Updated IterHA to have option linear_decay

aiida_phonopy/workflows/iter_ha.py

@@ -3,7 +3,7 @@
 from phonopy.structure.dataset import get_displacements_and_forces
 from aiida.engine import WorkChain
 from aiida.plugins import WorkflowFactory, DataFactory
-from aiida.orm import Float, Int, QueryBuilder, Group, load_node
+from aiida.orm import Bool, Float, Int, QueryBuilder, Group, load_node
 from aiida.engine import while_, if_, calcfunction
 from aiida_phonopy.common.utils import phonopy_atoms_from_structure
 
@@ -169,6 +169,8 @@ def _modify_force_constants(ph):
 def get_random_displacements(structure,
                              number_of_snapshots,
                              temperature,
+                             number_of_steps_for_fitting,
+                             linear_decay,
                              **data):
     """Generate supercells with random displacemens
 
@@ -185,19 +187,19 @@ def get_random_displacements(structure,
     To control how to include previous snapshots, several parameters
     can be used.
 
-    1) data['max_previous_steps'] : Int
+    1) number_of_steps_for_fitting : Int
         Maximum number of previous phonon calculation steps included. When
         number of the previous phonon calculations is smaller than this
         number, all the previous phonon calculations are included. But
         this number is used for (2) in any case.
     2) linear_decay : True
         This will be an option, but currently always True.
         This controls weights of previous phonon calculations. One previous
-        phonon calculation is included 100%. (max_previous_steps + 1) previous
-        phonon calculation is not include. Between them, those are included
-        with linear scalings. The snapshots in each phonon calculation are
-        included from the first element of the list to the specified number,
-        i.e., [:num_included_snapshots].
+        phonon calculation is included 100%. (number_of_steps_for_fitting + 1)
+        previous phonon calculation is not include. Between them, those are
+        included with linear scalings. The snapshots in each phonon calculation
+        are included from the first element of the list to the specified
+        number, i.e., [:num_included_snapshots].
     3) data['include_ratio'] : Int
         After collecting snapshots in (2), all the snapshots are sorted by
         total energies. Then only lowest energy snapshots with 'include_ratio'
@@ -222,13 +224,14 @@ def get_random_displacements(structure,
     """
 
     displacements, forces, energies = _collect_dataset(data)
-    max_items = data['max_previous_steps'].value
+    max_items = number_of_steps_for_fitting.value
     if 'inclde_ratio' in data:
         ratio = data['inclde_ratio'].value
     else:
         ratio = None
     d, f, e, idx = _create_dataset(
-        displacements, forces, energies, max_items, ratio)
+        displacements, forces, energies, max_items, ratio,
+        linear_decay=linear_decay.value)
 
     # Calculate force constants by fitting using ALM
     phonon_setting_info = data['phinfo_1']
@@ -340,6 +343,8 @@ def define(cls, spec):
                    default=lambda: Float(300.0))
         spec.input('initial_nodes', valid_type=Dict, required=False)
         spec.input('include_ratio', valid_type=Float, required=False)
+        spec.input('linear_decay', valid_type=Bool, required=False,
+                   default=lambda: Bool(True))
         spec.outline(
             cls.initialize,
             if_(cls.import_initial_nodes)(
@@ -427,12 +432,13 @@ def _set_ave_fc(self, nodes):
             data['include_ratio'] = self.inputs.include_ratio
             self.report("Include ratio is %f."
                         % self.inputs.include_ratio.value)
-        data['max_previous_steps'] = self.inputs.number_of_steps_for_fitting
 
         displacements = get_random_displacements(
             nodes[-1].inputs.structure,
             self.inputs.number_of_snapshots,
             self.inputs.temperature,
+            self.inputs.number_of_steps_for_fitting,
+            self.inputs.linear_decay,
             **data)
 
         return displacements['displacement_dataset']