A feature of K-squared is search API that can use the min/max values embedded in the quad-tree structure to search for cells with values within a given range. This is largely implemented in the Rust code, but it needs a small refactor in order to work for floating point numbers. Essentially something similar to what's being done with MMBuffers to adjust the user requested range for the number of fractional bits used in the fixed point representation in each local node of the graph. Once floating point datasets are implemented the API can be exposed in the Python layer as well.
A feature of K-squared is search API that can use the min/max values embedded in the quad-tree structure to search for cells with values within a given range. This is largely implemented in the Rust code, but it needs a small refactor in order to work for floating point numbers. Essentially something similar to what's being done with MMBuffers to adjust the user requested range for the number of fractional bits used in the fixed point representation in each local node of the graph. Once floating point datasets are implemented the API can be exposed in the Python layer as well.