def plot_et(self, LAXIS, xbl, xbr, ybu, ybd, ilg):
    'Plot mean total energy stratification in the model'
    grd1 = self.xzn0
    plt1 = self.fht_et
    plt.figure(figsize=(7, 6))
    plt.gca().yaxis.get_major_formatter().set_powerlimits((0, 0))
    to_plot = [plt1]
    self.set_plt_axis(LAXIS, xbl, xbr, ybu, ybd, to_plot)
    plt.title('total energy')
    plt.plot(grd1, plt1, color='brown', label='$\\widetilde{\\varepsilon}_t$')
    if (self.ig == 1):
        setxlabel = 'x (cm)'
        setylabel = '$\\widetilde{\\varepsilon}_t$ (erg g$^{-1}$)'
        plt.xlabel(setxlabel)
        plt.ylabel(setylabel)
    elif (self.ig == 2):
        setxlabel = 'r (cm)'
        setylabel = '$\\widetilde{\\varepsilon}_t$ (erg g$^{-1}$)'
        plt.xlabel(setxlabel)
        plt.ylabel(setylabel)
    plt.legend(loc=ilg, prop={'size': 18})
    plt.show(block=False)
    if (self.fext == 'png'):
        plt.savefig((('RESULTS/' + self.data_prefix) + 'mean_et.png'))
    elif (self.fext == 'eps'):
        plt.savefig((('RESULTS/' + self.data_prefix) + 'mean_et.eps'))
Plot mean total energy stratification in the model
def plot_et(self, LAXIS, xbl, xbr, ybu, ybd, ilg):
    
    grd1 = self.xzn0
    plt1 = self.fht_et
    plt.figure(figsize=(7, 6))
    plt.gca().yaxis.get_major_formatter().set_powerlimits((0, 0))
    to_plot = [plt1]
    self.set_plt_axis(LAXIS, xbl, xbr, ybu, ybd, to_plot)
    plt.title('total energy')
    plt.plot(grd1, plt1, color='brown', label='$\\widetilde{\\varepsilon}_t$')
    if (self.ig == 1):
        setxlabel = 'x (cm)'
        setylabel = '$\\widetilde{\\varepsilon}_t$ (erg g$^{-1}$)'
        plt.xlabel(setxlabel)
        plt.ylabel(setylabel)
    elif (self.ig == 2):
        setxlabel = 'r (cm)'
        setylabel = '$\\widetilde{\\varepsilon}_t$ (erg g$^{-1}$)'
        plt.xlabel(setxlabel)
        plt.ylabel(setylabel)
    plt.legend(loc=ilg, prop={'size': 18})
    plt.show(block=False)
    if (self.fext == 'png'):
        plt.savefig((('RESULTS/' + self.data_prefix) + 'mean_et.png'))
    elif (self.fext == 'eps'):
        plt.savefig((('RESULTS/' + self.data_prefix) + 'mean_et.eps'))