Merge branch 'develop'

.pre-commit-config.yaml

@@ -11,7 +11,7 @@ repos:
         exclude: ^example/AlN-LDA/
 
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.9.7
+    rev: v0.9.9
     hooks:
       - id: ruff
         args: [ "--fix", "--show-fixes" ]

doc/changelog.md

@@ -2,6 +2,10 @@
 
 # Change Log
 
+## Mar-4-2025: Version 3.15.0
+
+- Release to follow the change of phonopy
+
 ## Mar-1-2025: Version 3.14.1
 
 - Release to follow the change of phonopy

doc/conf.py

@@ -58,9 +58,9 @@ copyright = "2015, Atsushi Togo"
 # built documents.
 #
 # The short X.Y version.
-version = "3.14"
+version = "3.15"
 # The full version, including alpha/beta/rc tags.
-release = "3.14.1"
+release = "3.15.0"
 
 # The language for content autogenerated by Sphinx. Refer to documentation
 # for a list of supported languages.

doc/pypolymlp.md

@@ -64,7 +64,7 @@ in the distribution from GitHub or PyPI.
    `phono3py_params.yaml`. Use {ref}`--cf3 <cf3_option>` and {ref}`--sp
    <sp_option>` option simultaneously.
 4. Develop MLPs. By default, 90 and 10 percents of the dataset are used for the
-   training and test, respectively. At this step `phono3py.pmlp` is saved.
+   training and test, respectively. At this step `polymlp.yaml` is saved.
 5. Generate displacements in supercells either systematic or random displacements.
 6. Evaluate MLPs for forces of the supercells generated in step 5.
 7. Calculate force constants from displacement-force dataset from steps 5 and 6.
@@ -217,7 +217,7 @@ Regression: model selection ...
 - alpha = 1.000e-01 : rmse (train, test) = 0.00002 0.00002
 - alpha = 1.000e+00 : rmse (train, test) = 0.00002 0.00002
 - alpha = 1.000e+01 : rmse (train, test) = 0.00002 0.00002
-MLPs were written into "phono3py.pmlp"
+MLPs were written into "polymlp.yaml"
 ------------------------------ pypolymlp end -------------------------------
 Generate displacements (--rd or -d) for proceeding to phonon calculations.
 Summary of calculation was written in "phono3py.yaml".
@@ -231,7 +231,7 @@ Summary of calculation was written in "phono3py.yaml".
 
 Information about the development of MLPs using pypolymlp is provided between
 the `pypolymlp start` and `pypolymlp end` sections. The polynomial MLPs are
-saved in the `phono3py.pmlp` file, which can be reused in subsequent phono3py
+saved in the `polymlp.yaml` file, which can be reused in subsequent phono3py
 executions with the `--pypolymlp` option when only displacements (and no forces)
 are provided.
 
@@ -240,7 +240,7 @@ are provided.
 
 With the `-d` option, displacements are systematically generated while taking
 crystal symmetry into account. When running with the `--pypolymlp` option, MLPs
-are read from `phono3py.pmlp` if the file exists. In this case, training data is
+are read from `polymlp.yaml` if the file exists. In this case, training data is
 no longer required, and files such as `phono3py.yaml` can be used as the input
 structure file.
 
@@ -274,7 +274,7 @@ NAC parameters were read from "phono3py.yaml".
 Pypolymlp is a generator of polynomial machine learning potentials.
 Please cite the paper: A. Seko, J. Appl. Phys. 133, 011101 (2023).
 Pypolymlp is developed at https://github.com/sekocha/pypolymlp.
-Load MLPs from "phono3py.pmlp".
+Load MLPs from "polymlp.yaml".
 ------------------------------ pypolymlp end -------------------------------
 Generate displacements
   Displacement distance: 0.01
@@ -318,7 +318,7 @@ Random displacements are generated by specifying {ref}`--rd
 <random_displacements_option>` option. To compute force constants with random
 displacements, an external force constants calculator is necessary. By default,
 symfc is used unless another force constants solver is explicitly specified.
-When running with the `--pypolymlp` option, MLPs are read from `phono3py.pmlp`
+When running with the `--pypolymlp` option, MLPs are read from `polymlp.yaml`
 if the file exists. In this case, training data is no longer required, and files
 such as `phono3py.yaml` can be used as the input structure file.
 
@@ -352,7 +352,7 @@ NAC parameters were read from "phono3py.yaml".
 Pypolymlp is a generator of polynomial machine learning potentials.
 Please cite the paper: A. Seko, J. Appl. Phys. 133, 011101 (2023).
 Pypolymlp is developed at https://github.com/sekocha/pypolymlp.
-Load MLPs from "phono3py.pmlp".
+Load MLPs from "polymlp.yaml".
 ------------------------------ pypolymlp end -------------------------------
 Generate random displacements
   Twice of number of snapshots will be generated for plus-minus displacements.
@@ -406,10 +406,10 @@ displacements. Note that to achieve accurate force constants, the actual number
 of generated supercells is twice the specified number. If `--rd` is omitted,
 systematic displacements are introduced.
 
-Once the file `phono3py.pmlp` is obtained, force constants can be calculated
-using MLPs from `phono3py.pmlp`. After removing the `fc3.hdf5` and `fc2.hdf5`
-files, `phono3py-load` will detect `phono3py.pmlp` and then compute the force
-constants by loading the MLPs from `phono3py.pmlp` as follows:
+Once the file `polymlp.yaml` is obtained, force constants can be calculated
+using MLPs from `polymlp.yaml`. After removing the `fc3.hdf5` and `fc2.hdf5`
+files, `phono3py-load` will detect `polymlp.yaml` and then compute the force
+constants by loading the MLPs from `polymlp.yaml` as follows:
 
 ```
 % phono3py-load --pypolymlp --rd 100 --amplitude 0.005 phono3py.yaml
@@ -441,7 +441,7 @@ NAC parameters were read from "phono3py.yaml".
 Pypolymlp is a generator of polynomial machine learning potentials.
 Please cite the paper: A. Seko, J. Appl. Phys. 133, 011101 (2023).
 Pypolymlp is developed at https://github.com/sekocha/pypolymlp.
-Load MLPs from "phono3py.pmlp".
+Load MLPs from "polymlp.yaml".
 ------------------------------ pypolymlp end -------------------------------
 Generate random displacements
   Twice of number of snapshots will be generated for plus-minus displacements.
@@ -542,3 +542,14 @@ the next 100 supercells) will be computed and included. With this procedure in
 mind, it may be convenient to generate a sufficiently large number of supercells
 with random displacements in advance, such as 1000 supercells, before starting
 the LTC calculation with pypolymlp.
+
+## Converting `phono3py.pmlp` to `polymlp.yaml`
+
+In older versions, polynomial MLPs were stored in `phono3py.pmlp`. This file can
+be converted to `polymlp.yaml` using the following Python snippet.
+
+```python
+from pypolymlp.mlp_dev.pypolymlp import Pypolymlp
+polymlp = Pypolymlp()
+polymlp.convert_to_yaml(filename_txt="phono3py.pmlp", filename_yaml="polymlp.yaml”)
+```

phono3py/cui/create_force_constants.py

@@ -525,7 +525,7 @@ def run_pypolymlp_to_compute_forces(
     random_seed: Optional[int] = None,
     prepare_dataset: bool = False,
     cutoff_pair_distance: Optional[float] = None,
-    mlp_filename: str = "phono3py.pmlp",
+    mlp_filename: Optional[str] = None,
     log_level: int = 0,
 ):
     """Run pypolymlp to compute forces."""
@@ -535,27 +535,48 @@ def run_pypolymlp_to_compute_forces(
         print("Please cite the paper: A. Seko, J. Appl. Phys. 133, 011101 (2023).")
         print("Pypolymlp is developed at https://github.com/sekocha/pypolymlp.")
 
-    if pathlib.Path(mlp_filename).exists():
-        if log_level:
-            print(f'Load MLPs from "{mlp_filename}".')
-        ph3py.load_mlp(mlp_filename)
-    elif forces_in_dataset(ph3py.mlp_dataset):
-        if log_level:
-            if mlp_params is None:
-                pmlp_params = PypolymlpParams()
-            else:
-                pmlp_params = parse_mlp_params(mlp_params)
-            print("Parameters:")
-            for k, v in asdict(pmlp_params).items():
-                if v is not None:
-                    print(f"  {k}: {v}")
-            print("Developing MLPs by pypolymlp...", flush=True)
-        ph3py.develop_mlp(params=mlp_params)
-        ph3py.save_mlp(filename=mlp_filename)
-        if log_level:
-            print(f'MLPs were written into "{mlp_filename}"', flush=True)
-    else:
-        raise RuntimeError(f'"{mlp_filename}" is not found.')
+    mlp_loaded = False
+    for mlp_filename in ["polymlp.yaml", "phono3py.pmlp"]:
+        _mlp_filename_list = list(pathlib.Path().glob(f"{mlp_filename}*"))
+        if _mlp_filename_list:
+            _mlp_filename = _mlp_filename_list[0]
+            print(_mlp_filename)
+            if _mlp_filename.suffix not in [
+                ".yaml",
+                ".pmlp",
+                ".xz",
+                ".gz",
+                ".bz2",
+                "lzma",
+            ]:
+                continue
+            if log_level:
+                print(f'Load MLPs from "{mlp_filename}".')
+            ph3py.load_mlp(mlp_filename)
+            mlp_loaded = True
+            if log_level and mlp_filename == "phono3py.pmlp":
+                print(f'Loading MLPs from "{_mlp_filename}" is obsolete.')
+            break
+
+    mlp_filename = "polymlp.yaml"
+    if not mlp_loaded:
+        if forces_in_dataset(ph3py.mlp_dataset):
+            if log_level:
+                if mlp_params is None:
+                    pmlp_params = PypolymlpParams()
+                else:
+                    pmlp_params = parse_mlp_params(mlp_params)
+                print("Parameters:")
+                for k, v in asdict(pmlp_params).items():
+                    if v is not None:
+                        print(f"  {k}: {v}")
+                print("Developing MLPs by pypolymlp...", flush=True)
+            ph3py.develop_mlp(params=mlp_params)
+            ph3py.save_mlp(filename=mlp_filename)
+            if log_level:
+                print(f'MLPs were written into "{mlp_filename}"', flush=True)
+        else:
+            raise RuntimeError(f'"{mlp_filename}" is not found.')
 
     if log_level:
         print("-" * 30 + " pypolymlp end " + "-" * 31, flush=True)

phono3py/cui/phono3py_script.py

@@ -1200,7 +1200,7 @@ def main(**argparse_control):
                 )
             ph3py.save(mlp_eval_filename)
 
-        # pypolymlp dataset is stored in "phono3py.pmlp" and stop here.
+        # pypolymlp dataset is stored in "polymlp.yaml" and stop here.
         if not prepare_dataset:
             if log_level:
                 print(

phono3py/version.py

@@ -34,4 +34,4 @@
 # ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
 # POSSIBILITY OF SUCH DAMAGE.
 
-__version__ = "3.14.1"
+__version__ = "3.15.0"

pyproject.toml

@@ -16,9 +16,10 @@ dependencies = [
     "matplotlib",
     "h5py",
     "spglib",
-    "phonopy>=2.37.1,<2.38",
+    "phonopy>=2.38.0,<2.39",
 ]
-license = { file = "LICENSE" }
+license = "BSD-3-Clause"
+license-files = ["LICENSE"]
 
 [project.urls]
 Homepage = "https://phonopy.github.io/phono3py/"

test/cui/test_phono3py_load_script.py

@@ -122,11 +122,11 @@ def test_phono3py_with_QE_calculator(load_phono3py_yaml):
 def test_phono3py_load_with_pypolymlp_si():
     """Test phono3py-load script with pypolymlp.
 
-    First run generates phono3py.pmlp.
-    Second run uses phono3py.pmlp.
+    First run generates polymlp.yaml.
+    Second run uses polymlp.yaml.
 
     """
-    pytest.importorskip("pypolymlp")
+    pytest.importorskip("pypolymlp", minversion="0.9.2")
     pytest.importorskip("symfc")
 
     argparse_control = _get_phono3py_load_args(
@@ -159,7 +159,7 @@ def test_phono3py_load_with_pypolymlp_si():
         "phono3py.yaml",
         "fc2.hdf5",
         "fc3.hdf5",
-        "phono3py.pmlp",
+        "polymlp.yaml",
         "phono3py_mlp_eval_dataset.yaml",
     ):
         file_path = pathlib.Path(cwd_called / created_filename)