Lattice dynamics workflow using Pheasy

.github/workflows/testing.yml

@@ -67,8 +67,20 @@ jobs:
           mkdir -p ~/.abinit/pseudos
           cp -r tests/test_data/abinit/pseudos/ONCVPSP-PBE-SR-PDv0.4 ~/.abinit/pseudos
           uv pip install .[strict,strict-forcefields,tests,abinit]
+          uv pip install -i https://test.pypi.org/simple/ pheasy==0.0.1  # Install pheasy
           uv pip install torch-runstats
           uv pip install --no-deps nequip==0.5.6
+
+
+      - name: Install ALA-Mode
+        run: |
+          micromamba activate a2
+          micromamba install -n a2 -c conda-forge numpy scipy h5py compilers “libblas=*=*mkl” spglib boost eigen cmake ipython mkl-include openmpi --yes  
+          git clone https://github.com/ttadano/ALM.git # do I need to modify this?
+          cd ALM # do I need to modify this?
+          cd python
+          python setup.py build # do I need to modify this?
+          uv pip install -e . # do I need to modify this?
 
       - name: Install pymatgen from master if triggered by pymatgen repo dispatch
         if: github.event_name == 'repository_dispatch' && github.event.action == 'pymatgen-ci-trigger'

.pre-commit-config.yaml

@@ -3,7 +3,7 @@ default_language_version:
 exclude: ^(.github/|tests/test_data/abinit/)
 repos:
 - repo: https://github.com/charliermarsh/ruff-pre-commit
-  rev: v0.7.3
+  rev: v0.8.0
   hooks:
   - id: ruff
     args: [--fix]
@@ -45,7 +45,7 @@ repos:
     args: [--ignore-words-list, 'titel,statics,ba,nd,te,atomate']
     types_or: [python, rst, markdown]
 - repo: https://github.com/kynan/nbstripout
-  rev: 0.8.0
+  rev: 0.8.1
   hooks:
     - id: nbstripout
       args:

docs/user/codes/index.md

@@ -6,4 +6,5 @@ The section gives the instructions for codes supported by atomate2.
 
 ```{toctree}
 vasp
+openmm
 ```

docs/user/codes/vasp.md

@@ -1,4 +1,5 @@
 (codes.vasp)=
+
 # VASP
 
 At present, most workflows in atomate2 use the Vienna *ab initio* simulation package
@@ -260,20 +261,48 @@ With the help of phonopy, these forces are then converted into a dynamical matri
 The dynamical matrices of three structures are then used as an input to the phonopy Grueneisen api
 to compute mode-dependent Grueneisen parameters.
 
-
 ### Quasi-harmonic Workflow
+
 Uses the quasi-harmonic approximation with the help of Phonopy to compute thermodynamic properties.
 First, a tight relaxation is performed. Subsequently, several optimizations at different constant
 volumes are performed. At each of the volumes, an additional phonon run is performed as well.
 Afterwards, equation of state fits are performed with phonopy.
 
-
-
 ### Equation of State Workflow
-An equation of state workflow is implemented. First, a tight relaxation is performed. Subsequently, several optimizations at different constant
+
+An equation of state (EOS) workflow is implemented. First, a tight relaxation is performed. Subsequently, several optimizations at different constant
 volumes are performed. Additional static calculations might be performed afterwards to arrive at more
-accurate energies. Then, an equation of state fit is performed with pymatgen.
+accurate energies. Then, an EOS fit is performed with pymatgen.
+
+The output of the workflow is, by default, a dictionary containing the energy and volume data generated with DFT, in addition to fitted equation of state parameters for all models currently available in pymatgen (Murnaghan, Birch-Murnaghan, Poirier-Tarantola, and Vinet/UBER).
+
+#### Materials Project-compliant workflows
+
+If the user wishes to reproduce the EOS data currently in the Materials Project, they should use the atomate 1-compatible `MPLegacy`-prefixed flows (and jobs and input sets). For performing updated PBE-GGA EOS flows with Materials Project-compliant parameters, the user should use the `MPGGA`-prefixed classes. Lastly, the `MPMetaGGA`-prefixed classes allow the user to perform Materials Project-compliant r<sup>2</sup>SCAN EOS workflows.
+
+**Summary:** For Materials Project-compliant equation of state (EOS) workflows, the user should use:
+* `MPGGAEosMaker` for faster, lower-accuracy calculation with the PBE-GGA
+* `MPMetaGGAEosMaker` for higher-accuracy but slower calculations with the r<sup>2</sup>SCAN meta-GGA
+* `MPLegacyEosMaker` for consistency with the PBE-GGA data currently distributed by the Materials Project
+
+#### Implementation details
+
+The Materials Project-compliant EOS flows, jobs, and sets currently use three prefixes to indicate their usage.
+* `MPGGA`: MP-compatible PBE-GGA (current)
+* `MPMetaGGA`: MP-compatible r<sup>2</sup>SCAN meta-GGA (current)
+* `MPLegacy`: a reproduction of the atomate 1 implementation, described in
+  K. Latimer, S. Dwaraknath, K. Mathew, D. Winston, and K.A. Persson, npj Comput. Materials **vol. 4**, p. 40 (2018), DOI: 10.1038/s41524-018-0091-x
+
+  For reference, the original atomate workflows can be found here:
+    * [`atomate.vasp.workflows.base.wf_bulk_modulus`](https://github.com/hackingmaterials/atomate/blob/main/atomate/vasp/workflows/presets/core.py#L564)
+    * [`atomate.vasp.workflows.base.bulk_modulus.get_wf_bulk_modulus`](https://github.com/hackingmaterials/atomate/blob/main/atomate/vasp/workflows/base/bulk_modulus.py#L21)
+
+In the original atomate 1 workflow and the atomate2 `MPLegacyEosMaker`, the k-point density is **extremely** high. This is despite the convergence tests in the supplementary information
+of Latimer *et al.* not showing strong sensitivity when the "number of ***k***-points per reciprocal atom" (KPPRA) is at least 3,000.
+
+To make the `MPGGAEosMaker` and `MPMetaGGAEosMaker` more tractable for high-throughput jobs, their input sets (`MPGGAEos{Relax,Static}SetGenerator` and `MPMetaGGAEos{Relax,Static}SetGenerator` respectively) still use the highest ***k***-point density in standard Materials Project jobs, `KSPACING = 0.22` Å<sup>-1</sup>, which is comparable to KPPRA = 3,000.
 
+This choice is justified by Fig. S12 of the supplemantary information of Latimer *et al.*, which shows that all fitted EOS parameters (equilibrium energy $E_0$, equilibrium volume $V_0$, bulk modulus $B_0$, and bulk modulus pressure derivative $B_1$) do not deviate by more than 1.5%, and typically by less than 0.1%, from well-converged values when KPPRA = 3,000.
 
 ### LOBSTER
 

pyproject.toml

@@ -43,6 +43,7 @@ amset = ["amset>=0.4.15", "pydash"]
 cclib = ["cclib"]
 mp = ["mp-api>=0.37.5"]
 phonons = ["phonopy>=1.10.8", "seekpath>=2.0.0"]
+pheasy = ["hiphive==1.3.1"]
 lobster = ["ijson>=3.2.2", "lobsterpy>=0.4.0"]
 defects = [
     "dscribe>=1.2.0",
@@ -51,7 +52,7 @@ defects = [
 ]
 forcefields = [
     "ase>=3.23.0",
-    "calorine<=2.2.1",
+    "calorine>=3.0",
     "chgnet>=0.2.2",
     "mace-torch>=0.3.3",
     "matgl>=1.1.3",
@@ -74,7 +75,7 @@ docs = [
     "FireWorks==2.0.3",
     "autodoc_pydantic==2.2.0",
     "furo==2024.8.6",
-    "ipython==8.29.0",
+    "ipython==8.30.0",
     "jsonschema[format]",
     "myst_parser==4.0.0",
     "numpydoc==1.8.0",
@@ -89,7 +90,7 @@ tests = [
     "pytest-cov==6.0.0",
     "pytest-mock==3.14.0",
     "pytest-split==0.10.0",
-    "pytest==8.3.3",
+    "pytest==8.3.4",
 ]
 strict = [
     "PyYAML==6.0.2",
@@ -98,17 +99,17 @@ strict = [
     "click==8.1.7",
     "custodian==2024.10.16",
     "dscribe==2.1.1",
-    "emmet-core==0.84.3rc3",
+    "emmet-core==0.84.3rc6",
     "ijson==3.3.0",
-    "jobflow==0.1.18",
+    "jobflow==0.1.19",
     "lobsterpy==0.4.9",
     "mdanalysis==2.7.0",
     "monty==2024.10.21",
-    "mp-api==0.42.2",
+    "mp-api==0.43.0",
     "numpy",
     "openmm-mdanalysis-reporter==0.1.0",
     "openmm==8.1.1",
-    "phonopy==2.27.0",
+    "phonopy==2.30.1",
     "pydantic-settings==2.6.1",
     "pydantic==2.9.2",
     "pymatgen-analysis-defects==2024.10.22",
@@ -117,14 +118,16 @@ strict = [
     "seekpath==2.1.0",
     "tblite==0.3.0; python_version < '3.12'",
     "typing-extensions==4.12.2",
+    "hiphive==1.3.1",
+    "f90nml==1.4.4",
 ]
 strict-forcefields = [
     "calorine==3.0",
     "chgnet==0.4.0",
     "mace-torch>=0.3.6",
     "matgl==1.1.3",
     "quippy-ase==0.9.14; python_version < '3.12'",
-    "sevenn==0.10.1",
+    "sevenn==0.10.2",
     "torch==2.5.1",
     "torchdata==0.7.1",                            # TODO: remove when issue fixed
 ]
@@ -207,7 +210,6 @@ ignore = [
     "PLR0913", # too many arguments
     "PLR0915", # too many local statements
     "PLR2004",
-    "PT004",   # pytest-missing-fixture-name-underscore
     "PT006",   # pytest-parametrize-names-wrong-type
     "PT013",   # pytest-incorrect-pytest-import
     "PTH",     # prefer Pathlib to os.path

src/atomate2/ase/schemas.py

@@ -99,7 +99,7 @@ class AseBaseModel(BaseModel):
     )
     molecule: Optional[Molecule] = Field(None, description="The molecule at this step.")
 
-    def model_post_init(self, __context: Any) -> None:
+    def model_post_init(self, _context: Any) -> None:
         """Establish alias to structure and molecule fields."""
         if self.structure is None and isinstance(self.mol_or_struct, Structure):
             self.structure = self.mol_or_struct

src/atomate2/common/flows/anharmonicity.py

@@ -81,7 +81,7 @@ def make(
             A previous calculation directory to use for copying outputs.
             Default is None.
         born: Optional[list[Matrix3D]]
-            Instead of recomputing born charges and epsilon, these values can also be
+            Instead of recomputing Born charges and epsilon, these values can also be
             provided manually. If born and epsilon_static are provided, the born run
             will be skipped it can be provided in the VASP convention with information
             for every atom in unit cell. Please be careful when converting structures

src/atomate2/common/flows/gruneisen.py

@@ -40,7 +40,7 @@ class BaseGruneisenMaker(Maker, ABC):
     generated for all the three structures (ground state, expanded and shrunk volume)
     and accurate forces are computed for these structures. With the help of phonopy,
     these forces are then converted into a dynamical matrix. This dynamical matrix of
-    three structures is then used as an input for the phonopy Grueneisen api
+    three structures is then used as an input for the phonopy Grueneisen API
     to compute Grueneisen parameters.