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 std::cout << "\tola001";
38 trajectory.push_back(curFrame);
39 size_t temp = window + tau;
40 std::cout << "\tola002";
41 if (trajectory.size() == temp + 1) {
42 trajectory.erase(trajectory.begin());
44 std::cout << "\tola003";
46 std::cout << "\tola004";
47 if ((frameNum - temp + 1) % tauStep == 0) {
49 selections.erase(selections.begin());
50 std::cout << "ola005" << std::endl;
53 std::cout << "\tola006";
56 void correlationType::readEval() {
57 std::cout << "ola005" << std::endl;
59 readWriteCorrelations(0);
60 subGraphRouts.resize(subGraphRouts.size() + 1);
61 std::cout << "ola006" << std::endl;
62 graphCalculations(1, static_cast< size_t >(tau));
63 std::cout << "ola007" << std::endl;
64 graphBackBoneEvaluation();
65 std::cout << "ola008" << std::endl;
69 void correlationType::printData() {
73 void correlationType::trajectoryPartition() {
74 std::vector< bool > temp1;
75 std::pair< size_t, size_t > temp2;
77 std::vector< std::vector < std::vector < size_t > > > selectionsTemp;
78 selectionsTemp.resize(selections.size());
79 for (size_t i1 {0}; i1 < selections.size(); i1++) {
80 selectionsTemp[i1].resize(selections[i1].size());
81 for (size_t i2 {0}; i2 < selections[i1].size(); i2++) {
82 selectionsTemp[i1][i2].resize(0);
83 for (size_t i3 {0}; i3 < selections[i1][i2].size(); i3++) {
84 for (size_t i4 {0}; i4 < index.size(); i4++) {
85 if (selections[i1][i2][i3] == index[i4]) {
86 selectionsTemp[i1][i2].push_back(i4);
93 selections = selectionsTemp;
94 for (auto &k : selections) {
96 temp1.resize(index.size(), true);
102 for (size_t i {0}; i < temp1.size(); i++) {
104 temp3 = std::numeric_limits<float>::max();
105 for (size_t f {0}; f < k.size(); f++) {
106 for (size_t j {0}; j < k[f].size(); j++) {
107 if (float temp4 {(reference[k[f][j]] - reference[i]).norm()}; temp3 > temp4) {
109 temp2 = std::make_pair(f, j);
113 k[temp2.first].push_back(i);
119 void correlationType::readWriteCorrelations(int rwMode) {
122 file = std::fopen((outputName + "-matrixData").c_str(), "a");
123 for (size_t i {0}; i < matrixes.size(); i++) {
124 std::fprintf(file, "%d %lud\n", count, i);
125 for (size_t j {0}; j < matrixes[i].size(); j++) {
126 for (size_t f {0}; f < matrixes[i][j].size(); f++) {
127 std::fprintf(file, "%.4f ", matrixes[i][j][f]); //~16
129 std::fprintf(file, "\n");
135 file = std::fopen((outputName + "-matrixData").c_str(), "r+");
137 matrixes.resize(static_cast< unsigned int >(tau + 1));
138 for (size_t i {0}; i < static_cast< size_t >(tau + 1); i++) {
139 int t0, t1, t2 = std::fscanf(file, "%d %d\n", &t0, &t1);
140 matrixes[i].resize(0);
141 matrixes[i].resize(index.size());
142 for (size_t j {0}; j < index.size(); j++) {
143 matrixes[i][j].resize(index.size());
144 for (size_t k {0}; k < index.size(); k++) {
145 t2 = std::fscanf(file, "%lf ", &matrixes[i][j][k]);
152 inline void correlationType::trajectoryFitting() {
153 std::vector< std::vector< std::pair< size_t, size_t > > > pairs;
155 pairs.resize(selections.front().size());
156 for (size_t i {0}; i < selections.front().size(); i++) {
158 for (size_t j {0}; j < selections.front()[i].size(); j++) {
159 pairs[i].push_back(std::make_pair(selections.front()[i][j], selections.front()[i][j]));
162 fitTrajectory.resize(0);
163 fitTrajectory.resize(selections.front().size(), trajectory);
164 #pragma omp parallel for schedule(dynamic) firstprivate(reference)
165 for (size_t i = 0; i < selections.front().size(); i++) {
166 for (size_t j {0}; j < fitTrajectory[i].size(); j++) {
167 MyFitNew(reference, fitTrajectory[i][j], pairs[i], 0);
171 for (size_t i {0}; i < selections.front().size(); i++) {
172 for (size_t j {0}; j < selections.front()[i].size(); j++) {
173 for (size_t k {0}; k < fitTrajectory[i].size(); k++) {
174 trajectory[k][selections.front()[i][j]] = fitTrajectory[i][k][selections.front()[i][j]];
180 inline void correlationType::matrixNullFitting() {
182 matrixes.resize(static_cast< size_t >(tau + 1));
183 for (auto &i : matrixes) {
185 i.resize(index.size());
188 j.resize(index.size());
196 void correlationType::correlationEval() {
199 std::vector< std::vector< double > > a, b, c;
200 std::vector< double > d;
201 d.resize(index.size(), 0.);
202 #pragma omp parallel for ordered schedule(dynamic) shared(matrixes) firstprivate(trajectory, reference)
203 for (size_t i = 0; i <= static_cast< size_t >(tau); i++) {
204 a.resize(0); b.resize(0); c.resize(0);
205 a.resize(index.size(), d); b.resize(index.size(), d); c.resize(index.size(), d);
206 for (size_t j {0}; j < static_cast< size_t >(window); j++) {
207 for (size_t k1 {0}; k1 < index.size(); k1++) {
208 for (size_t k2 {0}; k2 < index.size(); k2++) {
210 temp1 = trajectory[j][k1] - reference[k1];
211 temp2 = trajectory[j + i][k2] - reference[k2];
212 a[k1][k2] += (static_cast<double>(temp1[0]) * static_cast<double>(temp2[0]) +
213 static_cast<double>(temp1[1]) * static_cast<double>(temp2[1]) +
214 static_cast<double>(temp1[2]) * static_cast<double>(temp2[2]));
215 b[k1][k2] += (static_cast<double>(temp1[0]) * static_cast<double>(temp1[0]) +
216 static_cast<double>(temp1[1]) * static_cast<double>(temp1[1]) +
217 static_cast<double>(temp1[2]) * static_cast<double>(temp1[2]));
218 c[k1][k2] += (static_cast<double>(temp2[0]) * static_cast<double>(temp2[0]) +
219 static_cast<double>(temp2[1]) * static_cast<double>(temp2[1]) +
220 static_cast<double>(temp2[2]) * static_cast<double>(temp2[2]));
224 for (size_t j {0}; j < index.size(); j++) {
225 for (size_t k {0}; k < index.size(); k++) {
226 matrixes[i][j][k] = a[j][k] / (std::sqrt(b[j][k] * c[j][k]));
231 for (size_t i {0}; i < matrixes.size(); i++) {
232 for (size_t j {0}; j < matrixes[i].size(); j++) {
233 for (size_t k {0}; k < matrixes[i][j].size(); k++) {
234 matrixes[i][j][k] = std::round(matrixes[i][j][k] * 10000) / 10000;
238 readWriteCorrelations(1);
242 void correlationType::graphCalculations(size_t tauStart, size_t tauEnd) {
244 graph.resize(index.size());
245 subGraphPoints.resize(0);
246 subGraphRbr.resize(0);
247 for (size_t i {0}; i < index.size(); i++) {
248 graph[i].resize(index.size(), std::make_pair(0, -1));
251 for (size_t i {tauStart}; i <= tauEnd; i++) {
252 for (size_t j {0}; j < index.size(); j++) {
253 for (size_t k {j}; k < index.size(); k++) {
254 temp = reference[j] - reference[k];
255 if (double tempIf {std::max(std::abs(matrixes[i][j][k]), std::abs(matrixes[i][k][j]))}; (tempIf >= static_cast< double >(crlUpBorder)) &&
256 (static_cast< float >(norm(temp)) <= effRadius) && (std::abs(graph[j][k].first) < tempIf)) {
257 graph[j][k].first = tempIf;
258 graph[j][k].second = static_cast< int >(i);
263 std::vector< bool > graph_flags;
264 graph_flags.resize(0);
265 graph_flags.resize(index.size(), true);
266 std::vector< size_t > a;
267 std::vector< std::pair< size_t, size_t > > b;
270 std::vector< size_t > width1, width2, tempSubGraph;
271 for (size_t i {0}; i < index.size(); i++) {
272 if (graph_flags[i]) {
273 subGraphPoints.push_back(a);
274 subGraphRbr.push_back(b);
277 tempSubGraph.resize(0);
279 tempSubGraph.push_back(i);
280 graph_flags[i] = false;
281 while(width1.size() > 0) {
283 for (size_t j {0}; j < width1.size(); j++) {
284 for (size_t k {0}; k < index.size(); k++) {
285 if ((graph[width1[j]][k].second > -1) && graph_flags[k]) {
287 graph_flags[k] = false;
292 for (size_t j {0}; j < width2.size(); j++) {
293 tempSubGraph.push_back(width2[j]);
296 subGraphPoints.back() = tempSubGraph;
297 for (size_t j {0}; j < tempSubGraph.size(); j++) {
298 for (size_t k {0}; k < index.size(); k++) {
299 if (graph[tempSubGraph[j]][k].second > -1) {
300 subGraphRbr.back().push_back(std::make_pair(tempSubGraph[j], k));
308 bool correlationType::myComparisonFunction (const std::pair< int, double > i, const std::pair< int, double > j) {
309 return i.second < j.second;
312 void correlationType::graphBackBoneEvaluation() {
313 std::vector< double > key;
314 std::vector< long > path;
315 std::vector< std::pair< size_t, double > > que;
316 std::vector< std::pair< size_t, size_t > > a;
319 subGraphRouts.back().resize(0);
320 for (size_t i {0}; i < subGraphPoints.size(); i++) {
325 if (subGraphPoints[i].size() > 2) {
326 key.resize(index.size(), 2);
327 path.resize(index.size(), -1);
328 key[subGraphPoints[i][0]] = 0;
329 for (size_t j {0}; j < subGraphPoints[i].size(); j++) {
330 que.push_back(std::make_pair(subGraphPoints[i][j], key[subGraphPoints[i][j]]));
332 std::sort(que.begin(), que.end(), myComparisonFunction);
333 while (!que.empty()) {
334 v = que.front().first;
335 que.erase(que.begin());
336 for (size_t j {0}; j < subGraphRbr[i].size(); j++) {
338 if (subGraphRbr[i][j].first == v) {
339 u = subGraphRbr[i][j].second;
340 } else if (subGraphRbr[i][j].second == v) {
341 u = subGraphRbr[i][j].first;
345 for (size_t k {0}; k < que.size(); k++) {
346 if (que[k].first == u) {
352 if (double tempIf {1. - std::abs(graph[v][static_cast< size_t >(u)].first)};
353 flag && (key[static_cast< size_t >(u)] > tempIf)) {
354 path[static_cast< size_t >(u)] = v;
355 key[static_cast< size_t >(u)] = tempIf;
356 que[pos].second = key[static_cast< size_t >(u)];
357 sort(que.begin(), que.end(), myComparisonFunction);
361 subGraphRouts.back().push_back(a);
362 for (size_t j {0}; j < index.size(); j++) {
364 subGraphRouts.back().back().push_back(std::make_pair(path[j], j));
371 void correlationType::printOutputData() {
372 FILE *file {std::fopen((outputName + "-arrowsData.txt").c_str(), "w+")};
373 size_t same, pre {0};
374 std::vector< std::tuple< int, int, std::vector< int > > > table;
376 std::vector< int > a;
377 for (size_t i {0}; i < subGraphRouts.size(); i++) {
379 for (size_t j {i + 1}; j < subGraphRouts.size(); j++) {
380 if (subGraphRouts[j] == subGraphRouts[i]) {
387 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);
389 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);
391 for (size_t j {0}; j < subGraphRouts[i].size(); j++) {
392 for (size_t k {0}; k < subGraphRouts[i][j].size(); k++) {
393 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);
395 std::fprintf(file, "\n");
398 for (auto &j : subGraphRouts[i]) {
400 bool flag1 {true}, flag2 {true};
401 for (size_t m {0}; m < table.size(); m++) {
402 if (std::get<0>(table[m]) == index[k.first]) {
403 std::get<1>(table[m])++;
404 std::get<2>(table[m]).push_back(index[k.second]);
407 if (std::get<0>(table[m]) == index[k.second]) {
408 std::get<1>(table[m])++;
409 std::get<2>(table[m]).push_back(index[k.first]);
415 a.push_back(index[k.second]);
416 table.push_back(std::make_tuple(index[k.first], 1, a));
420 a.push_back(index[k.first]);
421 table.push_back(std::make_tuple(index[k.second], 1, a));
425 for (size_t j {0}; j < table.size(); j++) {
426 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]));
427 for (size_t k {0}; k < std::get<2>(table[j]).size(); k++) {
428 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());
430 std::fprintf(file, "\n");
433 std::vector< std::vector< std::pair< size_t, size_t > > > temp01, temp02;
434 std::vector< std::pair< size_t, size_t > > temp03, temp04, temp05;
435 temp01 = subGraphRouts[pre];
436 temp02 = subGraphRouts[same];
440 for (auto &j : temp01) {
445 for (auto &j : temp02) {
450 std::sort(temp03.begin(), temp03.end());
451 std::sort(temp04.begin(), temp04.end());
452 std::set_difference(temp03.begin(), temp03.end(), temp04.begin(), temp04.end(), std::inserter(temp05, temp05.begin()));
453 std::fprintf(file, "minus:\n");
454 for (auto &j : temp05) {
455 std::fprintf(file, "cgo_arrow (id %3d), (id %3d), radius=0.05\n", index[j.first] + 1, index[j.second] + 1);
458 std::set_difference(temp04.begin(), temp04.end(), temp03.begin(), temp03.end(), std::inserter(temp05, temp05.begin()));
459 std::fprintf(file, "plus:\n");
460 for (auto &j : temp05) {
461 std::fprintf(file, "cgo_arrow (id %3d), (id %3d), radius=0.05\n", index[j.first] + 1, index[j.second] + 1);