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Is your feature request related to a problem? Please describe. GeoPandas.GeoSeries.distance computes row-wise (pair-wise) shortest distance between geometries of a row. This matches ST_Distance(geometric) requirement.
Describe the solution you'd like
With all type combination between distances, We need to group geoseries into 6 groups:
closes#759
This PR adds `geoseries.distance`, computing distances between two geoseries.
Benchmarking distance API is a complicated task. Below I present the benchmark of a simplest case: distance between a pair of point geoseries. geopandas is also quite fast when computing simple point distances, througput peaks at 1e5 and gets surpassed by cuspatial for larger data sizes. Both geopandas and cuspatial sees performance drop when dealing with index alignments.
![image](https://github.com/rapidsai/cuspatial/assets/13521008/dc0772f4-2b35-41da-883c-39ba4e731f6a)
TODO:
- [x] Support distance to a single shapely object.
- [x] Benchmark against geopandas.
Authors:
- Michael Wang (https://github.com/isVoid)
Approvers:
- Mark Harris (https://github.com/harrism)
- H. Thomson Comer (https://github.com/thomcom)
URL: #1231
Is your feature request related to a problem? Please describe.
GeoPandas.GeoSeries.distance
computes row-wise (pair-wise) shortest distance between geometries of a row. This matches ST_Distance(geometric) requirement.Describe the solution you'd like
With all type combination between distances, We need to group geoseries into 6 groups:
Dispatch each group to the pairwise_X_Y_distance function. Return the result by scattering the result to original index alignment.
Groupby is performed on a dataframe with the typecodes from the two operands as key, indices from the two operances as value.
Tasks
pairwise_distance(mixed_geometry_column lhs, mixed_geometry_column rhs)
support #1058The text was updated successfully, but these errors were encountered: