130 lines
5.0 KiB
Python
130 lines
5.0 KiB
Python
import hashlib
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from typing import Sequence
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import pandas as pd
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import yaml
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from fastapi import HTTPException
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from sqlalchemy.future import select
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from db.crud import create, update, get_by_id, update_exp
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from db.models import LoadParameters, RecyclingParameters
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from db.models.experiment_parameters_model import ExperimentParameters
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from db.postgres_db_connection import async_session_postgres
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from macros_generator import load_calculation, recycling_calculation
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async def get_exp_parameters_by_category(category_id: int) -> Sequence[ExperimentParameters]:
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async with async_session_postgres() as session:
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result = await session.execute(
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select(ExperimentParameters).where(ExperimentParameters.experiment_category_id == category_id)
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)
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return result.scalars().all()
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async def get_exp_parameters_by_exp_hash(exp_hash: str) -> Sequence[ExperimentParameters]:
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async with async_session_postgres() as session:
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result = await session.execute(
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select(ExperimentParameters).where(ExperimentParameters.experiment_hash == exp_hash)
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)
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return result.scalars().all()
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def generate_experiment_hash(data: dict) -> str:
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"""Генерация уникального хеша на основе данных эксперимента"""
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hash_input = f"{data['outer_blades_count']}_{data['outer_blades_length']}_{data['outer_blades_angle']}_{data['middle_blades_count']}_{data['load']}_{data['recycling_level']}"
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return hashlib.sha256(hash_input.encode()).hexdigest()
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async def save_experiment_to_db(df: pd.DataFrame):
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for _, row in df.iterrows():
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try:
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# Преобразуем load и recycling_level в соответствующие id
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load = int(row['load'])
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recycling = int(row['recycling_level'])
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# Генерация хеша для experiment_hash
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experiment_hash = generate_experiment_hash(row)
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exp = await create(
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ExperimentParameters,
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outer_blades_count=int(row['outer_blades_count']),
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outer_blades_length=float(row['outer_blades_length']),
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outer_blades_angle=float(row['outer_blades_angle']),
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middle_blades_count=int(row['middle_blades_count']),
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load_id=None,
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recycling_id=None,
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experiment_hash=experiment_hash,
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oxidizer_temp=float(row['oxidizer_temp']),
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experiment_category_id=experiment_category_id
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)
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await process_and_save_experiment_data(exp.id, load, recycling)
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except Exception as e:
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print(f"Ошибка при сохранении данных: {e}")
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raise HTTPException(status_code=500, detail=f"Ошибка при сохранении данных: {e}")
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async def process_and_save_experiment_data(id: int, load: float, recycling_level: float) -> dict:
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try:
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experiment = await get_by_id(ExperimentParameters, id)
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if experiment is None:
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raise HTTPException(status_code=404, detail=f"ExperimentParameters с id {id} не найден.")
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yaml_file_path = "config.yaml"
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with open(yaml_file_path, "r", encoding="utf-8") as file:
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data = yaml.safe_load(file)
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diameters = data["parameters"]["diameters"]
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dict_load = load_calculation(load, diameters, None)
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primary_air_consumption = dict_load["primary_air_consumption"]
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secondary_air_consumption = dict_load["secondary_air_consumption"]
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gas_inlet_consumption = dict_load["gas_inlet_consumption"]
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alpha = dict_load["alpha"]
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gas_consumption = dict_load["gas_consumption"]
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air_consumption = dict_load["air_consumption"]
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dict_recycling = recycling_calculation(alpha, gas_consumption, air_consumption, recycling_level)
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co2 = dict_recycling["CO2"]
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n2 = dict_recycling["N2"]
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h2o = dict_recycling["H2O"]
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o2 = dict_recycling["O2"]
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load_params = await create(
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LoadParameters,
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load=int(load),
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primary_air_consumption=primary_air_consumption,
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secondary_air_consumption=secondary_air_consumption,
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gas_inlet_consumption=gas_inlet_consumption
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)
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recycling_params = await create(
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RecyclingParameters,
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load_id=load_params.id,
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recycling_level=int(recycling_level),
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co2=co2,
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n2=n2,
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h2o=h2o,
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o2=o2
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)
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await update_exp(
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ExperimentParameters,
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id=experiment.id,
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updated_data={
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"load_id": load_params.id,
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"recycling_id": recycling_params.id
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}
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)
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return {
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"message": "Данные успешно обработаны и сохранены.",
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"load_parameters": load_params,
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"recycling_parameters": recycling_params
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}
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except Exception as e:
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raise HTTPException(status_code=500, detail=f"An error occurred: {str(e)}")
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