def quickplot(data, xmin, xmax, xlabel, title, ylabel="Counts",
              figname="plot.pdf", counts=True, print_stats=True):
    """
    Simple plotting function - given a dictionary of data, produce a bar plot
    with the counts shown on the plot.
    """
    plt.figure(1, (6, 6))
    left, height = zip(*sorted(data.items()))
    pad = max(height) * .01
    if counts:
        for l, h in zip(left, height):
            if xmax and l > xmax:
                break
            plt.text(l, h + pad, str(h), color="darkslategray", size=8,
                     ha="center", va="bottom", rotation=90)
    if xmax is None:
        xmax = max(left)

    plt.bar(left, height, align="center")
    plt.xlabel(markup(xlabel))
    plt.ylabel(markup(ylabel))
    plt.title(markup(title))
    plt.xlim((xmin - .5, xmax + .5))

    # Basic statistics
    messages = []
    counts_over_xmax = sum([v for k, v in data.items() if k > xmax])
    if counts_over_xmax:
        messages += ["Counts over xmax({0}): {1}".format(xmax, counts_over_xmax)]
    kk = []
    for k, v in data.items():
        kk += [k] * v
    messages += ["Total: {0}".format(np.sum(height))]
    messages += ["Maximum: {0}".format(np.max(kk))]
    messages += ["Minimum: {0}".format(np.min(kk))]
    messages += ["Average: {0:.2f}".format(np.mean(kk))]
    messages += ["Median: {0}".format(np.median(kk))]
    ax = plt.gca()
    if print_stats:
        write_messages(ax, messages)

    set_human_axis(ax)
    set_ticklabels_helvetica(ax)
    savefig(figname)
dataset/ETHPy150Open tanghaibao/jcvi/graphics/base.py/quickplot/original