describe "#nearest" do
    it "should equal naive implementation" do 
      ndim = 2
      k = 3
      distance = ->(m : Array(Float64),n : Array(Float64)) do
        m.each_with_index.reduce(0) do |sum, (coord, index)|
          sum += (coord - n[index]) ** 2
          sum
        end
      end

      10.times do
        points = Array.new(10) do  Array.new(ndim) do rand(-10.0 .. 10.0) end end
        kd_tree = Kd::Tree(Float64).new(points)
        target = Array.new(ndim) do rand(-11.0 .. 11.0) end
        res = kd_tree.nearest(target,k)
        sorted = points.sort_by do |p| distance.call(p,target) end.reverse!
        (res - sorted[-k..]).should eq [] of Float64
      end
    end
  end

def nearest!(...)
  # ...
  if nearest.size < n 
    nearest << curr.pivot 
  else 
    nearest.sort_by! do |b| distance(b, query) end
    dist_curr_query = distance(curr.pivot, query)
    ix = nearest.rindex { |b| dist_curr_query < distance(b, query) }
    nearest[ix] = curr.pivot if ix
  end 
  # ...
end