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) % tauStep == 0) {
45 selections.erase(selections.begin());
46 std::cout << "ola004" << std::endl;
51 void correlationType::readEval() {
52 std::cout << "ola005" << std::endl;
54 readWriteCorrelations(0);
55 subGraphRouts.resize(subGraphRouts.size() + 1);
56 std::cout << "ola006" << std::endl;
57 graphCalculations(1, static_cast< size_t >(tau));
58 std::cout << "ola007" << std::endl;
59 graphBackBoneEvaluation();
60 std::cout << "ola008" << std::endl;
64 void correlationType::printData() {
68 void correlationType::trajectoryPartition() {
69 std::vector< bool > temp1;
70 std::pair< size_t, size_t > temp2;
72 std::vector< std::vector < std::vector < size_t > > > selectionsTemp;
73 selectionsTemp.resize(selections.size());
74 for (size_t i1 {0}; i1 < selections.size(); i1++) {
75 selectionsTemp[i1].resize(selections[i1].size());
76 for (size_t i2 {0}; i2 < selections[i1].size(); i2++) {
77 selectionsTemp[i1][i2].resize(0);
78 for (size_t i3 {0}; i3 < selections[i1][i2].size(); i3++) {
79 for (size_t i4 {0}; i4 < index.size(); i4++) {
80 if (selections[i1][i2][i3] == index[i4]) {
81 selectionsTemp[i1][i2].push_back(i4);
88 selections = selectionsTemp;
89 for (auto &k : selections) {
91 temp1.resize(index.size(), true);
97 for (size_t i {0}; i < temp1.size(); i++) {
99 temp3 = std::numeric_limits<float>::max();
100 for (size_t f {0}; f < k.size(); f++) {
101 for (size_t j {0}; j < k[f].size(); j++) {
102 if (float temp4 {(reference[k[f][j]] - reference[i]).norm()}; temp3 > temp4) {
104 temp2 = std::make_pair(f, j);
108 k[temp2.first].push_back(i);
114 void correlationType::readWriteCorrelations(int rwMode) {
117 file = std::fopen((outputName + "-matrixData").c_str(), "a");
118 for (size_t i {0}; i < matrixes.size(); i++) {
119 std::fprintf(file, "%d %lud\n", count, i);
120 for (size_t j {0}; j < matrixes[i].size(); j++) {
121 for (size_t f {0}; f < matrixes[i][j].size(); f++) {
122 std::fprintf(file, "%.4f ", matrixes[i][j][f]); //~16
124 std::fprintf(file, "\n");
130 file = std::fopen((outputName + "-matrixData").c_str(), "r+");
132 matrixes.resize(static_cast< unsigned int >(tau + 1));
133 for (size_t i {0}; i < static_cast< size_t >(tau + 1); i++) {
134 int t0, t1, t2 = std::fscanf(file, "%d %d\n", &t0, &t1);
135 matrixes[i].resize(0);
136 matrixes[i].resize(index.size());
137 for (size_t j {0}; j < index.size(); j++) {
138 matrixes[i][j].resize(index.size());
139 for (size_t k {0}; k < index.size(); k++) {
140 t2 = std::fscanf(file, "%lf ", &matrixes[i][j][k]);
147 inline void correlationType::trajectoryFitting() {
148 std::vector< std::vector< std::pair< size_t, size_t > > > pairs;
150 pairs.resize(selections.front().size());
151 for (size_t i {0}; i < selections.front().size(); i++) {
153 for (size_t j {0}; j < selections.front()[i].size(); j++) {
154 pairs[i].push_back(std::make_pair(selections.front()[i][j], selections.front()[i][j]));
157 fitTrajectory.resize(0);
158 fitTrajectory.resize(selections.front().size(), trajectory);
159 #pragma omp parallel for schedule(dynamic) firstprivate(reference)
160 for (size_t i = 0; i < selections.front().size(); i++) {
161 for (size_t j {0}; j < fitTrajectory[i].size(); j++) {
162 MyFitNew(reference, fitTrajectory[i][j], pairs[i], 0);
166 for (size_t i {0}; i < selections.front().size(); i++) {
167 for (size_t j {0}; j < selections.front()[i].size(); j++) {
168 for (size_t k {0}; k < fitTrajectory[i].size(); k++) {
169 trajectory[k][selections.front()[i][j]] = fitTrajectory[i][k][selections.front()[i][j]];
175 inline void correlationType::matrixNullFitting() {
177 matrixes.resize(static_cast< size_t >(tau + 1));
178 for (auto &i : matrixes) {
180 i.resize(index.size());
183 j.resize(index.size());
191 void correlationType::correlationEval() {
194 std::vector< std::vector< double > > a, b, c;
195 std::vector< double > d;
196 d.resize(index.size(), 0.);
197 #pragma omp parallel for ordered schedule(dynamic) shared(matrixes) firstprivate(trajectory, reference)
198 for (size_t i = 0; i <= static_cast< size_t >(tau); i++) {
199 a.resize(0); b.resize(0); c.resize(0);
200 a.resize(index.size(), d); b.resize(index.size(), d); c.resize(index.size(), d);
201 for (size_t j {0}; j < static_cast< size_t >(window); j++) {
202 for (size_t k1 {0}; k1 < index.size(); k1++) {
203 for (size_t k2 {0}; k2 < index.size(); k2++) {
205 temp1 = trajectory[j][k1] - reference[k1];
206 temp2 = trajectory[j + i][k2] - reference[k2];
207 a[k1][k2] += (static_cast<double>(temp1[0]) * static_cast<double>(temp2[0]) +
208 static_cast<double>(temp1[1]) * static_cast<double>(temp2[1]) +
209 static_cast<double>(temp1[2]) * static_cast<double>(temp2[2]));
210 b[k1][k2] += (static_cast<double>(temp1[0]) * static_cast<double>(temp1[0]) +
211 static_cast<double>(temp1[1]) * static_cast<double>(temp1[1]) +
212 static_cast<double>(temp1[2]) * static_cast<double>(temp1[2]));
213 c[k1][k2] += (static_cast<double>(temp2[0]) * static_cast<double>(temp2[0]) +
214 static_cast<double>(temp2[1]) * static_cast<double>(temp2[1]) +
215 static_cast<double>(temp2[2]) * static_cast<double>(temp2[2]));
219 for (size_t j {0}; j < index.size(); j++) {
220 for (size_t k {0}; k < index.size(); k++) {
221 matrixes[i][j][k] = a[j][k] / (std::sqrt(b[j][k] * c[j][k]));
226 for (size_t i {0}; i < matrixes.size(); i++) {
227 for (size_t j {0}; j < matrixes[i].size(); j++) {
228 for (size_t k {0}; k < matrixes[i][j].size(); k++) {
229 matrixes[i][j][k] = std::round(matrixes[i][j][k] * 10000) / 10000;
233 readWriteCorrelations(1);
237 void correlationType::graphCalculations(size_t tauStart, size_t tauEnd) {
239 graph.resize(index.size());
240 subGraphPoints.resize(0);
241 subGraphRbr.resize(0);
242 for (size_t i {0}; i < index.size(); i++) {
243 graph[i].resize(index.size(), std::make_pair(0, -1));
246 for (size_t i {tauStart}; i <= tauEnd; i++) {
247 for (size_t j {0}; j < index.size(); j++) {
248 for (size_t k {j}; k < index.size(); k++) {
249 temp = reference[j] - reference[k];
250 if (double tempIf {std::max(std::abs(matrixes[i][j][k]), std::abs(matrixes[i][k][j]))}; (tempIf >= static_cast< double >(crlUpBorder)) &&
251 (static_cast< float >(norm(temp)) <= effRadius) && (std::abs(graph[j][k].first) < tempIf)) {
252 graph[j][k].first = tempIf;
253 graph[j][k].second = static_cast< int >(i);
258 std::vector< bool > graph_flags;
259 graph_flags.resize(0);
260 graph_flags.resize(index.size(), true);
261 std::vector< size_t > a;
262 std::vector< std::pair< size_t, size_t > > b;
265 std::vector< size_t > width1, width2, tempSubGraph;
266 for (size_t i {0}; i < index.size(); i++) {
267 if (graph_flags[i]) {
268 subGraphPoints.push_back(a);
269 subGraphRbr.push_back(b);
272 tempSubGraph.resize(0);
274 tempSubGraph.push_back(i);
275 graph_flags[i] = false;
276 while(width1.size() > 0) {
278 for (size_t j {0}; j < width1.size(); j++) {
279 for (size_t k {0}; k < index.size(); k++) {
280 if ((graph[width1[j]][k].second > -1) && graph_flags[k]) {
282 graph_flags[k] = false;
287 for (size_t j {0}; j < width2.size(); j++) {
288 tempSubGraph.push_back(width2[j]);
291 subGraphPoints.back() = tempSubGraph;
292 for (size_t j {0}; j < tempSubGraph.size(); j++) {
293 for (size_t k {0}; k < index.size(); k++) {
294 if (graph[tempSubGraph[j]][k].second > -1) {
295 subGraphRbr.back().push_back(std::make_pair(tempSubGraph[j], k));
303 bool correlationType::myComparisonFunction (const std::pair< int, double > i, const std::pair< int, double > j) {
304 return i.second < j.second;
307 void correlationType::graphBackBoneEvaluation() {
308 std::vector< double > key;
309 std::vector< long > path;
310 std::vector< std::pair< size_t, double > > que;
311 std::vector< std::pair< size_t, size_t > > a;
314 subGraphRouts.back().resize(0);
315 for (size_t i {0}; i < subGraphPoints.size(); i++) {
320 if (subGraphPoints[i].size() > 2) {
321 key.resize(index.size(), 2);
322 path.resize(index.size(), -1);
323 key[subGraphPoints[i][0]] = 0;
324 for (size_t j {0}; j < subGraphPoints[i].size(); j++) {
325 que.push_back(std::make_pair(subGraphPoints[i][j], key[subGraphPoints[i][j]]));
327 std::sort(que.begin(), que.end(), myComparisonFunction);
328 while (!que.empty()) {
329 v = que.front().first;
330 que.erase(que.begin());
331 for (size_t j {0}; j < subGraphRbr[i].size(); j++) {
333 if (subGraphRbr[i][j].first == v) {
334 u = subGraphRbr[i][j].second;
335 } else if (subGraphRbr[i][j].second == v) {
336 u = subGraphRbr[i][j].first;
340 for (size_t k {0}; k < que.size(); k++) {
341 if (que[k].first == u) {
347 if (double tempIf {1. - std::abs(graph[v][static_cast< size_t >(u)].first)};
348 flag && (key[static_cast< size_t >(u)] > tempIf)) {
349 path[static_cast< size_t >(u)] = v;
350 key[static_cast< size_t >(u)] = tempIf;
351 que[pos].second = key[static_cast< size_t >(u)];
352 sort(que.begin(), que.end(), myComparisonFunction);
356 subGraphRouts.back().push_back(a);
357 for (size_t j {0}; j < index.size(); j++) {
359 subGraphRouts.back().back().push_back(std::make_pair(path[j], j));
366 void correlationType::printOutputData() {
367 FILE *file {std::fopen((outputName + "-arrowsData.txt").c_str(), "w+")};
368 size_t same, pre {0};
369 std::vector< std::tuple< int, int, std::vector< int > > > table;
371 std::vector< int > a;
372 for (size_t i {0}; i < subGraphRouts.size(); i++) {
374 for (size_t j {i + 1}; j < subGraphRouts.size(); j++) {
375 if (subGraphRouts[j] == subGraphRouts[i]) {
382 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);
384 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);
386 for (size_t j {0}; j < subGraphRouts[i].size(); j++) {
387 for (size_t k {0}; k < subGraphRouts[i][j].size(); k++) {
388 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);
390 std::fprintf(file, "\n");
393 for (auto &j : subGraphRouts[i]) {
395 bool flag1 {true}, flag2 {true};
396 for (size_t m {0}; m < table.size(); m++) {
397 if (std::get<0>(table[m]) == index[k.first]) {
398 std::get<1>(table[m])++;
399 std::get<2>(table[m]).push_back(index[k.second]);
402 if (std::get<0>(table[m]) == index[k.second]) {
403 std::get<1>(table[m])++;
404 std::get<2>(table[m]).push_back(index[k.first]);
410 a.push_back(index[k.second]);
411 table.push_back(std::make_tuple(index[k.first], 1, a));
415 a.push_back(index[k.first]);
416 table.push_back(std::make_tuple(index[k.second], 1, a));
420 for (size_t j {0}; j < table.size(); j++) {
421 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]));
422 for (size_t k {0}; k < std::get<2>(table[j]).size(); k++) {
423 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());
425 std::fprintf(file, "\n");
428 std::vector< std::vector< std::pair< size_t, size_t > > > temp01, temp02;
429 std::vector< std::pair< size_t, size_t > > temp03, temp04, temp05;
430 temp01 = subGraphRouts[pre];
431 temp02 = subGraphRouts[same];
435 for (auto &j : temp01) {
440 for (auto &j : temp02) {
445 std::sort(temp03.begin(), temp03.end());
446 std::sort(temp04.begin(), temp04.end());
447 std::set_difference(temp03.begin(), temp03.end(), temp04.begin(), temp04.end(), std::inserter(temp05, temp05.begin()));
448 std::fprintf(file, "minus:\n");
449 for (auto &j : temp05) {
450 std::fprintf(file, "cgo_arrow (id %3d), (id %3d), radius=0.05\n", index[j.first] + 1, index[j.second] + 1);
453 std::set_difference(temp04.begin(), temp04.end(), temp03.begin(), temp03.end(), std::inserter(temp05, temp05.begin()));
454 std::fprintf(file, "plus:\n");
455 for (auto &j : temp05) {
456 std::fprintf(file, "cgo_arrow (id %3d), (id %3d), radius=0.05\n", index[j.first] + 1, index[j.second] + 1);