Merge branch 'master' of https://github.com/aiidateam/aiida-quantumes…

…presso-hp into feat/voronoi

src/aiida_quantumespresso_hp/workflows/hp/parallelize_atoms.py

@@ -24,6 +24,10 @@ def define(cls, spec):
  spec.expose_inputs(HpBaseWorkChain, exclude=('only_initialization', 'clean_workdir'))
  spec.input('parallelize_qpoints', valid_type=orm.Bool, default=lambda: orm.Bool(False))
  spec.input('max_concurrent_base_workchains', valid_type=orm.Int, required=False)
+ spec.input(
+ 'init_walltime', valid_type=int, default=3600, non_db=True,
+ help='The walltime of the initialization `HpBaseWorkChain` in seconds (default: 3600).'
+ )
  spec.input('clean_workdir', valid_type=orm.Bool, default=lambda: orm.Bool(False),
  help='If `True`, work directories of all called calculation will be cleaned at the end of execution.')
  spec.outline(
@@ -56,7 +60,7 @@ def run_init(self):
  inputs = AttributeDict(self.exposed_inputs(HpBaseWorkChain))
  inputs.only_initialization = orm.Bool(True)
  inputs.clean_workdir = self.inputs.clean_workdir
- inputs.hp.metadata.options.max_wallclock_seconds = 3600 # 1 hour is more than enough
+ inputs.hp.metadata.options.max_wallclock_seconds = self.inputs.init_walltime
  inputs.metadata.call_link_label = 'initialization'
 
  node = self.submit(HpBaseWorkChain, **inputs)

src/aiida_quantumespresso_hp/workflows/hp/parallelize_qpoints.py

@@ -30,6 +30,10 @@ def define(cls, spec):
  super().define(spec)
  spec.expose_inputs(HpBaseWorkChain, exclude=('only_initialization', 'clean_workdir'))
  spec.input('max_concurrent_base_workchains', valid_type=orm.Int, required=False)
+ spec.input(
+ 'init_walltime', valid_type=int, default=3600, non_db=True,
+ help='The walltime of the initialization `HpBaseWorkChain` in seconds (default: 3600).'
+ )
  spec.input('clean_workdir', valid_type=orm.Bool, default=lambda: orm.Bool(False),
  help='If `True`, work directories of all called calculation will be cleaned at the end of execution.')
  spec.outline(
@@ -63,7 +67,7 @@ def run_init(self):
  inputs.hp.parameters = orm.Dict(parameters)
  inputs.clean_workdir = self.inputs.clean_workdir
 
- inputs.hp.metadata.options.max_wallclock_seconds = 3600 # 1 hour is more than enough
+ inputs.hp.metadata.options.max_wallclock_seconds = self.inputs.init_walltime
  inputs.metadata.call_link_label = 'initialization'
 
  node = self.submit(HpBaseWorkChain, **inputs)

src/aiida_quantumespresso_hp/workflows/hubbard.py

@@ -422,6 +422,22 @@ def get_pseudos(self) -> dict:
 
  return results
 
+ def relabel_hubbard_structure(self, workchain) -> None:
+ """Relabel the Hubbard structure if new types have been detected."""
+ from aiida_quantumespresso.utils.hubbard import is_intersite_hubbard
+
+ if not is_intersite_hubbard(workchain.outputs.hubbard_structure.hubbard):
+ for site in workchain.outputs.hubbard.dict.sites:
+ if not site['type'] == site['new_type']:
+ result = structure_relabel_kinds(
+ self.ctx.current_hubbard_structure, workchain.outputs.hubbard, self.ctx.current_magnetic_moments
+ )
+ self.ctx.current_hubbard_structure = result['hubbard_structure']
+ if self.ctx.current_magnetic_moments is not None:
+ self.ctx.current_magnetic_moments = result['starting_magnetization']
+ self.report('new types have been detected: relabeling the structure.')
+ return
+
  def run_relax(self):
  """Run the PwRelaxWorkChain to run a relax PwCalculation."""
  inputs = self.get_inputs(PwRelaxWorkChain, 'relax')
@@ -593,14 +609,14 @@ def inspect_hp(self):
 
  if not self.should_check_convergence():
  self.ctx.current_hubbard_structure = workchain.outputs.hubbard_structure
+ self.relabel_hubbard_structure(workchain)
+
  if not self.inputs.meta_convergence:
  self.report('meta convergence is switched off, so not checking convergence of Hubbard parameters.')
  self.ctx.is_converged = True
 
  def check_convergence(self):
  """Check the convergence of the Hubbard parameters."""
- from aiida_quantumespresso.utils.hubbard import is_intersite_hubbard
-
  workchain = self.ctx.workchains_hp[-1]
 
  # We store in memory the parameters before relabelling to make the comparison easier.
@@ -616,18 +632,7 @@ def check_convergence(self):
 
  # We check if new types were created, in which case we relabel the `HubbardStructureData`
  self.ctx.current_hubbard_structure = workchain.outputs.hubbard_structure
-
- if not is_intersite_hubbard(workchain.outputs.hubbard_structure.hubbard):
- for site in workchain.outputs.hubbard.dict.sites:
- if not site['type'] == site['new_type']:
- self.report('new types have been detected: relabeling the structure and starting new iteration.')
- result = structure_relabel_kinds(
- self.ctx.current_hubbard_structure, workchain.outputs.hubbard, self.ctx.current_magnetic_moments
- )
- self.ctx.current_hubbard_structure = result['hubbard_structure']
- if self.ctx.current_magnetic_moments is not None:
- self.ctx.current_magnetic_moments = result['starting_magnetization']
- break
+ self.relabel_hubbard_structure(workchain)
 
  if not self.should_check_convergence():
  return

tests/workflows/test_hubbard.py

@@ -223,6 +223,41 @@ def test_skip_relax_iterations(generate_workchain_hubbard, generate_inputs_hubba
  assert process.should_check_convergence()
 
 
+@pytest.mark.usefixtures('aiida_profile')
+def test_skip_relax_iterations_relabeling(
+ generate_workchain_hubbard, generate_inputs_hubbard, generate_hp_workchain_node, generate_hubbard_structure
+):
+ """Test `SelfConsistentHubbardWorkChain` when skipping the first relax iterations and relabeling is needed."""
+ from aiida.orm import Bool, Int
+
+ inputs = generate_inputs_hubbard()
+ inputs['skip_relax_iterations'] = Int(1)
+ inputs['meta_convergence'] = Bool(True)
+ process = generate_workchain_hubbard(inputs=inputs)
+ process.setup()
+
+ current_hubbard_structure = generate_hubbard_structure(u_value=1, only_u=True)
+ process.current_hubbard_structure = current_hubbard_structure
+ # 1
+ process.update_iteration()
+ assert process.ctx.skip_relax_iterations == 1
+ assert process.ctx.iteration == 1
+ assert not process.should_run_relax()
+ assert not process.should_check_convergence()
+ process.ctx.workchains_hp = [generate_hp_workchain_node(relabel=True, u_value=1, only_u=True)]
+ process.inspect_hp()
+ assert process.ctx.current_hubbard_structure.get_kind_names(
+ ) != process.ctx.workchains_hp[-1].outputs.hubbard_structure.get_kind_names()
+ # 2
+ process.update_iteration()
+ assert process.should_run_relax()
+ assert process.should_check_convergence()
+ # 3
+ process.update_iteration()
+ assert process.should_run_relax()
+ assert process.should_check_convergence()
+
+
 @pytest.mark.usefixtures('aiida_profile')
 def test_relax_frequency(generate_workchain_hubbard, generate_inputs_hubbard):
  """Test `SelfConsistentHubbardWorkChain` when `relax_frequency` is different from 1."""