A GOOD PRINTING

===============

This commit introduces the good printing of everything after the line minimization has been introduced.
Now it only stores the steps found good by the algorithm.

Moreover it also corrects the stress sign when the ensemble is loaded with load_from_calculator_output

Author: mesonepigreco

Modules/Ensemble.py

@@ -618,7 +618,7 @@ def load_from_calculator_output(self, directory, out_ext = ".pwo"):
 
             # Get the stress if any
             try:
-                stress = ase_struct.get_stress(voigt=False)
+                stress = - ase_struct.get_stress(voigt=False) 
                 # eV/A^3 -> Ry/bohr^3
                 stress /= Rydberg / Bohr**3
                 count_stress += 1

Modules/SchaMinimizer.py

@@ -231,6 +231,7 @@ def __init__(self, ensemble = None, root_representation = "normal",
         self.__gw__ = []
         self.__gw_err__ = []
         self.__KL__ = []
+        self.__good_kasteps__ = []
 
 
 
@@ -554,6 +555,10 @@ def minimization_step(self, custom_function_gradient = None):
 
         # Update the previous gradient
         self.prev_grad = dyn_grad
+
+        # If the step is good, pass chose it
+        if self.minimizer.new_direction:
+            self.__good_kasteps__.append(len(self.__fe__) - 1)
 
     def setup_from_namelist(self, input_file):
         """
@@ -1483,18 +1488,18 @@ def plot_results(self, save_filename = None, plot = True):
 
             self.__gc__.append(self.__gc__[-1])
             self.__gc_err__.append(self.__gc_err__[-1])
+
+        fe = np.array(self.__fe__)[self.__good_kasteps__] * __RyTomev__
+        fe_err = np.array(self.__fe_err__)[self.__good_kasteps__] * __RyTomev__
 
-        # Convert the data in numpy arrays
-        fe = np.array(self.__fe__) * __RyTomev__
-        fe_err = np.array(self.__fe_err__) * __RyTomev__
 
-        gc = np.array(self.__gc__) * __RyTomev__
-        gc_err = np.array(self.__gc_err__) * __RyTomev__
+        gc = np.array(self.__gc__)[self.__good_kasteps__] * __RyTomev__
+        gc_err = np.array(self.__gc_err__)[self.__good_kasteps__] * __RyTomev__
 
-        gw = np.array(self.__gw__) * __RyTomev__
-        gw_err = np.array(self.__gw_err__) * __RyTomev__
+        gw = np.array(self.__gw__)[self.__good_kasteps__] * __RyTomev__
+        gw_err = np.array(self.__gw_err__)[self.__good_kasteps__] * __RyTomev__
 
-        kl = np.array(self.__KL__, dtype = np.float64)
+        kl = np.array(self.__KL__, dtype = np.float64)[self.__good_kasteps__]
 
         steps = np.arange(len(fe))
 
@@ -1507,6 +1512,7 @@ def plot_results(self, save_filename = None, plot = True):
             np.savetxt(save_filename, np.real(np.transpose(save_data)),
                        header = "Steps; Free energy +- error [meV]; FC gradient +- error [bohr^2]; Structure gradient +- error [meV / A]; Kong-Liu N_eff")
             print ("Minimization data saved in %s." % save_filename)
+            print('Good steps at {}'.format(self.__good_kasteps__))
 
 
         # Plot

Modules/Utilities.py

@@ -546,39 +546,42 @@ def CFP_SaveAll(self, minim):
 
         if not sscha.Parallel.am_i_the_master():
             return
-        
-        # Get the weights if required
-        if self.save_weights:
-            self.weights.append(minim.ensemble.rho[:])
+
+        if minim.minimizer.new_direction:
 
-        if self.save_dynmats:
-            minim.dyn.save_qe(self.save_dyn_prefix + "_ka%05d_" % self.ka)
-        
-        if self.save_atomic_positions:
-            self.current_struct = minim.dyn.structure.copy()
+            # Get the weights if required
+            if self.save_weights:
+                self.weights.append(minim.ensemble.rho[:])
+                
+            if self.save_dynmats:
+                minim.dyn.save_qe(self.save_dyn_prefix + "_ka%05d_" % self.ka)
 
-        # This perform also the saving
-        self.CFP_SaveFrequencies(minim)
-        
-        # Update the step
-        self.ka += 1
+            if self.save_atomic_positions:
+                self.current_struct = minim.dyn.structure.copy()
+                
+            # This perform also the saving
+            self.CFP_SaveFrequencies(minim)
+            
+            # Update the step
+            self.ka += 1
 
 
     def CFP_SaveFrequencies(self, minim):
         """
         This custom method stores the total frequencies updating an exeternal file
         """
 
-        # Generate the supercell in real space
-        dyn_sc = minim.dyn.GenerateSupercellDyn( minim.ensemble.supercell )
+        # Generate the supercell in real space (Do it only if the frequency changes)
+        if minim.minimizer.new_direction:
+            dyn_sc = minim.dyn.GenerateSupercellDyn( minim.ensemble.supercell )
 
-        # Dyagonalize
-        w, pols = dyn_sc.DyagDinQ(0)
-        self.total_freqs.append(w)
-        
+            # Dyagonalize
+            w, pols = dyn_sc.DyagDinQ(0)
+            self.total_freqs.append(w)
+            
 
-        if self.__save_each_step:
-            self.Save()
+            if self.__save_each_step:
+                self.Save()