#  MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
#  Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
#  Released under the modified BSD license. See COPYING.md for more details.

import MIPLearn: to_model,
                 get_instance_features,
                 get_variable_features
                 find_violated_lazy_constraints
using JuMP

struct KnapsackData
    weights
    prices
    capacity
end

function to_model(data::KnapsackData)
    model = Model()
    n = length(data.weights)
    @variable(model, x[0:(n-1)], Bin)
    @objective(model, Max, sum(x[i] * data.prices[i+1] for i in 0:(n-1)))
    @constraint(
        model,
        eq_capacity,
        sum(
            x[i] * data.weights[i+1]
            for i in 0:(n-1)
        ) <= data.capacity,
    )
    return model
end

function get_instance_features(data::KnapsackData)
    return [0.]
end

function get_variable_features(data::KnapsackData, var, index)
    return [0.]
end

KnapsackInstance = @Instance(KnapsackData)