Revert "Remove fitsnap"

Author: pmrv

.ci_support/environment.yml

@@ -12,5 +12,6 @@ dependencies:
 - pyiron-data =0.0.25
 - pyparsing =3.1.1
 - scipy =1.11.4
+- fitsnap3 =3.1.0.4
 - pip:
   - runnerase==0.3.3

pyiron_potentialfit/fitsnap/__init__.py

@@ -0,0 +1,98 @@
+import numpy as np
+from fitsnap3lib.scrapers.ase_funcs import get_apre, create_shared_arrays
+
+
+def calc_bispectrum_names(twojmax):
+    lst = []
+    for j1 in range(0, twojmax + 1):
+        for j2 in range(0, j1 + 1):
+            for j in range(j1 - j2, min(twojmax, j1 + j2) + 1, 2):
+                if j >= j1:
+                    lst.append([j1 / 2.0, j2 / 2.0, j / 2.0])
+    return lst
+
+
+def ase_scraper(
+    s, frames, energies, forces, stresses=[[0, 0, 0], [0, 0, 0], [0, 0, 0]]
+):
+    """
+    Custom function to allocate shared arrays used in Calculator and build the internal list of
+    dictionaries `data` of configuration info. Customized version of `fitsnap3lib.scrapers.ase_funcs`.
+
+    Args:
+        s: fitsnap instance.
+        frames: list or array of ASE atoms objects.
+        energies: array of energies.
+        forces: array of forces for all configurations.
+        stresses: array of stresses for all configurations.
+
+    Creates a list of data dictionaries `s.data` suitable for fitsnap descriptor calculation.
+    If running in parallel, this list will be distributed over procs, so that each proc will have a
+    portion of the list.
+    """
+
+    create_shared_arrays(s, frames)
+    s.data = [
+        collate_data(a, e, f, s)
+        for (a, e, f, s) in zip(frames, energies, forces, stresses)
+    ]
+
+
+def collate_data(atoms, energy, forces, stresses):
+    """
+    Function to organize fitting data for FitSNAP from ASE atoms objects.
+
+    Args:
+        atoms: ASE atoms object for a single configuration of atoms.
+        energy: energy of a configuration.
+        forces: numpy array of forces for a configuration.
+        stresses: numpy array of stresses for a configuration.
+
+    Returns a fitsnap data dictionary for a single configuration.
+    """
+
+    # make a data dictionary for this config
+
+    apre = get_apre(cell=atoms.cell)
+    R = np.dot(np.linalg.inv(atoms.cell), apre)
+
+    positions = np.matmul(atoms.get_positions(), R)
+    cell = apre.T
+
+    data = {}
+    data["PositionsStyle"] = "angstrom"
+    data["AtomTypeStyle"] = "chemicalsymbol"
+    data["StressStyle"] = "bar"
+    data["LatticeStyle"] = "angstrom"
+    data["EnergyStyle"] = "electronvolt"
+    data["ForcesStyle"] = "electronvoltperangstrom"
+    data["Group"] = "Displaced_BCC"
+    data["File"] = None
+    data["Stress"] = stresses
+    data["Positions"] = positions
+    data["Energy"] = energy
+    data["AtomTypes"] = atoms.get_chemical_symbols()
+    data["NumAtoms"] = len(atoms)
+    data["Forces"] = forces
+    data["QMLattice"] = cell
+    data["test_bool"] = 0
+    data["Lattice"] = cell
+    data["Rotation"] = np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
+    data["Translation"] = np.zeros((len(atoms), 3))
+    data["eweight"] = 1.0
+    data["fweight"] = 1.0 / 150.0
+    data["vweight"] = 0.0
+
+    return data
+
+
+def subsample_twojmax(total_bispect, twojmax_lst):
+    bi_spect_names_str_lst = [str(lst) for lst in total_bispect]
+    twojmax_master_str_lst = [
+        [str(lst) for lst in calc_bispectrum_names(twojmax=tjm)] for tjm in twojmax_lst
+    ]
+    ind_lst = [
+        [desc in desc_lst for desc in bi_spect_names_str_lst]
+        for desc_lst in twojmax_master_str_lst
+    ]
+    return ind_lst

pyiron_potentialfit/fitsnap/common.py

@@ -0,0 +1,101 @@
+from mpi4py import MPI
+from fitsnap3lib.fitsnap import FitSnap
+from pyiron_base import PythonTemplateJob, DataContainer
+from pyiron_potentialfit.fitsnap.common import ase_scraper
+
+
+default_input = settings = {
+    "BISPECTRUM": {
+        "numTypes": 1,
+        "twojmax": 8,
+        "rcutfac": 4.812302818,
+        "rfac0": 0.99363,
+        "rmin0": 0.0,
+        "wj": 1.0,
+        "radelem": 0.5,
+        "type": "Be",
+        "wselfallflag": 0,
+        "chemflag": 0,
+        "bzeroflag": 0,
+        "quadraticflag": 0,
+    },
+    "CALCULATOR": {
+        "calculator": "LAMMPSSNAP",
+        "energy": 1,  # Calculate energy descriptors
+        "force": 1,  # Calculate force descriptors
+        "stress": 0,  # Calculate virial descriptors
+    },
+    "REFERENCE": {
+        "units": "metal",
+        "atom_style": "atomic",
+        "pair_style": "hybrid/overlay zero 10.0 zbl 4.0 4.8",
+        "pair_coeff1": "* * zero",
+        "pair_coeff2": "1 1 zbl 74 74",
+    },
+    "SOLVER": {"solver": "SVD", "compute_testerrs": 1, "detailed_errors": 1},
+    "EXTRAS": {
+        "dump_descriptors": 0,
+        "dump_truth": 0,
+        "dump_weights": 0,
+        "dump_dataframe": 0,
+    },
+    "MEMORY": {"override": 0},
+}
+
+
+class FitsnapJob(PythonTemplateJob):
+    def __init__(self, project, job_name):
+        super(FitsnapJob, self).__init__(project, job_name)
+        self.__version__ = "0.1"
+        self.__name__ = "FitsnapJob"
+        self.input.update(default_input)
+        self._lst_of_struct = []
+        self._lst_of_energies = []
+        self._lst_of_forces = []
+        self._coefficients = []
+
+    @property
+    def list_of_structures(self):
+        return self._lst_of_struct
+
+    @list_of_structures.setter
+    def list_of_structures(self, structure_lst):
+        self._lst_of_struct = structure_lst
+
+    @property
+    def list_of_energies(self):
+        return self._lst_of_energies
+
+    @list_of_energies.setter
+    def list_of_energies(self, energies):
+        self._lst_of_energies = energies
+
+    @property
+    def coefficients(self):
+        return self._coefficients
+
+    @property
+    def list_of_forces(self):
+        return self._lst_of_forces
+
+    @list_of_forces.setter
+    def list_of_forces(self, forces):
+        self._lst_of_forces = forces
+
+    def run_static(self):
+        comm = MPI.COMM_WORLD
+        input_dict = self.input.to_builtin()
+        snap = FitSnap(input_dict, comm=comm, arglist=["--overwrite"])
+        ase_scraper(
+            snap, self._lst_of_struct, self._lst_of_energies, self._lst_of_forces
+        )
+        snap.process_configs()
+        snap.solver.perform_fit()
+        self._coefficients = snap.solver.fit
+        self.status.finished = True
+
+    def to_hdf(self, hdf=None, group_name=None):
+        super(FitsnapJob, self).to_hdf(hdf=hdf, group_name=group_name)
+
+    def from_hdf(self, hdf=None, group_name=None):
+        super(FitsnapJob, self).from_hdf(hdf=hdf, group_name=group_name)

pyiron_potentialfit/fitsnap/job.py

@@ -36,7 +36,9 @@
         'numpy==1.26.2',
         'pyiron_base==0.6.9',
         'scipy==1.11.4',
+        'fitsnap3==3.1.0.4',
         'runnerase==0.3.3',
     ],
     cmdclass=versioneer.get_cmdclass(),
+    
 )