Improved minimizer

Modules/Minimizer.py

@@ -224,6 +224,9 @@ def run_step(self, gradient, kl_new):
             # Enlarge the step
             if not self.fixed_step:
                 self.step *= self.increment_step
+
+            # Perform the minimization step for new direction
+            self.current_x = self.old_x - self.step * self.direction
         else:
             # Proceed with the line minimization
 
@@ -243,14 +246,16 @@ def run_step(self, gradient, kl_new):
                     print("Step too large (scalar = {} | kl_ratio = {}), reducing to {}".format(scalar, kl_ratio, self.step))
                     #print("Direction: ", self.direction)
                     #print("Gradient: ", gradient)
+
+                # Try again with reduced step
+                self.current_x = self.old_x - self.step * self.direction
             else:
                 # The step is good, therefore next step perform a new direction
                 self.new_direction = True
                 if self.verbose:
                     print("Good step found with {}, try increment".format(self.step))
-
-        # Perform the minimiziation step
-        self.current_x = self.old_x - self.step * self.direction
+                # DO NOT update current_x - we accept the current position
+                # (current_x was already updated in the previous step)
 
 
     def update_dyn(self, new_kl_ratio, dyn_gradient, structure_gradient = None):

Modules/SchaMinimizer.py

@@ -964,11 +964,11 @@ def print_info(self):
         print (" supercell size = ", " ".join([str(x) for x in self.ensemble.supercell]))
 
         # Get the current frequencies
-        w, pols = self.dyn.GenerateSupercellDyn(self.ensemble.supercell).DyagDinQ(0)
+        w, pols = self.dyn.DiagonalizeSupercell()#self.dyn.GenerateSupercellDyn(self.ensemble.supercell).DyagDinQ(0)
         w *= __RyToCm__
 
         # Get the starting frequencies
-        w0, p0 = self.ensemble.dyn_0.GenerateSupercellDyn(self.ensemble.supercell).DyagDinQ(0)
+        w0, p0 = self.ensemble.dyn_0.DiagonalizeSupercell()
         w0 *= __RyToCm__
 
         print ()

Modules/fourier_gradient.jl

@@ -78,7 +78,7 @@ function get_gradient_fourier!(Φ_grad :: Array{Complex{T}, 3},
                     for i in 1:n_random
                         tmp = v_tilde[i, j, jq] * conj(δf_tilde[i, k, jq])
                         Φ_grad[j, k, jq] += tmp * weights[i]
-                        Φ_grad_err[j, k, jq] += tmp * conj(tmp) * weights[i]
+                        Φ_grad_err[j, k, jq] += abs2(tmp)  * weights[i]
 
                         # @views mul!(tmp, v_tilde[:, jq, i], δf_tilde[:, jq, i]')  
                         # @. tmp2 = tmp * conj(tmp)
@@ -103,9 +103,10 @@ function get_gradient_fourier!(Φ_grad :: Array{Complex{T}, 3},
     begin
         tmp_grad = zeros(Complex{T}, (3*nat, 3*nat, nq))
         for iq in 1:nq
-            @views Φ_grad[:, :, iq] .+= Φ_grad[:, :, iq]'
             @views tmp_grad[:, :, iq] .= Φ_grad[:, :, iq]
+            @views tmp_grad[:, :, iq] .+= Φ_grad[:, :, iq]'
         end
+        Φ_grad .= tmp_grad
         for iq in 1:nq
             @views tmp_grad[:, :, iq] .+= conj.(Φ_grad[:, :, minus_q_index[iq]]')
         end

meson.build

@@ -1,6 +1,6 @@
 project('python-sscha',
   ['c','fortran'],
-  version : '1.5.0',
+  version : '1.6.0',
   license: 'GPL',
   meson_version: '>= 1.1.0', # <- set min version of meson.
   default_options : [

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "mesonpy"
 
 [project]
 name = "python-sscha"
-version = "1.5.1"
+version = "1.6.0"
 description = "Python implementation of the sscha code"
 authors = [{name = "Lorenzo Monacelli"}] # Put here email
 readme = "README.md"