Python add_arguments Examples

Example #1

File: plot.py Project: placrosse/kodo

    def plot_setup(p):
        pylab.ylabel("Overhead [\%]")
        pylab.yscale('log')
        pylab.xscale('log', basex=2)
        pylab.xticks(
            list(scipy.unique(group['symbols'])),
            list(scipy.unique(group['symbols'])))
        plotter.set_slave_info(slavename)
        plotter.set_markers(p)

    for (slavename, symbols), group in sparse:
        p = group.pivot_table('mean', rows='symbols',
                              cols=['field', 'density']).plot()
        plot_setup(p)
        plotter.set_legend_title("(Field, Density)")
        plotter.write("sparse", slavename)

    for (slavename, symbols), group in dense:
        p = group.pivot_table('mean',  rows='symbols',
                              cols=['field', 'algorithm']).plot()
        plot_setup(p)
        plotter.set_legend_title("(Field, Algorithm)")
        plotter.write("dense", slavename)

    return df

if __name__ == '__main__':
    args = plot_helper.add_arguments(["json", "date", "output-format"])
    df = plot(args)

Example #2

File: plot.py Project: GOPRO1955/kodo

    def plot_setup(p):
        pylab.ylabel("Extra symbols [{}]".format(list(group['unit'])[0]))
        pylab.xscale('log', basex=2)
        pylab.xticks(list(scipy.unique(group['symbols'])))
        plotter.set_slave_info(slavename)
        plotter.set_markers(p)

    for (slavename, symbols), group in sparse:
        p = group.pivot_table('mean',
                              rows='symbols',
                              cols=['field', 'density']).plot()
        plot_setup(p)
        plotter.set_legend_title("(Field, Density)")
        plotter.write("sparse", slavename)

    for (slavename, symbols), group in dense:
        p = group.pivot_table('mean',
                              rows='symbols',
                              cols=['field', 'algorithm']).plot()
        plot_setup(p)
        plotter.set_legend_title("(Field, Algorithm)")
        plotter.write("dense", slavename)

    return df


if __name__ == '__main__':
    args = plot_helper.add_arguments(["json", "date", "output-format"])
    df = plot(args)

Example #3

File: plot_comparison.py Project: GOPRO1955/kodo

                pylab.ylabel("Throughput gain [\%]")
                pylab.xscale('log', basex=2)
                pylab.xticks(
                    list(scipy.unique(group['symbols'])),
                    list(scipy.unique(group['symbols'])))
                plotter.set_markers(p)
                plotter.set_slave_info(slavename)

            for symbols, group in sparse:
                p = group.pivot_table(
                    'gain',
                    rows='symbols',
                    cols=['field', 'density']).plot()
                plot_setup(p)
                plotter.set_legend_title("(Field, Density)")
                plotter.write("sparse", slavename)

            for symbols, group in dense:
                p = group.pivot_table('gain',  rows='symbols',
                                  cols=['field', 'algorithm']).plot()
                plot_setup(p)
                plotter.set_legend_title("(Field, Algorithm)")
                plotter.write("dense", slavename)

    return df

if __name__ == '__main__':
    args = plot_helper.add_arguments(
        ["coder", "date", "days", "output-format"])
    df = plot(args)