How to use the arcgis.geometry.filters.intersects function in arcgis

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github ngageoint / state-of-the-data / state-of-the-data-for-webgis / sotd_indicators / Indicator.py View on Github external
# Negative Buffer Used to Avoid Selecting More Than 1 Cell
            sp_filter = filters.intersects(
                Geometry(row[1].SHAPE).buffer(-.1),
                self.grid_wkid
            )

            if not indicator_url:
                df_current = SpatialDataFrame(
                    columns=field_schema.get(indicator),
                    geometry=[Geometry(json.loads(row[1].SHAPE.JSON))]
                )
                created = True

            else:
                # Negative Buffer to Select a Single Grid Cell
                sp_filter = filters.intersects(
                    Geometry(row[1].SHAPE).buffer(-.1),
                    self.grid_wkid
                )
                df_current = data_fl.query(geometry_filter=sp_filter,
                                           return_all_records=self.return_all_records).df

            # Set The First Instance
            if idx == 0:

                # Check If Cell Found in Target Indicator Layer
                if df_current.empty:

                    # Use Grid SDF Row Geom to Insert Empty Record for Target Indicator
                    data_fl.edit_features(adds=[
                        {
                            'attributes': {},
github ngageoint / state-of-the-data / state-of-the-data-for-webgis / sotd_indicators / Indicator.py View on Github external
def set_features(self):

        df_list = []

        for idx, row in enumerate(self.grid_sdf.iterrows()):#self.grid_sdf.iterrows()):

            geom = Geometry(row[1].SHAPE)

            print(idx)

            sp_filter = filters.intersects(geom, self.grid_wkid)

            data_fl = FeatureLayer(url=self.feat_url, gis=self.gis_conn)

            ## Change return all records to True
            df_list.append(
                data_fl.query(geometry_filter=sp_filter,
                              return_all_records=self.return_all_records).df
            )

        self.features = df_list