def main(argv):
argsf = {'func':['-li'], 'files':['simdata/svcsimn_d2a1_6.json', 'simdata/svcsimn_d3a1_2.json', 'simdata/svcsimn_d4a1_2.json'], '-m':['red'], '-yl':['$P(k_{in})$'], '-axisfsize':['large'], '-lb':[1.21], '-gl':[0], '-loc':[1], '-l':['sf, $\langle{dep}\\rangle = 1$', 'sf, $\langle{dep}\\rangle \\approx 1.5$', 'sf, $\langle{dep}\\rangle \\approx 2$']}
argexp = {'func':['-di'], 'files':['simdata/expsvcsimn_d2a1_5.json', 'simdata/expsvcsimn_d3a1_2.json', 'simdata/expsvcsimn_d4a1_3.json'], '-m':['blue'], '-xl':['In-degree $k_{in}$'], '-axisfsize':['large'], '-logy':[1], '-l':['exp, $\langle{dep}\\rangle = 1$', 'exp, $\langle{dep}\\rangle \\approx 1.5$', 'exp, $\langle{dep}\\rangle \\approx 2$']}
argrand = {'func':['-di'], 'files':['simdata/randsvcsimn_d2a1_5.json', 'simdata/randsvcsimn_d3a1_2.json', 'simdata/randsvcsimn_d4a1_3.json'], '-m':['yellow'], '-axisfsize':['large'], '-l':['rand, $\langle{dep}\\rangle = 1$', 'rand, $\langle{dep}\\rangle \\approx 1.5$', 'rand, $\langle{dep}\\rangle \\approx 2$']}
p.plt.subplot(131)
p.drawloglogdist(pl.loadarg([argsf])
, xlabel=pl.getargval(argsf, '-xl', [''])[0]
, ylabel=pl.getargval(argsf, '-yl', [''])[0]
, title=pl.getargval(argsf, '-t', [''])[0]
, markset=pl.getargval(argsf, '-m', ['var'])[0]
, xlim=pl.getargval(argsf, '-xlim')
, ylim=pl.getargval(argsf, '-ylim')
, axisfsize=pl.getaxisfsize(argsf)
, logbinbase=pl.getargval(argsf, '-lb', [1.21])[0]
, showexp=int(pl.getargval(argsf, '-g', [1])[0])
, legloc=int(pl.getargval(argsf, '-loc', [1])[0])
, isexpline=int(pl.getargval(argsf, '-gl', [1])[0]))
legend = p.plt.legend(argsf['-l'], labelspacing=0.1, numpoints=1)
p.plt.setp(legend.get_texts(), fontsize=12)
p.plt.subplot(132)
logx, logy = pl.getlogparam(argexp)
p.plotdegdist(pl.loadarg([argexp])
, markset=pl.getargval(argexp, '-m', ['var'])[0]
, title=pl.getargval(argexp, '-t', [''])[0]
, xylabels={'x': pl.getargval(argexp, '-xl', [''])[0], 'y': pl.getargval(argexp, '-yl', [''])[0]}
, nbins=int(pl.getargval(argexp, '-b', ['50'])[0])
, logx=logx, logy=logy
, xlim=pl.getargval(argexp, '-xlim')
, ylim=pl.getargval(argexp, '-ylim')
, legloc=int(pl.getargval(argexp, '-loc', [2])[0])
, axisfsize=pl.getaxisfsize(argexp))
legend = p.plt.legend(argexp['-l'], labelspacing=0.1, numpoints=1)
p.plt.setp(legend.get_texts(), fontsize=12)
p.plt.subplot(133)
logx, logy = pl.getlogparam(argrand)
p.plotdegdist(pl.loadarg([argrand])
, markset=pl.getargval(argrand, '-m', ['var'])[0]
, title=pl.getargval(argrand, '-t', [''])[0]
, xylabels={'x': pl.getargval(argrand, '-xl', [''])[0], 'y': pl.getargval(argrand, '-yl', [''])[0]}
, nbins=int(pl.getargval(argrand, '-b', ['50'])[0])
, logx=logx, logy=logy
, xlim=pl.getargval(argrand, '-xlim')
, ylim=pl.getargval(argrand, '-ylim')
, legloc=int(pl.getargval(argrand, '-loc', [2])[0])
, axisfsize=pl.getaxisfsize(argrand))
lines = p.plt.gca().get_lines()
for line in lines:
p.plt.setp(line, markerfacecolor='orange')
legend = p.plt.legend(argrand['-l'], labelspacing=0.1, numpoints=1)
p.plt.setp(legend.get_texts(), fontsize=12)
p.plt.gcf().suptitle('In-degree distribution of scale-free, exponential, and random service networks', fontsize=14)
p.processplot(p.plt)
def main(argv):
lsarg = []
lsarg.append({'func':['-di'], 'files':['simdata/lg_comp.json'], '-m':['star'], '-t':['In-degree distribution of the Language Grid and ProgrammableWeb service networks'], '-xl':['In-degree $k_{in}$'], '-yl':['Probability distribution $P(k_{in})$\nThe Language Grid'], '-l':['The Language Grid'], '-loc':[2], '-axisfsize':['large'], '-logx':[1], '-logy':[1]})
lsarg.append({'func':['-li'], 'files':['simdata/pwsvcsim_1.json'], '-m':['diamond'], '-yl':['ProgrammableWeb'], '-l':['ProgrammableWeb'], '-axisfsize':['large'], '-loc':[4], '-lb':[1.21], '-xlim':[-1,10000], '-logx':[1], '-logy':[1]})
ax = p.plt.axes([0.13, 0.12, 0.6, 0.78])
ax2 = p.plt.twinx(ax)
for i in range(len(lsarg)):
ds = []
func = lsarg[i]['func'][0]
step = p.STEP
argstep = getargval(lsarg[i], '-j')
if argstep:
step = int(argstep[0])
for finjson in lsarg[i]['files']:
f = open(finjson)
try:
data = json.load(f)
p.loaddata(ds, func, data, finjson, step)
finally:
f.close()
logx = False
arglogx = getargval(lsarg[i], '-logx')
if arglogx:
logx = int(arglogx[0]) > 0
logy = False
arglogy = getargval(lsarg[i], '-logy')
if arglogy:
logy = int(arglogy[0]) > 0
lb = p.LOGBINBASE
arglb = getargval(lsarg[i], '-lb')
if arglb:
lb = float(arglb[0])
xlim = getargval(lsarg[i], '-xlim')
ylim = getargval(lsarg[i], '-ylim')
plotfile = getargval(lsarg[i], '-v', [None])[0]
axisfsize = getargval(lsarg[i], '-axisfsize', ['medium'])[0]
try:
axisfsize = int(axisfsize)
except:
pass
if i == 0:
#func == p.FUNC_DISTINDEG:
p.plotdegdist(ds
, getargval(lsarg[i], '-l')
, getargval(lsarg[i], '-m', ['var'])[0]
, title=getargval(lsarg[i], '-t', [''])[0]
, xylabels={'x': getargval(lsarg[i], '-xl', [''])[0], 'y': getargval(lsarg[i], '-yl', [''])[0]}
, nbins=int(getargval(lsarg[i], '-b', ['50'])[0])
, logx=logx, logy=logy
, xlim=xlim
, ylim=ylim
, legloc=int(getargval(lsarg[i], '-loc', [2])[0])
, axisfsize=axisfsize
, ax=ax)
#, ax=p.plt.twinx(p.plt.gca()))
#, ax=p.plt.gca())
ax.set_ylabel(ax.get_ylabel(), color='#460046')
for tl in ax.get_yticklabels():
tl.set_color('#460046')
elif i == 1:
#func == p.FUNC_LOGINDEG:
p.drawloglogdist(ds
, xlabel=getargval(lsarg[i], '-xl', [''])[0]
, ylabel=getargval(lsarg[i], '-yl', [''])[0]
, title=getargval(lsarg[i], '-t', [''])[0]
, labels=getargval(lsarg[i], '-l')
, markset=getargval(lsarg[i], '-m', ['var'])[0]
, xlim=xlim
, ylim=ylim
, axisfsize=axisfsize
, legloc=int(getargval(lsarg[i], '-loc', [2])[0])
, logbinbase=lb
, showexp=int(getargval(lsarg[i], '-g', [1])[0])
, ax=ax2)
#, ax=p.plt.twinx(ax))
#, ax=p.plt.twinx(p.plt.gca()))
ax2.set_ylabel(ax2.get_ylabel(), color='#003200')
for tl in ax2.get_yticklabels():
tl.set_color('#003200')
p.processplot(p.plt, getargval(lsarg[i], '-s', [None])[0])
def main(argv):
lsarg = []
lsarg.append({'func':['-li'], 'files':['simdata/svcsimn_10k_10k_d2_a7_i10_avg1_8.json'], '-m':['reddia'], '-l':['scale-free'], '-g':[0], '-lb':['1.21']})
lsarg.append({'func':['-di'], 'files':['simdata/expsvcsimn_10k_10k_d2_a7_i10_avg1_8.json'], '-m':['bluepenta'], '-b':['100'], '-l':['exponential']})
lsarg.append({'func':['-di'], 'files':['simdata/randsvcsimn_10k_10k_d2_a11_i10_avg1_8.json'], '-m':['trihexaorg'], '-b':['100'], '-l':['random'], '-logx':[1], '-logy':[1], '-xlim':[1, 500], '-ylim':[1e-6, 1], '-t':['Scale-free, exponential, and random network degree distribution'], '-xl':['In-degree $k_{in}$'], '-yl':['Probability distribution $P(k_{in})$'], '-axisfsize':['large'], '-ncol':[1], '-loc':[1]})
for i in range(len(lsarg)):
ds = []
func = lsarg[i]['func'][0]
step = p.STEP
argstep = getargval(lsarg[i], '-j')
if argstep:
step = int(argstep[0])
f = open(lsarg[i]['files'][0])
try:
data = json.load(f)
p.loaddata(ds, func, data, lsarg[i]['files'][0], step)
finally:
f.close()
logx = False
arglogx = getargval(lsarg[i], '-logx')
if arglogx:
logx = int(arglogx[0]) > 0
logy = False
arglogy = getargval(lsarg[i], '-logy')
if arglogy:
logy = int(arglogy[0]) > 0
lb = p.LOGBINBASE
arglb = getargval(lsarg[i], '-lb')
if arglb:
lb = float(arglb[0])
xlim = getargval(lsarg[i], '-xlim')
ylim = getargval(lsarg[i], '-ylim')
plotfile = getargval(lsarg[i], '-v', [None])[0]
if func in [p.FUNC_LOGINDEG, p.FUNC_HISTINDEG]:
xlabel = 'In-degree'
elif func in [p.FUNC_LOGOUTDEG, p.FUNC_HISTOUTDEG]:
xlabel = 'Out-degree'
axisfsize = getargval(lsarg[i], '-axisfsize', ['medium'])[0]
try:
axisfsize = int(axisfsize)
except:
pass
ncol = int(getargval(lsarg[i], '-ncol', [1])[0])
numpoints = int(getargval(lsarg[i], '-numpoints', [1])[0])
if func in [p.FUNC_LOGINDEG, p.FUNC_LOGOUTDEG]:
# loglog degree distribution
p.drawloglogdist(ds
, xlabel=getargval(lsarg[i], '-xl', [''])[0]
, ylabel=getargval(lsarg[i], '-yl', [''])[0]
, title=getargval(lsarg[i], '-t', [''])[0]
, labels=getargval(lsarg[i], '-l')
, markset=getargval(lsarg[i], '-m', ['var'])[0]
, xlim=xlim
, ylim=ylim
, axisfsize=axisfsize
, logbinbase=lb
, showexp=int(getargval(lsarg[i], '-g', [1])[0])
, legloc=int(getargval(lsarg[i], '-loc', [1])[0])
, ax=p.plt.gca()
, ncol=ncol
, numpoints=numpoints)
elif func in [p.FUNC_DISTINDEG, p.FUNC_DISTOUTDEG]:
# degree distribution plot
if p.FUNC_DISTINDEG:
title = getargval(lsarg[i], '-t', ['Degree distribution of exponential network'])[0]
xylabels = {'x':getargval(lsarg[i], '-xl', ['k (degree)'])[0], 'y':getargval(lsarg[i], '-yl', ['P(k)'])[0]}
else:
title = getargval(lsarg[i], '-t', ['Outdegree distribution'])[0]
xylabels = {'x':getargval(lsarg[i], '-xl', ['Outdegree'])[0], 'y':getargval(lsarg[i], '-yl', ['Number of nodes'])[0]}
p.plotdegdist(ds
, getargval(lsarg[i], '-l')
, getargval(lsarg[i], '-m', ['var'])[0]
, title=title
, xylabels=xylabels
, nbins=int(getargval(lsarg[i], '-b', ['50'])[0])
, logx=logx, logy=logy
, xlim=xlim
, ylim=ylim
, axisfsize=axisfsize
, legloc=int(getargval(lsarg[i], '-loc', [1])[0])
, ax=p.plt.gca()
, ncol=ncol
, numpoints=numpoints)
p.processplot(p.plt, getargval(lsarg[i], '-s', [None])[0])
def main(argv):
lsarg = []
lsarg.append(
{
"func": ["-li"],
"files": ["simdata/svcsimn_10k_10k_d2_a7_i10_avg1_8.json"],
"-m": ["reddia"],
"-l": ["scale-free"],
"-g": [0],
"-lb": ["1.21"],
"-gl": [0],
}
)
lsarg.append(
{
"func": ["-di"],
"files": ["simdata/expsvcsimn_10k_10k_d2_a7_i10_avg1_8.json"],
"-m": ["bluepenta"],
"-b": ["100"],
"-l": ["exponential"],
}
)
lsarg.append(
{
"func": ["-di"],
"files": ["simdata/randsvcsimn_10k_10k_d2_a11_i10_avg1_8.json"],
"-m": ["trihexaorg"],
"-b": ["100"],
"-l": ["random"],
"-logx": [1],
"-logy": [1],
"-xlim": [1, 500],
"-ylim": [1e-6, 1],
"-t": ["Scale-free, exponential, and random network degree distribution"],
"-xl": ["In-degree $k_{in}$"],
"-yl": ["Probability distribution $P(k_{in})$"],
"-axisfsize": ["large"],
"-ncol": [1],
"-loc": [1],
}
)
for i in range(len(lsarg)):
ds = []
func = lsarg[i]["func"][0]
step = p.STEP
argstep = getargval(lsarg[i], "-j")
if argstep:
step = int(argstep[0])
f = open(lsarg[i]["files"][0])
try:
data = json.load(f)
p.loaddata(ds, func, data, lsarg[i]["files"][0], step)
finally:
f.close()
logx = False
arglogx = getargval(lsarg[i], "-logx")
if arglogx:
logx = int(arglogx[0]) > 0
logy = False
arglogy = getargval(lsarg[i], "-logy")
if arglogy:
logy = int(arglogy[0]) > 0
lb = p.LOGBINBASE
arglb = getargval(lsarg[i], "-lb")
if arglb:
lb = float(arglb[0])
xlim = getargval(lsarg[i], "-xlim")
ylim = getargval(lsarg[i], "-ylim")
plotfile = getargval(lsarg[i], "-v", [None])[0]
if func in [p.FUNC_LOGINDEG, p.FUNC_HISTINDEG]:
xlabel = "In-degree"
elif func in [p.FUNC_LOGOUTDEG, p.FUNC_HISTOUTDEG]:
xlabel = "Out-degree"
axisfsize = getargval(lsarg[i], "-axisfsize", ["medium"])[0]
try:
axisfsize = int(axisfsize)
except:
pass
ncol = int(getargval(lsarg[i], "-ncol", [1])[0])
numpoints = int(getargval(lsarg[i], "-numpoints", [1])[0])
if func in [p.FUNC_LOGINDEG, p.FUNC_LOGOUTDEG]:
# loglog degree distribution
p.drawloglogdist(
ds,
xlabel=getargval(lsarg[i], "-xl", [""])[0],
ylabel=getargval(lsarg[i], "-yl", [""])[0],
title=getargval(lsarg[i], "-t", [""])[0],
labels=getargval(lsarg[i], "-l"),
markset=getargval(lsarg[i], "-m", ["var"])[0],
xlim=xlim,
ylim=ylim,
axisfsize=axisfsize,
logbinbase=lb,
showexp=int(getargval(lsarg[i], "-g", [1])[0]),
legloc=int(getargval(lsarg[i], "-loc", [1])[0]),
ax=p.plt.gca(),
ncol=ncol,
numpoints=numpoints,
isexpline=int(getargval(lsarg[i], "-gl", [1])[0]),
)
elif func in [p.FUNC_DISTINDEG, p.FUNC_DISTOUTDEG]:
# degree distribution plot
if p.FUNC_DISTINDEG:
title = getargval(lsarg[i], "-t", ["Degree distribution of exponential network"])[0]
xylabels = {
"x": getargval(lsarg[i], "-xl", ["k (degree)"])[0],
"y": getargval(lsarg[i], "-yl", ["P(k)"])[0],
}
else:
title = getargval(lsarg[i], "-t", ["Outdegree distribution"])[0]
xylabels = {
"x": getargval(lsarg[i], "-xl", ["Outdegree"])[0],
"y": getargval(lsarg[i], "-yl", ["Number of nodes"])[0],
}
p.plotdegdist(
ds,
getargval(lsarg[i], "-l"),
getargval(lsarg[i], "-m", ["var"])[0],
title=title,
xylabels=xylabels,
nbins=int(getargval(lsarg[i], "-b", ["50"])[0]),
logx=logx,
logy=logy,
xlim=xlim,
ylim=ylim,
axisfsize=axisfsize,
legloc=int(getargval(lsarg[i], "-loc", [1])[0]),
ax=p.plt.gca(),
ncol=ncol,
numpoints=numpoints,
)
p.processplot(p.plt, getargval(lsarg[i], "-s", [None])[0])
