122 lines
2.8 KiB
Python
122 lines
2.8 KiB
Python
from __future__ import annotations
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from uuid import UUID
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from pydantic import BaseModel, Field
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from .operations import VectorSelectionBBox
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class ThematicRasterAcquireRequest(BaseModel):
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bbox: VectorSelectionBBox
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area_id: UUID | None = None
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product_key: str
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force_refresh: bool = False
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class ThematicRasterProductRead(BaseModel):
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key: str
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display_name: str
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theme: str
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metric_kind: str
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coverage_id: str
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native_resolution_m: float
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source_crs: str
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source_value_unit: str
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observation_year: int
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source_version: str
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catalog_url: str
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attribution: str
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license_note: str
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legend_min_label: str
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legend_max_label: str
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included_source_values: list[int]
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limitation_message: str
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analysis_resolution_m: float | None = None
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coverage_zones: list[str] = Field(default_factory=list)
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configured: bool = True
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status: str = "configured"
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class WalousAcquisitionResult(BaseModel):
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output_dataset_id: UUID
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reused: bool
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provider: str
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product_key: str
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display_name: str
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theme: str
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metric_kind: str
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resolution_m: float
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width: int
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height: int
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valid_pixel_count: int
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bbox_epsg4326: list[float]
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bbox_epsg3812: list[float]
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observation_year: int
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source_value_unit: str
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attribution: str
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limitation_message: str
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class ThematicRasterAcquisitionResult(BaseModel):
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output_dataset_id: UUID
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reused: bool
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provider: str
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product_key: str
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display_name: str
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theme: str
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metric_kind: str
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coverage_id: str
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resolution_m: float
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width: int
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height: int
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valid_pixel_count: int
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bbox_epsg4326: list[float]
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bbox_epsg31370: list[float]
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observation_year: int
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source_value_unit: str
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attribution: str
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limitation_message: str
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class ThematicRasterSelectionRequest(BaseModel):
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bbox: VectorSelectionBBox
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area_id: UUID | None = None
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class ThematicRasterMetric(BaseModel):
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metric_key: str
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metric_label: str
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metric_value: float
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metric_unit: str
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aggregation_method: str
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derived: bool = True
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is_estimate: bool = True
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class ThematicRasterSelectionSummary(BaseModel):
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metric_label: str
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metric_value: float
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metric_unit: str
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aggregation_method: str
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primary_metric_key: str
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metrics: list[ThematicRasterMetric]
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class ThematicRasterSelectionResponse(BaseModel):
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dataset_id: UUID
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product_key: str
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theme: str
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metric_kind: str
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selection_bbox: VectorSelectionBBox
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selection_area_id: UUID | None = None
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selected_cell_count: int
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valid_cell_count: int
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coverage_ratio: float
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resolution_m: float
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observation_year: int
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summary: ThematicRasterSelectionSummary
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unsupported_metrics: list[str]
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limitation_message: str
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generated_at: str
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