# 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, StrictInt, field_validator
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 ImageFormatSettings(BaseModel):
    """
    ImageFormatSettings
    """ # noqa: E501
    summation: StrictBool = Field(description="Enable summation of images to a given image_time If disabled images are saved according to original detector speed, but image count is adjusted ")
    geometry_transform: StrictBool = Field(description="Place module read-out into their location on composed detector and extend multipixels ")
    jungfrau_conversion: StrictBool = Field(description="Convert pixel value in ADU to photon counts/energy Only affects JUNGFRAU detector ")
    jungfrau_conversion_factor_ke_v: Optional[Union[Annotated[float, Field(le=500.0, strict=True, ge=0.001)], Annotated[int, Field(le=500, strict=True, ge=1)]]] = Field(default=None, description="Used to convert energy deposited into pixel to counts If not provided incident_energy_keV is used ", alias="jungfrau_conversion_factor_keV")
    bit_depth_image: Optional[StrictInt] = Field(default=None, description="Bit depth of resulting image (it doesn't affect the original detector value) If not provided value is adjusted automatically ")
    signed_output: Optional[StrictBool] = Field(default=None, description="Controls if pixels have signed output If not provided value is adjusted automatically ")
    mask_module_edges: StrictBool = Field(description="Mask 1 pixel on the module boundary ")
    mask_chip_edges: StrictBool = Field(description="Mask multipixels on chip boundary ")
    __properties: ClassVar[List[str]] = ["summation", "geometry_transform", "jungfrau_conversion", "jungfrau_conversion_factor_keV", "bit_depth_image", "signed_output", "mask_module_edges", "mask_chip_edges"]

    @field_validator('bit_depth_image')
    def bit_depth_image_validate_enum(cls, value):
        """Validates the enum"""
        if value is None:
            return value

        if value not in set([16, 32]):
            raise ValueError("must be one of enum values (16, 32)")
        return value

    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 ImageFormatSettings 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 ImageFormatSettings from a dict"""
        if obj is None:
            return None

        if not isinstance(obj, dict):
            return cls.model_validate(obj)

        _obj = cls.model_validate({
            "summation": obj.get("summation"),
            "geometry_transform": obj.get("geometry_transform"),
            "jungfrau_conversion": obj.get("jungfrau_conversion"),
            "jungfrau_conversion_factor_keV": obj.get("jungfrau_conversion_factor_keV"),
            "bit_depth_image": obj.get("bit_depth_image"),
            "signed_output": obj.get("signed_output"),
            "mask_module_edges": obj.get("mask_module_edges") if obj.get("mask_module_edges") is not None else True,
            "mask_chip_edges": obj.get("mask_chip_edges") if obj.get("mask_chip_edges") is not None else True
        })
        return _obj