API: the `geo_json_conformant` argument of `polygon_to_cells` is missing in v4

[Zeroto521]

uber/h3-py v3 polyfill has an argument called geo_json_conformant

https://github.com/uber/h3-py/blob/f8958ac788ea04e2b383c8b859f75a05c3fcb815/src/h3/api/_api_template.py#L495

But this argument is missing in uber/h3-py v4 polygon_to_cells

https://github.com/uber/h3-py/blob/3eece401ba311feeba99073eb65db2764ef85557/src/h3/api/_api_template.py#L400

But the document of uber/h3 v4 shows that geo_json_conformant is still in polygon_to_cells.

[mohit-at-delhivery]

Any updates on this? Also how can we get all h3 cells within a given polygon? Is it necessary to convert a normal polygon into an h3 polygon? if so an example would be really appreciated. I tried the following but it gives the error "Error: object of type 'Polygon' has no len()".

import h3 from shapely.geometry Polygon my_polygon = Polygon([(1, 0), (1, 1), (2, 1), (2, 0)]) h3.Polygon(my_polygon)

[ajfriend]

I'm working on the v4 interface here: https://github.com/uber/h3-py/pull/301

The major change is that we'll have functions like h3.geo_to_cells(geo, res) that can take in any object that implements a __geo_interface__, which should make it automatically compatible with many existing libraries like geopandas

[mohit-at-delhivery]

I am using v4 and I want to know the h3 cells contained within a shapely polygon. Currently how can we achieve this in v4, is there any work around for this? Please let me know.

[kamilmarwat]

I am using v4 and I want to know the h3 cells contained within a shapely polygon. Currently how can we achieve this in v4, is there any work around for this? Please let me know.

@mohit-at-delhivery by first creating a DataFrame with the h3-indexes given that the poly is a shapely Polygon and CRS is 4326

h3_filled_polygon = gpd.GeoDataFrame(
    data = list (
        h3.polygon_to_cells(
            h3.Polygon(poly.exterior.coords),
            res= 5,
        )),
    columns = ['h3']
)

Then create the polygon geometry

h3_filled_polygon['geometry']=h3_filled_polygon['h3'].apply(lambda x: shapely.Polygon(h3.cell_to_boundary(x)))

h3_filled_polygon = h3_filled_polygon.set_crs("4326")

but the problem with v4 is I am getting wrong shapes of the hex polygons. They are skewed, even when the projection is correct. So can't guarantee that.

[mohit-at-delhivery]

Hi @kamilmarwat .. the coordinates might be reversed if the grids are skewed?

Here is a solution that I found which is similar to yours

import h3
from shapely.wkt import loads
import folium

polygon_wkt = 'POLYGON((28.60651289028247 77.18724444355178, 28.614630596755424 77.21696054040207, 28.619245246847916 77.20519410779309, 28.622500481098306 77.1974097750062, 28.614460198648654 77.18849247015262, 28.60651289028247 77.18724444355178))'


# Convert Shapely polygon to h3.Polygon
shapely_polygon = loads(polygon_wkt)

# Get the exterior coordinates of the Shapely polygon
exterior_coords = list(shapely_polygon.exterior.coords)

# Convert the coordinates to H3 indexes
h3_indexes = [h3.latlng_to_cell(lat, lng, res=9) for lat, lng in exterior_coords]

# Convert H3 indexes back to coordinates
h3_coordinates = [h3.cell_to_latlng(h3_index) for h3_index in h3_indexes]

# Create an H3.Polygon from the H3 coordinates
h3_polygon = h3.Polygon(h3_coordinates)

cells = list(h3.polygon_to_cells(h3_polygon, res=9))

### Plotting the output
folium_map = folium.Map(location= [28.60651289028247, 77.18724444355178], zoom_start=14, control_scale=True)
folium.Polygon(loads(polygon_wkt).exterior.coords, color='red').add_to(folium_map)
for cell in cells:
    h3_polygons = h3.cells_to_polygons([cell])
    folium.Polygon(locations=h3_polygons[0].outer, 
                color='blue').add_to(folium_map)
folium_map

Also you can take one/two hop neighbour grids of all h3 grids in the "cells" variable as well just to make sure that no area of the polygon is left without an h3 grid.