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37 * Implements gmx::analysismodules::PairDistance.
39 * \author Teemu Murtola <teemu.murtola@gmail.com>
40 * \ingroup module_trajectoryanalysis
53 #include "gromacs/analysisdata/analysisdata.h"
54 #include "gromacs/analysisdata/modules/plot.h"
55 #include "gromacs/options/basicoptions.h"
56 #include "gromacs/options/filenameoption.h"
57 #include "gromacs/options/ioptionscontainer.h"
58 #include "gromacs/selection/nbsearch.h"
59 #include "gromacs/selection/selection.h"
60 #include "gromacs/selection/selectionoption.h"
61 #include "gromacs/trajectory/trajectoryframe.h"
62 #include "gromacs/trajectoryanalysis/analysissettings.h"
63 #include "gromacs/trajectoryanalysis/topologyinformation.h"
64 #include "gromacs/utility/arrayref.h"
65 #include "gromacs/utility/exceptions.h"
66 #include "gromacs/utility/stringutil.h"
71 namespace analysismodules
77 //! \addtogroup module_trajectoryanalysis
80 //! Enum value to store the selected value for `-type`.
81 enum class DistanceType : int
88 //! Enum value to store the selected value for `-refgrouping`/`-selgrouping`.
89 enum class GroupType : int
98 //! Strings corresponding to DistanceType.
99 const EnumerationArray<DistanceType, const char*> c_distanceTypeNames = { { "min", "max" } };
100 //! Strings corresponding to GroupType.
101 const EnumerationArray<GroupType, const char*> c_groupTypeNames = { { "all", "res", "mol",
105 * Implements `gmx pairdist` trajectory analysis module.
107 class PairDistance : public TrajectoryAnalysisModule
112 void initOptions(IOptionsContainer* options, TrajectoryAnalysisSettings* settings) override;
113 void initAnalysis(const TrajectoryAnalysisSettings& settings, const TopologyInformation& top) override;
115 TrajectoryAnalysisModuleDataPointer startFrames(const AnalysisDataParallelOptions& opt,
116 const SelectionCollection& selections) override;
117 void analyzeFrame(int frnr, const t_trxframe& fr, t_pbc* pbc, TrajectoryAnalysisModuleData* pdata) override;
119 void finishAnalysis(int nframes) override;
120 void writeOutput() override;
124 * Computed distances as a function of time.
126 * There is one data set for each selection in `sel_`.
127 * Within each data set, there is one column for each distance to be
128 * computed, as explained in the `-h` text.
130 AnalysisData distances_;
133 * Reference selection to compute distances to.
135 * mappedId() identifies the group (of type `refGroupType_`) into which
136 * each position belogs.
140 * Selections to compute distances from.
142 * mappedId() identifies the group (of type `selGroupType_`) into which
143 * each position belogs.
150 DistanceType distanceType_;
151 GroupType refGroupType_;
152 GroupType selGroupType_;
154 //! Number of groups in `refSel_`.
156 //! Maximum number of pairs of groups for one selection.
158 //! Initial squared distance for distance accumulation.
160 //! Cutoff squared for use in the actual calculation.
163 //! Neighborhood search object for the pair search.
164 AnalysisNeighborhood nb_;
166 // Copy and assign disallowed by base.
169 PairDistance::PairDistance() :
171 distanceType_(DistanceType::Min),
172 refGroupType_(GroupType::All),
173 selGroupType_(GroupType::All),
179 registerAnalysisDataset(&distances_, "dist");
183 void PairDistance::initOptions(IOptionsContainer* options, TrajectoryAnalysisSettings* settings)
185 static const char* const desc[] = {
186 "[THISMODULE] calculates pairwise distances between one reference",
187 "selection (given with [TT]-ref[tt]) and one or more other selections",
188 "(given with [TT]-sel[tt]). It can calculate either the minimum",
189 "distance (the default), or the maximum distance (with",
190 "[TT]-type max[tt]). Distances to each selection provided with",
191 "[TT]-sel[tt] are computed independently.[PAR]",
192 "By default, the global minimum/maximum distance is computed.",
193 "To compute more distances (e.g., minimum distances to each residue",
194 "in [TT]-ref[tt]), use [TT]-refgrouping[tt] and/or [TT]-selgrouping[tt]",
195 "to specify how the positions within each selection should be",
197 "Computed distances are written to the file specified with [TT]-o[tt].",
198 "If there are N groups in [TT]-ref[tt] and M groups in the first",
199 "selection in [TT]-sel[tt], then the output contains N*M columns",
200 "for the first selection. The columns contain distances like this:",
201 "r1-s1, r2-s1, ..., r1-s2, r2-s2, ..., where rn is the n'th group",
202 "in [TT]-ref[tt] and sn is the n'th group in the other selection.",
203 "The distances for the second selection comes as separate columns",
204 "after the first selection, and so on. If some selections are",
205 "dynamic, only the selected positions are used in the computation",
206 "but the same number of columns is always written out. If there",
207 "are no positions contributing to some group pair, then the cutoff",
208 "value is written (see below).[PAR]",
209 "[TT]-cutoff[tt] sets a cutoff for the computed distances.",
210 "If the result would contain a distance over the cutoff, the cutoff",
211 "value is written to the output file instead. By default, no cutoff",
212 "is used, but if you are not interested in values beyond a cutoff,",
213 "or if you know that the minimum distance is smaller than a cutoff,",
214 "you should set this option to allow the tool to use grid-based",
215 "searching and be significantly faster.[PAR]",
216 "If you want to compute distances between fixed pairs,",
217 "[gmx-distance] may be a more suitable tool."
220 settings->setHelpText(desc);
222 options->addOption(FileNameOption("o")
227 .defaultBasename("dist")
228 .description("Distances as function of time"));
231 DoubleOption("cutoff").store(&cutoff_).description("Maximum distance to consider"));
232 options->addOption(EnumOption<DistanceType>("type")
233 .store(&distanceType_)
234 .enumValue(c_distanceTypeNames)
235 .description("Type of distances to calculate"));
237 EnumOption<GroupType>("refgrouping")
238 .store(&refGroupType_)
239 .enumValue(c_groupTypeNames)
240 .description("Grouping of -ref positions to compute the min/max over"));
242 EnumOption<GroupType>("selgrouping")
243 .store(&selGroupType_)
244 .enumValue(c_groupTypeNames)
245 .description("Grouping of -sel positions to compute the min/max over"));
247 options->addOption(SelectionOption("ref").store(&refSel_).required().description(
248 "Reference positions to calculate distances from"));
249 options->addOption(SelectionOption("sel").storeVector(&sel_).required().multiValue().description(
250 "Positions to calculate distances for"));
253 //! Helper function to initialize the grouping for a selection.
254 int initSelectionGroups(Selection* sel, const gmx_mtop_t* top, GroupType type)
256 e_index_t indexType = INDEX_UNKNOWN;
259 case GroupType::All: indexType = INDEX_ALL; break;
260 case GroupType::Residue: indexType = INDEX_RES; break;
261 case GroupType::Molecule: indexType = INDEX_MOL; break;
262 case GroupType::None: indexType = INDEX_ATOM; break;
263 case GroupType::Count: GMX_THROW(InternalError("Invalid GroupType"));
265 return sel->initOriginalIdsToGroup(top, indexType);
269 void PairDistance::initAnalysis(const TrajectoryAnalysisSettings& settings, const TopologyInformation& top)
271 refGroupCount_ = initSelectionGroups(&refSel_, top.mtop(), refGroupType_);
274 distances_.setDataSetCount(sel_.size());
275 for (size_t i = 0; i < sel_.size(); ++i)
277 const int selGroupCount = initSelectionGroups(&sel_[i], top.mtop(), selGroupType_);
278 const int columnCount = refGroupCount_ * selGroupCount;
279 maxGroupCount_ = std::max(maxGroupCount_, columnCount);
280 distances_.setColumnCount(i, columnCount);
283 if (!fnDist_.empty())
285 AnalysisDataPlotModulePointer plotm(new AnalysisDataPlotModule(settings.plotSettings()));
286 plotm->setFileName(fnDist_);
287 if (distanceType_ == DistanceType::Max)
289 plotm->setTitle("Maximum distance");
293 plotm->setTitle("Minimum distance");
295 // TODO: Figure out and add a descriptive subtitle and/or a longer
296 // title and/or better legends based on the grouping and the reference
298 plotm->setXAxisIsTime();
299 plotm->setYLabel("Distance (nm)");
300 for (size_t g = 0; g < sel_.size(); ++g)
302 plotm->appendLegend(sel_[g].name());
304 distances_.addModule(plotm);
307 nb_.setCutoff(cutoff_);
311 initialDist2_ = std::numeric_limits<real>::max();
315 initialDist2_ = cutoff_ * cutoff_;
317 if (distanceType_ == DistanceType::Max)
321 cutoff2_ = cutoff_ * cutoff_;
325 * Temporary memory for use within a single-frame calculation.
327 class PairDistanceModuleData : public TrajectoryAnalysisModuleData
331 * Reserves memory for the frame-local data.
333 PairDistanceModuleData(TrajectoryAnalysisModule* module,
334 const AnalysisDataParallelOptions& opt,
335 const SelectionCollection& selections,
337 const Selection& refSel,
339 TrajectoryAnalysisModuleData(module, opt, selections)
341 distArray_.resize(maxGroupCount);
342 countArray_.resize(maxGroupCount);
343 refCountArray_.resize(refGroupCount);
344 if (!refSel.isDynamic())
346 initRefCountArray(refSel);
350 void finish() override { finishDataHandles(); }
353 * Computes the number of positions in each group in \p refSel
354 * and stores them into `refCountArray_`.
356 void initRefCountArray(const Selection& refSel)
358 std::fill(refCountArray_.begin(), refCountArray_.end(), 0);
360 while (refPos < refSel.posCount())
362 const int refIndex = refSel.position(refPos).mappedId();
363 const int startPos = refPos;
365 while (refPos < refSel.posCount() && refSel.position(refPos).mappedId() == refIndex)
369 refCountArray_[refIndex] = refPos - startPos;
374 * Squared distance between each group
376 * One entry for each group pair for the current selection.
377 * Enough memory is allocated to fit the largest calculation selection.
378 * This is needed to support neighborhood searching, which may not
379 * return the pairs in order: for each group pair, we need to search
380 * through all the position pairs and update this array to find the
381 * minimum/maximum distance between them.
383 std::vector<real> distArray_;
385 * Number of pairs within the cutoff that have contributed to the value
388 * This is needed to identify whether there were any pairs inside the
389 * cutoff and whether there were additional pairs outside the cutoff
390 * that were not covered by the neihborhood search.
392 std::vector<int> countArray_;
394 * Number of positions within each reference group.
396 * This is used to more efficiently compute the total number of pairs
397 * (for comparison with `countArray_`), as otherwise these numbers
398 * would need to be recomputed for each selection.
400 std::vector<int> refCountArray_;
403 TrajectoryAnalysisModuleDataPointer PairDistance::startFrames(const AnalysisDataParallelOptions& opt,
404 const SelectionCollection& selections)
406 return TrajectoryAnalysisModuleDataPointer(new PairDistanceModuleData(
407 this, opt, selections, refGroupCount_, refSel_, maxGroupCount_));
410 void PairDistance::analyzeFrame(int frnr, const t_trxframe& fr, t_pbc* pbc, TrajectoryAnalysisModuleData* pdata)
412 AnalysisDataHandle dh = pdata->dataHandle(distances_);
413 const Selection& refSel = TrajectoryAnalysisModuleData::parallelSelection(refSel_);
414 const SelectionList& sel = TrajectoryAnalysisModuleData::parallelSelections(sel_);
415 PairDistanceModuleData& frameData = *static_cast<PairDistanceModuleData*>(pdata);
416 std::vector<real>& distArray = frameData.distArray_;
417 std::vector<int>& countArray = frameData.countArray_;
419 if (cutoff_ > 0.0 && refSel.isDynamic())
421 // Count the number of reference positions in each group, so that
422 // this does not need to be computed again for each selection.
423 // This is needed only if it is possible that the neighborhood search
424 // does not cover all the pairs, hence the cutoff > 0.0 check.
425 // If refSel is static, then the array contents are static as well,
426 // and it has been initialized in the constructor of the data object.
427 frameData.initRefCountArray(refSel);
429 const std::vector<int>& refCountArray = frameData.refCountArray_;
431 AnalysisNeighborhoodSearch nbsearch = nb_.initSearch(pbc, refSel);
432 dh.startFrame(frnr, fr.time);
433 for (size_t g = 0; g < sel.size(); ++g)
435 const int columnCount = distances_.columnCount(g);
436 std::fill(distArray.begin(), distArray.begin() + columnCount, initialDist2_);
437 std::fill(countArray.begin(), countArray.begin() + columnCount, 0);
439 // Accumulate the number of position pairs within the cutoff and the
440 // min/max distance for each group pair.
441 AnalysisNeighborhoodPairSearch pairSearch = nbsearch.startPairSearch(sel[g]);
442 AnalysisNeighborhoodPair pair;
443 while (pairSearch.findNextPair(&pair))
445 const SelectionPosition& refPos = refSel.position(pair.refIndex());
446 const SelectionPosition& selPos = sel[g].position(pair.testIndex());
447 const int refIndex = refPos.mappedId();
448 const int selIndex = selPos.mappedId();
449 const int index = selIndex * refGroupCount_ + refIndex;
450 const real r2 = pair.distance2();
451 if (distanceType_ == DistanceType::Min)
453 if (distArray[index] > r2)
455 distArray[index] = r2;
460 if (distArray[index] < r2)
462 distArray[index] = r2;
468 // If it is possible that positions outside the cutoff (or lack of
469 // them) affects the result, then we need to check whether there were
470 // any. This is necessary for two cases:
471 // - With max distances, if there are pairs outside the cutoff, then
472 // the computed distance should be equal to the cutoff instead of
473 // the largest distance that was found above.
474 // - With either distance type, if all pairs are outside the cutoff,
475 // then countArray must be updated so that the presence flag
476 // in the output data reflects the dynamic selection status, not
477 // whether something was inside the cutoff or not.
481 // Loop over groups in this selection (at start, selPos is always
482 // the first position in the next group).
483 while (selPos < sel[g].posCount())
485 // Count the number of positions in this group.
486 const int selIndex = sel[g].position(selPos).mappedId();
487 const int startPos = selPos;
489 while (selPos < sel[g].posCount() && sel[g].position(selPos).mappedId() == selIndex)
493 const int count = selPos - startPos;
494 // Check all group pairs that contain this group.
495 for (int i = 0; i < refGroupCount_; ++i)
497 const int index = selIndex * refGroupCount_ + i;
498 const int totalCount = refCountArray[i] * count;
499 // If there were positions outside the cutoff,
500 // update the distance if necessary and the count.
501 if (countArray[index] < totalCount)
503 if (distanceType_ == DistanceType::Max)
505 distArray[index] = cutoff2_;
507 countArray[index] = totalCount;
513 // Write the computed distances to the output data.
515 for (int i = 0; i < columnCount; ++i)
517 if (countArray[i] > 0)
519 dh.setPoint(i, std::sqrt(distArray[i]));
523 // If there are no contributing positions, write out the cutoff
525 dh.setPoint(i, cutoff_, false);
532 void PairDistance::finishAnalysis(int /*nframes*/) {}
534 void PairDistance::writeOutput() {}
540 const char PairDistanceInfo::name[] = "pairdist";
541 const char PairDistanceInfo::shortDescription[] =
542 "Calculate pairwise distances between groups of positions";
544 TrajectoryAnalysisModulePointer PairDistanceInfo::create()
546 return TrajectoryAnalysisModulePointer(new PairDistance);
549 } // namespace analysismodules