plot P-V-T EOS curve fitting result

    :param fit_result: lmfit result object, see example jnb file for detail
    :param v_label: label for volume axis
    :param temp_fitline: temperatures to calculate isothermal compression
        curves, default = [300., 1000., 1500., 2000., 2500., 3000.]
    :param figsize: figure size, default = (7,7)
    :param height_ratios: height ratio between the main and residue plots,
        default = (3,1)
    :param ms_data: marker size for data points
    :param p_err: pressure error bar
    :param v_err: volume error bar
    :param cbar_loc: location of color bar
    :param pdf_filen: name of pdf output file
    :param title: title of the figure
    :return: None

def thermal_fit_result(fit_result, v_residual=None,
                       v_label='Unit-cell volume $(\mathrm{\AA}^3)$',
                       temp_fitline=np.asarray(
                           [300., 1000., 1500., 2000., 2500., 3000.]),
                       figsize=(5, 5), height_ratios=(3, 1), ms_data=50,
                       p_err=None, v_err=None, cbar_loc=(0.99, 0.1, .01, 0.82),
                       pdf_filen=None, title='Fit result'):
    """
    plot P-V-T EOS curve fitting result

    :param fit_result: lmfit result object, see example jnb file for detail
    :param v_label: label for volume axis
    :param temp_fitline: temperatures to calculate isothermal compression
        curves, default = [300., 1000., 1500., 2000., 2500., 3000.]
    :param figsize: figure size, default = (7,7)
    :param height_ratios: height ratio between the main and residue plots,
        default = (3,1)
    :param ms_data: marker size for data points
    :param p_err: pressure error bar
    :param v_err: volume error bar
    :param cbar_loc: location of color bar
    :param pdf_filen: name of pdf output file
    :param title: title of the figure
    :return: None
    """
    # basic figure setup
    f, ax = plt.subplots(2, 1, sharex=True, figsize=figsize,
                         gridspec_kw={'height_ratios': height_ratios})
    for ax_i in ax:
        ax_i.tick_params(direction='in')
    # read data to plot
    v_data = fit_result.userkws['v']
    temp_data = fit_result.userkws['temp']
    p_data = fit_result.data
    p_datafit = fit_result.best_fit
    v0 = uct.ufloat(fit_result.params['st_v0'].value,
                    fit_result.params['st_v0'].stderr)
    sm = plt.cm.ScalarMappable(cmap=c_map,
                               norm=plt.Normalize(
                                   vmin=300., vmax=temp_data.max()))
    a = sm.to_rgba(temp_fitline)
    v_fitline = np.linspace(v0.n, min(v_data), 1000)
    fitmodel_copy = copy.deepcopy(fit_result)
    for a_i, temp_i in zip(a, temp_fitline):
        p_fitline = fitmodel_copy.eval(v=v_fitline,
                                       temp=np.ones_like(v_fitline) * temp_i)
        ax[0].plot(p_fitline, v_fitline, c=a_i)
    # error range here does not make a lot sense, so not supported
    # if (p_err is not None) and (v_err is not None):
    ax[0].errorbar(p_data, v_data, xerr=p_err, yerr=v_err, fmt=' ', c='k',
                   capsize=0, elinewidth=0.5, label='Data', zorder=0)
    points = ax[0].scatter(p_data, v_data, marker='o', s=ms_data, c=temp_data,
                           cmap=c_map, vmin=300., vmax=temp_data.max(),
                           zorder=1)
    if v_residual is None:
        ax[1].scatter(p_data, p_data - p_datafit, marker='o', s=ms_data,
                      c=temp_data, cmap=c_map, vmin=300.,
                      vmax=temp_data.max(), zorder=1)
        ax[1].errorbar(p_data, p_data - p_datafit, yerr=p_err, fmt=' ', c='k',
                       capsize=0, elinewidth=0.5, label='Data', zorder=0)
        ax[1].set_ylabel('$P_{obs} - P_{fit}$')
    else:
        ax[1].scatter(p_data, v_residual, marker='o', s=ms_data, c=temp_data,
                      cmap=c_map, vmin=300., vmax=temp_data.max(), zorder=1)
        ax[1].errorbar(p_data, v_residual, yerr=p_err, fmt=' ', c='k',
                       capsize=0, elinewidth=0.5, label='Data', zorder=0)
        ax[1].set_ylabel('$V_{obs} - V_{fit}$')
    # ax[0].legend()
    position = f.add_axes(cbar_loc)
    f.colorbar(points, orientation="vertical", cax=position,
               ticks=temp_fitline)
    ax[1].axhline(0, c='k', ls='--')
    ax[1].set_xlabel('Pressure (GPa)')
    ax[0].set_ylabel(v_label)
    ax[0].set_title(title)
    plt.tight_layout()
    if pdf_filen is not None:
        f.savefig(pdf_filen)