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)
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)
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)
