
@testset "neighbour prices" begin
    println("pending")

    # ind_pref = []
    # for i in 1:20
    #     push!(ind_pref, sparse(collect(1:10), collect(1:10), rand(0:100, 10)))
    # end

    # budget = rand(150:200, 20)
    # capacity = fill(3, 20)
    # price = rand(30:70, 10)
    # max_spots = rand(5:7, 10)

    # dem = demand(price, ind_pref, budget, capacity)

    # # Test functions
    # #grad neighbour
    # grad_descent(price, clear_error)
    # # should return 5 element array (10 element vectors)

    # # indiv neighbour
    # #decrease_demand(k, price, dem, clear_error, ind_pref, budget, capacity)
    # k = 2
    # new_price = indiv_adjust(k, price, demand, clear_error, ind_pref, budget, capacity)
    # dem2 = demand(new_price, ind_pref, budget, capacity)
    # clear_error2 = dem2["total_demand"] - max_spots
    # #should find either new_price k = 0 or new clear error drop by 1

    # neighb_fun(price, demand, clear_error, ind_pref, budget, capacity)
    
end

