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feat: add dice input generation and player routines for NVT/NPT simulations

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This commit is contained in:
Vitor Hideyoshi
2026-03-14 18:28:15 -03:00
parent 53eb34a83e
commit 9f22304dd8
10 changed files with 534 additions and 51 deletions
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89
tests/config/test_player_config.py
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@@ -1,56 +1,62 @@
from diceplayer.config.dice_config import DiceConfig
from diceplayer.config.gaussian_config import GaussianConfig
from diceplayer.config.player_config import PlayerConfig
from diceplayer.config.player_config import PlayerConfig, RoutineType
import pytest
from typing import Any
def get_config_dict():
return {
"opt": True,
"mem": 12,
"maxcyc": 100,
"nprocs": 4,
"ncores": 4,
"dice": {
class TestPlayerConfig:
@pytest.fixture
def dice_payload(self) -> dict[str, Any]:
return {
"ljname": "test",
"outname": "test",
"dens": 1.0,
"nmol": [1],
"nstep": [1, 1],
},
"gaussian": {
}
@pytest.fixture
def gaussian_payload(self) -> dict[str, Any]:
return {
"level": "test",
"qmprog": "g16",
"keywords": "test",
},
}
class TestPlayerConfig:
@pytest.fixture
def dice_config(self):
return DiceConfig(
ljname="test",
outname="test",
dens=1.0,
nmol=[1],
nstep=[1, 1],
)
}
@pytest.fixture
def gaussian_config(self):
return GaussianConfig(
level="test",
qmprog="g16",
keywords="test",
)
def player_payload(
self, dice_payload: dict[str, Any], gaussian_payload: dict[str, Any]
) -> dict[str, Any]:
return {
"type": "both",
"mem": 12,
"max_cyc": 100,
"switch_cyc": 50,
"nprocs": 4,
"ncores": 4,
"dice": dice_payload,
"gaussian": gaussian_payload,
}
def test_class_instantiation(self, dice_config, gaussian_config):
@pytest.fixture
def dice_config(self, dice_payload: dict[str, Any]) -> DiceConfig:
return DiceConfig.model_validate(dice_payload)
@pytest.fixture
def gaussian_config(self, gaussian_payload: dict[str, Any]):
return GaussianConfig.model_validate(gaussian_payload)
def test_class_instantiation(
self, dice_config: DiceConfig, gaussian_config: GaussianConfig
):
player_dto = PlayerConfig(
opt=True,
type=RoutineType.BOTH,
mem=12,
maxcyc=100,
max_cyc=100,
switch_cyc=50,
nprocs=4,
ncores=4,
dice=dice_config,
@@ -61,22 +67,25 @@ class TestPlayerConfig:
assert isinstance(player_dto.dice, DiceConfig)
assert isinstance(player_dto.gaussian, GaussianConfig)
def test_min_altsteps(self, dice_config, gaussian_config):
def test_min_altsteps(
self, dice_config: DiceConfig, gaussian_config: GaussianConfig
):
player_dto = PlayerConfig(
opt=True,
type=RoutineType.BOTH,
mem=12,
maxcyc=100,
max_cyc=100,
switch_cyc=50,
nprocs=4,
ncores=4,
altsteps=100,
altsteps=0,
dice=dice_config,
gaussian=gaussian_config,
)
assert player_dto.altsteps == 20000
def test_from_dict(self):
player_dto = PlayerConfig.model_validate(get_config_dict())
def test_from_dict(self, player_payload: dict[str, Any]):
player_dto = PlayerConfig.model_validate(player_payload)
assert isinstance(player_dto, PlayerConfig)
assert isinstance(player_dto.dice, DiceConfig)

0
tests/dice/__init__.py Normal file
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65
tests/dice/test_dice_input.py Normal file
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@@ -0,0 +1,65 @@
from pathlib import Path
from diceplayer.config import PlayerConfig
from diceplayer.dice.dice_input import NVTEqConfig, NVTTerConfig, NPTTerConfig, NPTEqConfig
import pytest
class TestDiceInput:
@pytest.fixture
def player_config(self) -> PlayerConfig:
return PlayerConfig.model_validate(
{
"type": "both",
"mem": 12,
"max_cyc": 100,
"switch_cyc": 50,
"nprocs": 4,
"ncores": 4,
"dice": {
"ljname": "test",
"outname": "test",
"dens": 1.0,
"nmol": [1],
"nstep": [1, 1],
},
"gaussian": {
"level": "test",
"qmprog": "g16",
"keywords": "test",
},
}
)
def test_generate_nvt_ter_input(self, player_config: PlayerConfig):
dice_input = NVTTerConfig.from_config(player_config)
assert isinstance(dice_input, NVTTerConfig)
def test_generate_nvt_eq_input(self, player_config: PlayerConfig):
dice_input = NVTEqConfig.from_config(player_config)
assert isinstance(dice_input, NVTEqConfig)
def test_generate_npt_ter_input(self, player_config: PlayerConfig):
dice_input = NPTTerConfig.from_config(player_config)
assert isinstance(dice_input, NPTTerConfig)
def test_generate_npt_eq_input(self, player_config: PlayerConfig):
dice_input = NPTEqConfig.from_config(player_config)
assert isinstance(dice_input, NPTEqConfig)
def test_write_dice_config(self, player_config: PlayerConfig, tmp_path: Path):
dice_input = NVTTerConfig.from_config(player_config)
output_file = tmp_path / "nvt_ter.inp"
with open(output_file, "w") as file:
dice_input.write_dice_config(file)
assert output_file.exists()
print(output_file.read_text())

9
tests/state/test_state_handler.py
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@@ -12,9 +12,10 @@ class TestStateHandler:
@pytest.fixture
def player_config(self) -> PlayerConfig:
return PlayerConfig(
opt=True,
type="both",
mem=12,
maxcyc=100,
max_cyc=100,
switch_cyc=50,
nprocs=4,
ncores=4,
dice=DiceConfig(
@@ -87,7 +88,7 @@ class TestStateHandler:
state_handler.save(state)
different_config = player_config.model_copy(update={"opt": False})
different_config = player_config.model_copy(update={"max_cyc": 200})
retrieved_state = state_handler.get(different_config)
@@ -106,7 +107,7 @@ class TestStateHandler:
state_handler.save(state)
different_config = player_config.model_copy(update={"opt": False})
different_config = player_config.model_copy(update={"max_cyc": 200})
retrieved_state = state_handler.get(different_config, force=True)