80 lines
1.9 KiB
Python
80 lines
1.9 KiB
Python
from enum import Enum
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from typing import Optional, Dict, Tuple, List
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from psycopg.types import enum
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from pydantic import BaseModel, ConfigDict
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class ExperimentParametersPyDOE3(BaseModel):
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param_ranges: Dict[str, Tuple[float, float]]
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count_exp: int
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round_rules: List[int]
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class ExperimentParameters(BaseModel):
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outer_blades_count: str
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outer_blades_length: str
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outer_blades_angle: str
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middle_blades_count: str
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load: str
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recycling: str
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class ExperimentParametersPlot(BaseModel):
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file_id: str
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additional_dimension: str
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range: Tuple[float, float]
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class ChExperimentDBExperimentDataBody(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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volume: float
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nitrogen_oxide_emission: float
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temperature: float
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co_fraction: float
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co2_fraction: float
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x: float
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y: float
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z: float
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file_id: str
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class ExperimentCategoryBody(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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name: str
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class ExperimentDataBody(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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direction: float
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temperature: float
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nox: float
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co2: float
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co: float
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file_id: Optional[str]
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class ExperimentParametersBody(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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outer_blades_count: int
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outer_blades_length: float
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outer_blades_angle: float
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middle_blades_count: int
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load_id: Optional[int]
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recycling_id: Optional[int]
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experiment_hash: str
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class LoadParametersBody(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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load: int
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primary_air_consumption: float
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secondary_air_consumption: float
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gas_inlet_consumption: float
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class RecyclingParametersBody(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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load_id: Optional[int]
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recycling_level: int
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co2: float
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n2: float
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h2o: float
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o2: float
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