def plotCQIThroughput():
plot = Plot()
plot.setXLimits(-10, 25)
# plot.setXLimits(5, 10)
plot.setYLimits(0, 4.5)
plot.setXLabel("SINR")
plot.setYLabel("Throughput")
#(plot.width, plot.height) = (16,9) # getGoldenRatioDimensions(35)
fileName = "throughputsCQI"
for cqi in range(1, 16): #1..15
line = boomslang.Line()
(line.xValues, line.yValues) = getXYfromFile(fileName+".txt", 0, cqi)
# print line.xValues, line.yValues
if cqi==1:
line.label = "QPSK"
elif cqi==7:
line.label = "16 QAM"
elif cqi==10:
line.label = "64 QAM"
line.color = cqiStyles[cqi]['color']
line.lineStyle = cqiStyles[cqi]['lineStyle']
line.lineWidth = line.lineWidth * 3
plot.add(line)
plot.save(fileName+".pdf")
def plotMCSThroughput():
plot = Plot()
plot.setXLimits(-10, 25)
# plot.setXLimits(5, 10)
plot.setYLimits(0, 4.5)
plot.setXLabel("SINR")
plot.setYLabel("Throughput")
#(plot.width, plot.height) = (16,9) # getGoldenRatioDimensions(35)
fileName = "throughputsMCS"
for mcs in range(29):
line = boomslang.Line()
(line.xValues, line.yValues) = getXYfromFile(fileName+".txt", 0, mcs + 1)
# print line.xValues, line.yValues
if mcs==0:
line.label = "QPSK"
elif mcs==10:
line.label = "16 QAM"
elif mcs==17:
line.label = "64 QAM"
line.color = mcsStyles[mcs]['color']
line.lineStyle = mcsStyles[mcs]['lineStyle']
line.lineWidth = line.lineWidth * 3
plot.add(line)
plot.save(fileName+".pdf")
def main(argv):
# Parse flags
args = parser.parse_args()
expt_dirs_2000 = ['../test_scripts/nsdi-paper-data/Sep21--10-34-combine/memcached-rl-htb-mcrate-2000-mctenants-10-trafgentenants-0-run-1/',
'../test_scripts/nsdi-paper-data/Sep21--10-34-combine/memcached-rl-qfq-mcrate-2000-mctenants-10-trafgentenants-0-run-1/',
'../test_scripts/nsdi-paper-data/Sep21--10-34-combine/memcached-rl-eyeq-mcrate-2000-mctenants-10-trafgentenants-0-run-1/']
expt_dirs_3000 = ['../test_scripts/nsdi-paper-data/Sep21--10-34-combine/memcached-rl-htb-mcrate-3000-mctenants-10-trafgentenants-0-run-1/',
'../test_scripts/nsdi-paper-data/Sep21--10-34-combine/memcached-rl-qfq-mcrate-3000-mctenants-10-trafgentenants-0-run-1/',
'../test_scripts/nsdi-paper-data/Sep21--10-34-combine/memcached-rl-eyeq-mcrate-3000-mctenants-10-trafgentenants-0-run-1/']
# Read the properties for each directory from the expsift tags files
dir2props_dict_2000 = getDir2PropsDict(expt_dirs_2000)
dir2props_dict_3000 = getDir2PropsDict(expt_dirs_3000)
# Plot memcached latency comparison graph (msec)
mclat_plot_2000 = plotMcperfLatencyCDFComparisonDirs(dir2props_dict_2000)
mclat_plot_3000 = plotMcperfLatencyCDFComparisonDirs(dir2props_dict_3000)
# Specify the xTicks values to display
ticklabels_line_2000 = boomslang.Line()
ticklabels_line_2000.xTickLabels = [0.5, 1.0, 1.5]
ticklabels_line_2000.xTickLabelPoints = [0.5, 1.0, 1.5]
mclat_plot_2000.add(ticklabels_line_2000)
ticklabels_line_3000 = boomslang.Line()
ticklabels_line_3000.xTickLabels = [0.5, 1.0, 1.5]
ticklabels_line_3000.xTickLabelPoints = [0.5, 1.0, 1.5]
mclat_plot_3000.add(ticklabels_line_3000)
# Set title and legend
mclat_plot_2000.title = "2000 rpstc"
mclat_plot_3000.title = "3000 rpstc"
mclat_plot_3000.setYLabel('')
mclat_plot_3000.legend = None
mclat_plot_2000.hasLegend(location="lower right")
mclat_plot_2000.setLegendLabelSize("small")
# Plot layout
layout = boomslang.PlotLayout()
layout.addPlot(mclat_plot_2000, grouping='lat_cdfs')
layout.addPlot(mclat_plot_3000, grouping='lat_cdfs')
layout.setFigureDimensions(5, 3)
# Save the plot
layout.save(args.plot_filename)
return
def plotMCSEfficiency():
plot = Plot()
plot.setXLimits(-10, 25)
# plot.setXLimits(5, 10)
plot.setYLimits(0, 6)
plot.setXLabel("SINR")
plot.setYLabel("Spectral Efficiency [bits / s / Hz]")
#(plot.width, plot.height) = (16,9) # getGoldenRatioDimensions(35)
fileName = "efficienciesMCS"
for mcs in range(29):
line = boomslang.Line()
(line.xValues, line.yValues) = getXYfromFile(fileName+".txt", 0, mcs + 1)
# print line.xValues, line.yValues
if mcs==0:
line.label = "QPSK"
elif mcs==10:
line.label = "16 QAM"
elif mcs==17:
line.label = "64 QAM"
line.color = mcsStyles[mcs]['color']
line.lineStyle = mcsStyles[mcs]['lineStyle']
line.lineWidth = line.lineWidth * 3
plot.add(line)
shannon = boomslang.Line()
shannon.xValues = [x / 10 - 10 for x in range(350)]
shannon.yValues = [math.log(math.pow(10.0, x/10.0) + 1.0, 2.0) for x in shannon.xValues]
shannon.label = "Shannon Capacity"
plot.add(shannon)
# shannon60 = boomslang.Line()
# shannon60.xValues = [x / 10 - 10 for x in range(350)]
# shannon60.yValues = [0.6 * math.log(math.pow(10.0, x/10.0) + 1.0, 2.0) for x in shannon60.xValues]
# shannon60.label = "60% of Shannon Capacity"
# plot.add(shannon60)
plot.save(fileName+".pdf")
def cdfLineFromHist(hist, color="blue", width=2):
sorted_hist = sorted(hist.items())
cum_sum = numpy.cumsum(map(lambda (k, v): v, sorted_hist))
num_samples = cum_sum[-1]
cdf_line = boomslang.Line(color=color, width=width)
cdf_line.xValues = map(lambda (k, v): k, sorted_hist)
cdf_line.yValues = map(lambda y: y * 1.0 / num_samples, cum_sum)
return cdf_line
def plotCQIEfficiency():
plot = Plot()
plot.setXLimits(-10, 25)
# plot.setXLimits(5, 10)
plot.setYLimits(0, 6.0)
plot.setXLabel("SINR")
plot.setYLabel("Spectral Efficiency [bits / s / Hz]")
#(plot.width, plot.height) = (16,9) # getGoldenRatioDimensions(35)
fileName = "efficienciesCQI"
for cqi in range(1, 16): #1..15
line = boomslang.Line()
(line.xValues, line.yValues) = getXYfromFile(fileName+".txt", 0, cqi)
# print line.xValues, line.yValues
if cqi==1:
line.label = "QPSK"
elif cqi==7:
line.label = "16 QAM"
elif cqi==10:
line.label = "64 QAM"
line.color = cqiStyles[cqi]['color']
line.lineStyle = cqiStyles[cqi]['lineStyle']
line.lineWidth = line.lineWidth * 3
plot.add(line)
shannon = boomslang.Line()
shannon.xValues = [x / 10 - 10 for x in range(350)]
shannon.yValues = [math.log(math.pow(10.0, x/10.0) + 1.0, 2.0) for x in shannon.xValues]
shannon.label = "Shannon Capacity"
plot.add(shannon)
plot.save(fileName+".pdf")
def main(argv):
# Parse flags
args = parser.parse_args()
# Generate the list of experiment directories to compare
expt_dirs = []
if args.recursive:
for directory in args.expt_dirs:
directory = os.path.abspath(directory)
for (path, dirs, files) in os.walk(directory, followlinks=True):
# Check if an experiment directory was found
if os.path.exists(os.path.join(path, 'expsift_tags')):
#print 'Found experiment directory:', path
expt_dirs.append(path)
print 'Found %d experiment directories to compare' % len(expt_dirs)
else:
expt_dirs = args.expt_dirs
# Check if any experiment directories were found or not
if len(expt_dirs) == 0:
return
# Read the properties for each directory from the expsift tags files
dir2props_dict = getDir2PropsDict(expt_dirs)
# Plot trafgen throughput comparison graph
trafgenrate_plot = plotTrafgenThroughputComparisonDirs(dir2props_dict)
if FOR_PAPER:
# Set xLabel
trafgenrate_plot.setXLabel("Load (rpstc)")
# Tick labels
xmin, xmax = LOAD_LIMITS
xTickLabels = range(xmin, xmax + 1, 1000)
ticklabels_line = boomslang.Line()
ticklabels_line.xTickLabels = xTickLabels
ticklabels_line.xTickLabelPoints = xTickLabels
trafgenrate_plot.add(ticklabels_line)
# Label sizes
trafgenrate_plot.setXTickLabelSize("small")
trafgenrate_plot.save(args.plot_filename)
def main(argv):
# Parse flags
args = parser.parse_args()
if args.dataset == 0:
expt_dirs_base = [
'../test_scripts/nsdi-paper-data/Sep21--10-34-combine/'
]
plotMcperfLatencyCompare.LOAD_LIMITS = (1000, 7000)
elif args.dataset == 1:
expt_dirs_base = [
'../test_scripts/nsdi-paper-data/Sep20--07-02-iso-combine/'
]
plotMcperfLatencyCompare.LOAD_LIMITS = (1000, 5000)
else:
print 'Unknown dataset'
return
expt_dirs = []
for directory in expt_dirs_base:
directory = os.path.abspath(directory)
for (path, dirs, files) in os.walk(directory, followlinks=True):
# Check if an experiment directory was found
if os.path.exists(os.path.join(path, 'expsift_tags')):
#print 'Found experiment directory:', path
expt_dirs.append(path)
print 'Found %d experiment directories to compare' % len(expt_dirs)
# Read the properties for each directory from the expsift tags files
dir2props_dict = getDir2PropsDict(expt_dirs)
# Plot memcached latency comparison graphs (msec)
avg_plot = plotMcperfLatencyComparisonDirsWrapper(dir2props_dict, 'avg')
pc99_plot = plotMcperfLatencyComparisonDirsWrapper(dir2props_dict, 'pc99')
pc999_plot = plotMcperfLatencyComparisonDirsWrapper(
dir2props_dict, 'pc999')
# Set xLabel
avg_plot.setXLabel("Load (rpstc)")
pc99_plot.setXLabel("Load (rpstc)")
pc999_plot.setXLabel("Load (rpstc)")
# Set yLabel
avg_plot.setYLabel("Latency (msec)")
pc99_plot.setYLabel("Latency (msec)")
pc999_plot.setYLabel("Latency (msec)")
# Title
avg_plot.title = "Average"
pc99_plot.title = "99th percentile"
pc999_plot.title = "99.9th percentile"
# Tick labels
xmin, xmax = plotMcperfLatencyCompare.LOAD_LIMITS
xTickLabels = range(xmin, xmax + 1, 1000)
ticklabels_line = boomslang.Line()
ticklabels_line.xTickLabels = xTickLabels
ticklabels_line.xTickLabelPoints = xTickLabels
avg_plot.add(ticklabels_line)
pc99_plot.add(ticklabels_line)
pc999_plot.add(ticklabels_line)
# Label sizes
avg_plot.setXTickLabelSize("small")
pc99_plot.setXTickLabelSize("small")
pc999_plot.setXTickLabelSize("small")
avg_plot.setYTickLabelSize("small")
pc99_plot.setYTickLabelSize("small")
pc999_plot.setYTickLabelSize("small")
avg_plot.setTitleSize("small")
pc99_plot.setTitleSize("small")
pc999_plot.setTitleSize("small")
# Plot layout
layout = boomslang.PlotLayout()
layout.addPlot(avg_plot, grouping='throuput')
layout.addPlot(pc99_plot, grouping='throuput')
layout.addPlot(pc999_plot, grouping='throuput')
layout.setFigureDimensions(13.5, 3)
# Save the plot
layout.save(args.plot_filename)
return
def plotLineComparisonDirs(
dir2props_dict, # dict
xgroup_props, # list. Props to group along x axis
line_props, # list. Properties of line
fn_sort_lines,
fn_get_line_label,
fn_get_xgroup_value, # xValue. No separate label
fn_get_datapoint, # yValue
xLabel,
yLabel,
title,
xLimits=None,
yLimits=None,
for_paper=False):
# 1. Turn each directory's set of prop=val strings into a dictionary to
# easily look up the value of a particular property for the directory
dir2prop2val_dict = getDir2Prop2ValDict(dir2props_dict)
# 2. Find all the common and unique properties among all directories
common_props, unique_props = getCommonAndUniqueProperties(dir2props_dict)
# 3A. Find all unique values of line properties (each is separate line)
line2dir_dict = getDirGroupsByProperty(dir2props_dict,
line_props,
ignore=False)
unique_lines = line2dir_dict.keys()
# 3B. Sort the lines
fn_sort_lines(unique_lines)
# 4. Find all unique values of the xgroup properties
xgroup2dir_dict = getDirGroupsByProperty(dir2props_dict,
xgroup_props,
ignore=False)
unique_xgroups = xgroup2dir_dict.keys()
# 5. For each unique line,
# For each unique xgroup,
# Create an individual datapoints list
datapoints_dict = {}
for line in unique_lines:
datapoints_dict[line] = {}
for xgroup in unique_xgroups:
datapoints_dict[line][xgroup] = []
# 6. Visit each directory and populate the corresponding datapoints list for
# that directory.
for directory, prop_vals in dir2props_dict.iteritems():
# Find the line and xgroup of the directory
line = onlyIncludeProps(prop_vals, line_props)
xgroup = onlyIncludeProps(prop_vals, xgroup_props)
# Compute the datapoint for the directory
datapoint = fn_get_datapoint(directory)
# Add the data point
datapoints_dict[line][xgroup].append(datapoint)
# 7. For each unique line prop, create a line.
# Set the label and color for the line
colors = ('b', 'g', 'r', 'm', 'c', 'y')
all_lines_dict = {}
for index, line in enumerate(unique_lines):
l = boomslang.Line()
l.color = colors[index % len(colors)]
l.label = fn_get_line_label(line)
l.width = 2
l.marker = 'o'
all_lines_dict[line] = l
# 8. Compute average and stddev for each (line, xgroup) combination. This
# represents the avg and stddev across multiple trials.
# Add these to the corresponding lines.
for line, line_dict in datapoints_dict.iteritems():
for xgroup, datapoints in line_dict.iteritems():
avg = numpy.average(datapoints)
stddev = numpy.std(datapoints)
# Append xValue, yValue, yError to the line
xValue = fn_get_xgroup_value(xgroup)
all_lines_dict[line].xValues.append(xValue)
all_lines_dict[line].yValues.append(avg)
all_lines_dict[line].yErrors.append(stddev)
# 9. Create the plot and add all the lines
plot = boomslang.Plot()
for line in unique_lines:
plot.add(all_lines_dict[line])
# 9A. Set title and axes labels
plot.setXLabel(xLabel)
plot.setYLabel(yLabel)
plot.setTitle(title)
plot.hasLegend()
# 9B. Font size
plot.setLegendLabelSize("small")
plot.setTitleSize("small")
plot.setAxesLabelSize("small")
plot.setXTickLabelSize("small")
plot.setYTickLabelSize("small")
# 9C. Grid
plot.grid.color = "lightgray"
plot.grid.style = "dotted"
plot.grid.lineWidth = 0.8
plot.grid.visible = True
# 9D. xLimits, yLimits
if xLimits:
plot.xLimits = xLimits
if yLimits:
plot.yLimits = yLimits
# 10. Set dimensions of the plot
if for_paper:
plot.setDimensions(width=4.5)
# 11. Return the plot
return plot
