Еще один эксперимент с масками Engee Function

module PDIST2

mode_dict_t = Dict(1=>"euclidean",2=>"squaredeuclidean",3=>"manhattan",4=>"cosine")

function EF_pdist2(X::Matrix{Float64}, Y::Matrix{Float64}; metric::String="euclidean")
    m, n = size(X)
    p, n2 = size(Y)
    n == n2 || throw(DimensionMismatch("Number of columns in X and Y must match"))

    if metric == "euclidean"
        XX = sum(X.^2, dims=2)
        YY = sum(Y.^2, dims=2)
        D = XX .+ YY' .- 2 .* (X * Y')
        return sqrt.(max.(D, 0))
    
    elseif metric == "squaredeuclidean"
        XX = sum(X.^2, dims=2)
        YY = sum(Y.^2, dims=2)
        D = XX .+ YY' .- 2 .* (X * Y')
        return max.(D, 0)
    
    elseif metric == "manhattan"
        D = zeros(m, p)
        for j in 1:p
            for i in 1:m
                D[i, j] = sum(abs.(X[i, :] .- Y[j, :]))
            end
        end
        return D
    
    elseif metric == "cosine"
        XX = sqrt.(sum(X.^2, dims=2))
        YY = sqrt.(sum(Y.^2, dims=2))
        norms = XX .* YY'
        XY = X * Y'
        
        # Handle division by zero: set invalid entries to 0, then correct cases where both vectors are zero
        sim = zeros(size(XY))
        valid = norms .> 0
        sim[valid] .= XY[valid] ./ norms[valid]
        
        # Identify pairs where both vectors are zero (cosine similarity = 1)
        both_zero = (XX .== 0) .& (YY' .== 0)
        sim[both_zero] .= 1
        
        return 1 .- sim
    
    else
        throw(ArgumentError("Unknown metric: $metric. Supported metrics are 'euclidean', 'squaredeuclidean', 'manhattan', 'cosine'"))
    end
end


end