Exemple #1
0
def set_fn_model(flg=0):
    """ Load up f(N) model

    Parameters
    ----------
    flg : int, optional
      * 0 = Default model
      * 1 = Gamma

    Returns
    -------
    sfN_model : FNModel
    """
    if flg == 0:  # I may choose to pickle a few of these
        sfN_model = FNModel.default_model(use_mcmc=True)  # Hermite Spline
    elif flg == 1:
        sfN_model = FNModel('Gamma')
    elif flg == 2:
        tfN_model = FNModel.default_model()
        NHI_pivots = [11., 15., 17.0, 20.0, 21.5, 22.]
        param = []
        for NHI in NHI_pivots:
            imin = np.argmin(np.abs(NHI - tfN_model.pivots))
            param.append(tfN_model.param['sply'][imin])
        # Init
        sfN_model = FNModel('Hspline',
                            zmnx=(0.5, 5.5),
                            pivots=NHI_pivots,
                            param=dict(sply=np.array(param)))
    else:
        raise ValueError(
            'mcmc.set_model: Not ready for this type of fN model {:d}'.format(
                flg))
    #
    return sfN_model
Exemple #2
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def set_fn_model(flg=0, use_p14=False):
    """ Load up f(N) model

    Parameters
    ----------
    flg : int, optional
      * 0 = Default model
      * 1 = Gamma

    Returns
    -------
    sfN_model : FNModel
    """
    if flg == 0:  # I may choose to pickle a few of these
        sfN_model = FNModel.default_model(use_mcmc=True)  # Hermite Spline
    elif flg == 1:
        sfN_model = FNModel('Gamma')
    elif flg == 2:
        tfN_model = FNModel.default_model()
        # GGG analysis
        pdb.set_trace()  # BEING DEVELOPED IN GGG/LLS/Analysis/py
        zpivot = 4.4
        #NHI_pivots = [11., 15., 17.0, 20.0, 21.5, 22.]
        NHI_pivots = [11., 15., 17.0, 18.0, 20.0, 21.5, 22.]
        if use_p14:
            param = []
            for NHI in NHI_pivots:
                imin = np.argmin(np.abs(NHI - tfN_model.pivots))
                # Adjust for zpivot
                adj_parm = tfN_model.param['sply'][imin] + np.log10(
                    ((1 + zpivot) / (1 + tfN_model.zpivot))**tfN_model.gamma)
                param.append(adj_parm)
        else:
            #param = [-8.45, -13.959, -18.06, -21.000, -23.735, -24.88]
            if len(param) != len(NHI_pivots):
                raise ValueError("Incorrect number of parameters")
        # Init
        sfN_model = FNModel('Hspline',
                            zmnx=(0.5, 5.5),
                            pivots=NHI_pivots,
                            zpivot=zpivot,
                            param=dict(sply=np.array(param)))
    else:
        raise ValueError(
            'mcmc.set_model: Not ready for this type of fN model {:d}'.format(
                flg))
    #
    return sfN_model
Exemple #3
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def test_init_I14():
    # Class
    fN_I14 = FNModel('Gamma')
    # Mtype
    assert fN_I14.mtype == 'Gamma'
    assert fN_I14.zmnx == (0., 10.)