CDPP / AMDA_Kernel

Commit 2e05aaf70f15af9896caa7e46486eca685a7f642

Authored by Hacene SI HADJ MOHAND
1 parent 79c1e322
Exists in master and in 69 other branches 10038, 10098, 5390, 5770, 7616, 7875, 8459, 8528, 9016, 9016Bis, 9017, 9017-new, 9049, 9084, 9259, 9326, 9347, 9383, 9719, 9719.new, AllLegends, CDF_ISTP, CDF_ISTP_HOPEFULLY_ALL_WORKING, FER_10400, FER_10412, FER_10663, FER_10765, FER_11000, FER_11100, FER_11242, FER_11277, FER_11500, FER_11537, FER_11588, FER_11651, FER_19836, FER_5344, FER_6031, FER_6598, FER_6966, FER_7318, FER_7618, FER_7857, FER_8455, FER_9629, FER_CR41, FER_CR42, FER_CR43, FER_TFCat, Histo1D2D, JUNO_JEDI, MAZ_10936, MAZ_6018, MAZ_9016_New, MAZ_FIX_9016, SpeasyGet, amdadev, amdadev_test, cu2022, das2, density_maps, develop, evol_9042, feature/9259, pickle, rm_6912, rm_8932, test-merge, ubuntu

param 1d ok

Showing 2 changed files with 174 additions and 7 deletions   Show diff stats
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src/ExternLib/DataFiltering/DataFiltering.hh
  Diff comments   View file @2e05aaf
... ... @@ -35,7 +35,6 @@ namespace AMDA {
35 35  
36 36 template <typename ElemType>
37 37 struct FilteringContainer {
38   - ~FilteringContainer(){}
39 38 // size of real points(not nan and not spike)
40 39 int _size = 0;
41 40 int _nFilteredPoints = 0;
... ... @@ -48,10 +47,30 @@ namespace AMDA {
48 47 };
49 48  
50 49 template <typename ElemType>
51   - struct FilteringContainer1D {
52   - FilteringContainer1D(){}
53   - ~FilteringContainer1D(){
54   - delete &_size;
  50 + class FilteringContainer1D {
  51 + public:
  52 + FilteringContainer1D(){
  53 + }
  54 + void clean() {
  55 + _size.clear();
  56 + _nFilteredPoints.clear();
  57 + _sum.clear();
  58 + _sumsq.clear();
  59 + _ave.clear();
  60 + _sig.clear();
  61 + _values.clear();
  62 + _times.clear();
  63 + }
  64 +
  65 + void init(int size) {
  66 + std::vector<int> intVect(size, 0);
  67 + std::vector<ElemType> eltVect(size, 0);
  68 + _size = intVect;
  69 + _nFilteredPoints = intVect;
  70 + _sum = eltVect;
  71 + _sumsq = eltVect;
  72 + _ave = eltVect;
  73 + _sig = eltVect;
55 74 }
56 75 // size of real points(not nan and not spike)
57 76 std::vector<int> _size;
... ... @@ -190,7 +209,155 @@ namespace AMDA {
190 209  
191 210 };
192 211  
193   -
  212 + template <typename ElemType>
  213 + class DataFiltering1D : public Operation {
  214 + public:
  215 +
  216 + DataFiltering1D(Process& pProcess, ParamDataSpec<std::vector<ElemType> >& paramInput, double factor = Default::_factor, int nPoints = Default::_nPoints) :
  217 + Operation(pProcess),
  218 + _paramInput(paramInput),
  219 + _paramOutput(new ParamDataSpec<std::vector<ElemType> > ()),
  220 + _factor(factor),
  221 + _nPoints(nPoints),
  222 + _container(new FilteringContainer1D<ElemType>()){
  223 + _paramDataOutput = _paramOutput;
  224 + }
  225 +
  226 + virtual ~DataFiltering1D() {
  227 + }
  228 +
  229 + void write(ParamDataIndexInfo &pParamDataIndexInfo) {
  230 + // init container
  231 + int size = _paramInput.get(pParamDataIndexInfo._startIndex).size();
  232 + _container->init(size);
  233 +
  234 + for (unsigned int _index = pParamDataIndexInfo._startIndex;
  235 + _index < pParamDataIndexInfo._startIndex + pParamDataIndexInfo._nbDataToProcess;
  236 + ++_index) {
  237 + double crtTime = _paramInput.getTime(_index);
  238 + std::vector<ElemType> inputElt = _paramInput.get(_index);
  239 +
  240 + _paramOutput->pushTime(crtTime);
  241 + _paramOutput->getDataList().push_back(inputElt);
  242 +
  243 +
  244 + // initialiser et remplir container
  245 + if (*std::min_element(std::begin(_container->_size), std::end(_container->_size)) < _nPoints) {
  246 +
  247 + _container->_values.push_back(inputElt);
  248 + _container->_times.push_back(crtTime);
  249 + for (int i = 0; i < size; i++) {
  250 + if (!isNAN(inputElt[i])) {
  251 + _container->_sum[i] += inputElt[i];
  252 + _container->_sumsq[i] += inputElt[i] * inputElt[i];
  253 + _container->_size[i] += 1;
  254 + }
  255 + }
  256 + } else {
  257 + for (int i = 0; i < size; i++) {
  258 + _container->_ave[i] = (ElemType) _container->_sum[i] / _container->_size[i];
  259 + _container->_sig[i] = std::sqrt((_container->_sumsq[i] - _container->_sum[i] * _container->_sum[i] / _container->_size[i]) / _container->_size[i]);
  260 + }
  261 +
  262 + // filter Elements
  263 + for (auto elt = _container->_values.begin(); elt != _container->_values.end(); ++elt) {
  264 + int i;
  265 + for (auto it = elt->begin(); it != elt->end(); ++it) {
  266 + i = it - elt->begin();
  267 + ElemType crt_val = *it;
  268 + if (isNAN(crt_val)) {
  269 + continue;
  270 + }
  271 +
  272 + if (std::abs(crt_val - _container->_ave[i]) > _factor * _container->_sig[i]) {
  273 + _container->_sum[i] -= crt_val;
  274 + _container->_sumsq[i] -= crt_val*crt_val;
  275 + _container->_size[i] -= 1;
  276 + _container->_nFilteredPoints[i] += 1;
  277 + *it << NotANumber();
  278 + }
  279 + }
  280 + }
  281 + _paramOutput->pushTime(_container->_times.front());
  282 + _paramOutput->getDataList().push_back(_container->_values.front());
  283 + _container->_values.pop_front();
  284 + _container->_times.pop_front();
  285 + for (int i = 0; i < size; i++) {
  286 + if (!isNAN(_container->_values.front()[i])) {
  287 + _container->_size[i] -= 1;
  288 + _container->_sum[i] -= _container->_values.front()[i];
  289 + _container->_sumsq[i] -= _container->_values.front()[i] * _container->_values.front()[i];
  290 + }
  291 + if (!isNAN(inputElt[i])) {
  292 + _container->_sum[i] += inputElt[i];
  293 + _container->_sumsq[i] += inputElt[i] * inputElt[i];
  294 + _container->_size[i] += 1;
  295 + }
  296 + }
  297 + _container->_values.push_back(inputElt);
  298 + _container->_times.push_back(crtTime);
  299 + }
  300 + // last value filter and write
  301 + if (_index == pParamDataIndexInfo._startIndex + pParamDataIndexInfo._nbDataToProcess - 1) {
  302 + for (int i = 0; i < size; i++) {
  303 + _container->_ave[i] = (ElemType) _container->_sum[i] / _container->_size[i];
  304 + _container->_sig[i] = std::sqrt((_container->_sumsq[i] - _container->_sum[i] * _container->_sum[i] / _container->_size[i]) / _container->_size[i]);
  305 + }
  306 + for (auto elt = _container->_values.begin(); elt != _container->_values.end(); ++elt) {
  307 + int i;
  308 + for (auto it = elt->begin(); it != elt->end(); ++it) {
  309 + i = it - elt->begin();
  310 + ElemType crt_val = *it;
  311 + if (isNAN(crt_val)) {
  312 + continue;
  313 + }
  314 +
  315 + if (std::abs(crt_val - _container->_ave[i]) > _factor * _container->_sig[i]) {
  316 + _container->_sum[i] -= crt_val;
  317 + _container->_sumsq[i] -= crt_val*crt_val;
  318 + _container->_size[i] -= 1;
  319 + _container->_nFilteredPoints[i] += 1;
  320 + *it << NotANumber();
  321 + }
  322 + }
  323 + }
  324 +
  325 + std::list<double>::iterator itTimes = _container->_times.begin();
  326 + for (auto elt : _container->_values) {
  327 + _paramOutput->pushTime(*itTimes);
  328 + _paramOutput->getDataList().push_back(elt);
  329 + ++itTimes;
  330 + }
  331 + }
  332 +
  333 + }
  334 + }
  335 + private:
  336 + /**
  337 + * input data
  338 + */
  339 + ParamDataSpec<std::vector<ElemType > >& _paramInput;
  340 +
  341 + /**
  342 + * oupout filtered data
  343 + */
  344 + ParamDataSpec<std::vector<ElemType> >* _paramOutput;
  345 +
  346 + /**
  347 + * factor in term of sigma used in the filtering
  348 + */
  349 + double _factor;
  350 +
  351 + /**
  352 + Number of point used in the fitering algorithm
  353 + */
  354 + int _nPoints;
  355 +
  356 + /**
  357 + * Data container used during filtering
  358 + */
  359 + FilteringContainer1D<ElemType>* _container;
  360 + };
194 361 }
195 362 }
196 363 }
... ...
src/ExternLib/DataFiltering/DataFilteringCreator.hh
  Diff comments   View file @2e05aaf
... ... @@ -173,7 +173,7 @@ namespace AMDA {
173 173 }
174 174 template <typename Type>
175 175 void create1DOperation() {
176   -
  176 + _operation = new DataFiltering::DataFiltering1D<Type>(_process, dynamic_cast<ParamDataSpec<std::vector<Type> > &> (_paramData), _factor, _nPoints);
177 177 }
178 178  
179 179 Process &_process;
... ...