def plotScatter(scatter_data, output_path):
options = {
'plottype': 'points',
'key': False,
#~ 'ylabel': scatter_block[0][1],
'yformat': '%g',
'xformat': '%g',
}
stupidplot.gnuplotTable(scatter_data, output_path, options)
def plotScatter(scatter_data, output_path):
options = {
'plottype': 'points',
'key': False,
#~ 'ylabel': scatter_block[0][1],
'yformat': '%g',
'xformat': '%g',
}
stupidplot.gnuplotTable(scatter_data, output_path, options)
def plotAverage(average_data, output_path):
options = {
#~ 'plottype': 'points',
#~ 'key': False,
#~ 'ylabel': 'Transactions/s',
'errorbars': [1],
'yformat': '%g',
'xformat': '%g',
#~ 'xrange' : "[0:]",
'yrange': "[0:]",
}
stupidplot.gnuplotTable(average_data, output_path, options)
def plotAverage(average_data, output_path):
options = {
#~ 'plottype': 'points',
#~ 'key': False,
#~ 'ylabel': 'Transactions/s',
'errorbars': [1],
'yformat': '%g',
'xformat': '%g',
#~ 'xrange' : "[0:]",
'yrange' : "[0:]",
}
stupidplot.gnuplotTable(average_data, output_path, options)
def main():
if len(sys.argv) < 3:
sys.stderr.write(
"plot_raw.py [input file|- for stdin]+ [output prefix]\n")
sys.exit(1)
input_paths = sys.argv[1:-1]
output_prefix = sys.argv[-1]
output_throughput = output_prefix + "_thrpt.eps"
output_latency = output_prefix + "_ltncy.eps"
error = False
for path in (output_throughput, output_latency):
if os.path.exists(path):
sys.stderr.write(
"output path '%s' exists; please move it out of the way\n" %
path)
error = True
if error:
sys.exit(1)
throughputs = []
latencies = []
for input_path in input_paths:
throughput = [("time (s)", input_path)]
latency = [("time (s)", input_path)]
for r in CSVIterator(input_path):
start = r[0]
sample_average = r[1]
sample_throughput = r[2]
throughput.append([start, sample_throughput])
latency.append([start, sample_average])
throughputs.append(throughput)
latencies.append(latency)
options = {
'yformat': '%g',
'xformat': '%g',
'yrange': "[0:]",
}
options["ylabel"] = "Throughput (txns/s)"
stupidplot.gnuplotTable(throughputs, output_throughput, options)
options["ylabel"] = "Latency (us)"
#~ options["yrange"] = "[:1000000]"
stupidplot.gnuplotTable(latencies, output_latency, options)
def main():
if len(sys.argv) < 3:
sys.stderr.write("plot_raw.py [input file|- for stdin]+ [output prefix]\n")
sys.exit(1)
input_paths = sys.argv[1:-1]
output_prefix = sys.argv[-1]
output_throughput = output_prefix + "_thrpt.eps"
output_latency = output_prefix + "_ltncy.eps"
error = False
for path in (output_throughput, output_latency):
if os.path.exists(path):
sys.stderr.write("output path '%s' exists; please move it out of the way\n" % path)
error = True
if error:
sys.exit(1)
throughputs = []
latencies = []
for input_path in input_paths:
throughput = [("time (s)", input_path)]
latency = [("time (s)", input_path)]
for r in CSVIterator(input_path):
start = r[0]
sample_average = r[1]
sample_throughput = r[2]
throughput.append([start, sample_throughput])
latency.append([start, sample_average])
throughputs.append(throughput)
latencies.append(latency)
options = {
'yformat': '%g',
'xformat': '%g',
'yrange' : "[0:]",
}
options["ylabel"] = "Throughput (txns/s)"
stupidplot.gnuplotTable(throughputs, output_throughput, options)
options["ylabel"] = "Latency (us)"
#~ options["yrange"] = "[:1000000]"
stupidplot.gnuplotTable(latencies, output_latency, options)
def plot(path):
table = dataextract.readCSVTable(path)
# Take only the little endian results
#~ table = dataextract.select(table, [(1, "le")])
# Express buffer size in kB
table = [(r[0], r[1], r[2]/1024, r[3]) for r in table]
# Express throughput in GB/s
#~ table = [(r[0], r[1], r[2], r[3]/1024.) for r in table]
groups = dataextract.groupBy(table, [0, 1])
datasets = []
keys = groups.keys()
keys.sort(labelCmp)
for key in keys:
data = dataextract.selectStatsConfPlot(groups[key], [2], 3)
label = ("Buffer Size (kB)", "%s %s" % (LABEL_MAP[key[0]], LABEL_MAP[key[1]]))
#~ label = ("Buffer Size (kB)", LABEL_MAP[key[0]])
print label
data.insert(0, label)
datasets.append(data)
print data
#~ data = dataextract.selectStatsConfPlot(table, [0, 1, 2], 3)
#~ print data
options = {
"key": "bottom right",
"errorbars": [1],
"xrange": "[0:]",
"yrange": "[0:]",
#~ "ylabel": "Write Throughput (GB/s)",
#~ "ylabel": "Fill Byte Throughput (MB/s)",
"ylabel": "Fill Int Throughput (MB/s)",
"xformat": "%.0f",
#~ "xtics": "1024",
"yformat": "%.0f",
}
stupidplot.gnuplotTable(datasets, "out.eps", options)
#!/usr/bin/python # An example script for the "simple.tcl" example wireless ns2 scenario # This script parses the trace file and produces a graph showing the flow # throughput over time import sys import flowanalysis import throughputOverTime import stupidplot if len( sys.argv ) != 3: print "example.py <trace file> <output eps file>" sys.exit( 1 ) input = file( sys.argv[1] ) flows = flowanalysis.parseFlowsFromTrace( input ) input.close() data = throughputOverTime.throughputOverTime( flows ) stupidplot.gnuplotTable( data, sys.argv[2] )
average = [('Simultaneous Clients', server_type, '-95% confidence',
'+95% confidence')]
for row in table:
x = row[0]
for y in row[1:]:
scatter.append((x, y))
stats = statistics.stats([float(f) for f in row[1:]])
average.append(
(x, stats[0], stats[0] - stats[-1], stats[0] + stats[-1]))
options = {
'plottype': 'points',
'key': False,
'ylabel': scatter[0][1],
}
stupidplot.gnuplotTable(scatter, server_type + "-scatter.eps", options)
averages.append(average)
options = {
#~ 'plottype': 'points',
#~ 'key': False,
'ylabel': 'Messages/s',
'errorbars': [1],
'yformat': '%g',
'xformat': '%g',
'key': 'bottom right',
}
stupidplot.gnuplotTable(averages, "average.eps", options)
#!/usr/bin/python
import csv
import sys
import stupidplot
d = open(sys.argv[1])
samples = []
for row in csv.reader(d):
assert len(row) == 1
samples.append(float(row[0]))
d.close()
histogram = stupidplot.histogram(samples, 16, 40000, 56000)
stupidplot.gnuplotTable(histogram, "histogram.eps")
charsets = []
for r in connection.execute("select distinct charset from results"):
charsets.append(r[0])
for charset in charsets:
output = xaxis(c, "string_length", "chars_per_us", charset=charset)
average_out = []
for table in output:
average_table = [table[0]]
last_x = table[1][0]
sum = 0
count = 0
for row in table[1:]:
if last_x != row[0]:
average_table.append((last_x, sum/count))
sum = 0
count = 0
last_x = row[0]
sum += row[1]
count += 1
average_table.append((last_x, sum/count))
average_out.append(average_table)
options = {
#~ "plottype": "points",
"ylabel": "UTF-16 chars per us",
"key": "bottom right",
}
stupidplot.gnuplotTable(average_out, "stringbytebuffer-%s.eps" % charset, options)
scatter = [('Simultaneous Clients', 'Messages/s')]
average = [('Simultaneous Clients', server_type, '-95% confidence', '+95% confidence')]
for row in table:
x = row[0]
for y in row[1:]:
scatter.append((x, y))
stats = statistics.stats([float(f) for f in row[1:]])
average.append((x, stats[0], stats[0]-stats[-1], stats[0]+stats[-1]))
options = {
'plottype': 'points',
'key': False,
'ylabel': scatter[0][1],
}
stupidplot.gnuplotTable(scatter, server_type + "-scatter.eps", options)
averages.append(average)
options = {
#~ 'plottype': 'points',
#~ 'key': False,
'ylabel': 'Messages/s',
'errorbars': [1],
'yformat': '%g',
'xformat': '%g',
'key': 'bottom right',
}
stupidplot.gnuplotTable(averages, "average.eps", options)
paths = net.findShortestPathsHeuristic( src, dst )
length = len( paths[0] )
# Create the scenario file
scriptBuilder = networks.NS2ScriptBuilder( net )
scriptBuilder.addFlow( paths[0], UDP=False )
temp = tempfile.NamedTemporaryFile()
temp.write( scriptBuilder.getScript() )
temp.flush()
# Run the TCP simulation
pid,dataPipe = ns2stats.executeNs2( "ns %s 0" % ( temp.name ) )
# Parse the output
flows = flowanalysis.parseFlowsFromTrace( dataPipe )
dataPipe.close()
temp.close()
data = throughputOverTime( flows )
# Graph the data
options = {
'ylabel': 'Throughput (kBytes/s)',
}
stupidplot.gnuplotTable( data, "out.eps", options )
# Dump the network so we can draw it
temp = file( "out.txt", "w" )
temp.write( net.drawScript( [ paths[0] ] ) )
temp.close()
paths = net.findShortestPathsHeuristic(src, dst)
length = len(paths[0])
# Create the scenario file
scriptBuilder = networks.NS2ScriptBuilder(net)
scriptBuilder.addFlow(paths[0], UDP=False)
temp = tempfile.NamedTemporaryFile()
temp.write(scriptBuilder.getScript())
temp.flush()
# Run the TCP simulation
pid, dataPipe = ns2stats.executeNs2("ns %s 0" % (temp.name))
# Parse the output
flows = flowanalysis.parseFlowsFromTrace(dataPipe)
dataPipe.close()
temp.close()
data = throughputOverTime(flows)
# Graph the data
options = {
'ylabel': 'Throughput (kBytes/s)',
}
stupidplot.gnuplotTable(data, "out.eps", options)
# Dump the network so we can draw it
temp = file("out.txt", "w")
temp.write(net.drawScript([paths[0]]))
temp.close()
#!/usr/bin/python
import csv
import sys
import stupidplot
d = open(sys.argv[1])
samples = []
for row in csv.reader(d):
assert len(row) == 1
samples.append(float(row[0]))
d.close()
histogram = stupidplot.histogram(samples, 16, 40000, 56000)
stupidplot.gnuplotTable(histogram, "histogram.eps")
