コード例 #1
0
def test_wgt_group_collapse1():
    E_g = np.array([0.0, 4.0, 8.0])
    E_n = np.array([0.0, 2.5, 5.0, 7.5, 10.0])

    phi_n = np.array([0.0, 2.0, 1.0, 0.5])
    sigma_n = np.array([1.0, 2.0, 3.0, 4.0])
    wgts = np.array([0.00001, 0.00001, 0.00001, 0.00001])

    observed = group_collapse(sigma_n, phi_n, E_g=E_g, E_n=E_n, weights=wgts)
    expected = group_collapse(sigma_n, phi_n, E_g=E_g, E_n=E_n)
    assert_array_almost_equal(observed, expected)
コード例 #2
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ファイル: data_source.py プロジェクト: rwcarlsen/pyne
    def discretize(self, nuc, rx, temp=300.0, src_phi_g=None, dst_phi_g=None):
        """Discretizes the reaction channel from the source group structure to that 
        of the destination weighted by the group fluxes.  This implemenation is only
        valid for multi-group data sources.  Non-multigroup data source should also
        override this method.

        Parameters
        ----------
        nuc : int or str
            A nuclide.
        rx : int or str
            Reaction key ('gamma', 'alpha', 'p', etc.) or MT number.
        temp : float, optional
            Temperature [K] of material, defaults to 300.0.
        src_phi_g : array-like, optional
            Group fluxes for this data source, length src_ngroups.
        dst_phi_g : array-like, optional
            Group fluxes for the destiniation structure, length dst_ngroups.

        Returns
        -------
        dst_sigma : ndarry
            Destination cross section data, length dst_ngroups.

        """
        src_phi_g = self.src_phi_g if src_phi_g is None else np.asarray(src_phi_g) 
        src_sigma = self.reaction(nuc, rx, temp)
        dst_sigma = None if src_sigma is None else group_collapse(src_sigma, 
                                                        src_phi_g, dst_phi_g, 
                                                        self._src_to_dst_matrix)
        return dst_sigma
コード例 #3
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ファイル: channels.py プロジェクト: paulromano/pyne
def sigma_a_reaction(nuc, rx, E_g=None, E_n=None, phi_n=None):
    """Calculates the neutron absorption reaction cross-section for a nuclide for a 
    new, lower resolution group structure using a higher fidelity flux.  Note that 
    g indexes G, n indexes N, and G < N.

    Parameters
    ----------
    nuc : int, str, Material, or dict-like 
        A nuclide or nuclide-atom fraction mapping for which to calculate the 
        absorption reaction cross-section.
    rx : str
        Reaction key. ('gamma', 'alpha', 'p', etc.)
    E_g : array-like of floats, optional
        New, lower fidelity energy group structure [MeV] that is of length G+1. 
    E_n : array-like of floats, optional
        Higher resolution energy group structure [MeV] that is of length N+1. 
    phi_n : array-like of floats, optional
        The high-fidelity flux [n/cm^2/s] to collapse the fission cross-section over.  
        Length N.  

    Returns
    -------
    sigma_rx_g : ndarray 
        An array of the collapsed absorption reaction cross section.

    Notes
    -----
    This always pulls the absorption reaction cross-section out of the nuc_data.    

    See Also
    --------
    pyne.xs.cache.ABSORPTION_RX
    pyne.xs.cache.ABSORPTION_RX_MAP 
    """
    _prep_cache(E_g, E_n, phi_n)

    if isinstance(nuc, collections.Iterable) and not isinstance(nuc, basestring):
        return _atom_weight_channel(sigma_a_reaction, nuc, rx)

    # Get the absorption XS
    nuc_zz = nucname.zzaaam(nuc)
    key_n = ('sigma_rx_n', nuc_zz, rx)
    key_g = ('sigma_rx_g', nuc_zz, rx)

    # Don't recalculate anything if you don't have to
    if key_g in xs_cache:
        return xs_cache[key_g]
    else:
        sigma_rx_n = xs_cache[key_n]

    # Perform the group collapse, knowing that the right data is in the cache
    sigma_rx_g = group_collapse(sigma_rx_n, xs_cache['phi_n'], phi_g=xs_cache['phi_g'], 
                                partial_energies=xs_cache['partial_energy_matrix'])

    # Put this value back into the cache, with the appropriate label
    xs_cache[key_g] = sigma_rx_g

    return sigma_rx_g
コード例 #4
0
ファイル: channels.py プロジェクト: paulromano/pyne
def sigma_f(nuc, E_g=None, E_n=None, phi_n=None):
    """Calculates the neutron fission cross-section for a nuclide for a new, 
    lower resolution group structure using a higher fidelity flux.  Note that 
    g indexes G, n indexes N, and G < N.  If any of these are None-valued, 
    values from the cache are used.  The energy groups and fluxes are normally 
    ordered from highest-to-lowest energy.

    Parameters
    ----------
    nuc : int, str, Material, or dict-like 
        A nuclide or nuclide-atom fraction mapping for which to calculate the 
        fission cross-section.
    E_g : array-like of floats, optional
        New, lower fidelity energy group structure [MeV] that is of length G+1. 
    E_n : array-like of floats, optional
        Higher resolution energy group structure [MeV] that is of length N+1. 
    phi_n : array-like of floats, optional
        The high-fidelity flux [n/cm^2/s] to collapse the fission cross-section over.  
        Length N.  

    Returns
    -------
    sigma_f_g : ndarray 
        An array of the collapsed fission cross-section.

    Notes
    -----
    This always pulls the fission cross-section out of nuc_data library.    

    """
    _prep_cache(E_g, E_n, phi_n)

    if isinstance(nuc, collections.Iterable) and not isinstance(nuc, basestring):
        return _atom_weight_channel(sigma_f, nuc)

    # Get the fission XS
    nuc_zz = nucname.zzaaam(nuc)
    sigma_f_n_nuc_zz = ('sigma_f_n', nuc_zz)
    sigma_f_g_nuc_zz = ('sigma_f_g', nuc_zz)

    # Don't recalculate anything if you don't have to
    if sigma_f_g_nuc_zz in xs_cache:
        return xs_cache[sigma_f_g_nuc_zz]
    else:
        sigma_f_n = xs_cache[sigma_f_n_nuc_zz]

    # Perform the group collapse, knowing that the right data is in the cache
    sigma_f_g = group_collapse(sigma_f_n, xs_cache['phi_n'], phi_g=xs_cache['phi_g'], 
                               partial_energies=xs_cache['partial_energy_matrix'])

    # Put this value back into the cache, with the appropriate label
    xs_cache[sigma_f_g_nuc_zz] = sigma_f_g

    return sigma_f_g
コード例 #5
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def test_group_collapse1():
    E_g = np.array([0.0, 4.0, 8.0])
    E_n = np.array([0.0, 2.5, 5.0, 7.5, 10.0])

    phi_n = np.array([0.0, 2.0, 1.0, 0.5])
    sigma_n = np.array([1.0, 2.0, 3.0, 4.0])

    expected = np.array([2.0, 5.0 / 1.9])

    # First way of calling
    observed = group_collapse(sigma_n, phi_n, E_g=E_g, E_n=E_n)
    assert_array_almost_equal(observed, expected)

    # Second method of calling
    p_g = phi_g(E_g, E_n, phi_n)
    pem = partial_energy_matrix(E_g, E_n)
    observed = group_collapse(sigma_n, phi_n, phi_g=p_g, partial_energies=pem)
    assert_array_almost_equal(observed, expected)

    # bad call
    assert_raises(ValueError, group_collapse, sigma_n, phi_n)
コード例 #6
0
ファイル: test_models.py プロジェクト: chrisdembia/pyne
def test_group_collapse1():
    E_g = np.array([0.0, 4.0, 8.0])
    E_n = np.array([0.0, 2.5, 5.0, 7.5, 10.0])

    phi_n = np.array([0.0, 2.0, 1.0, 0.5])
    sigma_n = np.array([1.0, 2.0, 3.0, 4.0])

    expected = np.array([2.0, 5.0 / 1.9])

    # First way of calling
    observed = group_collapse(sigma_n, phi_n, E_g=E_g, E_n=E_n)
    assert_array_almost_equal(observed, expected)

    # Second method of calling
    p_g = phi_g(E_g, E_n, phi_n)
    pem = partial_energy_matrix(E_g, E_n)
    observed = group_collapse(sigma_n, phi_n, phi_g=p_g, partial_energies=pem)
    assert_array_almost_equal(observed, expected)

    # bad call
    assert_raises(ValueError, group_collapse, sigma_n, phi_n)