chengkai3
76 lines
3.7 KiB
Python
76 lines
3.7 KiB
Python
from __future__ import annotations
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from datetime import datetime
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from typing import TYPE_CHECKING, Any
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from uuid import uuid4
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from sqlalchemy import JSON, Boolean, DateTime, Float, Index, Integer, String, Text
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from sqlalchemy.orm import Mapped, mapped_column, relationship
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from ..core.database import Base
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from .base import utcnow
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if TYPE_CHECKING:
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from .lightning_sample import LightningCurrentSample
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class LightningCurrentEvent(Base):
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__tablename__ = "lightning_current_event"
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__table_args__ = (
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Index("idx_lc_event_event_id", "event_id"),
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Index("idx_lc_event_time", "event_time"),
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Index("idx_lc_region", "region_id"),
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Index("idx_lc_location_tag", "location_tag"),
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Index("idx_lc_polarity", "polarity"),
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Index("idx_lc_wave_shape", "wave_shape"),
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Index("idx_lc_peak_abs", "peak_abs_current_ka"),
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Index("idx_lc_synthetic", "is_synthetic"),
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)
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id: Mapped[str] = mapped_column(String(32), primary_key=True, default=lambda: uuid4().hex)
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event_id: Mapped[str] = mapped_column(String(64), unique=True, nullable=False)
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source_file_name: Mapped[str | None] = mapped_column(String(255))
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event_time: Mapped[datetime | None] = mapped_column(DateTime(timezone=True), index=True)
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sample_count: Mapped[int] = mapped_column(Integer, default=0)
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sample_interval_us: Mapped[float | None] = mapped_column(Float)
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sampling_frequency_hz: Mapped[float | None] = mapped_column(Float)
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peak_current_ka: Mapped[float | None] = mapped_column(Float)
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peak_abs_current_ka: Mapped[float | None] = mapped_column(Float)
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wavefront_time_t1_us: Mapped[float | None] = mapped_column(Float)
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half_value_time_t2_us: Mapped[float | None] = mapped_column(Float)
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steepness_ka_per_us: Mapped[float | None] = mapped_column(Float)
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action_integral_j_ohm: Mapped[float | None] = mapped_column(Float)
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wave_shape: Mapped[str | None] = mapped_column(String(32), index=True)
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polarity: Mapped[str] = mapped_column(String(16), default="unknown", index=True)
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stroke_count: Mapped[int] = mapped_column(Integer, default=1)
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stroke_peaks_json: Mapped[list[dict[str, Any]]] = mapped_column(JSON, default=list)
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region_id: Mapped[str | None] = mapped_column(String(64), index=True)
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location_tag: Mapped[str | None] = mapped_column(String(255), index=True)
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city: Mapped[str | None] = mapped_column(String(128), index=True)
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longitude: Mapped[float | None] = mapped_column(Float)
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latitude: Mapped[float | None] = mapped_column(Float)
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altitude_m: Mapped[float | None] = mapped_column(Float)
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sensor_model: Mapped[str | None] = mapped_column(String(128))
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install_position: Mapped[str | None] = mapped_column(String(128))
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weather_level: Mapped[str | None] = mapped_column(String(64))
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pressure_hpa: Mapped[float | None] = mapped_column(Float)
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humidity_percent: Mapped[float | None] = mapped_column(Float)
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is_synthetic: Mapped[bool] = mapped_column(Boolean, default=False, index=True)
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feature_json: Mapped[dict[str, Any]] = mapped_column(JSON, default=dict)
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notes: Mapped[str | None] = mapped_column(Text)
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create_date: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=utcnow, index=True)
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create_user: Mapped[str | None] = mapped_column(String(64), index=True)
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update_date: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=utcnow, onupdate=utcnow)
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update_user: Mapped[str | None] = mapped_column(String(64), index=True)
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samples: Mapped[list[LightningCurrentSample]] = relationship(
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"LightningCurrentSample",
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back_populates="event",
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lazy="noload",
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cascade="all, delete-orphan",
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order_by="LightningCurrentSample.seq_no.asc()",
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)
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