# Version 1.1.0

• Consolidated package colour helpers into a single palettes() function and removed hcas_color() and ref_density_color().
• Changed drop_features so excluded RS variables are removed from the active feature set before C++ distance calculations, instead of being zeroed in place.

# 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.

v0.2.0 release

Version 0.2.0

• Added drop_features parameter to fully exclude specific remote sensing variables from both the histogram and benchmark functions.
• Added a condition to ensure that k_obs is less than or equal to k_pred.
• A new histogram normalisation method has been implemented in R using the legacy = FALSE argument to mitigate edge effects.
• The zero-zero point (reference self-count) in the raw histogram is now excluded prior to normalisation.
• The histogram function arguments have changed to data and samples.

v0.1.6 release

Version 0.1.6

• Added a scale_factor parameter to allow user-defined correction of geographic CRS distance calculations, enhancing flexibility in handling distance conversions (previously set to a default value only).
• Enhanced C++ code for improved efficiency in point class creation.