Initial commit

Author: PythonFZ

.gitignore

@@ -0,0 +1,160 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/

.pre-commit-config.yaml

@@ -0,0 +1,19 @@
+exclude: '.git|.tox'
+default_stages: [commit]
+fail_fast: true
+
+repos:
+  - repo: https://github.com/psf/black
+    rev: 22.8.0
+    hooks:
+      - id: black
+
+  - repo: https://github.com/timothycrosley/isort
+    rev: 5.10.1
+    hooks:
+      - id: isort
+
+  - repo: https://github.com/charliermarsh/ruff-pre-commit
+    rev: v0.0.133
+    hooks:
+      - id: ruff

README.md

@@ -0,0 +1,43 @@
+# Write a ZnTrack Node
+
+## Setup environment
+1. Install miniconda https://docs.conda.io/en/latest/miniconda.html
+2. Install poetry https://python-poetry.org/docs/
+3. Create an environment `conda create -n asemd python`
+4. Activate environment `conda activate asemd`
+5. Install package `poetry install`
+
+## Test package
+run `pytest .` to check if all the tests pass.
+
+The package should work as follows:
+
+```python
+import ase_md
+
+atoms = ase_md.simulator.generate_atoms(size=2)
+
+    atoms_list = ase_md.simulator.run_simulation(
+        atoms=atoms, temperature=300, timestep=1.0, dump_interval=5, steps=20
+    )
+
+    rdf = ase_md.simulator.compute_rdf(
+        atoms_list=atoms_list, rmax=1.0, nbins=50, elements="Cu"
+    )
+```
+
+which builds a DAG like:
+
+[![](https://mermaid.ink/img/pako:eNpNj7EOwjAMRH8l8twOwJYBCRFg6lKYIAxW40KlJqlSRwhV_XdCSyU82ffOtm6AyhsCCXXrX9UTA4uL0k78yiW4umk4EYsde9truIs8305gnUAZnSjUv7pJ6t7bLjKJUh0TggwsBYuNSX-G73EN_CRLGmRqDdUYW9ag3ZissTPIdDAN-wCSQ6QMMLI_v121zLNHNfgIaEHW2PZJpWmnmPNMsTLo0F29XzzjBz3ATgs?type=png)](https://mermaid.live/edit#pako:eNpNj7EOwjAMRH8l8twOwJYBCRFg6lKYIAxW40KlJqlSRwhV_XdCSyU82ffOtm6AyhsCCXXrX9UTA4uL0k78yiW4umk4EYsde9truIs8305gnUAZnSjUv7pJ6t7bLjKJUh0TggwsBYuNSX-G73EN_CRLGmRqDdUYW9ag3ZissTPIdDAN-wCSQ6QMMLI_v121zLNHNfgIaEHW2PZJpWmnmPNMsTLo0F29XzzjBz3ATgs)
+
+## Rewrite the package
+- Add an Example using DVC (without ZnTrack)
+- Add an Example using ZnTrack
+- Add an Example using MLFlow
+- Add an Example using Hydra
+
+You can also consider other packages you want to try out.
+Some can be found here https://github.com/pditommaso/awesome-pipeline.
+
+## Run experiments:
+Test your workflow with different parameters for all Nodes and compare them.

ase_md/__init__.py

@@ -0,0 +1,24 @@
+"""ASE MD package."""
+import importlib.metadata
+import logging
+import sys
+
+from ase_md import simulator
+
+__all__ = ["simulator"]
+
+__version__ = importlib.metadata.version("ase_md")
+
+
+logger = logging.getLogger(__name__)
+logger.setLevel(logging.INFO)
+
+# Formatter for advanced logging
+# formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s : %(message)s')
+formatter = logging.Formatter("%(asctime)s (%(levelname)s): %(message)s")
+
+channel = logging.StreamHandler(sys.stdout)
+channel.setLevel(logging.DEBUG)
+channel.setFormatter(formatter)
+
+logger.addHandler(channel)

ase_md/simulator.py

@@ -0,0 +1,76 @@
+"""The ASE MD simulator.
+
+References
+----------
+https://wiki.fysik.dtu.dk/ase/tutorials/md/md.html
+
+"""
+import typing
+
+import ase
+import ase.geometry.analysis
+import numpy as np
+import tqdm
+from ase import units
+from ase.calculators.emt import EMT
+from ase.lattice.cubic import FaceCenteredCubic
+from ase.md.velocitydistribution import MaxwellBoltzmannDistribution
+from ase.md.verlet import VelocityVerlet
+
+
+def generate_atoms(size: int = 3) -> ase.Atoms:
+    """Generate fcc of Cu."""
+    return FaceCenteredCubic(
+        directions=[[1, 0, 0], [0, 1, 0], [0, 0, 1]],
+        symbol="Cu",
+        size=(size, size, size),
+        pbc=True,
+    )
+
+
+def printenergy(a: ase.Atoms) -> None:
+    """Function to print the potential, kinetic and total energy."""
+    epot = a.get_potential_energy() / len(a)
+    ekin = a.get_kinetic_energy() / len(a)
+    print(
+        "Energy per atom: Epot = %.3feV  Ekin = %.3feV (T=%3.0fK)  Etot = %.3feV"
+        % (epot, ekin, ekin / (1.5 * units.kB), epot + ekin)
+    )
+
+
+def run_simulation(
+    atoms: ase.Atoms,
+    temperature: float = 300,
+    timestep: float = 5.0,
+    steps: int = 20,
+    dump_interval: int = 10,
+) -> typing.List[ase.Atoms]:
+    """Run an MD Simulation using ase."""
+    # Describe the interatomic interactions with the Effective Medium Theory
+    atoms.calc = EMT()
+
+    # Set the momenta corresponding to T=300K
+    MaxwellBoltzmannDistribution(atoms, temperature_K=temperature)
+
+    # We want to run MD with constant energy using the VelocityVerlet algorithm.
+    dyn = VelocityVerlet(atoms, timestep * units.fs)  # fs time step.
+
+    atoms_list = []
+
+    # Now run the dynamics
+    printenergy(atoms)
+    for _ in tqdm.trange(steps, ncols=100):
+        dyn.run(dump_interval)
+        printenergy(atoms)
+        atoms_list.append(atoms.copy())
+
+    return atoms_list
+
+
+def compute_rdf(
+    atoms_list: typing.List[ase.Atoms], rmax: float, nbins: int, elements: str
+) -> dict:
+    """Compute RDF."""
+    analysis = ase.geometry.analysis.Analysis(atoms_list)
+    data = analysis.get_rdf(rmax=rmax, nbins=nbins, elements=elements)
+    return {"x": np.linspace(0, rmax, nbins), "y": np.mean(data, axis=0)}