refactor: restructure dice environment handling and update Python version requirement

control.example.yml

@@ -13,10 +13,11 @@ diceplayer:
         nprocs: 1
         nmol: [1, 200]
         dens: 1.5
-        nstep: [200, 300]
-        isave: 100
+        nstep: [200, 200]
+        vstep: 1000
+        isave: 30
         outname: 'phb'
-        progname: 'dice'
+        progname: '/home/hideyoshi/.local/bin/dice'
         ljname: 'phb.ljc.example'
         randominit: 'always'
         seed: 12345

diceplayer/dice/dice_handler.py

@@ -1,14 +1,21 @@
+import warnings
+
 from diceplayer.dice.dice_input import (
     NPTEqConfig,
     NPTTerConfig,
     NVTEqConfig,
     NVTTerConfig,
 )
-from diceplayer.dice.dice_wrapper import DiceWrapper
+from diceplayer.dice.dice_wrapper import (
+    DiceEnvironment,
+    DiceWrapper,
+)
+from diceplayer.environment import Atom, Molecule
 from diceplayer.logger import logger
 from diceplayer.state.state_model import StateModel
 
 import shutil
+from itertools import batched, chain, islice
 from pathlib import Path
 from threading import Thread
 
@@ -17,7 +24,7 @@ class DiceHandler:
     def __init__(self, step_directory: Path):
         self.dice_directory = step_directory / "dice"
 
-    def run(self, state: StateModel, cycle: int) -> StateModel:
+    def run(self, state: StateModel, cycle: int) -> list[Atom]:
         if self.dice_directory.exists():
             logger.info(
                 f"Found dice directory: {self.dice_directory}, this directory will be purged for a clean state"
@@ -25,14 +32,10 @@ class DiceHandler:
             shutil.rmtree(self.dice_directory)
         self.dice_directory.mkdir(parents=True)
 
-        simulation_results = self.run_simulations(state, cycle)
+        return self.run_simulations(state, cycle)
 
-        result = self.aggregate_results(simulation_results)
-
-        return self.commit_simulation_state(state, result)
-
-    def run_simulations(self, state: StateModel, cycle: int) -> list[dict]:
-        results = []
+    def run_simulations(self, state: StateModel, cycle: int) -> list[Atom]:
+        results: list[list[Atom]] = []
 
         threads = []
         for p in range(state.config.dice.nprocs):
@@ -48,15 +51,14 @@ class DiceHandler:
                 f"Expected {state.config.dice.nprocs} simulation results, but got {len(results)}"
             )
 
-        return results
-
-    def aggregate_results(self, simulation_results: list[dict]) -> dict: ...
-
-    def commit_simulation_state(self, state: StateModel, result: dict) -> StateModel:
-        return state
+        return self._aggregate_results(state, results)
 
     def _simulation_process(
-        self, state: StateModel, cycle: int, proc: int, results: list[dict]
+        self,
+        state: StateModel,
+        cycle: int,
+        proc: int,
+        results: list[list[Atom]],
     ) -> None:
         proc_directory = self.dice_directory / f"{proc:02d}"
         if proc_directory.exists():
@@ -84,7 +86,12 @@ class DiceHandler:
             npt_eq_config = NPTEqConfig.from_config(state.config)
             dice.run(npt_eq_config)
 
-        results.append(dice.parse_results(state.system))
+        results.extend(
+            [
+                self._filter_environment_sites(state, environment)
+                for environment in dice.parse_results()
+            ]
+        )
 
     @staticmethod
     def _generate_phb_file(state: StateModel, proc_directory: Path) -> None:
@@ -113,3 +120,67 @@ class DiceHandler:
                     )
 
     def _generate_last_xyz(self, state: StateModel, proc_directory: Path) -> None: ...
+
+    @staticmethod
+    def _filter_environment_sites(
+        state: StateModel, environment: DiceEnvironment
+    ) -> list[Atom]:
+        picked_environment = []
+
+        ref_molecule = state.system.molecule[0]
+        ref_molecule_sizes = ref_molecule.sizes_of_molecule()
+        ref_n_sites = len(ref_molecule.atom) * state.config.dice.nmol[0]
+
+        min_distance = min(
+            (environment.thickness[i] - ref_molecule_sizes[i]) / 2 for i in range(3)
+        )
+
+        site_iter = iter(environment.items)
+        _ = list(islice(site_iter, ref_n_sites))
+
+        for molecule_index, molecule in enumerate(state.system.molecule[1:], start=1):
+            molecule_n_atoms = len(molecule.atom)
+            molecule_n_sites = molecule_n_atoms * state.config.dice.nmol[molecule_index]
+
+            sites = list(islice(site_iter, molecule_n_sites))
+
+            for molecule_sites in batched(sites, molecule_n_atoms):
+                new_molecule = Molecule("ASEC TMP MOLECULE")
+
+                for site_index, atom_site in enumerate(molecule_sites):
+                    new_molecule.add_atom(
+                        Atom(
+                            molecule.atom[site_index].lbl,
+                            molecule.atom[site_index].na,
+                            atom_site.x,
+                            atom_site.y,
+                            atom_site.z,
+                            molecule.atom[site_index].chg,
+                            molecule.atom[site_index].eps,
+                            molecule.atom[site_index].sig,
+                        )
+                    )
+
+                if molecule.signature() != new_molecule.signature():
+                    _message = f"Skipping sites because the molecule signature does not match the reference molecule. Expected {molecule.signature()} but got {new_molecule.signature()}"
+                    warnings.warn(_message)
+                    logger.warning(_message)
+                    continue
+
+                if ref_molecule.minimum_distance(new_molecule) >= min_distance:
+                    continue
+
+                picked_environment.extend(new_molecule.atom)
+
+        return picked_environment
+
+    @staticmethod
+    def _aggregate_results(state: StateModel, results: list[list[Atom]]) -> list[Atom]:
+        norm_factor = round(state.config.dice.nstep[-1] / state.config.dice.isave)
+
+        agg_results = []
+        for atom in chain(*[r for r in results]):
+            atom.chg = atom.chg * norm_factor
+            agg_results.append(atom)
+
+        return agg_results

diceplayer/dice/dice_wrapper.py

@@ -1,10 +1,39 @@
 import diceplayer.dice.dice_input as dice_input
 from diceplayer.config import DiceConfig
-from diceplayer.environment import System
+
+from pydantic import TypeAdapter
+from pydantic.dataclasses import dataclass
 
 import subprocess
+from itertools import islice
 from pathlib import Path
-from typing import Final
+from typing import Final, List, Self
+
+
+@dataclass(slots=True, frozen=True)
+class DiceEnvironmentItem:
+    atom: str
+    x: float
+    y: float
+    z: float
+
+
+DiceEnvironmentItemAdapter = TypeAdapter(DiceEnvironmentItem)
+
+
+@dataclass(slots=True)
+class DiceEnvironment:
+    number_of_sites: int
+    thickness: List[float]
+    items: List[DiceEnvironmentItem]
+
+    @classmethod
+    def new(cls, thickness: List[float]) -> Self:
+        return cls(number_of_sites=0, thickness=thickness, items=[])
+
+    def add_site(self, site: DiceEnvironmentItem):
+        self.items.append(site)
+        self.number_of_sites += 1
 
 
 DICE_FLAG_LINE: Final[int] = -2
@@ -22,7 +51,10 @@ class DiceWrapper:
 
         with open(output_path, "w") as outfile, open(input_path, "r") as infile:
             exit_status = subprocess.call(
-                self.dice_config.progname, stdin=infile, stdout=outfile, cwd=self.working_directory
+                self.dice_config.progname,
+                stdin=infile,
+                stdout=outfile,
+                cwd=self.working_directory,
             )
 
         if exit_status != 0:
@@ -35,9 +67,37 @@ class DiceWrapper:
 
         raise RuntimeError(f"Dice simulation failed with exit status {exit_status}")
 
-    def parse_results(self, system: System) -> dict:
-        results = {}
-        for output_file in sorted(self.working_directory.glob("phb*.xyz")):
-            ...
+    def parse_results(self) -> list[DiceEnvironment]:
+        results = []
+
+        positions_file = self.working_directory / "phb.xyz"
+        if not positions_file.exists():
+            raise RuntimeError(f"Positions file not found at {self.working_directory}")
+
+        with open(positions_file, "r") as f:
+            while True:
+                line = f.readline()
+                if not line.startswith("    "):
+                    break
+
+                environment = DiceEnvironment(
+                    number_of_sites=int(line.strip()),
+                    thickness=[float(n) for n in f.readline().split()[-3:]],
+                    items=[],
+                )
+
+                # Skip the comment line
+
+                environment.items.extend(
+                    [
+                        DiceEnvironmentItemAdapter.validate_python(
+                            {"atom": site[0], "x": site[1], "y": site[2], "z": site[3]}
+                        )
+                        for atom in islice(f, environment.number_of_sites)
+                        if (site := atom.strip().split()) and len(site) == 4
+                    ]
+                )
+
+                results.append(environment)
 
         return results

diceplayer/environment/molecule.py

@@ -2,7 +2,6 @@ from __future__ import annotations
 
 from diceplayer.environment import Atom
 from diceplayer.logger import logger
-from diceplayer.utils.cache import invalidate_computed_properties
 from diceplayer.utils.misc import BOHR2ANG, EA_2_DEBYE
 from diceplayer.utils.ptable import GHOST_NUMBER
 
@@ -15,7 +14,6 @@ from typing_extensions import List, Self, Tuple
 import math
 from copy import deepcopy
 from dataclasses import field
-from functools import cached_property
 
 
 @dataclass
@@ -34,11 +32,11 @@ class Molecule:
     molname: str
     atom: List[Atom] = field(default_factory=list)
 
-    @cached_property
+    @property
     def total_mass(self) -> float:
         return sum(atom.mass for atom in self.atom)
 
-    @cached_property
+    @property
     def com(self) -> npt.NDArray[np.float64]:
         com = np.zeros(3)
 
@@ -49,7 +47,7 @@ class Molecule:
 
         return com
 
-    @cached_property
+    @property
     def inertia_tensor(self) -> npt.NDArray[np.float64]:
         """
         Calculates the inertia tensor of the molecule.
@@ -79,7 +77,6 @@ class Molecule:
 
         return inertia_tensor
 
-    @invalidate_computed_properties()
     def add_atom(self, a: Atom) -> None:
         """
         Adds Atom instance to the molecule.
@@ -90,7 +87,6 @@ class Molecule:
 
         self.atom.append(a)
 
-    @invalidate_computed_properties()
     def remove_atom(self, a: Atom) -> None:
         """
         Removes Atom instance from the molecule.
@@ -101,7 +97,6 @@ class Molecule:
 
         self.atom.remove(a)
 
-    @invalidate_computed_properties()
     def move_center_of_mass_to_origin(self) -> None:
         """
         Updated positions based on the center of mass of the molecule
@@ -111,7 +106,6 @@ class Molecule:
             atom.ry -= self.com[1]
             atom.rz -= self.com[2]
 
-    @invalidate_computed_properties()
     def rotate_to_standard_orientation(self) -> None:
         """
         Rotates the molecule to the standard orientation
@@ -315,3 +309,12 @@ class Molecule:
         diff = coords_a[:, None, :] - coords_b[None, :, :]
         d2 = np.sum(diff**2, axis=-1)
         return np.sqrt(d2.min())
+
+    def signature(self) -> List[int]:
+        """
+        Returns the signature of the molecule, which is a list of the number of atoms of each type in the molecule.
+
+        Returns:
+            List[int]: signature of the molecule
+        """
+        return [a.lbl for a in self.atom]

diceplayer/optimization/optimization_handler.py

@@ -1,11 +1,29 @@
 from diceplayer.config.player_config import RoutineType
+from diceplayer.dice.dice_wrapper import DiceEnvironmentItem
+from diceplayer.environment import Atom
+from diceplayer.logger import logger
 from diceplayer.state.state_model import StateModel
 
+from pathlib import Path
+
 
 class OptimizationHandler:
-    @staticmethod
-    def run(state: StateModel, current_cycle: int) -> StateModel:
-        print(f"Running Optimization - {current_cycle}")
+    def __init__(self, step_directory: Path):
+        self.optimization_directory = step_directory / "optimization"
+
+    def run(
+        self,
+        state: StateModel,
+        current_cycle: int,
+        dice_environment: list[Atom],
+    ) -> StateModel:
+        routine = self._fetch_current_routine(state, current_cycle)
+        logger.info(
+            f"Running Optimization - {current_cycle} - {routine} - {self.optimization_directory}"
+        )
+
+        logger.info(dice_environment)
+
         return state
 
     @staticmethod

diceplayer/player.py

@@ -1,6 +1,7 @@
 from diceplayer.config.player_config import PlayerConfig
 from diceplayer.dice.dice_handler import DiceHandler
 from diceplayer.logger import logger
+from diceplayer.optimization.optimization_handler import OptimizationHandler
 from diceplayer.state.state_handler import StateHandler
 from diceplayer.state.state_model import StateModel
 from diceplayer.utils.potential import read_system_from_phb
@@ -45,9 +46,13 @@ class Player:
             if not step_directory.exists():
                 step_directory.mkdir(parents=True)
 
-            state = DiceHandler(step_directory).run(state, state.current_cycle)
+            dice_environment = DiceHandler(step_directory).run(
+                state, state.current_cycle
+            )
 
-            # state = OptimizationHandler.run(state, state.current_cycle)
+            state = OptimizationHandler(step_directory).run(
+                state, state.current_cycle, dice_environment
+            )
 
             state.current_cycle += 1
             self._state_handler.save(state)

pyproject.toml

@@ -8,7 +8,7 @@ authors = [
 readme = "README.md"
 license = "GPL-2.0-only"
 scripts = { diceplayer = "diceplayer.__main__:main" }
-requires-python = ">=3.10"
+requires-python = ">=3.12"
 dynamic = ["version"]
 
 

tests/_assets/__init__.py

@@ -0,0 +1,4 @@
+from pathlib import Path
+
+
+ASSETS_DIR = Path(__file__).parent

tests/dice/test_dice_handler.py

@@ -0,0 +1,92 @@
+from diceplayer.config import DiceConfig, GaussianConfig, PlayerConfig
+from diceplayer.dice.dice_handler import DiceHandler
+from diceplayer.dice.dice_wrapper import DiceWrapper
+from diceplayer.state.state_model import StateModel
+from diceplayer.utils.potential import read_system_from_phb
+from tests._assets import ASSETS_DIR
+
+import pytest
+
+from pathlib import Path
+
+
+class TestDiceHandler:
+    @pytest.fixture
+    def working_directory(self) -> Path:
+        return ASSETS_DIR
+
+    @pytest.fixture
+    def player_config(self, working_directory: Path) -> PlayerConfig:
+        return PlayerConfig(
+            type="both",
+            mem=12,
+            max_cyc=100,
+            switch_cyc=50,
+            ncores=4,
+            dice=DiceConfig(
+                nprocs=4,
+                ljname=working_directory / "phb.ljc",
+                outname="test",
+                dens=1.0,
+                nmol=[1, 200],
+                nstep=[1000, 1000],
+            ),
+            gaussian=GaussianConfig(
+                level="test",
+                qmprog="g16",
+                keywords="test",
+            ),
+        )
+
+    @pytest.fixture
+    def state_model(self, player_config: PlayerConfig) -> StateModel:
+        return StateModel(
+            config=player_config,
+            system=read_system_from_phb(player_config),
+            current_cycle=0,
+        )
+
+    @pytest.fixture
+    def dice_wrapper(
+        self, player_config: PlayerConfig, working_directory: Path
+    ) -> DiceWrapper:
+        return DiceWrapper(player_config.dice, working_directory)
+
+    @pytest.fixture
+    def dice_handler(self, tmp_path) -> DiceHandler:
+        return DiceHandler(tmp_path)
+
+    def test_filter_environment_sites(
+        self,
+        dice_handler: DiceHandler,
+        dice_wrapper: DiceWrapper,
+        state_model: StateModel,
+    ) -> None:
+        environment = dice_wrapper.parse_results()[0]
+
+        filtered_environment = dice_handler._filter_environment_sites(
+            state_model, environment
+        )
+
+        assert len(filtered_environment) < environment.number_of_sites
+
+    def test_aggregate_results(
+        self,
+        dice_handler: DiceHandler,
+        dice_wrapper: DiceWrapper,
+        state_model: StateModel,
+    ) -> None:
+        environments = dice_wrapper.parse_results()
+
+        picked_environments = [
+            dice_handler._filter_environment_sites(state_model, env)
+            for env in environments
+        ]
+
+        aggregated_environment = dice_handler._aggregate_results(
+            state_model, picked_environments
+        )
+
+        assert len(aggregated_environment) == sum(
+            len(env) for env in picked_environments
+        )

tests/dice/test_dice_wrapper.py

@@ -0,0 +1,38 @@
+from diceplayer.config import DiceConfig
+from diceplayer.dice.dice_wrapper import DiceEnvironment, DiceWrapper
+from tests._assets import ASSETS_DIR
+
+import pytest
+
+from pathlib import Path
+
+
+class TestDiceWrapper:
+    @pytest.fixture(autouse=True)
+    def dice_config(self) -> DiceConfig:
+        return DiceConfig.model_validate(
+            {
+                "nprocs": 4,
+                "ljname": "test",
+                "outname": "test",
+                "dens": 1.0,
+                "nmol": [1],
+                "nstep": [1, 1],
+            }
+        )
+
+    @pytest.fixture(autouse=True)
+    def working_directory(self) -> Path:
+        return ASSETS_DIR
+
+    @pytest.fixture(autouse=True)
+    def dice_wrapper(
+        self, dice_config: DiceConfig, working_directory: Path
+    ) -> DiceWrapper:
+        return DiceWrapper(dice_config, working_directory)
+
+    def test_parse_results(self, dice_wrapper: DiceWrapper) -> None:
+        results = dice_wrapper.parse_results()
+
+        assert isinstance(results, list)
+        assert all(isinstance(env, DiceEnvironment) for env in results)

uv.lock

@@ -1,10 +1,6 @@
 version = 1
 revision = 3
-requires-python = ">=3.10"
-resolution-markers = [
-    "python_full_version >= '3.11'",
-    "python_full_version < '3.11'",
-]
+requires-python = ">=3.12"
 
 [[package]]
 name = "annotated-types"
@@ -35,21 +31,9 @@ dependencies = [
     { name = "pathspec" },
     { name = "platformdirs" },
     { name = "pytokens" },
-    { name = "tomli", marker = "python_full_version < '3.11'" },
-    { name = "typing-extensions", marker = "python_full_version < '3.11'" },
 ]
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