Source code for sepal_ui.aoi.aoi_model

"""Model object dedicated to AOI selection."""

import json
from pathlib import Path
from typing import Dict, List, Optional, Tuple, Union

import ee
import geopandas as gpd
import pandas as pd
import pygadm
import pygaul
import traitlets as t
from ipyleaflet import GeoJSON
from typing_extensions import Self

from sepal_ui import color
from sepal_ui.frontend import styles as ss
from sepal_ui.message import ms
from sepal_ui.model import Model
from sepal_ui.scripts import gee
from sepal_ui.scripts import utils as su

__all__ = ["AoiModel"]


[docs] class AoiModel(Model): # ########################################################################### # ### dataset const ### # ########################################################################### MAPPING: Path = Path(__file__).parents[1] / "data" / "gaul_iso.json" "GAUL -> ISO-3 mapping of country code" ASSET_SUFFIX: str = "aoi_" "The suffix to identify the asset in GEE" # ########################################################################### # ### const methods ### # ########################################################################### CUSTOM: str = ms.aoi_sel.custom "The word displayed for custom method in the relevant lang" ADMIN: str = ms.aoi_sel.administrative "The word displayed for admin method in the relevant lang" METHODS: Dict[str, Dict[str, str]] = { "ADMIN0": {"name": ms.aoi_sel.adm[0], "type": ADMIN}, "ADMIN1": {"name": ms.aoi_sel.adm[1], "type": ADMIN}, "ADMIN2": {"name": ms.aoi_sel.adm[2], "type": ADMIN}, "SHAPE": {"name": ms.aoi_sel.vector, "type": CUSTOM}, "DRAW": {"name": ms.aoi_sel.draw, "type": CUSTOM}, "POINTS": {"name": ms.aoi_sel.points, "type": CUSTOM}, "ASSET": {"name": ms.aoi_sel.asset, "type": CUSTOM}, } "The word displayed for all selection methods in the relevant lang" # ########################################################################### # ### widget related traitlets ### # ########################################################################### method: t.Unicode = t.Unicode(None, allow_none=True).tag(sync=True) "str: the currently selected method" point_json: t.Dict = t.Dict(None, allow_none=True).tag(sync=True) "dict: information that will be use to transform the csv into a gdf" vector_json: t.Dict = t.Dict(None, allow_none=True).tag(sync=True) "dict: information that will be use to transform the vector file into a gdf" geo_json: t.Dict = t.Dict(None, allow_none=True).tag(sync=True) "dict: the drawn geojson shape" admin: t.Unicode = t.Unicode(None, allow_none=True).tag(sync=True) "The admin number selected" asset_name: t.Unicode = t.Unicode(None, allow_none=True).tag(sync=True) "The asset name (only for GEE model)" asset_json: t.Dict = t.Dict(None, allow_none=True).tag(sync=True) "The asset json description (only for GEE model)" name: t.Unicode = t.Unicode(None, allow_none=True).tag(sync=True) "The name of the file to create (used only in drawn shaped)" # ########################################################################### # ### model parameters ### # ########################################################################### gee: bool = True "either or not the model is bound to gee" folder: Union[str, Path] = "" "The folder name used in GEE related component, mainly used for debugging" default_vector: Optional[Union[str, Path]] = None "The default vector file that will be used to produce the gdf. need to be readable by fiona and/or GDAL/OGR" default_admin: Optional[str] = None "The default administrative area in GADM or GAUL norm" default_asset: Optional[str] = None "The default asset name, need to point to a readable FeatureCollection" # ########################################################################### # ### model outputs ### # ########################################################################### dst_asset_id: str = "" "The exported asset id" selected_feature: Optional[Union[ee.Feature, gpd.GeoDataFrame]] = None "The Feature associated with a query" gdf: Optional[gpd.GeoDataFrame] = None "The geodataframe corresponding to the selected AOI" feature_collection: Optional[ee.FeatureCollection] = None "The feature Collection generated by the parameters (only for GEE models)" ipygeojson: Optional[GeoJSON] = None "The representation of the AOI as a ipyleaflet layer"
[docs] def __init__( self, gee: bool = True, vector: Optional[Union[str, Path]] = None, asset: Optional[Union[str, Path]] = None, admin: Optional[str] = None, folder: Union[str, Path] = "", ) -> None: """An Model object dedicated to the sorage and the manipulation of aoi. It is meant to be used with the AoiView object (embedded in the AoiTile). By using this you will be able to provide your application with aoi as an ee_object or a gdf, depending if you activated the ee binding or not. The class also provide insight on your aoi geometry. Args: gee: whether or not the aoi selector should be using the EarthEngine binding vector: the path to the default vector object admin: the administrative code of the default selection. Need to be GADM if ee==False and GAUL 2015 if ee==True. asset: the default asset. Can only work if ee==True folder: the init GEE asset folder where the asset selector should start looking (debugging purpose) .. deprecated:: 2.3.2 'asset_name' will be used as variable to store 'ASSET' method info. To get the destination saved asset id, please use 'dst_asset_id' variable. """ super().__init__() # the ee retated information self.gee = gee if gee: su.init_ee() self.folder = str(folder) or ee.data.getAssetRoots()[0]["id"] # set default values self.set_default(vector, admin, asset)
[docs] def set_default( self, vector: Optional[Union[str, Path]] = None, admin: Optional[str] = None, asset: Optional[Union[str, Path]] = None, ) -> Self: """Set the default value of the object and create a gdf/feature_collection out of it. Args: vector: the default vector file that will be used to produce the gdf. need to be readable by fiona and/or GDAL/OGR admin: the default administrative area in GADM or GAUL norm asset: the default asset name, need to point to a readable FeatureCollection """ # save the default values self.default_vector = vector self.default_asset = self.asset_name = str(asset) if asset else None self.asset_json = ( {"pathname": asset, "column": "ALL", "value": None} if asset else None ) self.default_admin = self.admin = admin # cast the vector to json self.vector_json = ( {"pathname": str(vector), "column": "ALL", "value": None} if vector else None ) # cast the asset to json self.asset_json = ( {"pathname": asset, "column": "ALL", "value": None} if asset else None ) # set the default gdf if possible if self.vector_json is not None: self.set_object("SHAPE") elif self.admin: self.set_object("ADMIN0") # any level will work elif self.asset_json is not None: self.set_object("ASSET") return self
[docs] def set_object(self, method: str = "") -> Self: """Set the object (gdf/featurecollection) based on the model inputs. The method can be manually overwritten by setting the ``method`` parameter. Args: method: a model loading method """ # clear the model output if existing self.clear_output() # overwrite self.method self.method = method or self.method if self.method in ["ADMIN0", "ADMIN1", "ADMIN2"]: self._from_admin(self.admin) elif self.method == "POINTS": self._from_points(self.point_json) elif self.method == "SHAPE": self._from_vector(self.vector_json) elif self.method == "DRAW": self._from_geo_json(self.geo_json) elif self.method == "ASSET": self._from_asset(self.asset_json) else: raise Exception(ms.aoi_sel.exception.no_inputs) return self
def _from_asset(self, asset_json: dict) -> Self: """Set the ee.FeatureCollection output from an existing asset.""" if not (asset_json["pathname"]): raise Exception(ms.aoi_sel.exception.no_asset) if asset_json["column"] != "ALL": if asset_json["value"] is None: raise Exception(ms.aoi_sel.exception.no_value) # set the name self.name = Path(asset_json["pathname"]).stem.replace(self.ASSET_SUFFIX, "") self.asset_name = asset_json["pathname"] ee_col = ee.FeatureCollection(asset_json["pathname"]) if asset_json["column"] != "ALL": column = asset_json["column"] value = asset_json["value"] ee_col = ee_col.filterMetadata(column, "equals", value) self.name = f"{self.name}_{column}_{value}" # set the feature collection self.feature_collection = ee_col # create a gdf form the feature_collection features = self.feature_collection.getInfo()["features"] self.gdf = gpd.GeoDataFrame.from_features(features).set_crs(epsg=4326) return self def _from_points(self, point_json: dict) -> Self: """Set the object output from a csv json. Args: point_json: the geo_interface description of the points """ if not all(point_json.values()): raise Exception(ms.aoi_sel.exception.incomplete) # cast the pathname to pathlib Path point_file = Path(point_json["pathname"]) # check that the columns are well set values = [v for v in point_json.values()] if not len(values) == len(set(values)): raise Exception(ms.aoi_sel.exception.duplicate_key) # create the gdf df = pd.read_csv(point_file, sep=None, engine="python") self.gdf = gpd.GeoDataFrame( df, crs="EPSG:4326", geometry=gpd.points_from_xy( df[point_json["lng_column"]], df[point_json["lat_column"]] ), ) # set the name self.name = point_file.stem if self.gee: # transform the gdf to ee.FeatureCollection self.feature_collection = ee.FeatureCollection(self.gdf.__geo_interface__) # export as a GEE asset self.export_to_asset() return self def _from_vector(self, vector_json: dict) -> Self: """Set the object output from a vector json. Args: vector_json: the dict describing the vector file, and column filter """ if not (vector_json["pathname"]): raise Exception(ms.aoi_sel.exception.no_file) if vector_json["column"] != "ALL": if vector_json["value"] is None: raise Exception(ms.aoi_sel.exception.no_value) # cast the pathname to pathlib Path vector_file = Path(vector_json["pathname"]) # create the gdf self.gdf = gpd.read_file(vector_file).to_crs("EPSG:4326") # set the name using the file stem self.name = vector_file.stem # filter it if necessary if vector_json["value"] is not None: self.gdf = self.gdf[self.gdf[vector_json["column"]] == vector_json["value"]] self.name = f"{self.name}_{vector_json['column']}_{vector_json['value']}" if self.gee: # transform the gdf to ee.FeatureCollection self.feature_collection = su.geojson_to_ee(self.gdf.__geo_interface__) # export as a GEE asset self.export_to_asset() return self def _from_geo_json(self, geo_json: dict) -> Self: """Set the gdf output from a geo_json. Args: geo_json: the __geo_interface__ dict of a geometry drawn on the map """ if not geo_json: raise Exception(ms.aoi_sel.exception.no_draw) # remove the style property from geojson as it's not recognize by geopandas and gee for feat in geo_json["features"]: if "style" in feat["properties"]: del feat["properties"]["style"] # create the gdf self.gdf = gpd.GeoDataFrame.from_features(geo_json).set_crs(epsg=4326) # normalize the name self.name = su.normalize_str(self.name) if self.gee: # transform the gdf to ee.FeatureCollection self.feature_collection = su.geojson_to_ee(self.gdf.__geo_interface__) # export as a GEE asset self.export_to_asset() else: # save the geojson in downloads path = Path("~", "downloads", "aoi").expanduser() path.mkdir( exist_ok=True, parents=True ) # if nothing have been run the downloads folder doesn't exist self.gdf.to_file(path / f"{self.name}.geojson", driver="GeoJSON") return self def _from_admin(self, admin: str) -> Self: """Set the object according to the given an administrative code in the GADM/GAUL codes. Args: admin: the admin code corresponding to FAO GAUl (if gee) or GADM """ if not admin: raise Exception(ms.aoi_sel.exception.no_admlyr) # get the data from either the pygaul or the pygadm libs # pygaul needs extra work as ISO codes are not included in the GEE dataset if self.gee: self.feature_collection = pygaul.AdmItems(admin=admin) features = self.feature_collection.getInfo()["features"] self.gdf = gpd.GeoDataFrame.from_features(features).set_crs(epsg=4326) gaul_country = str(self.gdf.ADM0_CODE.unique()[0]) iso = json.loads(self.MAPPING.read_text())[gaul_country] self.gdf["ISO"] = iso else: self.gdf = pygadm.AdmItems(admin=admin) # generate the name from the columns r = self.gdf.iloc[0] names = [su.normalize_str(r[c]) for c in self.gdf.columns if "NAME" in c] names[0] = r.ISO if self.gee else r.GID_0[:3] self.name = "_".join(names) return self
[docs] def clear_output(self) -> Self: """Clear the output of the aoi selector without changing the traits and/or the parameters.""" # reset the outputs self.gdf = None self.feature_collection = None self.ipygeojson = None self.selected_feature = None self.dst_asset_id = None return self
[docs] def clear_attributes(self) -> Self: """Return all attributes to their default state. Note: Set the default setting as current object. """ # keep the default admin = self.default_admin vector = self.default_vector asset = self.default_asset # delete all the traits [setattr(self, attr, None) for attr in self.trait_names()] # reset the outputs self.clear_output() # reset the default self.set_default(vector, admin, asset) return self
[docs] def get_columns(self) -> List[str]: """Retrieve the columns or variables from self excluding geometries and gee index. Returns: sorted list of column names """ if self.gdf is None: raise Exception(ms.aoi_sel.exception.no_gdf) if self.gee: aoi_ee = ee.Feature(self.feature_collection.first()) columns = aoi_ee.propertyNames().getInfo() list_ = [ col for col in columns if col not in ["system:index", "Shape_Area"] ] else: list_ = list(set(["geometry"]) ^ set(self.gdf.columns.to_list())) return sorted(list_)
[docs] def get_fields(self, column: str) -> List[str]: """Retrieve the fields from a column. Args: A column name to query over the asset Returns: sorted list of fields value """ if self.gdf is None: raise Exception(ms.aoi_sel.exception.no_gdf) if self.gee: fields = self.feature_collection.distinct(column).aggregate_array(column) list_ = fields.getInfo() else: list_ = self.gdf[column].to_list() return sorted(list_)
[docs] def get_selected( self, column: str, field: str ) -> Union[ee.Feature, gpd.GeoDataFrame]: """Select an ee object based on selected column and field. Args: column: the selected column in the dataset field: the value to search in the selected column Returns: The Feature associated with the query """ if self.gdf is None: raise Exception(ms.aoi_sel.exception.no_gdf) if self.gee: selected_feature = self.feature_collection.filterMetadata( column, "equals", field ) else: selected_feature = self.gdf[self.gdf[column] == field] return selected_feature
[docs] def total_bounds(self) -> Tuple[float, float, float, float]: """Reproduce the behaviour of the total_bounds method from geopandas. Returns: minxx, miny, maxx, maxy """ if self.gdf is None: raise ValueError(ms.aoi_sel.exception.no_gdf) return self.gdf.total_bounds.tolist()
[docs] def export_to_asset(self) -> Self: """Export the feature_collection as an asset (only for ee model).""" asset_name = self.ASSET_SUFFIX + self.name asset_id = str(Path(self.folder, asset_name)) self.dst_asset_id = asset_id # check if the table already exist if asset_id in [a["name"] for a in gee.get_assets(self.folder)]: return self # check if the task is running if gee.is_running(asset_name): return self # run the task task_config = { "collection": self.feature_collection, "description": asset_name, "assetId": asset_id, } task = ee.batch.Export.table.toAsset(**task_config) task.start() return self
[docs] def get_ipygeojson(self, style: Optional[dict] = None) -> GeoJSON: """Converts current geopandas object into ipyleaflet GeoJSON. Args: style: the predefined style of the aoi. It's by default using a "success" ``sepal_ui.color`` with 0.5 transparent fill color. It can be completely replace by a fully qualified `style dictionary <https://ipyleaflet.readthedocs.io/en/latest/layers/geo_json.html>`__. Use the ``sepal_ui.color`` object to define any color to remain compatible with light and dark theme. Returns: The geojson layer of the aoi gdf, ready to use in a Map """ if self.gdf is None: raise Exception(ms.aoi_sel.exception.no_gdf) # read the data from geojson and add the name as a property of the shape # useful when handler are added from ipyleaflet data = json.loads(self.gdf.to_json()) for f in data["features"]: f["properties"]["name"] = self.name # adapt the style to the theme if style is None: style = json.loads((ss.JSON_DIR / "aoi.json").read_text()) style.update(color=color.primary, fillColor=color.primary) # create a GeoJSON object # attribution="SEPAL(c)" is not recognized yet # https://github.com/jupyter-widgets/ipyleaflet/issues/847 self.ipygeojson = GeoJSON(data=data, style=style, name="aoi") return self.ipygeojson