How to use the jcvi.graphics.base.normalize_axes function in jcvi

loci = loci.split(",")
    for ax, locus in zip(axes, loci):
        plot_allelefreq(ax, df, locus)

    # Delete unused axes
    for ax in axes[len(loci):]:
        ax.set_axis_off()

    root = fig.add_axes([0, 0, 1, 1])
    pad = .03
    if not opts.nopanels:
        panel_labels(root, ((pad / 2, 1 - pad, "A"), (.5 + pad, 1 - pad, "B"),
                        (pad / 2, 2 / 3. - pad / 2, "C"), (.5 + pad, 2 / 3. - pad / 2, "D"),
                        (pad / 2, 1 / 3. , "E"), (.5 + pad, 1 / 3. , "F"),
                        ))
    normalize_axes(root)

    image_name = "allelefreq." + iopts.format
    savefig(image_name, dpi=iopts.dpi, iopts=iopts)

style="white", cmap="coolwarm")

    if len(args) != 1:
        sys.exit(not p.print_help())

    jsonfile, = args
    fig = plt.figure(figsize=(iopts.w, iopts.h))
    gs = gridspec.GridSpec(2, 2)
    ax1 = fig.add_subplot(gs[:, 0])
    ax2 = fig.add_subplot(gs[0, 1])
    ax3 = fig.add_subplot(gs[1, 1])
    plt.tight_layout(pad=3)
    pf = plot_panel(jsonfile, ax1, ax2, ax3, opts.cmap)

    root = fig.add_axes([0, 0, 1, 1])
    normalize_axes(root)

    image_name = "likelihood2.{}.".format(pf) + iopts.format
    savefig(image_name, dpi=iopts.dpi, iopts=iopts)

p.duplicate(a, b)
    p.draw()

    p = OpticalMapAlign(fig, [pad + 2 * w, 2 * w, w, w])
    p.invert(a, b)
    p.draw()

    p = OpticalMapAlign(fig, [pad + 2 * w, w, w, w])
    p.delete(a, b)
    p.draw()

    p = OpticalMapAlign(fig, [pad + 2 * w, 0, w, w])
    p.duplicate(a, b)
    p.draw()

    normalize_axes(root)

    image_name = mode + "." + iopts.format
    savefig(image_name, dpi=iopts.dpi, iopts=iopts)

colors = "rbg" if nval == 3 else ["lightgray"] + list("rbg")
    ystart = ymax
    for d in data:
        xstart = xmin
        for dd, c in zip(d, colors):
            xend = xstart + (xmax - xmin) * dd
            root.plot((xstart, xend), (ystart, ystart), "-", color=c)
            xstart = xend
        ystart -= yinterval

    root.text(.05, .5, "{0} LMD50 SNPs".format(len(data)),
              ha="center", va="center", rotation=90, color="lightslategray")

    for x, t, c in zip((.3, .5, .7), ("REF", "ALT", "HET"), "rbg"):
        root.text(x, .95, t, color=c, ha="center", va="center")
    normalize_axes(root)

    image_name = pf + "." + iopts.format
    savefig(image_name, dpi=iopts.dpi, iopts=iopts)

if calib:
            o.calibrate(pixel_cm_ratio, tr)
        print(o, file=fw)
        i = o.seedno
        if i > 7:
            continue
        ax4.text(.01, yy, str(i), va="center", bbox=dict(fc='none', ec='k'))
        ax4.text(.1, yy, o.pixeltag, va="center")
        yy -= .04
        ax4.add_patch(Rectangle((.1, yy - .025), .12, .05, lw=0,
                      fc=rgb_to_hex(o.rgb)))
        ax4.text(.27, yy, o.hashtag, va="center")
        yy -= .06
    ax4.text(.1 , yy, "(A total of {0} objects displayed)".format(nb_labels),
             color="darkslategray")
    normalize_axes(ax4)

    for ax in (ax1, ax2, ax3):
        xticklabels = [int(x) for x in ax.get_xticks()]
        yticklabels = [int(x) for x in ax.get_yticks()]
        ax.set_xticklabels(xticklabels, family='Helvetica', size=8)
        ax.set_yticklabels(yticklabels, family='Helvetica', size=8)

    image_name = op.join(outdir, pf + "." + iopts.format)
    savefig(image_name, dpi=iopts.dpi, iopts=iopts)
    return objects

dataA = import_data(dataA)
    dataB = import_data(dataB)
    dataC = import_data(dataC)
    dataD = import_data(dataD)
    subplot(A, dataA, "Inversion error rate", "Accuracy", xlim=.5)
    subplot(B, dataB, "Translocation error rate", "Accuracy", xlim=.5,
                      legend=("intra-chromosomal", "inter-chromosomal",
                              "75\% intra + 25\% inter"))
    subplot(C, dataC, "Number of input maps", "Accuracy", xcast=int)
    subplot(D, dataD, "Number of input maps", "Accuracy", xcast=int)

    labels = ((.03, .97, "A"), (.53, .97, "B"),
              (.03, .47, "C"), (.53, .47, "D"))
    panel_labels(root, labels)

    normalize_axes(root)
    image_name = "simulation." + iopts.format
    savefig(image_name, dpi=iopts.dpi, iopts=iopts)

duos, = ax.plot(duos, "o", mfc='w', mec='g')
    trios, = ax.plot(trios, "o", mfc='w', mec='b')
    ax.set_title("Mendelian errors based on trios and duos in HLI samples")
    nduos = "Mendelian errors in 362 duos"
    ntrios = "Mendelian errors in 339 trios"
    ax.legend([trios, duos], [ntrios, nduos], loc='best')

    ax.set_xticks(ticks)
    ax.set_xticklabels(treds, rotation=45, ha="right", size=8)
    yticklabels = [int(x) for x in ax.get_yticks()]
    ax.set_yticklabels(yticklabels, family='Helvetica')
    ax.set_ylabel("Mendelian errors (\%)")
    ax.set_ylim(ymin, 20)

    normalize_axes(root)

    image_name = "mendelian_errors." + iopts.format
    savefig(image_name, dpi=iopts.dpi, iopts=iopts)

ypos = y - pad
    xx = markers[0], ends[0]
    root.plot(xx, (ypos, ypos), "-", lw=2, color=lsg)
    root.text(sum(xx) / 2, ypos - pad, "34,115bp", **fontprop)
    xx = markers[1], begs[1]
    root.plot(xx, (ypos, ypos), "-", lw=2, color=lsg)
    root.text(sum(xx) / 2, ypos - pad, "81,276bp", **fontprop)

    root.plot((ends[0], begs[1]), (y, y), ":", lw=2, color=lsg)
    root.text(sum(markers) / 2, ypos - 3 * pad, r"$\textit{Estimated gap size: 96,433bp}$",
                                  color="r", ha="center", va="center")

    labels = ((.05, .95, 'A'), (.05, .6, 'B'), (.05, .27, 'C'))
    panel_labels(root, labels)
    normalize_axes(root)

    pf = "estimategaps"
    image_name = pf + "." + iopts.format
    savefig(image_name, dpi=iopts.dpi, iopts=iopts)

# ax4: Pair
    tredparse_results = parse_results("tredparse_results_het-pair.txt", exclude=20)
    title = SIMULATED_DIPLOID + " (Sub-model 4: Paired-end reads)"
    plot_compare(ax4, title, tredparse_results, None, color=color,
                 max_insert=max_insert, risk=False)

    for ax in (ax1, ax2, ax3, ax4):
        ax.set_xlim(0, max_insert)
        ax.set_ylim(0, max_insert)

    root = fig.add_axes([0, 0, 1, 1])
    pad = .03
    panel_labels(root, ((pad / 2, 1 - pad, "A"), (1 / 2., 1 - pad, "B"),
                        (pad / 2, 1 / 2. , "C"), (1 / 2., 1 / 2. , "D")))
    normalize_axes(root)

    image_name = "power." + iopts.format
    savefig(image_name, dpi=iopts.dpi, iopts=iopts)

solid_capstyle="round", solid_joinstyle="round")
    ax.plot(xdata, ydata, "k.", mec="k", mfc="w", mew=3, ms=12)
    ax.vlines(p, [0], [110], colors="beige", lw=3)
    normalize_lms_axis(ax, xlim=110, ylim=110)
    HorizontalChromosome(root, .6, .6 + w, .09, patch=patch,
                         height=.02, lw=2)
    scaffolds = ("a", "-c", "b")
    for i, s in enumerate(scaffolds):
        xx = (patch[i] + patch[i + 1]) / 2
        root.text(xx, .09, s, va="center", ha="center")
    root.text(.6 + w / 2, .04, "LMS($a||-c||b$) = 10", ha="center")

    labels = ((.05, .95, 'A'), (.05, .48, 'B'), (.55, .48, 'C'))
    panel_labels(root, labels)

    normalize_axes(root)

    pf = "lms"
    image_name = pf + "." + iopts.format
    savefig(image_name, dpi=iopts.dpi, iopts=iopts)