v6.0.0-alpha.1

Almost a year in the making and counting, Kiddo v6 is effectively a full rewrite, addressing some
long-standing issues.

• V6 represents a fundamental shift to a unified single KdTree struct, replacing the previous
  mutable/immutable and float/fixed splits. The need for separate mutable / immutable trees has
  been removed by introducing the LeafStrategy trait, which the KdTree has as a generic parameter.
  LeafStrategies can be mutable or immutable.
• KdTree is also now generic over the new StemStrategy trait too. The combination of these two
  orthogonal traits allow experimentation and selection of alternative stem layouts and traversal
  mechanisms, alongside configurable leaf strategies, for performance experimentation.
• The query API has been refactored from a handful of separate methods that were not particularly
  cohesive into a single unified fluent builder API. The builder approach is much more orthogonal,
  and protects against breaking changes when new options are introduced in the future. It permits
  constraints to be encoded in the type system for impossible option combinations, prevents the need
  for as many methods that differ only by some combination of features; allowing for configurable
  result type projection, query types, and query configurations with defaults that match the v5-era
  separate methods.
• Some of the other new features added include configurable boundary-inclusivity, periodic boundary
  conditions, the within_unsorted_visit result mode to avoid materialization of results, TryFrom
  for converting between different KdTree types, new_from_source, and replace_item.
• Distance metric coverage has also been expanded and tidied up, including the addition of Chebyshev
  Minkowski, and Dot Product metrics and support for queries whose result type is wider than the
  stored coordinate type, which is especially important for fixed-point trees.
• With regard to the Stem Strategy trait system, alongside the Eytzinger ordering from v5 and prior
  is still available but now supports configurable prefetch behaviour. I've introduced the new
  Donnelly stem ordering via a family of stem strategies, featuring configurable pre-fetch and block size,
  unrolled traversal, SIMD descent, and full SIMD pruning and backtracking variants. The SIMD variant
  contains custom AVX2, AVX512, and NEON kernels.