161 lines
8.0 KiB
Python
161 lines
8.0 KiB
Python
# coding: utf-8
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"""
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Jungfraujoch
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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.
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The version of the OpenAPI document: 1.0.0-rc.23
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Contact: filip.leonarski@psi.ch
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Generated by OpenAPI Generator (https://openapi-generator.tech)
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Do not edit the class manually.
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""" # noqa: E501
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from __future__ import annotations
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import pprint
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import re # noqa: F401
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import json
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from pydantic import BaseModel, ConfigDict
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from typing import Any, ClassVar, Dict, List, Optional
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from jfjoch_client.models.broker_status import BrokerStatus
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from jfjoch_client.models.calibration_statistics_inner import CalibrationStatisticsInner
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from jfjoch_client.models.detector_list import DetectorList
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from jfjoch_client.models.detector_settings import DetectorSettings
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from jfjoch_client.models.detector_status import DetectorStatus
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from jfjoch_client.models.fpga_status_inner import FpgaStatusInner
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from jfjoch_client.models.image_format_settings import ImageFormatSettings
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from jfjoch_client.models.instrument_metadata import InstrumentMetadata
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from jfjoch_client.models.measurement_statistics import MeasurementStatistics
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from jfjoch_client.models.spot_finding_settings import SpotFindingSettings
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from jfjoch_client.models.zeromq_preview_settings import ZeromqPreviewSettings
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from typing import Optional, Set
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from typing_extensions import Self
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class JfjochStatistics(BaseModel):
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"""
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Pool statistics for Jungfraujoch to reduce transfers between frontend and jfjoch_broker
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""" # noqa: E501
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detector: Optional[DetectorStatus] = None
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detector_list: Optional[DetectorList] = None
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detector_settings: Optional[DetectorSettings] = None
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image_format_settings: Optional[ImageFormatSettings] = None
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instrument_metadata: Optional[InstrumentMetadata] = None
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data_processing_settings: Optional[SpotFindingSettings] = None
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measurement: Optional[MeasurementStatistics] = None
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broker: Optional[BrokerStatus] = None
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fpga: Optional[List[FpgaStatusInner]] = None
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calibration: Optional[List[CalibrationStatisticsInner]] = None
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zeromq_preview: Optional[ZeromqPreviewSettings] = None
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__properties: ClassVar[List[str]] = ["detector", "detector_list", "detector_settings", "image_format_settings", "instrument_metadata", "data_processing_settings", "measurement", "broker", "fpga", "calibration", "zeromq_preview"]
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model_config = ConfigDict(
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populate_by_name=True,
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validate_assignment=True,
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protected_namespaces=(),
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)
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def to_str(self) -> str:
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"""Returns the string representation of the model using alias"""
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return pprint.pformat(self.model_dump(by_alias=True))
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def to_json(self) -> str:
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"""Returns the JSON representation of the model using alias"""
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# TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead
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return json.dumps(self.to_dict())
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@classmethod
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def from_json(cls, json_str: str) -> Optional[Self]:
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"""Create an instance of JfjochStatistics from a JSON string"""
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return cls.from_dict(json.loads(json_str))
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def to_dict(self) -> Dict[str, Any]:
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"""Return the dictionary representation of the model using alias.
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This has the following differences from calling pydantic's
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`self.model_dump(by_alias=True)`:
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* `None` is only added to the output dict for nullable fields that
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were set at model initialization. Other fields with value `None`
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are ignored.
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"""
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excluded_fields: Set[str] = set([
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])
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_dict = self.model_dump(
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by_alias=True,
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exclude=excluded_fields,
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exclude_none=True,
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)
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# override the default output from pydantic by calling `to_dict()` of detector
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if self.detector:
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_dict['detector'] = self.detector.to_dict()
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# override the default output from pydantic by calling `to_dict()` of detector_list
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if self.detector_list:
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_dict['detector_list'] = self.detector_list.to_dict()
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# override the default output from pydantic by calling `to_dict()` of detector_settings
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if self.detector_settings:
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_dict['detector_settings'] = self.detector_settings.to_dict()
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# override the default output from pydantic by calling `to_dict()` of image_format_settings
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if self.image_format_settings:
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_dict['image_format_settings'] = self.image_format_settings.to_dict()
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# override the default output from pydantic by calling `to_dict()` of instrument_metadata
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if self.instrument_metadata:
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_dict['instrument_metadata'] = self.instrument_metadata.to_dict()
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# override the default output from pydantic by calling `to_dict()` of data_processing_settings
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if self.data_processing_settings:
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_dict['data_processing_settings'] = self.data_processing_settings.to_dict()
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# override the default output from pydantic by calling `to_dict()` of measurement
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if self.measurement:
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_dict['measurement'] = self.measurement.to_dict()
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# override the default output from pydantic by calling `to_dict()` of broker
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if self.broker:
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_dict['broker'] = self.broker.to_dict()
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# override the default output from pydantic by calling `to_dict()` of each item in fpga (list)
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_items = []
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if self.fpga:
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for _item_fpga in self.fpga:
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if _item_fpga:
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_items.append(_item_fpga.to_dict())
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_dict['fpga'] = _items
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# override the default output from pydantic by calling `to_dict()` of each item in calibration (list)
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_items = []
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if self.calibration:
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for _item_calibration in self.calibration:
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if _item_calibration:
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_items.append(_item_calibration.to_dict())
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_dict['calibration'] = _items
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# override the default output from pydantic by calling `to_dict()` of zeromq_preview
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if self.zeromq_preview:
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_dict['zeromq_preview'] = self.zeromq_preview.to_dict()
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return _dict
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@classmethod
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def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
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"""Create an instance of JfjochStatistics from a dict"""
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if obj is None:
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return None
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if not isinstance(obj, dict):
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return cls.model_validate(obj)
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_obj = cls.model_validate({
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"detector": DetectorStatus.from_dict(obj["detector"]) if obj.get("detector") is not None else None,
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"detector_list": DetectorList.from_dict(obj["detector_list"]) if obj.get("detector_list") is not None else None,
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"detector_settings": DetectorSettings.from_dict(obj["detector_settings"]) if obj.get("detector_settings") is not None else None,
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"image_format_settings": ImageFormatSettings.from_dict(obj["image_format_settings"]) if obj.get("image_format_settings") is not None else None,
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"instrument_metadata": InstrumentMetadata.from_dict(obj["instrument_metadata"]) if obj.get("instrument_metadata") is not None else None,
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"data_processing_settings": SpotFindingSettings.from_dict(obj["data_processing_settings"]) if obj.get("data_processing_settings") is not None else None,
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"measurement": MeasurementStatistics.from_dict(obj["measurement"]) if obj.get("measurement") is not None else None,
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"broker": BrokerStatus.from_dict(obj["broker"]) if obj.get("broker") is not None else None,
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"fpga": [FpgaStatusInner.from_dict(_item) for _item in obj["fpga"]] if obj.get("fpga") is not None else None,
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"calibration": [CalibrationStatisticsInner.from_dict(_item) for _item in obj["calibration"]] if obj.get("calibration") is not None else None,
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"zeromq_preview": ZeromqPreviewSettings.from_dict(obj["zeromq_preview"]) if obj.get("zeromq_preview") is not None else None
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})
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return _obj
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