Plot portfolio composition map in Julia (or Matlab)

I am optimizing portfolio of N stocks over M levels of expected return. So after doing this I get the time series of weights (i.e. a N x M matrix where where each row is a combination of stock weights for a particular level of expected return). Weights add up to 1.

Now I want to plot something called portfolio composition map (right plot on the picture), which is a plot of these stock weights over all levels of expected return, each with a distinct color and length (at every level of return) is proportional to it's weight.

My questions is how to do this in Julia (or MATLAB)?

I came across this and the accepted solution seemed so complex. Here's how I would do it:

using Plots
@userplot PortfolioComposition

@recipe function f(pc::PortfolioComposition)
    weights, returns = pc.args
    weights = cumsum(weights,dims=2)
    seriestype := :shape
    for c=1:size(weights,2)
        sx = vcat(weights[:,c], c==1 ? zeros(length(returns)) : reverse(weights[:,c-1]))
        sy = vcat(returns, reverse(returns))
        @series Shape(sx, sy)
    end
end

# fake data
tickers = ["IBM", "Google", "Apple", "Intel"]
N = 10
D = length(tickers)
weights = rand(N,D)
weights ./= sum(weights, dims=2)
returns = sort!((1:N) + D*randn(N))

# plot it
portfoliocomposition(weights, returns, labels = tickers)