Source code for pyenzyme.enzymeml.core.replicate

# File:
# Project: core
# Author: Jan Range
# License: BSD-2 clause
# Copyright (c) 2022 Institute of Biochemistry and Technical Biochemistry Stuttgart

from pydantic import Field, validator, PrivateAttr
from typing import List, TYPE_CHECKING, Optional
from dataclasses import dataclass

from pyenzyme.enzymeml.core.enzymemlbase import EnzymeMLBase
from pyenzyme.enzymeml.core.ontology import DataTypes
from pyenzyme.enzymeml.core.exceptions import DataError
from pyenzyme.enzymeml.core.utils import type_checking, deprecated_getter

if TYPE_CHECKING:  # pragma: no cover
    static_check_init_args = dataclass
    static_check_init_args = type_checking

[docs]@static_check_init_args class Replicate(EnzymeMLBase): id: str = Field( ..., description="Unique identifier of the replicate", ) species_id: str = Field( ..., description="Unique identifier of the species that has been measured.", regex=r"[s|r|p][\d]+", ) measurement_id: Optional[str] = Field( None, description="Unique identifier of the measurement that the replicate is part of.", regex=r"m[\d]+", ) data_type: DataTypes = Field( DataTypes.CONCENTRATION, description="Type of data that was measured (e.g. concentration)", ) data_unit: str = Field( ..., description="SI unit of the data that was measured.", ) time_unit: str = Field( ..., description="Time unit of the replicate.", ) time: List[float] = Field( None, description="Time steps of the replicate.", ) data: List[float] = Field( None, description="Data that was measured.", ) is_calculated: bool = Field( False, description="Whether or not the data has been generated by simulation.", ) uri: Optional[str] = Field( None, description="URI of the protein.", ) creator_id: Optional[str] = Field( None, description="Unique identifier of the author.", ) # * Private _time_unit_id: Optional[str] = PrivateAttr(None) _data_unit_id: Optional[str] = PrivateAttr(None) _enzmldoc = PrivateAttr(default=None)
[docs] @validator("data") def check_data_completeness(cls, data: List[float], values: dict): if values.get("time") is None and data is not None: # Check if time is given raise DataError( "No time values provided for the data yet. \ Please include time values too, using the 'time' attribute" ) elif values.get("time"): # Check if the data complies with the time values timesteps = len(values["time"]) if timesteps != len(data): raise DataError( f"The number of steps provided for the data [{len(data)}] does not match the number of timesteps [{timesteps}] for replicate '{values['id']}'" ) return data
# ! Getters
[docs] def data_unitdef(self): """Returns the appropriate unitdef if an enzmldoc is given""" if not self._enzmldoc: return None return self._enzmldoc._unit_dict[self._data_unit_id]
[docs] def time_unitdef(self): """Returns the appropriate unitdef if an enzmldoc is given""" if not self._enzmldoc: return None return self._enzmldoc._unit_dict[self._time_unit_id]
[docs] @deprecated_getter("measurement_id") def getMeasurement(self): return self.measurement_id
[docs] @deprecated_getter("is_calculated") def getIsCalculated(self): return self.is_calculated
[docs] @deprecated_getter("replicate_id") def getReplica(self): return
[docs] @deprecated_getter("species_id") def getReactant(self): return self.species_id
[docs] @deprecated_getter("data_type") def getType(self): return self.data_type
[docs] @deprecated_getter("data_unit") def getDataUnit(self): return self.data_unit
[docs] @deprecated_getter("time_unit") def getTimeUnit(self): return self.time_unit
[docs] @deprecated_getter("time' and 'data") def getData(self, sep=False): return self.time,