Webb21 sep. 2024 · Signature: trimesh.creation.triangulate_polygon( polygon, triangle_args=None, engine=None, **kwargs, ) Docstring: Given a shapely polygon create a triangulation using a python interface to `triangle.c` or mapbox-earcut. > pip install triangle > pip install mapbox_earcut Parameters ----- polygon : Shapely.geometry.Polygon … Webb17 mars 2024 · P = Polygon (L) Now, it might seem that L is redundant since the last point is the same as the first one. But that's actually not a problem since Shapely would …
python - Smoothing polygons in contour map? - Geographic …
WebbSorted by: 6. Here is some Python code that does what you want. First, building the alpha shape (see my previous answer ): def alpha_shape (points, alpha, only_outer=True): """ Compute the alpha shape (concave hull) of a set of points. :param points: np.array of shape (n,2) points. :param alpha: alpha value. :param only_outer: boolean value to ... WebbTogether with the newer syntax provided by shapely, avoiding partial, the working snippet looks like this: project = pyproj.Transformer.from_proj ( pyproj.Proj ('epsg:4326'), # source coordinate system pyproj.Proj ('epsg:3857'), always_xy=True ) # destination coordinate system transform (project.transform, polygon) To be honest, even after ... fnx maintenance schedule
How to use the shapely.geometry.LineString function in shapely
Webb30 jan. 2024 · Shapely itself is not multithreaded, but its functions generally allow for multithreading by releasing the Global Interpreter Lock (GIL) during execution. Normally in Python, the GIL prevents multiple threads from computing at the same time. Webb22 dec. 2014 · While shapely doesn't natively understand coordinate systems, shapely.ops.transform () can do that along with pyproj. If pyproj.Proj can understand your both of your coordinate systems, then it can be made into a function that shapely can transform with. From the shapely docs: pyproj >= 2.1.0 Webb12 nov. 2024 · import geopandas as gpd from shapely.geometry import Polygon, MultiPolygon def groupby_multipoly (df, by, aggfunc="first"): data = df.drop (labels=df.geometry.name, axis=1) aggregated_data = data.groupby (by=by).agg (aggfunc) # Process spatial component def merge_geometries (block): return MultiPolygon … green whatchoo talkin\u0027 bout