Files
Jungfraujoch/python-client/jfjoch_client/models/preview_settings.py
2024-10-23 19:03:09 +02:00

102 lines
4.2 KiB
Python

# coding: utf-8
"""
Jungfraujoch
API to control Jungfraujoch developed by the Paul Scherrer Institute (Switzerland). Jungfraujoch is a data acquisition and analysis system for pixel array detectors, primarly PSI JUNGFRAU. Jungfraujoch uses FPGA boards to acquire data at high data rates.
The version of the OpenAPI document: 1.0.0-rc.23
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
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 PreviewSettings(BaseModel):
"""
Settings for JPEG rendering of preview images
""" # noqa: E501
saturation: Annotated[int, Field(le=65535, strict=True, ge=0)] = Field(description="Saturation value to set contrast in the preview image")
show_spots: Optional[StrictBool] = Field(default=True, description="Show spot finding results on the image")
show_roi: Optional[StrictBool] = Field(default=False, description="Show ROI areas on the image")
jpeg_quality: Optional[Annotated[int, Field(le=100, strict=True, ge=0)]] = Field(default=100, description="Quality of JPEG image (100 - highest; 0 - lowest)")
show_indexed: Optional[StrictBool] = Field(default=False, description="Preview indexed images only")
show_user_mask: Optional[StrictBool] = Field(default=False, description="Show user mask")
resolution_ring: Optional[Union[Annotated[float, Field(le=100.0, strict=True, ge=0.1)], Annotated[int, Field(le=100, strict=True, ge=1)]]] = 0.1
__properties: ClassVar[List[str]] = ["saturation", "show_spots", "show_roi", "jpeg_quality", "show_indexed", "show_user_mask", "resolution_ring"]
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 PreviewSettings 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 PreviewSettings from a dict"""
if obj is None:
return None
if not isinstance(obj, dict):
return cls.model_validate(obj)
_obj = cls.model_validate({
"saturation": obj.get("saturation"),
"show_spots": obj.get("show_spots") if obj.get("show_spots") is not None else True,
"show_roi": obj.get("show_roi") if obj.get("show_roi") is not None else False,
"jpeg_quality": obj.get("jpeg_quality") if obj.get("jpeg_quality") is not None else 100,
"show_indexed": obj.get("show_indexed") if obj.get("show_indexed") is not None else False,
"show_user_mask": obj.get("show_user_mask") if obj.get("show_user_mask") is not None else False,
"resolution_ring": obj.get("resolution_ring") if obj.get("resolution_ring") is not None else 0.1
})
return _obj