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Copy pathplot_queue.py
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159 lines (134 loc) · 4.42 KB
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'''
Plot queue occupancy over time
'''
from helper import *
import plot_defaults
plot_defaults.quarter_size()
from matplotlib.ticker import MaxNLocator
from pylab import figure
parser = argparse.ArgumentParser()
parser.add_argument('--files', '-f',
help="Queue timeseries output to one plot",
required=True,
action="store",
nargs='+',
dest="files")
parser.add_argument('--maxy',
help="Max mbps on y-axis..",
type=int,
default=1000,
action="store",
dest="maxy")
parser.add_argument('--miny',
help="Min mbps on y-axis..",
type=int,
default=0,
action="store",
dest="miny")
parser.add_argument('--legend', '-l',
help="Legend to use if there are multiple plots. File names used as default.",
action="store",
nargs="+",
default=None,
dest="legend")
parser.add_argument('--out', '-o',
help="Output png file for the plot.",
default=None, # Will show the plot
dest="out")
parser.add_argument('-s', '--summarise',
help="Summarise the time series plot (boxplot). First 10 and last 10 values are ignored.",
default=False,
dest="summarise",
action="store_true")
parser.add_argument('--cdf',
help="Plot CDF of queue timeseries (first 10 and last 10 values are ignored)",
default=False,
dest="cdf",
action="store_true")
parser.add_argument('--labels',
help="Labels for x-axis if summarising; defaults to file names",
required=False,
default=[],
nargs="+",
dest="labels")
parser.add_argument('--every',
help="If the plot has a lot of data points, plot one every EVERY (x,y) point (default 1).",
default=1,
type=int)
args = parser.parse_args()
if args.labels is None:
args.labels = args.files
if args.legend is None:
args.legend = []
for file in args.files:
args.legend.append(file)
to_plot=[]
def get_style(i):
if i == 0:
return {'color': 'red'}
else:
return {'color': 'black', 'ls': '-.'}
print args.files
fig = figure()
ax = fig.add_subplot(111)
for i, f in enumerate(args.files):
data = read_list(f)
xaxis = map(float, col(0, data))
start_time = xaxis[0]
xaxis = map(lambda x: x - start_time, xaxis)
qlens = map(float, col(1, data))
if args.summarise or args.cdf:
to_plot.append(qlens[10:-10])
else:
xaxis = xaxis[::args.every]
qlens = qlens[::args.every]
ax.plot(xaxis, qlens, label=args.legend[i], lw=2, **get_style(i))
ax.xaxis.set_major_locator(MaxNLocator(4))
#plt.title("Queue sizes")
plt.title("")
plt.ylabel("Packets")
plt.grid(True)
#yaxis = range(0, 1101, 50)
#ylabels = map(lambda y: str(y) if y%100==0 else '', yaxis)
#plt.yticks(yaxis, ylabels)
#plt.ylim((0,1100))
plt.ylim((args.miny,args.maxy))
if args.summarise:
plt.xlabel("Link Rates")
plt.boxplot(to_plot)
xaxis = range(1, 1+len(args.files))
plt.xticks(xaxis, args.labels)
for x in xaxis:
y = pc99(to_plot[x-1])
print x, y
if x == 1:
s = '99pc: %d' % y
offset = (-20,20)
else:
s = str(y)
offset = (-10, 20)
plt.annotate(s, (x,y+1), xycoords='data',
xytext=offset, textcoords='offset points',
arrowprops=dict(arrowstyle="->"))
elif args.cdf:
fig = figure()
ax = fig.add_subplot(111)
for i,data in enumerate(to_plot):
xs, ys = cdf(map(int, data))
ax.plot(xs, ys, label=args.legend[i], lw=2, **get_style(i))
plt.ylabel("Fraction")
plt.xlabel("Packets")
plt.ylim((0, 1.0))
plt.legend(args.legend, loc="upper left")
plt.title("")
ax.xaxis.set_major_locator(MaxNLocator(4))
else:
plt.xlabel("Seconds")
if args.legend:
plt.legend(args.legend, loc="upper left")
else:
plt.legend(args.files)
if args.out:
plt.savefig(args.out)
else:
plt.show()