Пример #1
0
    def plot_rb(self):

        fig = plt.figure()
        plt.plot(self.zeta_array, self.rb)
        plt.plot(self.zeta_array, self.rb_maxrho)

        ax = plt.gca()
        ax.set_ylabel(r'$k_p r_b$', fontsize=14)
        ax.set_xlabel(r'$k_p \zeta$', fontsize=14)
        ax.legend([r'$r_b$ from zero crossing', r'$r_b$ from global maximum'])

        filesuffix = '_t_%06.f' % (np.floor(self.g3d.get_time()))
        fileprefix = 'plasma_charge_rb'
        saveformat = 'eps'
        savepath = self.args.savepath

        mkdirs_if_nexist(savepath)

        savename = fileprefix + filesuffix + '.' + saveformat

        fig.savefig(savepath + '/' + savename, format=saveformat)

        if self.args.h5plot:
            h5lp = H5Plot()
            h5lp.inherit_matplotlib_line_plots(ax)
            h5lp.write(savepath + '/' + fileprefix + filesuffix + '.h5')

        if self.args.verbose:
            print('Saved "' + savename + '" at: ' + self.args.savepath)
        plt.close(fig)
Пример #2
0
    def plot_r_lines(self):

        if not hasattr(self, 'r_z_slice_model'):
            self.gen_model_sheath()

        z_inds = np.int16(np.linspace(0, self.Nzeta - 1, 10))

        fig = plt.figure()
        for z_ind in z_inds:
            p = plt.plot(self.r_array, self.r_z_slice[:, z_ind])
            plt.plot(self.r_array,
                     self.r_z_slice_model[:, z_ind],
                     color=p[0].get_color(),
                     linestyle='--')
            plt.plot(self.r_array,
                     self.r_z_slice_model_flocmax[:, z_ind],
                     color=p[0].get_color(),
                     linestyle='-.')

        ax = plt.gca()
        ax.set_ylabel(r'$\rho$', fontsize=14)
        ax.set_xlabel(r'$k_p r$', fontsize=14)

        filesuffix = '_t_%06.f' % (np.floor(self.g3d.get_time()))
        fileprefix = 'plasma_charge_r'
        saveformat = 'eps'
        savepath = self.args.savepath

        mkdirs_if_nexist(savepath)

        savename = fileprefix + filesuffix + '.' + saveformat

        fig.savefig(savepath + '/' + savename, format=saveformat)
        plt.close(fig)

        if self.args.h5plot:
            h5lp = H5Plot()
            h5lp.inherit_matplotlib_line_plots(ax)
            h5lp.write(savepath + '/' + fileprefix + filesuffix + '.h5')

        if self.args.verbose:
            print('Saved "' + savename + '" at: ' + self.args.savepath)
Пример #3
0
def saveas_eps_pdf(fig,
                   savepath,
                   savename,
                   h5plot=True,
                   verbose=True,
                   fformat='pdf',
                   transparent=True):

    fformat_list = ['eps', 'pdf']

    if fformat not in fformat_list:
        print("Error: fformat must be one of: " + fformat_list)

    if savepath != None:
        if savepath == '':
            savepath = '.'
        else:
            mkdirs_if_nexist(savepath)
        fig.savefig(savepath + '/' + savename + '.' + fformat,
                    format=fformat,
                    transparent=transparent)

        if verbose:
            sys.stdout.write('Saved "%s.%s" at: %s/\n' %
                             (savename, fformat, savepath))
            sys.stdout.flush()

        if h5plot:
            h5lp = H5Plot()
            h5lp.inherit_matplotlib_line_plots(plt.gca())
            h5lp.write(savepath + '/' + savename + '.h5')

            if verbose:
                sys.stdout.write('Saved "%s.h5" at: %s/\n' %
                                 (savename, savepath))
                sys.stdout.flush()
Пример #4
0
def calc_transversal_probability_density(r_max, nx, nb, ni, rbunch, lbunch):
    ELECTRON_CHARGE_IN_COUL = 1.60217657e-19
    ELECTRON_MASS_IN_KG = 9.10938291e-31
    VAC_PERMIT_FARAD_PER_M = 8.854187817e-12
    SPEED_OF_LIGHT_IN_M_PER_S = 299792458
    omega_alpha = 4.13e16
    # [s^-1]
    E_alpha = 5.1e11
    # [V/m]
    elec_density = 1e+23  # [1/m^3]
    omega_p = np.sqrt(4 * np.pi * elec_density * (ELECTRON_CHARGE_IN_COUL**2) /
                      (VAC_PERMIT_FARAD_PER_M * ELECTRON_MASS_IN_KG))
    E_0 = omega_p * ELECTRON_MASS_IN_KG * SPEED_OF_LIGHT_IN_M_PER_S / ELECTRON_CHARGE_IN_COUL
    #Use zeta array in order to calculate delta t

    savepath = './plots/g3d-line/'
    mkdirs_if_nexist(savepath)

    bunch_array = np.arange(0, lbunch + lbunch / 10, lbunch / 10)
    bunch_array_sum = np.cumsum(bunch_array)

    deltat = np.abs(bunch_array_sum) / omega_p

    vcalc_ion_rate = np.vectorize(calc_ion_rate)

    r_array = np.arange(0, r_max + r_max / nx, r_max / nx)

    c1prime = -1 / 2 * nb
    c3prime = -1 / 2 * rbunch**2 * (nb)

    savename = 'Ex_analytic'

    E = np.zeros(shape=np.shape(r_array))
    for i in range(len(r_array)):
        if (r_array[i] <= rbunch):
            E[i] = np.real(c1prime) * r_array[i]
        else:
            E[i] = np.real(c3prime) / r_array[i]

    fig = plt.figure()
    ax = fig.add_subplot(111)

    ax.plot(np.append(-r_array[::-1], r_array), np.append(-(E[::-1]), E[:]))
    x, Ex = plot_hipace_Ex(-0.2)  # input = zeta pos
    ax.plot(x, Ex)

    h5lp = H5Plot()
    h5lp.inherit_matplotlib_line_plots(ax)
    h5lp.write(savepath + '/' + savename + '.h5')
    plt.show()
    #use zeta array for shaping the elctric field to get the same spacing etc.
    #print(Earray)

    ionization_rate = np.zeros(shape=np.shape(r_array))
    ionization_rate[:] = vcalc_ion_rate(E * E_0, 1, 13.659843449, 13.659843449,
                                        0, 0)  # complete formulae for hydrogen
    #print(ionization_rate[1])

    fig = plt.figure()
    ax = fig.add_subplot(111)
    #print('Deltat is %0.3e' %deltat)
    #computing the ionization probability

    savename = 'ion_probability_test'
    ion_probability = np.zeros(shape=(len(bunch_array) - 1,
                                      len(ionization_rate)))
    for i in range(1, 2):  #len(bunch_array)):
        ion_probability[i -
                        1, :] = 1.0 - np.exp(-ionization_rate[:] * deltat[i])
        ax.plot(np.append(-r_array[::-1], r_array),
                np.append((ion_probability[i - 1, ::-1]),
                          ion_probability[i - 1, :]),
                label=('prob at lb: ' +
                       str(np.around(bunch_array[i], decimals=1))))
        #ax.legend()

    h5lp = H5Plot()
    h5lp.inherit_matplotlib_line_plots(ax)
    h5lp.write(savepath + '/' + savename + '.h5')
    plt.show()
Пример #5
0
    def plot_deltarho_rhomax_sheathcharge(self):

        if not hasattr(self, 'rb'):
            self.calc_rb()

        if not hasattr(self, 'rho_max'):
            self.calc_deltarho_rhomax_sheathcharge()

        fig_charge = plt.figure()
        plt.plot(self.zeta_array, self.charge)
        ax_charge = plt.gca()
        ax_charge.set_ylabel(r'$\lambda=\int_{r_b}^\infty r \rho(r) dr$',
                             fontsize=14)
        ax_charge.set_xlabel(r'$k_p \zeta$', fontsize=14)
        charge_fileprefix = 'charge'

        fig_rhomax = plt.figure()
        plt.plot(self.zeta_array, self.rho_max)
        plt.plot(self.zeta_array, self.rho_flocmax)
        ax_rhomax = plt.gca()
        ax_rhomax.legend(
            [r'using global maximum', r'using first local maximum'])
        ax_rhomax.set_ylabel(r'$\rho_\mathrm{max}$', fontsize=14)
        ax_rhomax.set_xlabel(r'$k_p \zeta$', fontsize=14)
        rhomax_fileprefix = 'rho_max'

        fig_deltarho = plt.figure()
        plt.plot(self.zeta_array, self.delta_rho)
        plt.plot(self.zeta_array, self.delta_rho_flocmax)
        ax_deltarho = plt.gca()
        ax_deltarho.legend(
            [r'using global maximum', r'using first local maximum'])
        ax_deltarho.set_ylabel(r'$\Delta_\rho$', fontsize=14)
        ax_deltarho.set_xlabel(r'$k_p \zeta$', fontsize=14)
        deltarho_fileprefix = 'delta_rho'

        filesuffix = '_t_%06.f' % (np.floor(self.g3d.get_time()))
        saveformat = 'eps'
        savepath = self.args.savepath

        mkdirs_if_nexist(savepath)

        charge_savename = charge_fileprefix + filesuffix + '.' + saveformat
        rhomax_savename = rhomax_fileprefix + filesuffix + '.' + saveformat
        deltarho_savename = deltarho_fileprefix + filesuffix + '.' + saveformat

        fig_charge.savefig(savepath + '/' + charge_savename, format=saveformat)
        if self.args.verbose:
            print('Saved "' + charge_savename + '" at: ' + self.args.savepath)

        fig_rhomax.savefig(savepath + '/' + rhomax_savename, format=saveformat)
        if self.args.verbose:
            print('Saved "' + rhomax_savename + '" at: ' + self.args.savepath)

        fig_deltarho.savefig(savepath + '/' + deltarho_savename,
                             format=saveformat)
        if self.args.verbose:
            print('Saved "' + deltarho_savename + '" at: ' +
                  self.args.savepath)

        if self.args.h5plot:
            h5lp = H5Plot()
            h5lp.inherit_matplotlib_line_plots(ax_charge)
            h5lp.write(savepath + '/' + charge_fileprefix + filesuffix + '.h5')

            h5lp = H5Plot()
            h5lp.inherit_matplotlib_line_plots(ax_rhomax)
            h5lp.write(savepath + '/' + rhomax_fileprefix + filesuffix + '.h5')

            h5lp = H5Plot()
            h5lp.inherit_matplotlib_line_plots(ax_deltarho)
            h5lp.write(savepath + '/' + deltarho_fileprefix + filesuffix +
                       '.h5')

        plt.show()
Пример #6
0
def main():

    parser = h5plot_parser()
    args = parser.parse_args()

    if len(sys.argv) == 1:
        parser.print_help()
        sys.exit(1)

    fig = plt.figure(figsize=(6, 5))

    if (args.line_no != None) and (len(args.line_no) != len(args.paths)):
        print(
            'ERROR: number of selected lines must be equal to the number of provided hdf5 files!'
        )
        sys.exit(1)

    if (args.labels != None) and (len(args.labels) != len(args.paths)):
        print(
            'ERROR: number of prepend labels must be equal to the number of provided hdf5 files!'
        )
        sys.exit(1)

    h5lp = []

    linestyles = ['-', '--', '-.', ':']
    save_append_str = ''
    type_str = 'comp'

    if not args.latexoff:
        plt.rc('text', usetex=True)
        plt.rc('font', family='serif')

    j = 0
    if args.diff:
        h5firstlp = H5Plot()
        h5firstlp.read(args.paths[0])
        type_str = 'diff'
        for (x, y, label, linestyle, color) in h5firstlp.get_line_plots():
            if j == 0:
                x0 = x
                y0 = y
            j += 1

    h5firstlp = H5Plot()
    h5firstlp.read(args.paths[0])
    for (x, y, label, linestyle, color) in h5firstlp.get_line_plots():
        if not args.extrue:
            if (any(y < 0) and any(y > 0)):
                for i in range(1, len(x)):
                    if y[i] > 0 and y[i - 1] < 0:
                        y_strich = -(y[i + 5] - y[i - 6]) / abs(x[i + 5] -
                                                                x[i - 6])
                        print('slope around root: from %f to %f  is : %f' %
                              ((x[i + 5]), x[i - 6], y_strich))
            else:
                print('there are not roots')
        else:
            for i in range(1, len(x)):
                if x[i - 1] * x[i] < 0:
                    y_strich = (y[i] - y[i - 1]) / abs(x[i] - x[i - 1])
                    print('slope at x = %f is : %f' %
                          ((x[i] + x[i - 1]) / 2, y_strich))

    i = 0
    for path in args.paths:
        if not os.path.isfile(path):
            print('ERROR: File %s does not exist!' % path)
            sys.exit(1)

        h5lp.append(H5Plot())
        h5lp[i].read(path)

        if args.cno == None:
            argcolor = plt.cm.Dark2(i)
        else:
            argcolor = plt.cm.Dark2(args.cno[i])

        j = 0
        for (x, y, label, linestyle, color) in h5lp[i].get_line_plots():
            if args.labels != None:
                save_append_str += '_' + args.labels[i]
                label = args.labels[i]

            if label == '_line0':
                label = path

            if not args.latexoff:
                if label[0] != '$' or label[-1] != '$':
                    label = r'$\textrm{' + label + '}$'

            if args.diff:
                if (j == 0 and i == 0):
                    continue
                else:
                    y -= np.interp(x, x0, y0)

            if args.lstyle == None:
                linestyle_code = linestyles[i % len(linestyles)]
            else:
                linestyle_code = linestyles[args.lstyle[i]]

            if (args.line_no != None):
                if args.line_no[i] == j:
                    if args.absylog:
                        plt.semilogy(x,
                                     y,
                                     label=label,
                                     linestyle=linestyle_code,
                                     color=argcolor)
                    else:
                        plt.plot(x,
                                 y,
                                 label=label,
                                 linestyle=linestyle_code,
                                 color=argcolor)
            else:
                if args.absylog:
                    plt.semilogy(x,
                                 y,
                                 label=label,
                                 linestyle=linestyle_code,
                                 color=argcolor)
                else:
                    #plt.plot(x, y, label=label, linestyle=linestyle, color=color)
                    plt.plot(x,
                             y,
                             label=label,
                             linestyle=linestyle_code,
                             color=argcolor)
            j += 1
        i += 1

    ax = plt.gca()
    ax.set_xlabel(h5lp[0].get_xlab(), fontsize=14)
    ax.set_ylabel(h5lp[0].get_ylab(), fontsize=14)
    handles, labels = ax.get_legend_handles_labels()
    #plt.legend(flip(handles, 2), flip(labels, 2), ncol=2)
    plt.legend(frameon=False)
    plt.gcf().subplots_adjust(left=0.15, bottom=0.15)
    if not (-3.0 < math.log(np.max(abs(y)), 10) < 3.0):
        ax.yaxis.set_major_formatter(FormatStrFormatter('%.1e'))
        plt.gcf().subplots_adjust(left=0.18)
    plt.show()
    fname, fext = os.path.splitext(args.paths[0])

    save_path_name = fname + save_append_str + '_' + type_str + '.' + args.file_format
    fig.savefig(save_path_name, format=args.file_format)
    plt.close(fig)
    if args.verbose:
        sys.stdout.write('Saved: %s\n' % save_path_name)
        sys.stdout.flush()
Пример #7
0
def main():

    parser = h5plot_parser()
    args = parser.parse_args()

    if len(sys.argv) == 1:
        parser.print_help()
        sys.exit(1)

    fig = plt.figure(figsize=(6, 5))

    if (args.line_no != None) and (len(args.line_no) != len(args.paths)):
        print(
            'ERROR: number of selected lines must be equal to the number of provided hdf5 files!'
        )
        sys.exit(1)

    if (args.labels != None) and (len(args.labels) != len(args.paths)):
        print(
            'ERROR: number of prepend labels must be equal to the number of provided hdf5 files!'
        )
        sys.exit(1)

    h5lp = []

    linestyles = ['-', '--', '-.', ':']
    save_append_str = ''
    type_str = 'comp'

    if not args.latexoff:
        plt.rc('text', usetex=True)
        plt.rc('font', family='serif')

    j = 0
    if args.diff:
        h5firstlp = H5Plot()
        h5firstlp.read(args.paths[0])
        type_str = 'diff'
        for (x, y, label, linestyle, color) in h5firstlp.get_line_plots():
            if j == 0:
                x0 = x
                y0 = y
            j += 1

    h5firstlp = H5Plot()
    h5firstlp.read(args.paths[0])
    for (x, y, label, linestyle, color) in h5firstlp.get_line_plots():
        x_p = x[int(np.floor(len(x) / 2)):]
        y_p = y[int(np.floor(len(y) / 2)):]

        n = len(x_p)  #the number of data
        mean = sum(x_p * y_p) / n  #note this correction
        sigma = sum(y_p * (x_p - mean)**2) / n

        def gaus(x, a, x0, sigma):
            return a * exp(-(x - x0)**2 / (2 * sigma**2))

        popt, pcov = curve_fit(gaus, x_p, y_p, p0=[max(y_p), mean, sigma])

    i = 0
    for path in args.paths:
        if not os.path.isfile(path):
            print('ERROR: File %s does not exist!' % path)
            sys.exit(1)

        h5lp.append(H5Plot())
        h5lp[i].read(path)

        if args.cno == None:
            argcolor = plt.cm.Dark2(i)
        else:
            argcolor = plt.cm.Dark2(args.cno[i])

        j = 0
        for (x, y, label, linestyle, color) in h5lp[i].get_line_plots():
            if args.labels != None:
                save_append_str += '_' + args.labels[i]
                label = args.labels[i]

            if label == '_line0':
                label = path

            if not args.latexoff:
                if label[0] != '$' or label[-1] != '$':
                    label = r'$\textrm{' + label + '}$'

            if args.diff:
                if (j == 0 and i == 0):
                    continue
                else:
                    y -= np.interp(x, x0, y0)

            if args.lstyle == None:
                linestyle_code = linestyles[i % len(linestyles)]
            else:
                linestyle_code = linestyles[args.lstyle[i]]

            if (args.line_no != None):
                if args.line_no[i] == j:
                    if args.absylog:
                        plt.semilogy(x,
                                     y,
                                     label=label,
                                     linestyle=linestyle_code,
                                     color=argcolor)
                    else:
                        plt.plot(x,
                                 y,
                                 label=label,
                                 linestyle=linestyle_code,
                                 color=argcolor)
                        plt.plot(x_p, gaus(x_p, *popt), 'r--', label='fit')
            else:
                if args.absylog:
                    plt.semilogy(x,
                                 y,
                                 label=label,
                                 linestyle=linestyle_code,
                                 color=argcolor)
                else:
                    #plt.plot(x, y, label=label, linestyle=linestyle, color=color)
                    plt.plot(x,
                             y,
                             label=label,
                             linestyle=linestyle_code,
                             color=argcolor)
                    plt.plot(x_p, gaus(x_p, *popt), 'r--', label='fit')
            j += 1
        i += 1

    ax = plt.gca()
    ax.set_xlabel(h5lp[0].get_xlab(), fontsize=14)
    ax.set_ylabel(h5lp[0].get_ylab(), fontsize=14)
    handles, labels = ax.get_legend_handles_labels()
    #plt.legend(flip(handles, 2), flip(labels, 2), ncol=2)
    plt.legend(frameon=False)
    plt.gcf().subplots_adjust(left=0.15, bottom=0.15)
    if not (-3.0 < math.log(np.max(abs(y)), 10) < 3.0):
        ax.yaxis.set_major_formatter(FormatStrFormatter('%.1e'))
        plt.gcf().subplots_adjust(left=0.18)
    plt.show()
    fname, fext = os.path.splitext(args.paths[0])

    save_path_name = fname + save_append_str + '_' + type_str + '.' + args.file_format
    fig.savefig(save_path_name, format=args.file_format)
    plt.close(fig)
    if args.verbose:
        sys.stdout.write('Saved: %s\n' % save_path_name)
        sys.stdout.flush()
Пример #8
0
def main():


    parser = h5plot_parser()
    args = parser.parse_args()

    if args.maketitle:
        ''' Calculating plasma frequency for length '''
        ELECTRON_CHARGE_IN_COUL   =    1.60217657e-19
        ELECTRON_MASS_IN_KG       =    9.10938291e-31
        VAC_PERMIT_FARAD_PER_M    =    8.854187817e-12
        SPEED_OF_LIGHT_IN_M_PER_S =    299792458.0

        omega_p = np.sqrt( args.n0 * (ELECTRON_CHARGE_IN_COUL**2)/ (VAC_PERMIT_FARAD_PER_M * ELECTRON_MASS_IN_KG));
        skin_depth = SPEED_OF_LIGHT_IN_M_PER_S/omega_p
        
        

    if len(sys.argv)==1:
        parser.print_help()
        sys.exit(1)

    saveformat = args.file_format

    h5lp = []

    linestyles = ['-', '--', '-.', ':']
    save_append_str = ''
    type_str = 'comp'

    if args.latexon:
        plt.rc('text', usetex=True)
        plt.rc('font', family='serif') 

    j = 0

    i = 0
    
    
    
    for path in args.paths:
        fig = plt.figure(figsize=(7,5))
        if not os.path.isfile(path):
            print('ERROR: File %s does not exist!' % path)
            sys.exit(1)          
            
        h5lp.append(H5Plot())
        h5lp[i].read(path)
        timestamp = path.split("_")[-1].split(".h5")[0]
        
        if args.data2:
            for files in args.data2:
                if timestamp in files or args.manual:
                    print('Reading second data set...')
                    h5secondlp = H5Plot()
                    h5secondlp.read(files)

        
        
        
        if args.cno == None:
            argcolor = plt.cm.tab20(6)
        else:
            argcolor = plt.cm.tab20(args.cno[0])
        
        j = 0
        for (x, y, label, linestyle, color) in h5lp[i].get_line_plots():
            if args.labels != None:
                save_append_str += '_' + args.labels[i]
                label = args.labels[i]

            if label == '_line0':
                label = path

            if args.latexon:
                if label[0] != '$' or label[-1] != '$':
                    label = r'$\textrm{' + label + '}$'


            if args.abs:
                y = np.abs(y)

            if args.lstyle == None:
                linestyle_code = linestyles[0]
            else:
                linestyle_code = linestyles[args.lstyle[0]]

            
            if args.absylog:
                plt.semilogy( x, y, label=label, linestyle=linestyle_code, color=argcolor, zorder=20)
            else:    
                #plt.plot(x, y, label=label, linestyle=linestyle, color=color)
                plt.plot(x, y, label=label, linestyle=linestyle_code, color=argcolor, zorder=20)      
            

        ax = plt.gca()
        ax.tick_params('y', colors=argcolor)
        plt.gcf().subplots_adjust(left=0.15, bottom=0.15, right=1-0.15)       
        if not (-3.0 < math.log(np.max(abs(y)),10) < 3.0):
            ax.yaxis.set_major_formatter(FormatStrFormatter('%.1e'))
            plt.gcf().subplots_adjust(left=0.18) 
        ax2 = ax.twinx()
        
        ''' PLOTTING THE SECOND PLOT '''
        if args.cno == None:
            argcolor = plt.cm.tab20(1)
        else:
            argcolor = plt.cm.tab20(args.cno[1])
        ax2.tick_params('y', colors=argcolor)
        j = 0
        for (x2, y2, label, linestyle, color) in h5secondlp.get_line_plots():
            if args.labels != None:
                save_append_str += '_' + args.labels[i]
                label = args.labels[i]

            if label == '_line0':
                label = path

            if args.latexon:
                if label[0] != '$' or label[-1] != '$':
                    label = r'$\textrm{' + label + '}$'

            if args.abs:
                y2 = np.abs(y2)

            if args.lstyle == None:
                linestyle_code = linestyles[0]
            else:
                linestyle_code = linestyles[args.lstyle[1]]

            
            if args.absy2log:
                plt.semilogy( x2, y2, label=label, linestyle=linestyle_code, color=argcolor, zorder=0)
            else:    
                #plt.plot(x, y, label=label, linestyle=linestyle, color=color)
                plt.plot(x2, y2, label=label, linestyle=linestyle_code, color=argcolor, zorder=0)      
            



        if args.xlim != None:
            ax.set_xlim(args.xlim[0],args.xlim[1])
        if args.ylim != None:
            ax.set_ylim(args.ylim[0],args.ylim[1])
        if args.y2lim != None:
            ax2.set_ylim(args.y2lim[0],args.y2lim[1])
            
        if args.xlab != None:
            xlab = args.xlab
        else:
            xlab = h5lp[0].get_xlab()
    

        if args.ylab != None:
            ylab = args.ylab
        else:
            ylab = []
            ylab.append(h5lp[0].get_ylab())
            ylab.append(h5secondlp.get_ylab())
            
        if args.latexon:
            if xlab[0] != '$' or xlab[-1] != '$':
                        xlab = r'$' + xlab + '$'
                        
                        
        if args.latexon:
            if ylab[0,0] != '$' or ylab[0,-1] != '$':
                        ylab[0] = r'$' + ylab[0] + '$'
                        ylab[1] = r'$' + ylab[1] + '$'

        ax.set_xlabel(xlab, fontsize=14)
        ax.set_ylabel(ylab[0], fontsize=14)
        ax2.set_ylabel(ylab[1], fontsize=14)   
        
        
        ax.set_zorder(ax2.get_zorder()+1) # put ax in front of ax2
        ax.patch.set_visible(False) # hide the 'canvas' 
        # handles, labels = ax.get_legend_handles_labels()
        # #plt.legend(flip(handles, 2), flip(labels, 2), ncol=2)
        # plt.legend(frameon=False)
        #plt.gcf().subplots_adjust(left=0.15, bottom=0.15, right=0.15)       
        if not (-3.0 < math.log(np.max(abs(y2)),10) < 3.0):
            ax2.yaxis.set_major_formatter(FormatStrFormatter('%.1e'))
            plt.gcf().subplots_adjust(right=1-0.18)          
        #plt.show()

        ''' make the title '''
        if args.maketitle:
            time = np.around(float(timestamp))
            distance = time*skin_depth*1e2
            title = 'Time: ' + str(time) + r'$\,\omega_p^{-1}$ ' + '   Distance: ' + str(np.around(distance,2)) + r'$\,$cm'
            plt.title(title)
            
        if args.show:
            plt.show()
            
        spath, fname  = os.path.split(args.paths[0])
        if args.savepath != None:
            spath = args.savepath

        if not args.manual:
            save_name = type_str + '_' + fname + save_append_str + '_' +  timestamp
        else:
            save_name = type_str + '_' + fname + save_append_str
        
        if saveformat==args.file_format:
            saveas_png(fig, spath, save_name, args.dpi)
        else:
            saveas_eps_pdf(fig, savepath=spath, savename=save_name)
        

        
        plt.close(fig)