diff --git a/.github/workflows/pipeline.yml b/.github/workflows/pipeline.yml index 6bb0b2a..33b3420 100644 --- a/.github/workflows/pipeline.yml +++ b/.github/workflows/pipeline.yml @@ -21,6 +21,8 @@ jobs: - name: Test shell: bash -l {0} run: | + export ESPRESSO_PSEUDO=$(pwd)/espresso/pseudo + pip install --no-deps --no-build-isolation -e qe_xml_parser verdi presto --profile-name pwd echo -e 'from aiida import load_profile\nload_profile()\n\nfrom python_workflow_definition.aiida import load_workflow_json\n\n\nif __name__ == "__main__":\n workgraph = load_workflow_json(file_name="workflow.json")\n workgraph.run()' > test_with_aiida.py python test_with_aiida.py @@ -40,6 +42,8 @@ jobs: - name: Test shell: bash -l {0} run: | + export ESPRESSO_PSEUDO=$(pwd)/espresso/pseudo + pip install --no-deps --no-build-isolation -e qe_xml_parser echo -e 'from jobflow.managers.local import run_locally\nfrom python_workflow_definition.jobflow import load_workflow_json\n\n\nif __name__ == "__main__":\n flow = load_workflow_json(file_name="workflow.json")\n print(run_locally(flow))' > test_with_jobflow.py python test_with_jobflow.py @@ -58,5 +62,7 @@ jobs: - name: Test shell: bash -l {0} run: | + export ESPRESSO_PSEUDO=$(pwd)/espresso/pseudo + pip install --no-deps --no-build-isolation -e qe_xml_parser echo -e 'from python_workflow_definition.pyiron_base import load_workflow_json\n\n\nif __name__ == "__main__":\n delayed_object_lst = load_workflow_json(file_name="workflow.json")\n print(delayed_object_lst[-1].pull())' > test_with_pyiron.py python test_with_pyiron.py diff --git a/README.md b/README.md index 2519e0f..eda96c0 100644 --- a/README.md +++ b/README.md @@ -1,30 +1,4 @@ -# Arithmetic Example Workflow -[![Pipeline](https://github.com/pythonworkflow/example-workflow/actions/workflows/pipeline.yml/badge.svg)](https://github.com/pythonworkflow/example-workflow/actions/workflows/pipeline.yml) - -Template repository for publishing an interoperable workflow based on the Python Workflow Definition. - -## Content -The minimal workflow consists of three files: - -| File | Explanation | -|-------------------|---------------------------------------------------------| -| `environment.yml` | Conda environment for software dependencies | -| `workflow.py` | Python functions representing the nodes of the workflow | -| `workflow.json` | Workflow graph consisting of nodes and edges | - -Additional optional files for the publication of the workflow: - -| File | Explanation | -|----------------------------------|------------------------------------------| -| `README.md` | Readme file to introduce the workflow | -| `.github/workflows/pipeline.yml` | Github Actions to test the workflow | - -## Publish your workflow -You can publish your workflow in five simple steps: -* Fork the repository and clone your fork locally. -* Export your workflow to the Python Workflow Definition using the `python_workflow_definition` Python package, by calling the `write_workflow_json()` function. -* Replace the `environment.yml`, `workflow.py` and `workflow.json` in your local folder with the files for your workflow. In addition, you can add additional files if they are required and update the `README.md` to explain your workflow. -* Commit the files locally using `git add -A` and `git commit -m "add my workflow"` -* Push your workflow to Github `git push` - +# Quantum Espresso Bulk Modulus Workflow +[![Pipeline](https://github.com/pythonworkflow/quantum-espresso-bulk-modulus-workflow/actions/workflows/pipeline.yml/badge.svg)](https://github.com/pythonworkflow/quantum-espresso-bulk-modulus-workflow/actions/workflows/pipeline.yml) +Workflow to calculate the equilibrium bulk modulus with the [quantum ESPRESSO](https://www.quantum-espresso.org) density functional theory simulation code. This repository demonstrates the use of the [python-workflow-definition](https://github.com/pythonworkflow/python-workflow-definition) Python package and the [example-workflow](https://github.com/pythonworkflow/example-workflow) repository template. diff --git a/environment.yml b/environment.yml index 60e3675..ce2abac 100644 --- a/environment.yml +++ b/environment.yml @@ -2,5 +2,12 @@ channels: - conda-forge dependencies: - python =3.12 +- ase=3.24.0 +- hatchling =1.27.0 +- matplotlib=3.10.1 +- xmlschema=3.4.3 +- optimade=1.2.3 +- qe=7.2 +- qe-tools=2.0.0 - pip: - python-workflow-definition==0.0.1 diff --git a/espresso/pseudo/Al.pbe-n-kjpaw_psl.1.0.0.UPF b/espresso/pseudo/Al.pbe-n-kjpaw_psl.1.0.0.UPF new file mode 100644 index 0000000..4c9c861 --- /dev/null +++ b/espresso/pseudo/Al.pbe-n-kjpaw_psl.1.0.0.UPF @@ -0,0 +1,18497 @@ + + + Generated using "atomic" code by A. Dal Corso v.5.1 + Author: ADC + Generation date: 10Oct2014 + Pseudopotential type: PAW + Element: Al + Functional: SLA PW PBX PBC + + Suggested minimum cutoff for wavefunctions: 29. Ry + Suggested minimum cutoff for charge density: 143. Ry + The Pseudo was generated with a Scalar-Relativistic Calculation + Local Potential by smoothing AE potential with Bessel fncs, cutoff radius: 1.9000 + Pseudopotential contains additional information for GIPAW reconstruction. + + Valence configuration: + nl pn l occ Rcut Rcut US E pseu + 3S 1 0 2.00 1.700 1.900 -0.569826 + 3P 2 1 1.00 1.700 2.000 -0.199338 + Generation configuration: + 3S 1 0 2.00 1.700 1.900 -0.569824 + 3S 1 0 0.00 1.700 1.900 6.000000 + 3P 2 1 1.00 1.700 2.000 -0.199338 + 3P 2 1 0.00 1.700 2.000 3.500000 + 3D 3 2 0.00 1.700 1.900 0.100000 + 3D 3 2 0.00 1.700 1.900 0.300000 + + Pseudization used: troullier-martins + + &input + title='Al', + zed=13., + rel=1, + config='[Ne] 3s2 3p1 3d-1', + iswitch=3, + dft='PBE' + / + &inputp + lpaw=.true., + pseudotype=3, + file_pseudopw='Al.pbe-n-kjpaw_psl.1.0.0.UPF', + author='ADC', + lloc=-1, + rcloc=1.9, + which_augfun='PSQ', + rmatch_augfun_nc=.true., + nlcc=.true., + new_core_ps=.true., + rcore=1.8, + tm=.true. + / +6 +3S 1 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a/qe_xml_parser/src/qe_xml_parser/__init__.py b/qe_xml_parser/src/qe_xml_parser/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/qe_xml_parser/src/qe_xml_parser/parsers.py b/qe_xml_parser/src/qe_xml_parser/parsers.py new file mode 100644 index 0000000..ab9395b --- /dev/null +++ b/qe_xml_parser/src/qe_xml_parser/parsers.py @@ -0,0 +1,70 @@ +import numpy + +from xmlschema import XMLSchema +from qe_tools import CONSTANTS + +from ase import Atoms +from importlib.resources import files + +from . import schemas + + +def parse_pw(xml_file): + """Parse a Quantum Espresso XML output file.""" + + xml_dict = XMLSchema(str(files(schemas) / "qes_230310.xsd")).to_dict(xml_file) + + parsed_results = {} + + try: + cell = ( + numpy.array( + [v for v in xml_dict["output"]["atomic_structure"]["cell"].values()] + ) + * CONSTANTS.bohr_to_ang + ) + symbols = [ + el["@name"] + for el in xml_dict["output"]["atomic_structure"]["atomic_positions"]["atom"] + ] + positions = ( + numpy.array( + [ + el["$"] + for el in xml_dict["output"]["atomic_structure"][ + "atomic_positions" + ]["atom"] + ] + ) + * CONSTANTS.bohr_to_ang + ) + + parsed_results["ase_structure"] = Atoms( + cell=cell, + positions=positions, + symbols=symbols, + pbc=True, + ) + except KeyError: + pass + + try: + parsed_results["energy"] = ( + xml_dict["output"]["total_energy"]["etot"] * CONSTANTS.ry_to_ev + ) + except KeyError: + pass + + try: + parsed_results["forces"] = ( + numpy.array(xml_dict["output"]["forces"]["$"]).reshape( + xml_dict["output"]["forces"]["@dims"] + ) + * 2 + * CONSTANTS.ry_to_ev + / CONSTANTS.bohr_to_ang + ) + except KeyError: + pass + + return parsed_results diff --git a/qe_xml_parser/src/qe_xml_parser/schemas/__init__.py b/qe_xml_parser/src/qe_xml_parser/schemas/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/qe_xml_parser/src/qe_xml_parser/schemas/qes_230310.xsd b/qe_xml_parser/src/qe_xml_parser/schemas/qes_230310.xsd new file mode 100644 index 0000000..43d036a 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{"target": 30, "targetPort": "3", "source": 6, "sourcePort": "volume"}, + {"target": 30, "targetPort": "4", "source": 7, "sourcePort": "volume"}, + {"target": 8, "targetPort": "volume_lst", "source": 30, "sourcePort": null}, + {"target": 31, "targetPort": "0", "source": 3, "sourcePort": "energy"}, + {"target": 31, "targetPort": "1", "source": 4, "sourcePort": "energy"}, + {"target": 31, "targetPort": "2", "source": 5, "sourcePort": "energy"}, + {"target": 31, "targetPort": "3", "source": 6, "sourcePort": "energy"}, + {"target": 31, "targetPort": "4", "source": 7, "sourcePort": "energy"}, + {"target": 8, "targetPort": "energy_lst", "source": 31, "sourcePort": null} ] -} +} \ No newline at end of file diff --git a/workflow.py b/workflow.py index 3a12993..dcb6a1d 100644 --- a/workflow.py +++ b/workflow.py @@ -1,6 +1,88 @@ -def get_prod_and_div(x, y): - return {"prod": x * y, "div": x / y} +import json +import os +import subprocess +from ase.build import bulk +from ase.io import write +from qe_xml_parser.parsers import parse_pw +import matplotlib.pyplot as plt +from optimade.adapters.structures.ase import from_ase_atoms, get_ase_atoms +from optimade.models.structures import StructureResourceAttributes, StructureResource -def get_sum(x, y): - return x + y + +def write_input(input_dict, working_directory="."): + filename = os.path.join(working_directory, "input.pwi") + os.makedirs(working_directory, exist_ok=True) + write( + filename=filename, + images=json_to_ase(atoms_json=input_dict["structure"]), + Crystal=True, + kpts=input_dict["kpts"], + input_data={ + "calculation": input_dict["calculation"], + "occupations": "smearing", + "degauss": input_dict["smearing"], + }, + pseudopotentials=input_dict["pseudopotentials"], + tstress=True, + tprnfor=True, + ) + + +def collect_output(working_directory="."): + output = parse_pw(os.path.join(working_directory, "pwscf.xml")) + return { + "structure": ase_to_json(atoms=output["ase_structure"]), + "energy": output["energy"], + "volume": output["ase_structure"].get_volume(), + } + + +def calculate_qe(working_directory, input_dict): + write_input( + input_dict=input_dict, + working_directory=working_directory, + ) + subprocess.check_output( + "mpirun -np 1 pw.x -in input.pwi > output.pwo", + cwd=working_directory, + shell=True, + ) + return collect_output(working_directory=working_directory) + + +def generate_structures(structure, strain_lst): + structure_lst = [] + for strain in strain_lst: + structure_strain = json_to_ase(atoms_json=structure) + structure_strain.set_cell( + structure_strain.cell * strain ** (1 / 3), scale_atoms=True + ) + structure_lst.append(structure_strain) + return {f"s_{i}": ase_to_json(atoms=s) for i, s in enumerate(structure_lst)} + + +def plot_energy_volume_curve(volume_lst, energy_lst): + plt.plot(volume_lst, energy_lst) + plt.xlabel("Volume") + plt.ylabel("Energy") + plt.savefig("evcurve.png") + + +def get_bulk_structure(element, a, cubic): + ase_atoms = bulk( + name=element, + a=a, + cubic=cubic, + ) + return ase_to_json(atoms=ase_atoms) + + +def ase_to_json(atoms): + struct_opt = from_ase_atoms(atoms=atoms) + return json.dumps(struct_opt.model_dump(mode="json")) + + +def json_to_ase(atoms_json): + structure_restore = StructureResourceAttributes.model_validate_json(atoms_json) + return get_ase_atoms(optimade_structure=StructureResource(id="ase", attributes=structure_restore))