21 dggridtest

In [1]:

from dggrid4py import tool, DGGRIDv8

# create an initial instance that knows where the dggrid tool lives, configure temp workspace and log/stdout output
# if you have 

dggrid_exec = tool.get_portable_executable(".")

dggrid_instance = DGGRIDv8(
    executable=dggrid_exec,
    working_dir=".",
    capture_logs=True,
    silent=True,
    has_gdal=False,
    tmp_geo_out_legacy=True,
    debug=False,
)

import geopandas
import shapely
points = [shapely.Point(20.5, 57.5), shapely.Point(21.0, 58.0)]
geodf_points_wgs84 = geopandas.GeoDataFrame({'name': ['A', 'B']}, geometry=points, crs='EPSG:4326')
gdf4 = dggrid_instance.cells_for_geo_points(geodf_points_wgs84, True,'IGEO7', 20, 
                                            output_address_type='Z7')
                                            # output_address_type='HIERNDX',
                                            # output_hier_ndx_system='Z3', output_hier_ndx_form ='DIGIT_STRING')
print(gdf4.head())


# global ISEA4T grid at resolution 5 into GeoDataFrame to Shapefile
# gdf1 = dggrid_instance.grid_cell_polygons_for_extent('ISEA3H', 0, split_dateline=True)
# gdf1 = gdf1.set_crs("EPSG:4326")      # or gdf1.set_crs(4326)
# print(gdf1.head())
    # gdf1.to_file('isea4t_5.geojson')
# gdf_centroids = dggrid_instance.grid_cell_centroids_for_extent(dggs_type='ISEA7H', resolution=4, mixed_aperture_level=None, clip_geom=None)

# # clip extent
# clip_bound = shapely.geometry.box(20.2,57.00, 28.4,60.0)

# # ISEA7H grid at resolution 9, for extent of provided WGS84 rectangle into GeoDataFrame to Shapefile
# gdf3 = dggrid_instance.grid_cell_polygons_for_extent('ISEA7H', 9, clip_geom=clip_bound)
# print(gdf3.head())
# gdf3.to_file('grids/est_shape_isea7h_9.shp')

# # generate cell and areal statistics for a ISEA7H grids from resolution 0 to 8 (return a pandas DataFrame)
# df1 = dggrid_instance.grid_stats_table('ISEA7H', 8)
# print(df1.head(8))
# df1.to_csv('isea7h_8_stats.csv', index=False)

# # generate the DGGS grid cells that would cover a GeoDataFrame of points, return Polygons with cell IDs as GeoDataFrame
# points = [shapely.Point(20.5, 57.5), shapely.Point(21.0, 58.0)]
# geodf_points_wgs84 = geopandas.GeoDataFrame({'name': ['A', 'B']}, geometry=points, crs='EPSG:4326')
# gdf4 = dggrid_instance.cells_for_geo_points(geodf_points_wgs84, False, 'ISEA7H', 5)
# print(gdf4.head())
# gdf4.to_file('polycells_from_points_isea7h_5.shp')

# # generate the DGGS grid cells that would cover a GeoDataFrame of points, return cell IDs added as column to the points GDF
# gdf5 = dggrid_instance.cells_for_geo_points(geodf_points_wgs84=geodf_points_wgs84, cell_ids_only=True, dggs_type='ISEA4H', resolution=8)
# print(gdf5.head())
# gdf5.to_file('geopoint_cellids_from_points_isea4h_8.shp')

# # generate DGGS grid cell polygons based on 'cell_id_list' (a list or np.array of provided cell_ids)
# gdf6 = dggrid_instance.grid_cell_polygons_from_cellids(cell_id_list=[1, 4, 8], dggs_type='ISEA7H', resolution=5)
# print(gdf6.head())
# gdf6.to_file('from_seqnums_isea7h_5.shp')

# # v0.2.6 API update split at dateline for cartesian GIS tools
# gdf7 = dggrid_instance.grid_cell_polygons_for_extent('ISEA7H', 3, split_dateline=True)
# gdf7.to_file('global_isea7h_3_interrupted.shp')

# gdf_z1 = dggrid_instance.grid_cell_polygons_for_extent('IGEO7', 5, clip_geom=clip_bound, output_address_type='Z7_STRING')
# print(gdf_z1.head(3))

# df_z1 = dggrid_instance.guess_zstr_resolution(gdf_z1['name'].values, 'IGEO7', input_address_type='Z7_STRING')
# print(df_z1.head(3))

# df_q2di = dggrid_instance.address_transform(gdf_z1['name'].values, 'IGEO7', 5, input_address_type='Z7_STRING', output_address_type='Q2DI')
# print(df_q2di.head(3))

# df_tri = dggrid_instance.address_transform(gdf_z1['name'].values, 'IGEO7', 5, input_address_type='Z7_STRING', output_address_type='PROJTRI')
# print(df_tri.head(3))

from dggrid4py import tool, DGGRIDv8 # create an initial instance that knows where the dggrid tool lives, configure temp workspace and log/stdout output # if you have dggrid_exec = tool.get_portable_executable(".") dggrid_instance = DGGRIDv8( executable=dggrid_exec, working_dir=".", capture_logs=True, silent=True, has_gdal=False, tmp_geo_out_legacy=True, debug=False, ) import geopandas import shapely points = [shapely.Point(20.5, 57.5), shapely.Point(21.0, 58.0)] geodf_points_wgs84 = geopandas.GeoDataFrame({'name': ['A', 'B']}, geometry=points, crs='EPSG:4326') gdf4 = dggrid_instance.cells_for_geo_points(geodf_points_wgs84, True,'IGEO7', 20, output_address_type='Z7') # output_address_type='HIERNDX', # output_hier_ndx_system='Z3', output_hier_ndx_form ='DIGIT_STRING') print(gdf4.head()) # global ISEA4T grid at resolution 5 into GeoDataFrame to Shapefile # gdf1 = dggrid_instance.grid_cell_polygons_for_extent('ISEA3H', 0, split_dateline=True) # gdf1 = gdf1.set_crs("EPSG:4326") # or gdf1.set_crs(4326) # print(gdf1.head()) # gdf1.to_file('isea4t_5.geojson') # gdf_centroids = dggrid_instance.grid_cell_centroids_for_extent(dggs_type='ISEA7H', resolution=4, mixed_aperture_level=None, clip_geom=None) # # clip extent # clip_bound = shapely.geometry.box(20.2,57.00, 28.4,60.0) # # ISEA7H grid at resolution 9, for extent of provided WGS84 rectangle into GeoDataFrame to Shapefile # gdf3 = dggrid_instance.grid_cell_polygons_for_extent('ISEA7H', 9, clip_geom=clip_bound) # print(gdf3.head()) # gdf3.to_file('grids/est_shape_isea7h_9.shp') # # generate cell and areal statistics for a ISEA7H grids from resolution 0 to 8 (return a pandas DataFrame) # df1 = dggrid_instance.grid_stats_table('ISEA7H', 8) # print(df1.head(8)) # df1.to_csv('isea7h_8_stats.csv', index=False) # # generate the DGGS grid cells that would cover a GeoDataFrame of points, return Polygons with cell IDs as GeoDataFrame # points = [shapely.Point(20.5, 57.5), shapely.Point(21.0, 58.0)] # geodf_points_wgs84 = geopandas.GeoDataFrame({'name': ['A', 'B']}, geometry=points, crs='EPSG:4326') # gdf4 = dggrid_instance.cells_for_geo_points(geodf_points_wgs84, False, 'ISEA7H', 5) # print(gdf4.head()) # gdf4.to_file('polycells_from_points_isea7h_5.shp') # # generate the DGGS grid cells that would cover a GeoDataFrame of points, return cell IDs added as column to the points GDF # gdf5 = dggrid_instance.cells_for_geo_points(geodf_points_wgs84=geodf_points_wgs84, cell_ids_only=True, dggs_type='ISEA4H', resolution=8) # print(gdf5.head()) # gdf5.to_file('geopoint_cellids_from_points_isea4h_8.shp') # # generate DGGS grid cell polygons based on 'cell_id_list' (a list or np.array of provided cell_ids) # gdf6 = dggrid_instance.grid_cell_polygons_from_cellids(cell_id_list=[1, 4, 8], dggs_type='ISEA7H', resolution=5) # print(gdf6.head()) # gdf6.to_file('from_seqnums_isea7h_5.shp') # # v0.2.6 API update split at dateline for cartesian GIS tools # gdf7 = dggrid_instance.grid_cell_polygons_for_extent('ISEA7H', 3, split_dateline=True) # gdf7.to_file('global_isea7h_3_interrupted.shp') # gdf_z1 = dggrid_instance.grid_cell_polygons_for_extent('IGEO7', 5, clip_geom=clip_bound, output_address_type='Z7_STRING') # print(gdf_z1.head(3)) # df_z1 = dggrid_instance.guess_zstr_resolution(gdf_z1['name'].values, 'IGEO7', input_address_type='Z7_STRING') # print(df_z1.head(3)) # df_q2di = dggrid_instance.address_transform(gdf_z1['name'].values, 'IGEO7', 5, input_address_type='Z7_STRING', output_address_type='Q2DI') # print(df_q2di.head(3)) # df_tri = dggrid_instance.address_transform(gdf_z1['name'].values, 'IGEO7', 5, input_address_type='Z7_STRING', output_address_type='PROJTRI') # print(df_tri.head(3))

                 name           geometry   lon   lat
0  244146921975218925  POINT (20.5 57.5)  20.5  57.5
1  244880873744371191      POINT (21 58)  21.0  58.0