leerho commented on PR #62:
URL: https://github.com/apache/datasketches-rust/pull/62#issuecomment-3770275536

   There is some documentation, but it is still sparse.
   
   From the [datasketches website](https://datasketches.apache.org), you can 
find under Code Docs [CPP 
5.2.0](https://apache.github.io/datasketches-cpp/5.2.0/) then 
[Namespaces/DensitySketch](https://apache.github.io/datasketches-cpp/5.2.0/classdatasketches_1_1density__sketch.html).
  Then scroll down to the Detailed Description.
   
   I have not used this sketch, but in many scientific areas it is important to 
understand the density at a point in an large algebraic field.
   
   This sketch is constructed with a value _k_, which controls the overall size 
and accuracy of the sketch, _dim_, the number of spacial dimensions, a _Kernel_ 
function, which does the work of identifying the density at a point in 
_dim-space_ within a _dim-sphere_ whose radial sensitivity is controlled by the 
_Kernal_ density function (A common one is Gaussian, but user can supply 
others), and finally an _Allocator_.
   
   The input is a stream of floating-point vectors of size _dim_.  A query is 
basically a _get_estimate(point)_ where the _point_ is a _dim_vector_.  Once 
the sketch reaches size k, it starts summarizing the field into a _core-set_ of 
points which approximates the most dense points in the field.   I would study 
some of the test cases for some simple examples and read the [Karnin & 
Liberty](https://proceedings.mlr.press/v99/karnin19a/karnin19a.pdf) paper.
   
   


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