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[pre-commit.ci] auto fixes from pre-commit.com hooks
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pre-commit-ci[bot] committed Sep 30, 2024
1 parent dc81d43 commit 97b69fd
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Showing 2 changed files with 16 additions and 13 deletions.
25 changes: 13 additions & 12 deletions src/aiida_sssp_workflow/workflows/convergence/cohesive_energy.py
Original file line number Diff line number Diff line change
Expand Up @@ -189,7 +189,7 @@ def compute_xy(

reference_node = orm.load_node(report.reference.uuid)
output_parameters_r: orm.Dict = reference_node.outputs.output_parameters
y_ref = output_parameters_r['cohesive_energy_per_atom']
y_ref = output_parameters_r["cohesive_energy_per_atom"]

xs = []
ys = []
Expand All @@ -198,24 +198,25 @@ def compute_xy(
if node_point.exit_status != 0:
# TODO: log to a warning file for where the node is not finished_okay
continue

x = node_point.wavefunction_cutoff
xs.append(x)

node = orm.load_node(node_point.uuid)
output_parameters_p: orm.Dict = node.outputs.output_parameters

y = (output_parameters_p['cohesive_energy_per_atom'] - y_ref) / y_ref * 100
y = (output_parameters_p["cohesive_energy_per_atom"] - y_ref) / y_ref * 100
ys.append(y)
ys_cohesive_energy_per_atom.append(output_parameters_p['cohesive_energy_per_atom'])
ys_cohesive_energy_per_atom.append(
output_parameters_p["cohesive_energy_per_atom"]
)

return {
'xs': xs,
'ys': ys,
'ys_relative_diff': ys,
'ys_cohesive_energy_per_atom': ys_cohesive_energy_per_atom,
'metadata': {
'unit': '%',
}
"xs": xs,
"ys": ys,
"ys_relative_diff": ys,
"ys_cohesive_energy_per_atom": ys_cohesive_energy_per_atom,
"metadata": {
"unit": "%",
},
}

4 changes: 3 additions & 1 deletion src/aiida_sssp_workflow/workflows/transferability/eos.py
Original file line number Diff line number Diff line change
Expand Up @@ -472,7 +472,9 @@ def extract_eos(
continue

raw_eos[k] = point_node.outputs.eos.output_volume_energy.get_dict()
birch_murnaghan_fit[k] = point_node.outputs.eos.output_birch_murnaghan_fit.get_dict()
birch_murnaghan_fit[k] = (
point_node.outputs.eos.output_birch_murnaghan_fit.get_dict()
)
metric_dict[k] = point_node.outputs.output_parameters.get_dict()

return raw_eos, birch_murnaghan_fit, metric_dict

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