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TODO.md

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Road to 1.9

  • do todo below
  • compile book
  • run test
  • compile function index
  • [] run CRAN check
  • RECOMPILE ALL INTERNAL DATASETS

multi.ace

  • check that "combined" properly recycles the tree's node labels.

bootstrapping dimensions

  • New argument for boot.matrix: what to specify whether to bootstrap rows ("rows" - the default), columns ("columns") or both (c("rows", "columns")). Thanks to Gavin Thomas for this suggestion.
  • implement checks for what
  • implement checks for dimensions (can now be integer or numeric - number to bootstrap)
  • update the dispRity pipeline to call the bootstrapped dimensions.
  • documentation
  • test
  • add sampling probabilities tutorial

RAM helpers

  • General rehaul of the dispRity RAM management! All disparity metrics can now have an optional RAM.help component that can generate any specific calculation and storage of data for helping the metric. This is then internally used by dispRity to pre-calculate and optimise operations that use a lot of RAM or CPU time. For example, you can now use RAM.help = vegan::vegdist to pre-calculate all distances in the trait space using vegan::vegdist. These pre-calculated distances are then used by the disparity metric avoiding recalculating distances internally. Thanks to Neha Sharma for this suggestion.
    1. metrics can now have RAM.help arguments that intake a function that will run some pre-calculations. For example, this function can be vegan::vegdist.
    1. detect the need for RAM help in get.dispRity.metric.handle
    1. compute heavy calculations at the whole data level in dispRity using the RAM.help function before the lapply_loop
    1. store the calculations in data similarly as tree as RAM.helper
    1. run the metrics using a potential RAM.helper similarly as tree.
  • documentation
  • test
  • update all the dispRity functions that have a check.dist.matrix function to use a helper neighbours span.tree.length pairwise.dist func.eve count.neighbours
  • do speed test for ego boost

Generalise pipeline for distance matrices.

  • add an option keep.distance = TRUE to dispRity which does:
    • detect data as a distance matrix or not
    • if yes + keep.distance = TRUE OR if no + keep.distance = TRUE + RAM.helper + distance based metric -> apply bootstrap or anything on rows and columns
    • if no, then old behaviour.
    • flag new default with warning messages when detecting if yes. "Data is considered as a distance matrix and analysed by keeping the distances (toggle off using keep.distances = FALSE").

Vignettes and manual

  • make a dispRity.multi vignette

  • make a dist.help section in the manual

  • update the bootstrap section in the manual with the dimensions

  • add count.neigbhours to the metrics section (New metric: count.neighbours to count the number of neighbours for each elements within a certain radius (thanks to Rob MacDonald for the suggestion).)

  • make a MCMCglmm related standalone vignette

  • make a morpho disparity (Claddis) standalone vignette

Minor improvements:

  • Make roundness work for non-VCV matrices (specify the axis function, e.g. variances or quantiles).
  • TODO
  • Add vegan::adonis2 ref in adonis.dispRity
  • TODO
  • add references in .Rd:
  • reduce.space algorithms
  • vegan algorithms

Bug fixes

  • Check MacOS bugs in the coverage pipeline
  • TODO