#!/usr/bin/env julia

# Execute the authors' exact qcorridor.jl implementation for Figure 3.
# Usage: julia run_qcommit_official.jl AUTHORS_QCORRIDOR_JL OUTPUT_CSV

if length(ARGS) != 2
    error("expected AUTHORS_QCORRIDOR_JL OUTPUT_CSV")
end

include(abspath(ARGS[1]))

const T = 1000
const SEEDS = 0:999
const LENGTHS = (5, 10, 20, 50, 100, 200)
const ALPHA0 = 0.1
const ALPHAT = 0.01
const EPS0 = 0.1
const EPST = 0.01

function curve(k::Int, committed::Bool)
    counts = zeros(Int, T)
    for seed in SEEDS
        _, qs = qcorridor(
            T, k, committed, seed, ALPHA0, ALPHAT, EPS0, EPST, 0
        )
        for t in 1:T
            # The optimal reactive policy selects right in both features.
            counts[t] += (qs[t, 1, 2] > qs[t, 1, 1] &&
                          qs[t, 2, 2] > qs[t, 2, 1])
        end
    end
    return counts
end

open(abspath(ARGS[2]), "w") do io
    println(io, "mode,k,t,optimal_count,total_seeds")
    for committed in (true, false)
        mode = committed ? "committed" : "regular"
        for k in LENGTHS
            counts = curve(k, committed)
            for t in 1:T
                println(io, mode, ",", k, ",", t, ",", counts[t], ",", length(SEEDS))
            end
        end
    end
end