Interpret correctly the signs in the affinity matrix
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1 changed files with 18 additions and 16 deletions
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@ -31,27 +31,28 @@ function loadclassification()::Classification
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clf
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end
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function loadcostsdf()::DataFrame
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function loadaffinitiesdf()::DataFrame
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df = CSV.read("data/associations.csv", copycols=true)
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colnames = String.(names(df))
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colnames = Symbol.(Unicode.normalize.(colnames, casefold=true, stripmark=true))
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rename!(df, colnames)
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df.name = colnames[2:end]
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# df = coalesce.(df, 0.0)
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@info "loaded cost matrix for $(size(df, 1)) plants"
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@info "loaded affinity matrix for $(size(df, 1)) plants"
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df
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end
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function computecost(plant1::Symbol, plant2::Symbol, costs_df::DataFrame, classification::Classification)::Float64
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"Compute the cost between two plants, using their families if necessary."
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function computecost(plant1::Symbol, plant2::Symbol, affinities_df::DataFrame, classification::Classification)::Float64
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@debug "computecost($plant1, $plant2)"
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if plant1 in names(costs_df) && plant2 in names(costs_df)
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cost = costs_df[costs_df.name .== plant1, plant2][1]
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if plant1 in names(affinities_df) && plant2 in names(affinities_df)
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affinity = affinities_df[affinities_df.name .== plant1, plant2][1]
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else
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cost = missing
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affinity = missing
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end
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if !ismissing(cost)
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return cost
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if !ismissing(affinity)
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return -affinity
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end
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parent1 = getfirstparent(plant1, classification)
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@ -60,24 +61,25 @@ function computecost(plant1::Symbol, plant2::Symbol, costs_df::DataFrame, classi
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return 0.0
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end
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@debug "computecost($(parent1.name), $(parent2.name))"
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if parent1.name in names(costs_df) && parent2.name in names(costs_df)
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cost = costs_df[costs_df.name .== parent1.name, parent2.name][1]
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if parent1.name in names(affinities_df) && parent2.name in names(affinities_df)
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affinity = affinities_df[affinities_df.name .== parent1.name, parent2.name][1]
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end
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if !ismissing(cost)
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return cost
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if !ismissing(affinity)
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return -affinity
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end
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return 0.0
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end
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function costsmatrix(plants::Vector{Symbol}, costs_df::DataFrame, classification::Classification)::Matrix{Float64}
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[computecost(plant1, plant2, costs_df, classification) for plant1 in plants, plant2 in plants]
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"Compute the costs matrix for all plants"
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function costsmatrix(plants::Vector{Symbol}, affinities_df::DataFrame, classification::Classification)::Matrix{Float64}
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[computecost(plant1, plant2, affinities_df, classification) for plant1 in plants, plant2 in plants]
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end
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function loadcosts()
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plants = loadplants()
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clf = loadclassification()
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costs_df = loadcostsdf()
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costs = costsmatrix(plants.name, costs_df, clf)
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affinities_df = loadaffinitiesdf()
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costs = costsmatrix(plants.name, affinities_df, clf)
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end
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