# coding: utf-8 """ Jungfraujoch Jungfraujoch Broker Web API The version of the OpenAPI document: 1.0.0-rc.15 Contact: filip.leonarski@psi.ch Generated by OpenAPI Generator (https://openapi-generator.tech) Do not edit the class manually. """ # noqa: E501 from __future__ import annotations import pprint import re # noqa: F401 import json from pydantic import BaseModel, ConfigDict, Field, StrictBool, StrictFloat, StrictInt from typing import Any, ClassVar, Dict, List, Optional, Union from typing_extensions import Annotated from typing import Optional, Set from typing_extensions import Self class AzimIntSettings(BaseModel): """ AzimIntSettings """ # noqa: E501 polarization_factor: Optional[Union[Annotated[float, Field(le=1.0, strict=True, ge=-1.0)], Annotated[int, Field(le=1, strict=True, ge=-1)]]] = Field(default=None, description="If polarization factor is provided, than polarization correction is enabled.") solid_angle_corr: StrictBool = Field(description="Apply solid angle correction for radial integration") high_q_recip_a: Union[StrictFloat, StrictInt] = Field(alias="high_q_recipA") low_q_recip_a: Union[StrictFloat, StrictInt] = Field(alias="low_q_recipA") q_spacing: Union[StrictFloat, StrictInt] __properties: ClassVar[List[str]] = ["polarization_factor", "solid_angle_corr", "high_q_recipA", "low_q_recipA", "q_spacing"] model_config = ConfigDict( populate_by_name=True, validate_assignment=True, protected_namespaces=(), ) def to_str(self) -> str: """Returns the string representation of the model using alias""" return pprint.pformat(self.model_dump(by_alias=True)) def to_json(self) -> str: """Returns the JSON representation of the model using alias""" # TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead return json.dumps(self.to_dict()) @classmethod def from_json(cls, json_str: str) -> Optional[Self]: """Create an instance of AzimIntSettings from a JSON string""" return cls.from_dict(json.loads(json_str)) def to_dict(self) -> Dict[str, Any]: """Return the dictionary representation of the model using alias. This has the following differences from calling pydantic's `self.model_dump(by_alias=True)`: * `None` is only added to the output dict for nullable fields that were set at model initialization. Other fields with value `None` are ignored. """ excluded_fields: Set[str] = set([ ]) _dict = self.model_dump( by_alias=True, exclude=excluded_fields, exclude_none=True, ) return _dict @classmethod def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]: """Create an instance of AzimIntSettings from a dict""" if obj is None: return None if not isinstance(obj, dict): return cls.model_validate(obj) _obj = cls.model_validate({ "polarization_factor": obj.get("polarization_factor"), "solid_angle_corr": obj.get("solid_angle_corr") if obj.get("solid_angle_corr") is not None else True, "high_q_recipA": obj.get("high_q_recipA"), "low_q_recipA": obj.get("low_q_recipA"), "q_spacing": obj.get("q_spacing") }) return _obj