def plot_hist(rtts):
import hplotting
gp = hplotting.gp_plotter(loglog=False)
data = '\n'.join(['%.6f' % rtt for rtt in rtts])
gp.setup(xlabel='bin width = 1e-6 s')
gp.cmd('binwidth=1e-6')
gp.cmd('set boxwidth binwidth')
gp.cmd('bin(x,width)=width*floor(x/width) + binwidth/2.0')
gp.cmd("plot '-' using (bin($1,binwidth)):(1.0) smooth freq with boxes\n %s\n e" % (data), flush=True)
gp.quit()
def xcplotter(xc, gp=None):
"""Initialize gnuplot and periodically update the graph."""
if options.no_plot: return
gp = hplotting.gp_plotter()
if not gp.gp: return
getdata_str = xc.getdata_str
gp_cmd = gp.cmd
xc_conf_int = xc.conf_int
fps = 1.0/options.fps
# use these to plot axis ranges
min_x, max_x = (1,options.L)
min_y, max_y = (1e-6,1e-0)
# set plot options
gp.setup(xlabel='log_{10}(lag) [s]',
ylabel='log_{10}(autocovariance)',
xrange=(min_x, max_x),
yrange=(min_y,max_y),
xtics=[(i*options.delta,i) for i in 10**arange(log10(options.L)+1)],
)
ydata = ''
i=0
while xc.is_alive():
i += 1
if i%10==0: # plot confidence levels every 10 frames
ci_level = xc_conf_int()
#gp.arrow(min_x, ci_level, max_x, ci_level, '3', 8)
gp.level(ci_level, min_x, max_x)
# TODO does not terminate cleanly if X11 display cannot be opened
time.sleep(fps)
ydata = getdata_str()
if ydata:
gp_cmd("plot '-' with points ls 3\n %s\n e" % ydata, flush=True)
# calculate confidence interval
ci_level = xc_conf_int()
# plot confidence interval level
#gp.arrow(min_x, ci_level, max_x, ci_level, '3', 8)
gp.level(ci_level, min_x, max_x)
# perform fitting for values larger than ci_level
(d,y0) = xc.fit() # TODO thresh=ci_level
H = xc.hurst(d)
ydata = getdata_str()
if H:
# plot H linear fit and label it
gp.label('H=%.2f' % H, 2, 1.2*(y0))
gp.arrow(1, y0, xc.L, y0*xc.L**d, '4')
#xh = 10**((log10(ci_level)-log10(y0))/d)
#gp.arrow(1, y0, xh, y0*xh**d, '4')
if ydata:
gp_cmd("plot '-' with points ls 3\n %s\n e" % ydata)
# save plot to EPS
gp.set_term_eps(options.savefile)
# we must replot everything to save it to the file
# plot H linear fit and label it
gp.label('H=%.2f' % H, 2, 1.2*(y0))
#gp.arrow(1, y0, xc.L, y0*xc.L**d, '4')
gp.level(ci_level, min_x, max_x)
if ydata:
gp_cmd("plot '-' with points ls 3\n %s\n e" % ydata)
gp.quit()
def avplotter(av):
if not options.plot: return
gp = hplotting.gp_plotter()
if not gp.gp: return
getdata_str = av.getdata_str
gp_cmd = gp.cmd
fps = 1.0/options.fps
# use these to plot axis ranges
min_x = options.M[0]*options.delta
max_x = options.M[1]*options.delta
min_y, max_y = (1e-5,1e-0)
# set plot options
gp.setup(xlabel='log_{10}(M) [s]',
ylabel='log_{10}(aggregate variance)',
xrange=(min_x, max_x),
yrange=(min_y, max_y),
)
# draw auxiliarry lines
#y0=1e-0
#gp.arrow(min_x,y0, max_x,y0/(max_x/options.delta))
#gp.arrow(min_x,y0, y0/0.1,1e-4)
i = 0
try:
while av.is_alive():
#if not gp.gp: break
i += 1
if i%10==0: # calculate and plot hurst fit every 10 frames
(d,y0) = av.fit()
if y0!=-1:
# plot H linear fit and label it
gp.arrow(min_x, y0*(min_x/options.delta)**d, max_x, y0*(max_x/options.delta)**d,'2')
# sleep before redrawing
time.sleep(fps)
data = getdata_str()
if data:
gp_cmd("plot '-' with points ls 4\n %s\n e\n" % (data), flush=True)
except ValueError as e:
print e # gnuplot error
return
# replot with label
(d,y0) = av.fit()
if y0!=-1:
# plot H linear fit and label it
gp.label('H=%.2f' % (av.hurst(d)), min_x*5, 2*y0*(min_x*5/options.delta)**d, '2')
gp.arrow(min_x, y0*(min_x/options.delta)**d, max_x, y0*(max_x/options.delta)**d,'2')
data = getdata_str()
if data:
gp_cmd("plot '-' with points ls 4\n %s\n e\n" % (data), flush=True)
# save plot to EPS
gp.set_term_eps(options.savefile)
# we must replot everything to save it to the file
(d,y0) = av.fit()
if y0!=-1:
# plot H linear fit and label it
gp.label('H=%.2f' % (av.hurst(d)), min_x*5, 2*y0*(min_x*5/options.delta)**d, '2')
gp.arrow(min_x, y0*(min_x/options.delta)**d, max_x, y0*(max_x/options.delta)**d,'2')
data = getdata_str()
gp_cmd("plot '-' with points ls 4\n %s\n e\n" % (data), flush=True)
gp.quit()
