Workflows: fix logic for relabeling (#40)

The current logic avoids checking the convergence
of Hubbard parameters if relabeling is performed.
This is incorrect and it is removed.

src/aiida_quantumespresso_hp/workflows/hubbard.py

@@ -633,7 +633,6 @@ def check_convergence(self):
  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']
- return
 
  if not len(ref_params) == len(new_params):
  self.report('The new and old Hubbard parameters have different lenghts. Assuming to be at the first cycle.')

tests/workflows/test_hubbard.py

@@ -357,11 +357,17 @@ def test_relabel_check_convergence(
  # Mocking current (i.e. "old") and "new" HubbardStructureData,
  # containing different Hubbard parameters
  process.ctx.current_hubbard_structure = generate_hubbard_structure()
- process.ctx.workchains_hp = [generate_hp_workchain_node(relabel=True)]
+ process.ctx.workchains_hp = [generate_hp_workchain_node(relabel=True, u_value=100)]
 
  process.check_convergence()
  assert not process.ctx.is_converged
 
+ process.ctx.current_hubbard_structure = generate_hubbard_structure(u_value=99.99)
+ process.ctx.workchains_hp = [generate_hp_workchain_node(relabel=True, u_value=100)]
+
+ process.check_convergence()
+ assert process.ctx.is_converged
+
 
 @pytest.mark.usefixtures('aiida_profile')
 def test_inspect_hp(generate_workchain_hubbard, generate_inputs_hubbard, generate_hp_workchain_node):