(), 0.0); }
for (int j = 0; j < calcDists[i].size(); j++) {
int row = calcDists[i][j].seq1;
int column = calcDists[i][j].seq2;
double dist = calcDists[i][j].dist;
results[row][column] = dist;
results[column][row] = dist;
}
}
}
for (int i = 0; i < calcDists.size(); i++) { calcDists[i].clear(); }
}
if (iters != 0) {
//we need to find the average distance and standard deviation for each groups distance
vector< vector<seqDist> > calcAverages = m->getAverages(calcDistsTotals, "average");
//print results
for (int i = 0; i < calcDists.size(); i++) {
results.resize(thisLookup.size());
for (int k = 0; k < thisLookup.size(); k++) { results[k].resize(thisLookup.size(), 0.0); }
for (int j = 0; j < calcAverages[i].size(); j++) {
int row = calcAverages[i][j].seq1;
int column = calcAverages[i][j].seq2;
float dist = calcAverages[i][j].dist;
results[row][column] = dist;
results[column][row] = dist;
}
}
}
return results;
}
catch(exception& e) {
m->errorOut(e, "GetMetaCommunityCommand", "generateDistanceMatrix");
exit(1);
}
}
/**************************************************************************************************/
int GetMetaCommunityCommand::driver(vector<SharedRAbundVector*> thisLookup, vector< vector<seqDist> >& calcDists, Calculator* matrixCalculator) {
try {
vector<SharedRAbundVector*> subset;
for (int k = 0; k < thisLookup.size(); k++) { // pass cdd each set of groups to compare
for (int l = 0; l < k; l++) {
if (k != l) { //we dont need to similiarity of a groups to itself
subset.clear(); //clear out old pair of sharedrabunds
//add new pair of sharedrabunds
subset.push_back(thisLookup[k]); subset.push_back(thisLookup[l]);
//if this calc needs all groups to calculate the pair load all groups
if (matrixCalculator->getNeedsAll()) {
//load subset with rest of lookup for those calcs that need everyone to calc for a pair
for (int w = 0; w < thisLookup.size(); w++) {
if ((w != k) && (w != l)) { subset.push_back(thisLookup[w]); }
}
}
vector<double> tempdata = matrixCalculator->getValues(subset); //saves the calculator outputs
if (m->control_pressed) { return 1; }
seqDist temp(l, k, tempdata[0]);
//cout << l << '\t' << k << '\t' << tempdata[0] << endl;
calcDists[0].push_back(temp);
}
}
}
return 0;
}
catch(exception& e) {
m->errorOut(e, "MatrixOutputCommand", "driver");
exit(1);
}
}
//**********************************************************************************************************************
|
