Merge pull request #173 from aglowacki/master

General bug fixes

src/core/defines.h

@@ -55,8 +55,8 @@ POSSIBILITY OF SUCH DAMAGE.
 static std::time_t now_c;
 #define logit now_c=std::chrono::system_clock::to_time_t(std::chrono::system_clock::now());std::cout<<std::put_time(std::localtime(&now_c),"[%F_%T]\t")<<__FILE__<<"::"<<__FUNCTION__<<"():"<<__LINE__<<"\t"
 #define logit_s std::cout
-#define logE logit<<"Error: "
-#define logW logit<<"Warning: "
+#define logE logit<<"\033[1;31mError: \033[0;m"
+#define logW logit<<"\033[1;33mWarning: \033[0;m"
 #define logI logit<<"Info: "
 
 #if defined _WIN32 || defined __CYGWIN__

src/core/main.cpp

@@ -75,7 +75,7 @@ void help()
     logit_s<<"--quick-and-dirty : Integrate the detector range into 1 spectra.\n";
 //	logit_s<< "--mem-limit <limit> : Limit the memory usage. Append M for megabytes or G for gigabytes\n";
     logit_s<<"--optimize-fit-override-params : <int> Integrate the 8 largest mda datasets and fit with multiple params.\n"<<
-               "  1 = matrix batch fit\n  2 = batch fit without tails\n  3 = batch fit with tails\n  4 = batch fit with free E, everything else fixed \n  5 = batch fit without tails, and fit energy quadratic";
+               "  1 = matrix batch fit\n  2 = batch fit without tails\n  3 = batch fit with tails\n  4 = batch fit with free E, everything else fixed \n  5 = batch fit without tails, and fit energy quadratic\n";
     logit_s<<"--optimize-fit-routine : <general,hybrid> General (default): passes elements amplitudes as fit parameters. Hybrid only passes fit parameters and fits element amplitudes using NNLS\n";
     logit_s<<"--optimizer <lmfit, mpfit> : Choose which optimizer to use for --optimize-fit-override-params or matrix fit routine \n";
     logit_s<<"--optimizer-fx-tols <tol_override_val> : F_TOL, X_TOL, Default is LM_FIT = " << DP_LM_USERTOL << " , MP_FIT = " << 1.192e-10 << "\n";

src/data_struct/detector.cpp

@@ -190,7 +190,7 @@ void Detector<T_real>::update_element_quants(Fitting_Routines routine,
                             }
                             else
                             {
-                                eq_itr.e_cal_ratio += 1.0e-10;
+                                eq_itr.e_cal_ratio += (T_real)1.0e-10;
                             }
                         }
                     }

src/fitting/models/base_model.h

@@ -83,7 +83,7 @@ class DLL_EXPORT Base_Model
     /**
      * @brief ~Base_Model : Destructor
      */
-    ~Base_Model() {}
+    virtual ~Base_Model() {}
 
     /**
      * @brief fit_parameters : returns Fit_Parameters class of the required fit parameters to run a fitting

src/fitting/models/gaussian_model.cpp

@@ -108,7 +108,7 @@ Fit_Parameters<T_real> Gaussian_Model<T_real>::_generate_default_fit_parameters(
 
     fit_params.add_parameter(Fit_Param<T_real>(STR_COMPTON_ANGLE,		 (T_real)0.0, (T_real)359.0, (T_real)90.0, (T_real)0.1,       E_Bound_Type::LIMITED_LO_HI));
     fit_params.add_parameter(Fit_Param<T_real>(STR_COMPTON_FWHM_CORR,    (T_real)1.0, (T_real)4.0, (T_real)1.0,  (T_real)0.1,       E_Bound_Type::LIMITED_LO_HI));
-    fit_params.add_parameter(Fit_Param<T_real>(STR_COMPTON_AMPLITUDE,    (T_real)-0.0001, (T_real)0.0001, (T_real)5.0, (T_real)0.00001,  E_Bound_Type::FIT));
+    fit_params.add_parameter(Fit_Param<T_real>(STR_COMPTON_AMPLITUDE,    (T_real)0.00001, (T_real)10.00, (T_real)5.0, (T_real)0.00001,  E_Bound_Type::FIT));
     fit_params.add_parameter(Fit_Param<T_real>(STR_COMPTON_F_STEP,		 (T_real)0.0, (T_real)1.0, (T_real)0.0,  (T_real)0.1,       E_Bound_Type::FIXED));
     fit_params.add_parameter(Fit_Param<T_real>(STR_COMPTON_F_TAIL,		 (T_real)0.0, (T_real)1.0, (T_real)0.1,  (T_real)0.1,       E_Bound_Type::LIMITED_LO));
     fit_params.add_parameter(Fit_Param<T_real>(STR_COMPTON_GAMMA,		 (T_real)0.1, (T_real)10., (T_real)1.0,  (T_real)0.1,       E_Bound_Type::FIXED));

src/fitting/models/gaussian_model.h

@@ -66,7 +66,7 @@ class DLL_EXPORT Gaussian_Model: public Base_Model<T_real>
 public:
     Gaussian_Model();
 
-    ~Gaussian_Model();
+    virtual ~Gaussian_Model();
 
     virtual const Fit_Parameters<T_real>& fit_parameters() const { return _fit_parameters; }
 

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;
@@ -175,6 +175,7 @@ void quantification_residuals_lmfit( const T_real *par, int m_dat, const void *d
 template<typename T_real>
 LMFit_Optimizer<T_real>::LMFit_Optimizer() : Optimizer<T_real>()
 {
+    this->_last_outcome = -1;
 
     if (std::is_same<T_real, float>::value)
     {
@@ -282,6 +283,10 @@ OPTIMIZER_OUTCOME LMFit_Optimizer<T_real>::minimize(Fit_Parameters<T_real> *fit_
 
     User_Data<T_real> ud;
     std::vector<T_real> fitp_arr = fit_params->to_array();
+    if (fitp_arr.size() == 0)
+    {
+        return OPTIMIZER_OUTCOME::STOPPED;
+    }
     std::vector<T_real> perror(fitp_arr.size());
 
     size_t total_itr = _options.patience * (fitp_arr.size() + 1);
@@ -330,9 +335,9 @@ 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);
 
     if (fit_params->contains(STR_NUM_ITR) )
@@ -386,12 +391,16 @@ OPTIMIZER_OUTCOME LMFit_Optimizer<T_real>::minimize_func(Fit_Parameters<T_real>*
     fill_gen_user_data(ud, fit_params, spectra, energy_range, background, gen_func, use_weights);
 
     std::vector<T_real> fitp_arr = fit_params->to_array();
+    if (fitp_arr.size() == 0)
+    {
+        return OPTIMIZER_OUTCOME::STOPPED;
+    }
     std::vector<T_real> perror(fitp_arr.size());
 
     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);
 
     if (fit_params->contains(STR_NUM_ITR) )
@@ -437,12 +446,16 @@ OPTIMIZER_OUTCOME LMFit_Optimizer<T_real>::minimize_quantification(Fit_Parameter
     ud.fit_parameters = fit_params;
 
     std::vector<T_real> fitp_arr = fit_params->to_array();
+    if (fitp_arr.size() == 0)
+    {
+        return OPTIMIZER_OUTCOME::STOPPED;
+    }
     std::vector<T_real> perror(fitp_arr.size());
 
     lm_status_struct<T_real> status;
-    lmmin( fitp_arr.size(), &fitp_arr[0], 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);
 
     if (fit_params->contains(STR_NUM_ITR))
@@ -481,6 +494,18 @@ OPTIMIZER_OUTCOME LMFit_Optimizer<T_real>::minimize_quantification(Fit_Parameter
 
 // ----------------------------------------------------------------------------
 
+template<typename T_real>
+std::string LMFit_Optimizer<T_real>::detailed_outcome(int outcome)
+{
+    if (outcome > -1 && outcome < 13)
+    {
+        return  lm_infmsg[outcome];
+    }
+    return "Unknown";
+}
+
+// ----------------------------------------------------------------------------
+
 TEMPLATE_CLASS_DLL_EXPORT LMFit_Optimizer<float>;
 TEMPLATE_CLASS_DLL_EXPORT LMFit_Optimizer<double>;
 

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,
@@ -94,6 +94,8 @@ class DLL_EXPORT LMFit_Optimizer: public Optimizer<T_real>
 
     virtual void set_options(std::unordered_map<std::string, T_real> opt);
 
+    virtual std::string detailed_outcome(int outcome);
+
 private:
 
     struct lm_control_struct<T_real> _options;