Huge performance optimization: re-use the distances computed when making a recurrence matrix

Alright, we stand to gain MASSIVE, 2x, performance benefit here for all RecurrenceTypes except RecurrenceThreshold. Take a look at our source code that computes the recurrence threshold for a given type: https://github.com/JuliaDynamics/RecurrenceAnalysis.jl/blob/main/src/matrices/recurrence_specification.jl#L78-L153

For all types (besides RecurrenceThreshold) we are computing all the distances across all pairs of points, to estimate a threshold. Then, we give this threshold to the low-level recurrence_matrix function which computes all distances all over again. We can be much smarter than that and just store somewhere the distance matrtix and pass it around until we reach the recurrence_matrix function, which then does a trivial boolean conversion rmat = dmat .< threhold; return SparseMatrix(rmat).

This is such a simple code base improvement with such a massive impact.