import numpy as np 
    # Convert econ to gym
def convert_econ_to_gym(econ):
        gy=[]
        gy=[v for k,v in econ.items()]
        return gy

def convert_gym_to_econ(gy):
        econ={}
        for k in range(len(gy)):
            econ[k]=gy[k]
        return econ



def build_packager(sub_obs, put_in_both=None):
        """
        Decides which keys-vals should be flattened or not.
        put_in_both: include in both (e.g., 'time')
        """
        if put_in_both is None:
            put_in_both = []
        keep_as_is = []
        flatten = []
        wrap_as_list = {}
        for k, v in sub_obs.items():
            if isinstance(v, np.ndarray):
                multi_d_array = len(v.shape) > 1
            else:
                multi_d_array = False

            if k == "action_mask" or multi_d_array:
                keep_as_is.append(k)
            else:
                flatten.append(k)
                if k in put_in_both:
                    keep_as_is.append(k)

            wrap_as_list[k] = np.isscalar(v)

        flatten = sorted(flatten)

        return keep_as_is, flatten, wrap_as_list

   
def package(obs_dict, keep_as_is, flatten, wrap_as_list):
            """Flattens observation with packagers."""

            new_obs = {k: obs_dict[k] for k in keep_as_is}
            if len(flatten) == 1:
                k = flatten[0]
                o = obs_dict[k]
                if wrap_as_list[k]:
                    o = [o]
                new_obs["flat"] = np.array(o, dtype=np.float32)
            else:
                to_flatten = [
                    [obs_dict[k]] if wrap_as_list[k] else obs_dict[k] for k in flatten
                ]
                try:
                    new_obs["flat"] = np.concatenate(to_flatten).astype(np.float32)
                except ValueError:
                    for k, v in zip(flatten, to_flatten):
                        print(k, np.array(v).shape)
                        print(v)
                        print("")
                    raise
            
            return new_obs