def covlen(args):
    """
    %prog covlen covfile fastafile

    Plot coverage vs length. `covfile` is two-column listing contig id and
    depth of coverage.
    """
    import numpy as np
    import pandas as pd
    import seaborn as sns
    from jcvi.formats.base import DictFile

    p = OptionParser(covlen.__doc__)
    p.add_option("--maxsize", default=1000000, type="int", help="Max contig size")
    p.add_option("--maxcov", default=100, type="int", help="Max contig size")
    p.add_option("--color", default='m', help="Color of the data points")
    p.add_option("--kind", default="scatter",
                 choices=("scatter", "reg", "resid", "kde", "hex"),
                 help="Kind of plot to draw")
    opts, args, iopts = p.set_image_options(args, figsize="8x8")

    if len(args) != 2:
        sys.exit(not p.print_help())

    covfile, fastafile = args
    cov = DictFile(covfile, cast=float)
    s = Sizes(fastafile)
    data = []
    maxsize, maxcov = opts.maxsize, opts.maxcov
    for ctg, size in s.iter_sizes():
        c = cov.get(ctg, 0)
        if size < maxsize:
            continue
        if c > maxcov:
            continue
        data.append((size, c))

    x, y = zip(*data)
    x = np.array(x)
    y = np.array(y)
    logging.debug("X size {0}, Y size {1}".format(x.size, y.size))

    df = pd.DataFrame()
    xlab, ylab = "Length", "Coverage of depth (X)"
    df[xlab] = x
    df[ylab] = y
    sns.jointplot(xlab, ylab, kind=opts.kind, data=df,
                  xlim=(0, maxsize), ylim=(0, maxcov),
                  stat_func=None, edgecolor="w", color=opts.color)

    figname = covfile + ".pdf"
    savefig(figname, dpi=iopts.dpi, iopts=iopts)
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