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madsjulia · Aug 7, 2024 · 0aa57fa · 0aa57fa
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commit 0aa57fa
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Showing 3 changed files with 4 additions and 7 deletions.
diff --git a/src/MadsLevenbergMarquardt.jl b/src/MadsLevenbergMarquardt.jl
@@ -440,7 +440,7 @@ function levenberg_marquardt(f::Function, g::Function, x0, o::Function=x->(x'*x)
 		# Solving for the minimum gives:
 		#    (J'*J + lambda*DtD) * delta_x == -J^T * f(x), where DtD = diagm(sum(J.^2,1))
 		# Where we use the equivalence: diagm(J'*J) = diagm(sum(J.^2, 1))
-		# It is additionally useful to bound the elements of DtD below to help prevent "parameter evaporation".
+		# It is additionally useful to bind the elements of DtD below to help prevent "parameter evaporation".
 		# DtD = diagm(Float64[max(x, MIN_DIAGONAL) for x in sum( J.^2, 1 )])
 		# DtDidentity used instead; seems to work better; LM in Mads.c uses DtDidentity
 		JpJ = J' * J

diff --git a/src/MadsPlot.jl b/src/MadsPlot.jl
@@ -649,7 +649,6 @@ function plotobsSAresults(madsdata::AbstractDict, result::AbstractDict; filter::
 		else
 			d[1,i] = i
 			no_time_field = true
-
 		end
 		d[2,i] = haskey(obsdict[obskey], "target") ? obsdict[obskey]["target"] : NaN
 		for (j, paramkey) in enumerate(paramkeys)
@@ -665,12 +664,12 @@ function plotobsSAresults(madsdata::AbstractDict, result::AbstractDict; filter::
 	if mintes < 0
 		tes = tes .- mintes
 	end
-	tes ./=  maximumnan(tes)
+	tes ./= maximumnan(tes)
 	minmes = minimumnan(mes)
 	if minmes < 0
 		mes = mes .- minmes
 	end
-	mes ./=  maximumnan(mes)
+	mes ./= maximumnan(mes)
 	smags = order ? sortperm(vec(sum(tes; dims=1)); rev=true) : collect(1:nP)
 	pp = Array{Any}(undef, 0)
 	if ytitle != ""

diff --git a/src/MadsSensitivityAnalysis.jl b/src/MadsSensitivityAnalysis.jl
@@ -877,7 +877,7 @@ function computeparametersensitities(madsdata::AbstractDict, saresults::Abstract
 	var = saresults["var"]
 	pvar = OrderedCollections.OrderedDict{Union{String,Symbol},Float64}() # parameter variance
 	pmes = OrderedCollections.OrderedDict{Union{String,Symbol},Float64}() # parameter main effect (first order) sensitivities
-	ptes = OrderedCollections.OrderedDict{Union{String,Symbol},Float64}()	# parameter total effect sensitivities
+	ptes = OrderedCollections.OrderedDict{Union{String,Symbol},Float64}() # parameter total effect sensitivities
 	for i = eachindex(paramkeys)
 		pv = pm = pt = 0
 		for j = eachindex(obskeys)
@@ -951,7 +951,6 @@ argtext=Dict("madsdata"=>"MADS problem dictionary",
 function printSAresults(madsdata::AbstractDict, results::AbstractDict)
 	mes = results["mes"]
 	tes = results["tes"]
-	N = results["samplesize"]
 	#=
 	madsoutput("Mean\n")
 	madsoutput("\t")
@@ -1033,7 +1032,6 @@ argtext=Dict("madsdata"=>"MADS problem dictionary",
 function printSAresults2(madsdata::AbstractDict, results::AbstractDict)
 	mes = results["mes"]
 	tes = results["tes"]
-	N = results["samplesize"]
 	print("Main Effect Indices")
 	print("\t")
 	obskeys = getobskeys(madsdata)