diff --git a/cdr_schemas/cdr_responses/prospectivity.py b/cdr_schemas/cdr_responses/prospectivity.py index bccb40c..688ed1e 100644 --- a/cdr_schemas/cdr_responses/prospectivity.py +++ b/cdr_schemas/cdr_responses/prospectivity.py @@ -1,11 +1,13 @@ from datetime import datetime from typing import List, Union +from geojson_pydantic import LineString, Point, Polygon from pydantic import BaseModel, ConfigDict, Field from cdr_schemas.prospectivity_input import ( CreateCriticalMineralAssessment, CreateDataSource, + DataTypeId, TranformMethods, ) from cdr_schemas.prospectivity_models import NeuralNetUserOptions, SOMTrainConfig @@ -26,8 +28,35 @@ class CreateProcessDataLayer(BaseModel): data_source: DataSource = Field(description="Data source to create this layer") title: str = Field(description="Title to use for processed layer") transform_methods: TranformMethods = Field( - default="", description="Transformation method used" + default_factory=list, description="Transformation method used" ) + label_raster: bool = Field(description="A label layer for training") + + +class DataTypeIdWithGeom(DataTypeId): + geom: Point | LineString | Polygon = Field(description="Adding feature coords") + + +class CreateVectorProcessDataLayer(BaseModel): + label_raster: bool = Field( + default=False, description="Layer used to train prospectivity models" + ) + title: str = Field(description="Title to use for processed layer") + evidence_features: List[DataTypeIdWithGeom] = Field( + default_factory=list, description="Feature ids from the cdr" + ) + extra_geometries: List[Point | LineString | Polygon] = Field( + default_factory=list, + description="site locations selected by expert. Use EPSG:4326 only", + ) + transform_methods: TranformMethods = Field( + default_factory=list, description="Transformation method used" + ) + + +class ProcessedDataLayer(BaseModel): + layer_id: str = Field(description="Layer id") + download_url: str = Field(description="Download url") class ProspectModelMetaData(BaseModel): @@ -40,6 +69,22 @@ class ProspectModelMetaData(BaseModel): cma: CriticalMineralAssessment = Field(description="CMA info") model_type: str train_config: Union[SOMTrainConfig, NeuralNetUserOptions] - evidence_layers: List[CreateProcessDataLayer] + evidence_layers: List[ProcessedDataLayer] = Field( + description="Processed data layer ids." + ) + + model_config = ConfigDict(protected_namespaces=()) + + +class ProcessDataLayers(BaseModel): + cma: CriticalMineralAssessment = Field(description="CMA info") + + evidence_layers: List[CreateProcessDataLayer] = Field( + default_factory=list, description="Datasource and preprocess steps" + ) + vector_layers: List[CreateVectorProcessDataLayer] = Field( + default_factory=list, + description="Vector features and preprocess steps. EPSG:4326", + ) model_config = ConfigDict(protected_namespaces=()) diff --git a/cdr_schemas/prospectivity_input.py b/cdr_schemas/prospectivity_input.py index ffe161f..659ee63 100644 --- a/cdr_schemas/prospectivity_input.py +++ b/cdr_schemas/prospectivity_input.py @@ -2,7 +2,7 @@ from enum import Enum from typing import List, Optional, Union -from geojson_pydantic import MultiPolygon +from geojson_pydantic import LineString, MultiPolygon, Point, Polygon from pydantic import BaseModel, ConfigDict, Field from cdr_schemas.prospectivity_models import ( @@ -102,32 +102,73 @@ class CreateCriticalMineralAssessment(BaseModel): # MTRI UI TO CDR: # define preprocessing actions class DefineProcessDataLayer(BaseModel): - cma_id: str = Field(description="ID of the cma") - data_source_id: str = Field(description="Data source id used to create this layer") + data_source_id: str = Field( + description="Processed data source id used to create this layer" + ) title: str = Field(description="Title to use for processed layer") transform_methods: TranformMethods = Field( default_factory=list, description="Transformation method used" ) + label_raster: bool = Field( + default=False, description="Layer used to train prospectivity models" + ) # TA3 TO CDR: # Send along with a processed data layer used for training to support their model output. # TA3 can send each layer of the training stack used to generate the output one layer at a time + + +class RawDataType(str, Enum): + MINERAL_SITE = "mineral_site" + POINT = "point" + LINE = "line" + POLYGON = "polygon" + TIF = "tif" + VECTOR = "vector" + + +class DataTypeId(BaseModel): + raw_data_type: RawDataType = Field(description="Type of feature.") + id: str = Field(description="Id of feature in cdr") + + class SaveProcessedDataLayer(BaseModel): - model_run_id: str = Field( - description="Connect this processed data layer to a model run output layer" - ) - data_source_id: str = Field(description="Data source id used to create this layer") cma_id: str = Field(description="ID of the cma") - title: str = Field(description="Title for processed layer") + title: str = Field(description="Title of processed layer") + label_raster: bool = Field( + default=False, description="Layer used to train prospectivity models" + ) + raw_data_info: List[DataTypeId] = Field( + default_factory=list, description="cdr ids and types of all features used" + ) + extra_geometries: List = Field( + default_factory=list, description="Extra geometries used to create this layer" + ) system: str system_version: str transform_methods: TranformMethods = Field( - default="", description="Transformation method used" + default_factory=list, description="Transformation methods used" ) model_config = ConfigDict(protected_namespaces=()) +class DefineVectorProcessDataLayer(BaseModel): + label_raster: bool = Field( + default=False, description="Layer used to train prospectivity models" + ) + title: str = Field(description="Title to use for processed layer") + evidence_features: List[DataTypeId] = Field( + default_factory=list, description="cdr ids and types of all features used" + ) + extra_geometries: List[Point | LineString | Polygon] = Field( + default_factory=list, description="Extra geometries to be used" + ) + transform_methods: TranformMethods = Field( + default_factory=list, description="Transformation methods used" + ) + + # MTRI UI to CDR: # defines the cma, model training config and layer preprocessing steps class CreateProspectModelMetaData(BaseModel): @@ -139,9 +180,28 @@ class CreateProspectModelMetaData(BaseModel): organization: str = "" model_type: str train_config: Union[SOMTrainConfig, NeuralNetUserOptions] + evidence_layers: List[str] = Field( + description="List of ids of processed data layers" + ) + + model_config = ConfigDict(protected_namespaces=()) + + +# MTRI UI to CDR: +# defines the layer preprocessing steps +class CreateProcressDataLayers(BaseModel): + cma_id: str = Field(description="CMA id") + system: str + 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