@@ -509,7 +509,8 @@ struct Control {
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real_T propScale {};
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real_T nsTolerance {};
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boolean_T calcSldDuringFit {};
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- py::array_t <real_T> resampleParams;
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+ real_T resampleMinAngle {};
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+ real_T resampleNPoints {};
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real_T updateFreq {};
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real_T updatePlotFreq {};
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real_T nSamples {};
@@ -914,8 +915,8 @@ RAT::struct2_T createStruct2T(const Control& control)
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stringToRatArray (control.procedure , control_struct.procedure .data , control_struct.procedure .size );
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stringToRatArray (control.display , control_struct.display .data , control_struct.display .size );
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control_struct.xTolerance = control.xTolerance ;
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- control_struct.resampleParams [ 0 ] = control.resampleParams . at ( 0 ) ;
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- control_struct.resampleParams [ 1 ] = control.resampleParams . at ( 1 ) ;
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+ control_struct.resampleMinAngle = control.resampleMinAngle ;
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+ control_struct.resampleNPoints = control.resampleNPoints ;
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stringToRatArray (control.boundHandling , control_struct.boundHandling .data , control_struct.boundHandling .size );
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control_struct.adaptPCR = control.adaptPCR ;
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control_struct.checks = createStruct3 (control.checks );
@@ -1616,7 +1617,8 @@ PYBIND11_MODULE(rat_core, m) {
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.def_readwrite (" propScale" , &Control::propScale)
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.def_readwrite (" nsTolerance" , &Control::nsTolerance)
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.def_readwrite (" calcSldDuringFit" , &Control::calcSldDuringFit)
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- .def_readwrite (" resampleParams" , &Control::resampleParams)
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+ .def_readwrite (" resampleMinAngle" , &Control::resampleMinAngle)
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+ .def_readwrite (" resampleNPoints" , &Control::resampleNPoints)
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.def_readwrite (" updateFreq" , &Control::updateFreq)
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.def_readwrite (" updatePlotFreq" , &Control::updatePlotFreq)
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.def_readwrite (" nSamples" , &Control::nSamples)
@@ -1633,14 +1635,14 @@ PYBIND11_MODULE(rat_core, m) {
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return py::make_tuple (ctrl.parallel , ctrl.procedure , ctrl.display , ctrl.xTolerance , ctrl.funcTolerance ,
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ctrl.maxFuncEvals , ctrl.maxIterations , ctrl.populationSize , ctrl.fWeight , ctrl.crossoverProbability ,
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ctrl.targetValue , ctrl.numGenerations , ctrl.strategy , ctrl.nLive , ctrl.nMCMC , ctrl.propScale ,
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- ctrl.nsTolerance , ctrl.calcSldDuringFit , ctrl.resampleParams , ctrl.updateFreq , ctrl. updatePlotFreq ,
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- ctrl.nSamples , ctrl.nChains , ctrl.jumpProbability , ctrl.pUnitGamma , ctrl.boundHandling , ctrl.adaptPCR ,
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- ctrl.IPCFilePath , ctrl.checks . fitParam , ctrl.checks .fitBackgroundParam , ctrl.checks .fitQzshift ,
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- ctrl.checks .fitScalefactor , ctrl.checks .fitBulkIn , ctrl.checks .fitBulkOut ,
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+ ctrl.nsTolerance , ctrl.calcSldDuringFit , ctrl.resampleMinAngle , ctrl.resampleNPoints ,
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+ ctrl.updateFreq , ctrl.updatePlotFreq , ctrl.nSamples , ctrl.nChains , ctrl.jumpProbability , ctrl.pUnitGamma ,
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+ ctrl.boundHandling , ctrl.adaptPCR , ctrl. IPCFilePath , ctrl.checks .fitParam , ctrl.checks .fitBackgroundParam ,
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+ ctrl.checks .fitQzshift , ctrl. checks . fitScalefactor , ctrl.checks .fitBulkIn , ctrl.checks .fitBulkOut ,
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ctrl.checks .fitResolutionParam , ctrl.checks .fitDomainRatio );
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},
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[](py::tuple t) { // __setstate__
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- if (t.size () != 36 )
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+ if (t.size () != 37 )
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throw std::runtime_error (" Encountered invalid state unpickling ProblemDefinition object!" );
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/* Create a new C++ instance */
@@ -1664,25 +1666,26 @@ PYBIND11_MODULE(rat_core, m) {
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ctrl.propScale = t[15 ].cast <real_T>();
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ctrl.nsTolerance = t[16 ].cast <real_T>();
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ctrl.calcSldDuringFit = t[17 ].cast <boolean_T>();
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- ctrl.resampleParams = t[18 ].cast <py::array_t <real_T>>();
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- ctrl.updateFreq = t[19 ].cast <real_T>();
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- ctrl.updatePlotFreq = t[20 ].cast <real_T>();
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- ctrl.nSamples = t[21 ].cast <real_T>();
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- ctrl.nChains = t[22 ].cast <real_T>();
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- ctrl.jumpProbability = t[23 ].cast <real_T>();
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- ctrl.pUnitGamma = t[24 ].cast <real_T>();
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- ctrl.boundHandling = t[25 ].cast <std::string>();
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- ctrl.adaptPCR = t[26 ].cast <boolean_T>();
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- ctrl.IPCFilePath = t[27 ].cast <std::string>();
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+ ctrl.resampleMinAngle = t[18 ].cast <real_T>();
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+ ctrl.resampleNPoints = t[19 ].cast <real_T>();
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+ ctrl.updateFreq = t[20 ].cast <real_T>();
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+ ctrl.updatePlotFreq = t[21 ].cast <real_T>();
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+ ctrl.nSamples = t[22 ].cast <real_T>();
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+ ctrl.nChains = t[23 ].cast <real_T>();
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+ ctrl.jumpProbability = t[24 ].cast <real_T>();
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+ ctrl.pUnitGamma = t[25 ].cast <real_T>();
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+ ctrl.boundHandling = t[26 ].cast <std::string>();
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+ ctrl.adaptPCR = t[27 ].cast <boolean_T>();
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+ ctrl.IPCFilePath = t[28 ].cast <std::string>();
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- ctrl.checks .fitParam = t[28 ].cast <py::array_t <real_T>>();
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- ctrl.checks .fitBackgroundParam = t[29 ].cast <py::array_t <real_T>>();
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- ctrl.checks .fitQzshift = t[30 ].cast <py::array_t <real_T>>();
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- ctrl.checks .fitScalefactor = t[31 ].cast <py::array_t <real_T>>();
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- ctrl.checks .fitBulkIn = t[32 ].cast <py::array_t <real_T>>();
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- ctrl.checks .fitBulkOut = t[33 ].cast <py::array_t <real_T>>();
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- ctrl.checks .fitResolutionParam = t[34 ].cast <py::array_t <real_T>>();
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- ctrl.checks .fitDomainRatio = t[35 ].cast <py::array_t <real_T>>();
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+ ctrl.checks .fitParam = t[29 ].cast <py::array_t <real_T>>();
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+ ctrl.checks .fitBackgroundParam = t[30 ].cast <py::array_t <real_T>>();
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+ ctrl.checks .fitQzshift = t[31 ].cast <py::array_t <real_T>>();
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+ ctrl.checks .fitScalefactor = t[32 ].cast <py::array_t <real_T>>();
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+ ctrl.checks .fitBulkIn = t[33 ].cast <py::array_t <real_T>>();
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+ ctrl.checks .fitBulkOut = t[34 ].cast <py::array_t <real_T>>();
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+ ctrl.checks .fitResolutionParam = t[35 ].cast <py::array_t <real_T>>();
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+ ctrl.checks .fitDomainRatio = t[36 ].cast <py::array_t <real_T>>();
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return ctrl;
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}));
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