4 correlationType::~correlationType() {}
6 // конструктор класса для инициализации
7 correlationType::correlationType() {}
9 correlationType::correlationType(const std::vector< RVec > &ref, int wnd, int taau, int tau_st, float crlUp, float effRad, int mod,
10 const std::string &out, const std::vector< int > &indx,
11 const std::vector< std::vector < std::vector < size_t > > > &sels,
12 const std::vector< std::string > &rsNames) {
13 setDefaults(ref, wnd, taau, tau_st, crlUp, effRad, mod, out, indx, sels, rsNames);
16 void correlationType::setDefaults(const std::vector< RVec > &ref, int wnd, int taau, int tau_st, float crlUp, float effRad, int mod,
17 const std::string &out, const std::vector< int > &indx,
18 const std::vector< std::vector < std::vector < size_t > > > &sels,
19 const std::vector< std::string > &rsNames) {
20 // очень странная штука в индуском стиле... зачем столько ифов?!!!
21 if (ref.size() != 0) {reference = ref;}
22 if (wnd != -1) {window = wnd;}
23 if (taau != -1) {tau = taau;}
24 if (tau_st != -1) {tauStep = tau_st;}
25 if (crlUp != -1) {crlUpBorder = crlUp;}
26 if (effRad != -1) {effRadius = effRad;}
27 if (mod != -1) {mode = mod;}
28 if (out != "") {outputName = out;}
29 if (sels.size() != 0) {selections = sels;}
30 if (rsNames.size() > 0) {resNames = rsNames;}
31 if (indx.size() > 0) {index = indx;}
32 subGraphRouts.resize(0);
33 trajectoryPartition();
36 void correlationType::update(const int frameNum, const std::vector< RVec > &curFrame) {
37 trajectory.push_back(curFrame);
38 size_t temp = window + tau;
39 if (trajectory.size() == temp + 1) {
40 trajectory.erase(trajectory.begin());
43 if ( ((frameNum - temp + 1) >= 0) && ((frameNum - temp + 1) % tauStep == 0)) {
45 selections.erase(selections.begin());
46 std::cout << "\n\t\tcorrEval successful\n" << std::endl;
51 void correlationType::readEval() {
53 readWriteCorrelations(0);
54 subGraphRouts.resize(subGraphRouts.size() + 1);
55 graphCalculations(1, static_cast< size_t >(tau));
56 graphBackBoneEvaluation();
60 void correlationType::printData() {
64 void correlationType::trajectoryPartition() {
65 std::vector< bool > temp1;
66 std::pair< size_t, size_t > temp2;
68 std::vector< std::vector < std::vector < size_t > > > selectionsTemp;
69 selectionsTemp.resize(selections.size());
70 for (size_t i1 {0}; i1 < selections.size(); i1++) {
71 selectionsTemp[i1].resize(selections[i1].size());
72 for (size_t i2 {0}; i2 < selections[i1].size(); i2++) {
73 selectionsTemp[i1][i2].resize(0);
74 for (size_t i3 {0}; i3 < selections[i1][i2].size(); i3++) {
75 for (size_t i4 {0}; i4 < index.size(); i4++) {
76 if (selections[i1][i2][i3] == index[i4]) {
77 selectionsTemp[i1][i2].push_back(i4);
84 selections = selectionsTemp;
85 for (auto &k : selections) {
87 temp1.resize(index.size(), true);
93 for (size_t i {0}; i < temp1.size(); i++) {
95 temp3 = std::numeric_limits<float>::max();
96 for (size_t f {0}; f < k.size(); f++) {
97 for (size_t j {0}; j < k[f].size(); j++) {
98 if (float temp4 {(reference[k[f][j]] - reference[i]).norm()}; temp3 > temp4) {
100 temp2 = std::make_pair(f, j);
104 k[temp2.first].push_back(i);
110 void correlationType::readWriteCorrelations(int rwMode) {
113 file = std::fopen((outputName + "-matrixData").c_str(), "a");
114 for (size_t i {0}; i < matrixes.size(); i++) {
115 std::fprintf(file, "%d %lud\n", count, i);
116 for (size_t j {0}; j < matrixes[i].size(); j++) {
117 for (size_t f {0}; f < matrixes[i][j].size(); f++) {
118 std::fprintf(file, "%.4f ", matrixes[i][j][f]); //~16
120 std::fprintf(file, "\n");
126 file = std::fopen((outputName + "-matrixData").c_str(), "r+");
128 matrixes.resize(static_cast< unsigned int >(tau + 1));
129 for (size_t i {0}; i < static_cast< size_t >(tau + 1); i++) {
130 int t0, t1, t2 = std::fscanf(file, "%d %d\n", &t0, &t1);
131 matrixes[i].resize(0);
132 matrixes[i].resize(index.size());
133 for (size_t j {0}; j < index.size(); j++) {
134 matrixes[i][j].resize(index.size());
135 for (size_t k {0}; k < index.size(); k++) {
136 t2 = std::fscanf(file, "%lf ", &matrixes[i][j][k]);
143 inline void correlationType::trajectoryFitting() {
144 std::vector< std::vector< std::pair< size_t, size_t > > > pairs;
146 pairs.resize(selections.front().size());
147 for (size_t i {0}; i < selections.front().size(); i++) {
149 for (size_t j {0}; j < selections.front()[i].size(); j++) {
150 pairs[i].push_back(std::make_pair(selections.front()[i][j], selections.front()[i][j]));
153 fitTrajectory.resize(0);
154 fitTrajectory.resize(selections.front().size(), trajectory);
155 #pragma omp parallel for schedule(dynamic) firstprivate(reference)
156 for (size_t i = 0; i < selections.front().size(); i++) {
157 for (size_t j {0}; j < fitTrajectory[i].size(); j++) {
158 MyFitNew(reference, fitTrajectory[i][j], pairs[i], 0);
162 for (size_t i {0}; i < selections.front().size(); i++) {
163 for (size_t j {0}; j < selections.front()[i].size(); j++) {
164 for (size_t k {0}; k < fitTrajectory[i].size(); k++) {
165 trajectory[k][selections.front()[i][j]] = fitTrajectory[i][k][selections.front()[i][j]];
171 inline void correlationType::matrixNullFitting() {
173 matrixes.resize(static_cast< size_t >(tau + 1));
174 for (auto &i : matrixes) {
176 i.resize(index.size());
179 j.resize(index.size());
187 void correlationType::correlationEval() {
190 std::vector< std::vector< double > > a, b, c;
191 std::vector< double > d;
192 d.resize(index.size(), 0.);
193 #pragma omp parallel for ordered schedule(dynamic) shared(matrixes) firstprivate(trajectory, reference)
194 for (size_t i = 0; i <= static_cast< size_t >(tau); i++) {
195 a.resize(0); b.resize(0); c.resize(0);
196 a.resize(index.size(), d); b.resize(index.size(), d); c.resize(index.size(), d);
197 for (size_t j {0}; j < static_cast< size_t >(window); j++) {
198 for (size_t k1 {0}; k1 < index.size(); k1++) {
199 for (size_t k2 {0}; k2 < index.size(); k2++) {
201 temp1 = trajectory[j][k1] - reference[k1];
202 temp2 = trajectory[j + i][k2] - reference[k2];
203 a[k1][k2] += (static_cast<double>(temp1[0]) * static_cast<double>(temp2[0]) +
204 static_cast<double>(temp1[1]) * static_cast<double>(temp2[1]) +
205 static_cast<double>(temp1[2]) * static_cast<double>(temp2[2]));
206 b[k1][k2] += (static_cast<double>(temp1[0]) * static_cast<double>(temp1[0]) +
207 static_cast<double>(temp1[1]) * static_cast<double>(temp1[1]) +
208 static_cast<double>(temp1[2]) * static_cast<double>(temp1[2]));
209 c[k1][k2] += (static_cast<double>(temp2[0]) * static_cast<double>(temp2[0]) +
210 static_cast<double>(temp2[1]) * static_cast<double>(temp2[1]) +
211 static_cast<double>(temp2[2]) * static_cast<double>(temp2[2]));
215 for (size_t j {0}; j < index.size(); j++) {
216 for (size_t k {0}; k < index.size(); k++) {
217 matrixes[i][j][k] = a[j][k] / (std::sqrt(b[j][k] * c[j][k]));
222 for (size_t i {0}; i < matrixes.size(); i++) {
223 for (size_t j {0}; j < matrixes[i].size(); j++) {
224 for (size_t k {0}; k < matrixes[i][j].size(); k++) {
225 matrixes[i][j][k] = std::round(matrixes[i][j][k] * 10000) / 10000;
229 readWriteCorrelations(1);
233 void correlationType::graphCalculations(size_t tauStart, size_t tauEnd) {
235 graph.resize(index.size());
236 subGraphPoints.resize(0);
237 subGraphRbr.resize(0);
238 for (size_t i {0}; i < index.size(); i++) {
239 graph[i].resize(index.size(), std::make_pair(0, -1));
242 for (size_t i {tauStart}; i <= tauEnd; i++) {
243 for (size_t j {0}; j < index.size(); j++) {
244 for (size_t k {j}; k < index.size(); k++) {
245 temp = reference[j] - reference[k];
246 if (double tempIf {std::max(std::abs(matrixes[i][j][k]), std::abs(matrixes[i][k][j]))}; (tempIf >= static_cast< double >(crlUpBorder)) &&
247 (static_cast< float >(norm(temp)) <= effRadius) && (std::abs(graph[j][k].first) < tempIf)) {
248 graph[j][k].first = tempIf;
249 graph[j][k].second = static_cast< int >(i);
254 std::vector< bool > graph_flags;
255 graph_flags.resize(0);
256 graph_flags.resize(index.size(), true);
257 std::vector< size_t > a;
258 std::vector< std::pair< size_t, size_t > > b;
261 std::vector< size_t > width1, width2, tempSubGraph;
262 for (size_t i {0}; i < index.size(); i++) {
263 if (graph_flags[i]) {
264 subGraphPoints.push_back(a);
265 subGraphRbr.push_back(b);
268 tempSubGraph.resize(0);
270 tempSubGraph.push_back(i);
271 graph_flags[i] = false;
272 while(width1.size() > 0) {
274 for (size_t j {0}; j < width1.size(); j++) {
275 for (size_t k {0}; k < index.size(); k++) {
276 if ((graph[width1[j]][k].second > -1) && graph_flags[k]) {
278 graph_flags[k] = false;
283 for (size_t j {0}; j < width2.size(); j++) {
284 tempSubGraph.push_back(width2[j]);
287 subGraphPoints.back() = tempSubGraph;
288 for (size_t j {0}; j < tempSubGraph.size(); j++) {
289 for (size_t k {0}; k < index.size(); k++) {
290 if (graph[tempSubGraph[j]][k].second > -1) {
291 subGraphRbr.back().push_back(std::make_pair(tempSubGraph[j], k));
299 bool correlationType::myComparisonFunction (const std::pair< int, double > i, const std::pair< int, double > j) {
300 return i.second < j.second;
303 void correlationType::graphBackBoneEvaluation() {
304 std::vector< double > key;
305 std::vector< long > path;
306 std::vector< std::pair< size_t, double > > que;
307 std::vector< std::pair< size_t, size_t > > a;
310 subGraphRouts.back().resize(0);
311 for (size_t i {0}; i < subGraphPoints.size(); i++) {
316 if (subGraphPoints[i].size() > 2) {
317 key.resize(index.size(), 2);
318 path.resize(index.size(), -1);
319 key[subGraphPoints[i][0]] = 0;
320 for (size_t j {0}; j < subGraphPoints[i].size(); j++) {
321 que.push_back(std::make_pair(subGraphPoints[i][j], key[subGraphPoints[i][j]]));
323 std::sort(que.begin(), que.end(), myComparisonFunction);
324 while (!que.empty()) {
325 v = que.front().first;
326 que.erase(que.begin());
327 for (size_t j {0}; j < subGraphRbr[i].size(); j++) {
329 if (subGraphRbr[i][j].first == v) {
330 u = subGraphRbr[i][j].second;
331 } else if (subGraphRbr[i][j].second == v) {
332 u = subGraphRbr[i][j].first;
336 for (size_t k {0}; k < que.size(); k++) {
337 if (que[k].first == u) {
343 if (double tempIf {1. - std::abs(graph[v][static_cast< size_t >(u)].first)};
344 flag && (key[static_cast< size_t >(u)] > tempIf)) {
345 path[static_cast< size_t >(u)] = v;
346 key[static_cast< size_t >(u)] = tempIf;
347 que[pos].second = key[static_cast< size_t >(u)];
348 sort(que.begin(), que.end(), myComparisonFunction);
352 subGraphRouts.back().push_back(a);
353 for (size_t j {0}; j < index.size(); j++) {
355 subGraphRouts.back().back().push_back(std::make_pair(path[j], j));
362 void correlationType::printOutputData() {
363 FILE *file {std::fopen((outputName + "-arrowsData.txt").c_str(), "w+")};
364 size_t same, pre {0};
365 std::vector< std::tuple< int, int, std::vector< int > > > table;
367 std::vector< int > a;
368 for (size_t i {0}; i < subGraphRouts.size(); i++) {
370 for (size_t j {i + 1}; j < subGraphRouts.size(); j++) {
371 if (subGraphRouts[j] == subGraphRouts[i]) {
378 std::fprintf(file, "\n Starting time point = %d | correlations >= %0.2f | tau = %d | window = %d\n\n", static_cast< int >(i) * tauStep, static_cast< double >(crlUpBorder), tau, window);
380 std::fprintf(file, "\n Starting time point = [%d ; %d] | correlations >= %0.2f | tau = %d | window = %d\n\n", static_cast< int >(i) * tauStep, static_cast< int >(same) * tauStep, static_cast< double >(crlUpBorder), tau, window);
382 for (size_t j {0}; j < subGraphRouts[i].size(); j++) {
383 for (size_t k {0}; k < subGraphRouts[i][j].size(); k++) {
384 std::fprintf(file, "cgo_arrow (id %3d), (id %3d), radius=0.05\n", index[subGraphRouts[i][j][k].first] + 1, index[subGraphRouts[i][j][k].second] + 1);
386 std::fprintf(file, "\n");
389 for (auto &j : subGraphRouts[i]) {
391 bool flag1 {true}, flag2 {true};
392 for (size_t m {0}; m < table.size(); m++) {
393 if (std::get<0>(table[m]) == index[k.first]) {
394 std::get<1>(table[m])++;
395 std::get<2>(table[m]).push_back(index[k.second]);
398 if (std::get<0>(table[m]) == index[k.second]) {
399 std::get<1>(table[m])++;
400 std::get<2>(table[m]).push_back(index[k.first]);
406 a.push_back(index[k.second]);
407 table.push_back(std::make_tuple(index[k.first], 1, a));
411 a.push_back(index[k.first]);
412 table.push_back(std::make_tuple(index[k.second], 1, a));
416 for (size_t j {0}; j < table.size(); j++) {
417 std::fprintf(file, "residue %s connections %d | ", (resNames[static_cast< size_t >(std::find(index.begin(), index.end(), std::get<0>(table[j])) - index.begin())]).c_str(), std::get<1>(table[j]));
418 for (size_t k {0}; k < std::get<2>(table[j]).size(); k++) {
419 std::fprintf(file, "%s ", (resNames[static_cast< size_t >(std::find(index.begin(), index.end(), std::get<2>(table[j])[k]) - index.begin())]).c_str());
421 std::fprintf(file, "\n");
424 std::vector< std::vector< std::pair< size_t, size_t > > > temp01, temp02;
425 std::vector< std::pair< size_t, size_t > > temp03, temp04, temp05;
426 temp01 = subGraphRouts[pre];
427 temp02 = subGraphRouts[same];
431 for (auto &j : temp01) {
436 for (auto &j : temp02) {
441 std::sort(temp03.begin(), temp03.end());
442 std::sort(temp04.begin(), temp04.end());
443 std::set_difference(temp03.begin(), temp03.end(), temp04.begin(), temp04.end(), std::inserter(temp05, temp05.begin()));
444 std::fprintf(file, "minus:\n");
445 for (auto &j : temp05) {
446 std::fprintf(file, "cgo_arrow (id %3d), (id %3d), radius=0.05\n", index[j.first] + 1, index[j.second] + 1);
449 std::set_difference(temp04.begin(), temp04.end(), temp03.begin(), temp03.end(), std::inserter(temp05, temp05.begin()));
450 std::fprintf(file, "plus:\n");
451 for (auto &j : temp05) {
452 std::fprintf(file, "cgo_arrow (id %3d), (id %3d), radius=0.05\n", index[j.first] + 1, index[j.second] + 1);