# Version 1.0.0

• Renamed the reference density function to ref_density(), renamed the radial counting function (from proximity()) to radial_count(), and changed the reference density object class to reference_density.
• The order of input data has completely changed and both ref_density() and benchmark() functions require data with x, y, predicted, and observed remote sensing variable order.
• Complete re-write of the main C++ functions (for ref_density(), benchmark(), and radial_count()) using vectorised operations, including changing feature space distance calculations from double to float32, resulting in significant speed improvement (~10x) with no loss of accuracy.
• The Eigen C++ library is adapted as the main matrix engine.
• The dependency on KDtrees is dropped while keeping or even improving the speed.
• The reference density now performs only one-way pairwise distance calculations. As a result, the raw reference density values are exactly halved compared to before. This has no impact on the normalised reference density or the final output.
• The "corner value" in the reference density (previously calculated as the count of values) is no longer computed, since it is simply equal to the number of samples.
• The calibrate() function no longer performs interpolation. The output is now fully fitted using a monotonic spline.
• A fast spatial distance calculation is implemented (no difference for projected CRS with 0.01 meters accuracy).
• The geographic distance for lat/long is now corrected for the latitude of the source cell, not just the radius transformation to degrees.
• A new function (tiling()) is added for making raster tiles using raster or matrix data.
• The NaN pixels are now directly handled within C++ code.
• Expanded the test suite with additional C++-focused coverage, including edge cases and thread-consistency checks for core workflows.