merck / ceedesigns.jl Goto Github PK

In CEEDesigns.GenerativeDesigns, while "distances" and "similarities" are provided by a user through a function call, an "uncertainty" is given as a type. See the following for reference:

It may be worth unifying the style.

This issue is used to trigger TagBot; feel free to unsubscribe.

If you haven't already, you should update your TagBot.yml to include issue comment triggers.
Please see this post on Discourse for instructions and more details.

If you'd like for me to do this for you, comment TagBot fix on this issue.
I'll open a PR within a few hours, please be patient!

The Mahalanobis distance between a state with missing readouts for a subset of features and a "historical" row is essentially calculated as if we were setting the missing entry equal to the respective record in the "historical" row. See the following link for reference:

However, this might not be the optimal approach. For more information, consider the following resources: https://search.r-project.org/CRAN/refmans/modi/html/MDmiss.html and also https://www.jstor.org/stable/3559861, particularly on page 285.

Reintroduce the option to calculate the Mahalanobis distance between readout vectors.

• There is no need to compute the variance each time in:
  

  CEEDesigns.jl/src/GenerativeDesigns/distancebased.jl

  Lines 8 to 13 in d1d09c3

  	QuadraticDistance(; λ = 1, standardize = true) =
  	function (x, col; prior = ones(length(col)))
  	σ = standardize ? var(col, Weights(prior); corrected = false) : 1
  	return λ * (x .- col) .^ 2 / σ
  	end

• It might be better to preallocate the vectors in
  

  CEEDesigns.jl/src/GenerativeDesigns/distancebased.jl

  Lines 119 to 128 in d1d09c3

  	vec_evidence = map(colname -> get(evidence, colname, 0), non_targets)
  	distances = map(eachrow(data)) do row
  	vec_row = map(
  	colname -> haskey(evidence, colname) ? row[colname] : 0,
  	non_targets,
  	)
  	z = vec_evidence - vec_row
  	dot(z, Λ * z)
  	end

@JuliaRegistrator register()