X-Git-Url: https://git.donarmstrong.com/?p=mothur.git;a=blobdiff_plain;f=unifracweightedcommand.cpp;h=4883c48741717c677641c6b48bf7fe4ada0245f1;hp=47adc9a55b4ba929796fca2993138b89584bdee1;hb=18ccb5ee181cc69d8f8e9cbf178d7751e6199da5;hpb=1a5c2356c1b955c6ec024b2baf9f46377ee7c72e diff --git a/unifracweightedcommand.cpp b/unifracweightedcommand.cpp index 47adc9a..4883c48 100644 --- a/unifracweightedcommand.cpp +++ b/unifracweightedcommand.cpp @@ -359,7 +359,7 @@ int UnifracWeightedCommand::execute() { variables["[tag]"] = toString(i+1); string wFileName = getOutputFileName("weighted", variables); output = new ColumnFile(wFileName, itersString); - outputNames.push_back(wFileName); outputTypes["wweighted"].push_back(wFileName); + outputNames.push_back(wFileName); outputTypes["weighted"].push_back(wFileName); } userData = weighted.getValues(T[i], processors, outputDir); //userData[0] = weightedscore @@ -408,7 +408,7 @@ int UnifracWeightedCommand::execute() { delete newCt; delete subSampleTree; - if((thisIter+1) % 100 == 0){ m->mothurOut(toString(thisIter+1)); m->mothurOutEndLine(); } + if((thisIter+1) % 100 == 0){ m->mothurOutJustToScreen(toString(thisIter+1)+"\n"); } } if (m->control_pressed) { delete ct; for (int i = 0; i < T.size(); i++) { delete T[i]; } if (random) { delete output; } outSum.close(); for (int i = 0; i < outputNames.size(); i++) { m->mothurRemove(outputNames[i]); } return 0; } @@ -465,40 +465,28 @@ int UnifracWeightedCommand::getAverageSTDMatrices(vector< vector >& dist //we need to find the average distance and standard deviation for each groups distance //finds sum - vector averages; averages.resize(numComp, 0); - for (int thisIter = 0; thisIter < subsampleIters; thisIter++) { - for (int i = 0; i < dists[thisIter].size(); i++) { - averages[i] += dists[thisIter][i]; - } - } - - //finds average. - for (int i = 0; i < averages.size(); i++) { averages[i] /= (float) subsampleIters; } + vector averages = m->getAverages(dists); //find standard deviation - vector stdDev; stdDev.resize(numComp, 0); - - for (int thisIter = 0; thisIter < iters; thisIter++) { //compute the difference of each dist from the mean, and square the result of each - for (int j = 0; j < dists[thisIter].size(); j++) { - stdDev[j] += ((dists[thisIter][j] - averages[j]) * (dists[thisIter][j] - averages[j])); - } - } - for (int i = 0; i < stdDev.size(); i++) { - stdDev[i] /= (float) subsampleIters; - stdDev[i] = sqrt(stdDev[i]); - } + vector stdDev = m->getStandardDeviation(dists, averages); //make matrix with scores in it - vector< vector > avedists; avedists.resize(m->getNumGroups()); + vector< vector > avedists; //avedists.resize(m->getNumGroups()); for (int i = 0; i < m->getNumGroups(); i++) { - avedists[i].resize(m->getNumGroups(), 0.0); + vector temp; + for (int j = 0; j < m->getNumGroups(); j++) { temp.push_back(0.0); } + avedists.push_back(temp); } //make matrix with scores in it - vector< vector > stddists; stddists.resize(m->getNumGroups()); + vector< vector > stddists; //stddists.resize(m->getNumGroups()); for (int i = 0; i < m->getNumGroups(); i++) { - stddists[i].resize(m->getNumGroups(), 0.0); + vector temp; + for (int j = 0; j < m->getNumGroups(); j++) { temp.push_back(0.0); } + //stddists[i].resize(m->getNumGroups(), 0.0); + stddists.push_back(temp); } + //flip it so you can print it int count = 0; @@ -710,39 +698,32 @@ int UnifracWeightedCommand::runRandomCalcs(Tree* thisTree, vector usersS lines.clear(); -#if defined (__APPLE__) || (__MACH__) || (linux) || (__linux) || (__linux__) || (__unix__) || (__unix) - if(processors != 1){ - int numPairs = namesOfGroupCombos.size(); - int numPairsPerProcessor = numPairs / processors; + //breakdown work between processors + int numPairs = namesOfGroupCombos.size(); + int numPairsPerProcessor = numPairs / processors; - for (int i = 0; i < processors; i++) { - int startPos = i * numPairsPerProcessor; - if(i == processors - 1){ - numPairsPerProcessor = numPairs - i * numPairsPerProcessor; - } - lines.push_back(linePair(startPos, numPairsPerProcessor)); - } + for (int i = 0; i < processors; i++) { + int startPos = i * numPairsPerProcessor; + if(i == processors - 1){ numPairsPerProcessor = numPairs - i * numPairsPerProcessor; } + lines.push_back(linePair(startPos, numPairsPerProcessor)); } -#endif //get scores for random trees for (int j = 0; j < iters; j++) { - cout << j << endl; -#if defined (__APPLE__) || (__MACH__) || (linux) || (__linux) || (__linux__) || (__unix__) || (__unix) - if(processors == 1){ - driver(thisTree, namesOfGroupCombos, 0, namesOfGroupCombos.size(), rScores); - }else{ +//#if defined (__APPLE__) || (__MACH__) || (linux) || (__linux) || (__linux__) || (__unix__) || (__unix) + //if(processors == 1){ + // driver(thisTree, namesOfGroupCombos, 0, namesOfGroupCombos.size(), rScores); + // }else{ createProcesses(thisTree, namesOfGroupCombos, rScores); - } -#else - driver(thisTree, namesOfGroupCombos, 0, namesOfGroupCombos.size(), rScores); -#endif + // } +//#else + //driver(thisTree, namesOfGroupCombos, 0, namesOfGroupCombos.size(), rScores); +//#endif + if (m->control_pressed) { delete ct; for (int i = 0; i < T.size(); i++) { delete T[i]; } delete output; outSum.close(); for (int i = 0; i < outputNames.size(); i++) { m->mothurRemove(outputNames[i]); } return 0; } - //report progress - // m->mothurOut("Iter: " + toString(j+1)); m->mothurOutEndLine(); } lines.clear(); @@ -778,12 +759,11 @@ int UnifracWeightedCommand::runRandomCalcs(Tree* thisTree, vector usersS int UnifracWeightedCommand::createProcesses(Tree* t, vector< vector > namesOfGroupCombos, vector< vector >& scores) { try { -#if defined (__APPLE__) || (__MACH__) || (linux) || (__linux) || (__linux__) || (__unix__) || (__unix) - int process = 1; + int process = 1; vector processIDS; - EstOutput results; - + +#if defined (__APPLE__) || (__MACH__) || (linux) || (__linux) || (__linux__) || (__unix__) || (__unix) //loop through and create all the processes you want while (process != processors) { int pid = fork(); @@ -829,9 +809,53 @@ int UnifracWeightedCommand::createProcesses(Tree* t, vector< vector > na in.close(); m->mothurRemove(s); } +#else + //fill in functions + vector pDataArray; + DWORD dwThreadIdArray[processors-1]; + HANDLE hThreadArray[processors-1]; + vector cts; + vector trees; - return 0; -#endif + //Create processor worker threads. + for( int i=1; icopy(ct); + Tree* copyTree = new Tree(copyCount); + copyTree->getCopy(t); + + cts.push_back(copyCount); + trees.push_back(copyTree); + + vector< vector > copyScores = rScores; + + weightedRandomData* tempweighted = new weightedRandomData(m, lines[i].start, lines[i].num, namesOfGroupCombos, copyTree, copyCount, includeRoot, copyScores); + pDataArray.push_back(tempweighted); + processIDS.push_back(i); + + hThreadArray[i-1] = CreateThread(NULL, 0, MyWeightedRandomThreadFunction, pDataArray[i-1], 0, &dwThreadIdArray[i-1]); + } + + driver(t, namesOfGroupCombos, lines[0].start, lines[0].num, scores); + + //Wait until all threads have terminated. + WaitForMultipleObjects(processors-1, hThreadArray, TRUE, INFINITE); + + //Close all thread handles and free memory allocations. + for(int i=0; i < pDataArray.size(); i++){ + for (int j = pDataArray[i]->start; j < (pDataArray[i]->start+pDataArray[i]->num); j++) { + scores[j].push_back(pDataArray[i]->scores[j][pDataArray[i]->scores[j].size()-1]); + } + delete cts[i]; + delete trees[i]; + CloseHandle(hThreadArray[i]); + delete pDataArray[i]; + } + + +#endif + + return 0; } catch(exception& e) { m->errorOut(e, "UnifracWeightedCommand", "createProcesses"); @@ -891,7 +915,7 @@ void UnifracWeightedCommand::printWeightedFile() { for(int a = 0; a < numComp; a++) { output->initFile(groupComb[a], tags); //print each line - for (map::iterator it = validScores.begin(); it != validScores.end(); it++) { + for (map::iterator it = validScores.begin(); it != validScores.end(); it++) { data.push_back(it->first); data.push_back(rScoreFreq[a][it->first]); data.push_back(rCumul[a][it->first]); output->output(data); data.clear(); @@ -1061,7 +1085,7 @@ void UnifracWeightedCommand::calculateFreqsCumuls() { for (int f = 0; f < numComp; f++) { for (int i = 0; i < rScores[f].size(); i++) { //looks like 0,0,1,1,1,2,4,7... you want to make a map that say rScoreFreq[0] = 2, rScoreFreq[1] = 3... validScores[rScores[f][i]] = rScores[f][i]; - map::iterator it = rScoreFreq[f].find(rScores[f][i]); + map::iterator it = rScoreFreq[f].find(rScores[f][i]); if (it != rScoreFreq[f].end()) { rScoreFreq[f][rScores[f][i]]++; }else{ @@ -1074,9 +1098,9 @@ void UnifracWeightedCommand::calculateFreqsCumuls() { for(int a = 0; a < numComp; a++) { float rcumul = 1.0000; //this loop fills the cumulative maps and put 0.0000 in the score freq map to make it easier to print. - for (map::iterator it = validScores.begin(); it != validScores.end(); it++) { + for (map::iterator it = validScores.begin(); it != validScores.end(); it++) { //make rscoreFreq map and rCumul - map::iterator it2 = rScoreFreq[a].find(it->first); + map::iterator it2 = rScoreFreq[a].find(it->first); rCumul[a][it->first] = rcumul; //get percentage of random trees with that info if (it2 != rScoreFreq[a].end()) { rScoreFreq[a][it->first] /= iters; rcumul-= it2->second; }