Биорадар: Часть 2. Обучение ИНС реконструкции ЭКГ

using MAT                   
using Flux
using Random

struct RadarECG{T<:Vector{String}}
    files::T              
    win::Int
    step::Int
    map::Vector{Tuple{Int,Int}}   
    len_cache::Dict{String,Int}  
    cache::Dict{Int, Array{Float32,2}}  
end

function RadarECG(root::AbstractString; win::Int=5024, step::Int=1256)

    paths = filter(p -> occursin(r"^GDN\d{4}_.+\.mat$", basename(p)),
                   sort(readdir(root; join=true)))
    isempty(paths) && error("no .mat files in $root")

    len_cache = Dict{String,Int}()
    map = Tuple{Int,Int}[]

    for (i, path) in enumerate(paths)

        n = let m = matread(path)
                size(m["radar"], 1)
                # size(permutedims(m["radar"]), 1)
            end
        len_cache[path] = n
        nwin = 1 + max(0, (n - win) ÷ step)
        append!(map, ((i, w) for w in 0:(nwin-1)))
    end

    RadarECG(paths, win, step, map, len_cache, Dict{Int,Array{Float32,2}}())
end

Base.length(d::RadarECG) = length(d.map)

function Base.getindex(d::RadarECG, idx::Int)
    fi, wi = d.map[idx]

    if !haskey(d.cache, fi)
        m   = matread(d.files[fi])
        rad = Float32.(vec(m["radar"]))
        ecg = Float32.(vec(m["ecg"]))
        # rad = permutedims(Float32.(m["radar"]))
        # ecg = permutedims(Float32.(m["ecg"]))
        length(rad) == length(ecg) || error("length mismatch")
        d.cache[fi] = [rad'; ecg']      # ← ключевая строка
    end
    data = d.cache[fi]
    s = wi * d.step + 1              
    win = d.win
    ϵ = 1e-6
    radar_seg = data[1, s:(s+win-1)]
    ecg_seg   = data[2, s:(s+win-1)]

    
    return radar_seg, ecg_seg
end