def run_command(args, plt):
# read in all stats
stats = []
for stat in args.stats:
gs = gridstats.GridStats()
gs.read(stat)
stats.append(gs)
# create the LoadRate stats object
lrstats = ssplot.LoadRateStats(args.start, args.stop, args.step, stats)
# determine fields to plot
fields = ssplot.LoadRateStats.FIELDS
# gather data
xdata = lrstats.data['Injected']
ydatas = []
for field in fields:
ydatas.append(lrstats.data[field])
# create x and y axis labels
xlabel = 'Injected Rate (%)'
ylabel = 'Delivered Rate (%)'
# plot
mlp = ssplot.MultilinePlot(plt, xdata, ydatas)
mlp.set_xlabel(xlabel)
mlp.set_ylabel(ylabel)
mlp.set_data_labels(fields)
mlp.apply_args(args, *LoadRate._SKIP)
mlp.plot(args.plotfile)
return 0
def run_command(args, plt):
# create a sample stats object of latencies
stats = gridstats.GridStats()
stats.read(args.ifile)
# determine the fields and data labels to plot
fields = ssplot.LoadLatencyStats.FIELDS
if not args.minimum:
fields.remove('Minimum')
fields = list(reversed(fields))
# gather data
xdata = stats.row_names()
ydatas = []
for field in fields:
ydatas.append(stats.get_column(field))
# create x and y axis labels
xlabel = 'Time'
ylabel = 'Latency'
if args.units:
ylabel += ' ({0})'.format(args.units)
# plot
mlp = ssplot.MultilinePlot(plt, xdata, ydatas)
mlp.set_xlabel(xlabel)
mlp.set_ylabel(ylabel)
mlp.set_data_labels(fields)
mlp.apply_args(args, *TimeLatency._SKIP)
mlp.plot(args.plotfile)
return 0
def run_command(args, plt):
# create a sample stats object of latencies
stats = gridstats.GridStats()
stats.read(args.ifile)
# determine the fields and data labels to plot
fields = ['AveMinHops', 'AveHops', 'AveNonMinHops']
labels = ['Minimal Hops', 'Total Hops', 'Non-Minimal Hops']
if not args.non_minimal:
fields = fields[:-1]
labels = labels[:-1]
# gather data
xdata = stats.row_names()
ydatas = []
for field in fields:
ydatas.append(stats.get_column(field))
# create x and y axis labels
xlabel = 'Time'
ylabel = 'Average Hops'
# plot
mlp = ssplot.MultilinePlot(plt, xdata, ydatas)
mlp.set_xlabel(xlabel)
mlp.set_ylabel(ylabel)
mlp.set_data_labels(labels)
mlp.apply_args(args, *TimeAverageHops._SKIP)
mlp.plot(args.plotfile)
return 0
def run_command(args, plt):
# create a sample stats object of latencies
stats = gridstats.GridStats()
stats.read(args.ifile)
# determine the fields and data labels to plot
fields = ['PerMinimal', 'PerNonMinimal']
labels = ['Minimal %', 'Non-Minimal %']
# gather data
xdata = stats.row_names()
ydatas = []
for field in fields:
ydatas.append(stats.get_column(field))
# create x and y axis labels
xlabel = 'Time'
ylabel = 'Packets (%)'
# plot
mlp = ssplot.MultilinePlot(plt, xdata, ydatas)
mlp.set_xlabel(xlabel)
mlp.set_ylabel(ylabel)
mlp.set_data_labels(labels)
mlp.apply_args(args, *TimePercentMinimal._SKIP)
mlp.plot(args.plotfile)
return 0
def run_command(args, plt):
# read in all stats
stats = []
for stat in args.stats:
gs = handycsv.GridStats.read(stat)
stats.append(gs)
# create LoadHops stats object
lhstats = ssplot.LoadHopsStats(
args.start, args.stop, args.step, stats)
# determine the fields and data labels to plot
fields = ['PerMinimal', 'PerNonMinimal']
labels = ['Minimal %', 'Non-Minimal %']
# gather data
xdata = lhstats.data['Load']
ydatas = []
for field in fields:
ydatas.append(lhstats.data[field])
# create x and y axis labels
xlabel = 'Load ({0})'.format(args.load_units)
ylabel = 'Packets (%)'
# plot
mlp = ssplot.MultilinePlot(plt, xdata, ydatas)
mlp.set_xlabel(xlabel)
mlp.set_ylabel(ylabel)
mlp.set_data_labels(labels)
mlp.apply_args(args, *LoadPercentMinimal._SKIP)
mlp.plot(args.plotfile)
return 0
def run_command(args, plt):
# check inputs
assert args.start <= args.stop, 'start must be <= stop'
assert args.step > 0, 'step must be > 0.0'
gridsPerSet = len(numpy.arange(args.start, args.stop, args.step))
if len(args.stats) % gridsPerSet != 0:
print(('The number of stats file for data set is {0},\n'
'yet you specified {1} stats files. What gives?').format(
gridsPerSet, len(args.stats)))
return -1
dataSets = len(args.stats) // gridsPerSet
# read in all stats
stats = []
for stat in args.stats:
gs = handycsv.GridStats.read(stat)
stats.append(gs)
# create LoadLatency stats objects
llstats = []
for idx in range(dataSets):
# create the LoadLatencyStats object
llstat = ssplot.LoadLatencyStats(
args.start,
args.stop,
args.step,
stats[idx * gridsPerSet:(idx + 1) * gridsPerSet],
row=args.row)
# save the object
llstats.append(llstat)
# make sure the loads are all the same, gather data
xdata = llstats[0].data['Load']
ydatas = []
assert args.field in ssplot.LoadLatencyStats.FIELDS
for stat in llstats:
assert len(xdata) == len(set(xdata).intersection(stat.data['Load'])), \
'{0} != {1}'.format(mload, stat.data['Load'])
ydatas.append(stat.data[args.field])
# create x and y labels
xlabel = 'Load ({0})'.format(args.load_units)
ylabel = '{0} Latency'.format(args.field)
if args.latency_units:
ylabel += ' ({0})'.format(args.latency_units)
# plot
mlp = ssplot.MultilinePlot(plt, xdata, ydatas)
mlp.set_xlabel(xlabel)
mlp.set_ylabel(ylabel)
mlp.apply_args(args, *LoadLatencyCompare._SKIP)
mlp.plot(args.plotfile)
return 0
def run_command(args, plt):
# read in all rate stats
rate_stats = []
for stat in args.rate_stats:
gs = gridstats.GridStats()
gs.read(stat)
rate_stats.append(gs)
# create LoadRate stats object
lrstats = ssplot.LoadRateStats(
args.start, args.stop, args.step, rate_stats)
# read in all hops stats
hops_stats = []
for stat in args.hops_stats:
gs = gridstats.GridStats()
gs.read(stat)
hops_stats.append(gs)
# create LoadHops stats object
lhstats = ssplot.LoadHopsStats(
args.start, args.stop, args.step, hops_stats)
# determine the fields and data labels to plot
fields = ['Mean', 'Minimal', 'NonMinimal']
labels = ['Mean', 'Minimal', 'Non-Minimal']
# gather data
xdata = lhstats.data['Load']
mean_rate = lrstats.data['Mean']
min_percent = lhstats.data['PerMinimal']
nmin_percent = lhstats.data['PerNonMinimal']
ydatas = []
ydatas.append(mean_rate)
ydatas.append(numpy.multiply(mean_rate, min_percent))
ydatas.append(numpy.multiply(mean_rate, nmin_percent))
# create x and y axis labels
xlabel = 'Injected Rate (%)'
ylabel = 'Delivered Rate (%)'
# plot
mlp = ssplot.MultilinePlot(plt, xdata, ydatas)
mlp.set_xlabel(xlabel)
mlp.set_ylabel(ylabel)
mlp.set_data_labels(labels)
mlp.apply_args(args, *LoadRatePercent._SKIP)
mlp.plot(args.plotfile)
return 0
def run_command(args, plt):
# read in all stats
stats = []
for stat in args.stats:
gs = gridstats.GridStats()
gs.read(stat)
stats.append(gs)
# create LoadLatency stats object
llstats = ssplot.LoadLatencyStats(args.start,
args.stop,
args.step,
stats,
row=args.row)
# determine the fields to plot
fields = ssplot.LoadLatencyStats.FIELDS
if not args.minimum:
fields.remove('Minimum')
fields = list(reversed(fields))
# gather data
xdata = llstats.data['Load']
ydatas = []
for field in fields:
ydatas.append(llstats.data[field])
# create x and y axis labels
xlabel = 'Load (%)'
ylabel = 'Latency'
if args.units:
ylabel += ' ({0})'.format(args.units)
# plot
mlp = ssplot.MultilinePlot(plt, xdata, ydatas)
mlp.set_xlabel(xlabel)
mlp.set_ylabel(ylabel)
mlp.set_data_labels(fields)
mlp.apply_args(args, *LoadLatency._SKIP)
mlp.plot(args.plotfile)
return 0
def run_command(args, plt):
# read in all stats
stats = []
for stat in args.stats:
gs = handycsv.GridStats.read(stat)
stats.append(gs)
# create LoadHops stats object
lhstats = ssplot.LoadHopsStats(args.start, args.stop, args.step, stats)
# determine the fields and data labels to plot
fields = ['AveMinHops', 'AveHops', 'AveNonMinHops']
labels = ['Minimal Hops', 'Total Hops', 'Non-Minimal Hops']
if not args.non_minimal:
fields = fields[:-1]
labels = labels[:-1]
# gather data
xdata = lhstats.data['Load']
ydatas = []
for field in fields:
ydatas.append(lhstats.data[field])
# create x and y axis labels
xlabel = 'Load ({0})'.format(args.load_units)
ylabel = 'Average Hops'
# plot
mlp = ssplot.MultilinePlot(plt, xdata, ydatas)
mlp.set_xlabel(xlabel)
mlp.set_ylabel(ylabel)
mlp.set_data_labels(labels)
mlp.apply_args(args, *LoadAverageHops._SKIP)
mlp.plot(args.plotfile)
return 0
