fix more compiler warnings and add initializer to structs

src/fitting/optimizers/lmfit_optimizer.cpp

@@ -96,7 +96,7 @@ void residuals_lmfit( const T_real *par, int m_dat, const void *data, T_real *fv
         {
             (*ud->status_callback)(ud->cur_itr, ud->total_itr);
         }
-        catch (int e)
+        catch (...)
         {
             logI << "Cancel fitting" << std::endl;
             *userbreak = 1;
@@ -331,7 +331,7 @@ OPTIMIZER_OUTCOME LMFit_Optimizer<T_real>::minimize(Fit_Parameters<T_real> *fit_
     //control.verbosity = 3;
 
     /* perform the fit */
-    lmmin( fitp_arr.size(), &fitp_arr[0], energy_range.count(), (const void*) &ud, residuals_lmfit, &_options, &status );
+    lmmin( (int)fitp_arr.size(), &fitp_arr[0], (int)energy_range.count(), (const void*) &ud, residuals_lmfit, &_options, &status );
     logI<< "Outcome: "<<lm_infmsg[status.outcome]<<"\nNum iter: "<<status.nfev<<"\n Norm of the residue vector: "<<status.fnorm<<"\n";
     this->_last_outcome = status.outcome;
     fit_params->from_array(fitp_arr);
@@ -391,7 +391,7 @@ OPTIMIZER_OUTCOME LMFit_Optimizer<T_real>::minimize_func(Fit_Parameters<T_real>*
 
     lm_status_struct<T_real> status;
 
-    lmmin( fitp_arr.size(), &fitp_arr[0], energy_range.count(), (const void*) &ud, general_residuals_lmfit, &_options, &status );
+    lmmin((int)fitp_arr.size(), &fitp_arr[0], (int)energy_range.count(), (const void*) &ud, general_residuals_lmfit, &_options, &status );
     this->_last_outcome = status.outcome;
     fit_params->from_array(fitp_arr);
 
@@ -441,7 +441,7 @@ OPTIMIZER_OUTCOME LMFit_Optimizer<T_real>::minimize_quantification(Fit_Parameter
     std::vector<T_real> perror(fitp_arr.size());
 
     lm_status_struct<T_real> status;
-    lmmin( fitp_arr.size(), &fitp_arr[0], ud.quant_map.size(), (const void*) &ud, quantification_residuals_lmfit, &_options, &status );
+    lmmin((int)fitp_arr.size(), &fitp_arr[0], (int)ud.quant_map.size(), (const void*) &ud, quantification_residuals_lmfit, &_options, &status );
     logI << "\nOutcome: " << lm_infmsg[status.outcome] << "\nNum iter: " << status.nfev << "\nNorm of the residue vector: " << status.fnorm << "\n";
     this->_last_outcome = status.outcome;
     fit_params->from_array(fitp_arr);

src/fitting/optimizers/lmfit_optimizer.h

@@ -69,7 +69,7 @@ class DLL_EXPORT LMFit_Optimizer: public Optimizer<T_real>
 public:
     LMFit_Optimizer();
 
-    ~LMFit_Optimizer() {}
+    virtual ~LMFit_Optimizer() {}
 
     virtual OPTIMIZER_OUTCOME minimize(Fit_Parameters<T_real>*fit_params,
                                       const Spectra<T_real>* const spectra,

src/fitting/optimizers/mpfit_optimizer.cpp

@@ -470,7 +470,7 @@ OPTIMIZER_OUTCOME MPFit_Optimizer<T_real>::minimize(Fit_Parameters<T_real>*fit_p
 	std::vector<struct mp_par<T_real> > par;
 	par.resize(fitp_arr.size());
 
-    _options.maxfev = _options.maxiter * (fitp_arr.size() + 1);
+    _options.maxfev = _options.maxiter * ((int)fitp_arr.size() + 1);
 
 	_fill_limits(fit_params, par);
 
@@ -479,14 +479,14 @@ OPTIMIZER_OUTCOME MPFit_Optimizer<T_real>::minimize(Fit_Parameters<T_real>*fit_p
     result.resid = &resid[0];
     result.covar = &covar[0];
 
-    this->_last_outcome = mpfit(residuals_mpfit<T_real>, energy_range.count(), fitp_arr.size(), &fitp_arr[0], &par[0], &_options, (void *) &ud, &result);
+    this->_last_outcome = mpfit(residuals_mpfit<T_real>, (int)energy_range.count(), (int)fitp_arr.size(), &fitp_arr[0], &par[0], &_options, (void *) &ud, &result);
 
 	logI<< detailed_outcome(this->_last_outcome);
 
     fit_params->from_array(fitp_arr);
 
     T_real sum_resid = 0.0;
-    for (int i = 0; i < energy_range.count(); i++)
+    for (size_t i = 0; i < energy_range.count(); i++)
     {
         sum_resid += resid[i];
     }
@@ -622,14 +622,14 @@ OPTIMIZER_OUTCOME MPFit_Optimizer<T_real>::minimize_func(Fit_Parameters<T_real>
     result.xerror = &perror[0];
     result.resid = &resid[0];
 
-    info = mpfit(gen_residuals_mpfit<T_real>, energy_range.count(), fitp_arr.size(), &fitp_arr[0], &par[0], &_options, (void*)&ud, &result);
+    info = mpfit(gen_residuals_mpfit<T_real>, (int)energy_range.count(), (int)fitp_arr.size(), &fitp_arr[0], &par[0], &_options, (void*)&ud, &result);
 
     this->_last_outcome = info;
 
     fit_params->from_array(fitp_arr);
 
     T_real sum_resid = 0.0;
-    for (int i = 0; i < energy_range.count(); i++)
+    for (size_t i = 0; i < energy_range.count(); i++)
     {
         sum_resid += resid[i];
     }
@@ -766,15 +766,15 @@ OPTIMIZER_OUTCOME MPFit_Optimizer<T_real>::minimize_quantification(Fit_Parameter
 	par.resize(fitp_arr.size());
 	_fill_limits(fit_params, par);
 
-    this->_last_outcome = mpfit(quantification_residuals_mpfit<T_real>, ud.quant_map.size(), fitp_arr.size(), &fitp_arr[0], &par[0], &_options, (void *) &ud, &result);
+    this->_last_outcome = mpfit(quantification_residuals_mpfit<T_real>, (int)ud.quant_map.size(), (int)fitp_arr.size(), &fitp_arr[0], &par[0], &_options, (void *) &ud, &result);
     logI << "\nOutcome: " << optimizer_outcome_to_str(this->_outcome_map[this->_last_outcome]) << "\nNum iter: " << result.niter << "\n Norm of the residue vector: " << *result.resid << "\n";
 
     logI << detailed_outcome(this->_last_outcome);
 
     fit_params->from_array(fitp_arr);
 
     T_real sum_resid = 0.0;
-    for (int i = 0; i < quant_map->size(); i++)
+    for (size_t i = 0; i < quant_map->size(); i++)
     {
         sum_resid += resid[i];
     }

src/fitting/optimizers/mpfit_optimizer.h

@@ -66,7 +66,7 @@ class DLL_EXPORT MPFit_Optimizer: public Optimizer<T_real>
 public:
     MPFit_Optimizer();
 
-    ~MPFit_Optimizer() {}
+    virtual ~MPFit_Optimizer() {}
 
     virtual OPTIMIZER_OUTCOME minimize(Fit_Parameters<T_real>*fit_params,
                                         const Spectra<T_real>* const spectra,

src/fitting/optimizers/optimizer.h

@@ -93,6 +93,17 @@ DLL_EXPORT std::string optimizer_outcome_to_str(OPTIMIZER_OUTCOME outcome);
 template<typename T_real>
 struct User_Data
 {
+    User_Data()
+    {
+        fit_model = nullptr;
+        fit_parameters = nullptr;
+        elements = nullptr;
+        orig_spectra = nullptr;
+        status_callback = nullptr;
+        cur_itr = 0;
+        total_itr = 0;
+    }
+
     Base_Model<T_real>* fit_model;
     Spectra<T_real> spectra;
 	ArrayTr<T_real> weights;
@@ -110,6 +121,11 @@ struct User_Data
 template<typename T_real>
 struct Gen_User_Data
 {
+    Gen_User_Data()
+    {
+        fit_parameters = nullptr;
+    }
+
     Spectra<T_real> spectra;
 	ArrayTr<T_real> weights;
     Fit_Parameters<T_real>*fit_parameters;
@@ -122,6 +138,12 @@ struct Gen_User_Data
 template<typename T_real>
 struct Quant_User_Data
 {
+    Quant_User_Data()
+    {
+        quantification_model = nullptr;
+        fit_parameters = nullptr;
+    }
+
     quantification::models::Quantification_Model<T_real>* quantification_model;
     Fit_Parameters<T_real>* fit_parameters;
     std::unordered_map<std::string, Element_Quant<T_real>> quant_map;
@@ -274,9 +296,12 @@ template<typename T_real>
 class DLL_EXPORT Optimizer
 {
 public:
-    Optimizer(){}
+    Optimizer()
+    {
+        _last_outcome = -1;
+    }
 
-    ~Optimizer(){}
+    virtual ~Optimizer(){}
 
     virtual OPTIMIZER_OUTCOME minimize(Fit_Parameters<T_real> *fit_params,
                           const Spectra<T_real>* const spectra,

src/io/file/hl_file_io.h

@@ -359,8 +359,8 @@ DLL_EXPORT bool load_and_integrate_spectra_volume(std::string dataset_directory,
     std::string tmp_dataset_file = dataset_file;
     bool ret_val = true;
     std::vector<size_t> detector_num_arr{ detector_num };
-    size_t out_rows;
-    size_t out_cols;
+    size_t out_rows = 0;
+    size_t out_cols = 0;
     data_struct::IO_Callback_Func_Def<T_real>  cb_function = std::bind(&cb_load_spectra_data_helper<T_real>, std::placeholders::_1, std::placeholders::_2, std::placeholders::_3, std::placeholders::_4, std::placeholders::_5, std::placeholders::_6, std::placeholders::_7);
 
     if (dataset_directory.back() != DIR_END_CHAR)

src/support/lmfit_6.1/lmmin.hpp

@@ -400,11 +400,11 @@ void lm_lmpar(const int n, _T* r, const int ldr, const int* Pivot,
     _T LM_DWARF;
     if (std::is_same<_T, float>::value)
     {
-        LM_DWARF = FP_LM_DWARF;
+        LM_DWARF = (_T)FP_LM_DWARF;
     }
     else if (std::is_same<_T, double>::value)
     {
-        LM_DWARF = DP_LM_DWARF;
+        LM_DWARF = (_T)DP_LM_DWARF;
     }
 
     /*** Compute and store in x the Gauss-Newton direction. If the Jacobian