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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def create_from_yamlfile(cls, yamlfile):
 """Create a Castro data object from a yaml file contains the likelihood data."""

        data = load_yaml(yamlfile)
        nebins = len(data)
        emin = np.array([data[i]['emin'] for i in range(nebins)])
        emax = np.array([data[i]['emax'] for i in range(nebins)])
        ref_flux = np.array([data[i]['flux'][1] for i in range(nebins)])
        ref_eflux = np.array([data[i]['eflux'][1] for i in range(nebins)])
        conv = np.array([data[i]['eflux2npred'] for i in range(nebins)])
        ref_npred = conv*ref_eflux
        ones = np.ones(ref_flux.shape)
        ref_spec = ReferenceSpec(emin, emax, ones, ref_flux, ref_eflux, ref_npred)
        norm_data = np.array([data[i]['eflux'] for i in range(nebins)])
        ll_data =  np.array([data[i]['logLike'] for i in range(nebins)])
        max_ll = ll_data.max(1)
        nll_data = (max_ll - ll_data.T).T
        return cls(norm_data, nll_data, ref_spec, 'eflux')