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    # This file may not be shared/redistributed without permission. Please read copyright notice in the git repo. If this file contains other copyright notices disregard this text.
    from irlc.ex02.inventory import InventoryDPModel
    from irlc.ex02.dp import DP_stochastic
    import numpy as np
    
    # TODO: Code has been removed from here.
    raise NotImplementedError("Insert your solution and remove this error.")
    
    def a_get_policy(N: int, c: float, x0 : int) -> int:
        # TODO: Code has been removed from here.
        raise NotImplementedError("Insert your solution and remove this error.")
        return u
    
    def b_prob_one(N : int, x0 : int) -> float:
        # TODO: Code has been removed from here.
        raise NotImplementedError("Insert your solution and remove this error.")
        return pr_empty
    
    
    if __name__ == "__main__":
        model = InventoryDPModel()
        pi = [{s: 0 for s in model.S(k)} for k in range(model.N)]
        x0 = 0
        c = 0.5
        N = 3
        print(f"a) The policy choice for {c=} is {a_get_policy(N, c,x0)} should be 1")
        print(f"b) The probability of ending up with a single element in the inventory is {b_prob_one(N, x0)} and should be 0.492")