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class ModelBuilder:
    @classmethod
    def load_default_config(cls):
        # return dict of parameters
        ...


    def __init__(self, data: pd.DataFrame, trait: str, config: Dict):
        """
        Initialize the model builder.

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def z_link_func(x, data=mydata):
    stim = (np.asarray(dmatrix('0 + C(s, [[0], [1]])',
                               {'s': data.stimulus.loc[x.index]}))
    )
    # Apply z = (1 - x) to flip them along 0.5
    z_flip = stim - x
    # The above inverts those values we do not want to flip,
    # so invert them back
    z_flip[stim == 0] *= -1
    return z_flip

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