Files
Jungfraujoch/python-client/openapi_client/models/image_format_settings.py
2024-10-08 21:04:09 +02:00

114 lines
4.8 KiB
Python

# 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