def testCases_random(self):
experimentNumber = 10
iterationNumber = 10
last = time.time()
experiment = 0
while experiment < experimentNumber:
print 'EXPERIMENT', experiment, time.time() - last
last = time.time()
#Create a random history
history = RandomHistory(3, 3)
avg = history.avg()
#Undo stuff in the first graph
baseGraph = deAVG(avg)
if baseGraph.substitutionAmbiguity(
) == 0 or baseGraph.rearrangementAmbiguity() == 0:
continue
def reportGraph(graph, graphName, iteration, step):
graph = copy.copy(graph)
graph.addFreeRoots()
print "\t".join([
"graphName", graphName, "experiment",
str(experiment), "iteration",
str(iteration), "step",
str(step), "ambiguity",
str(graph.ambiguity()), "u_s",
str(graph.substitutionAmbiguity()), "u_r",
str(graph.rearrangementAmbiguity()), "lbsc",
str(graph.lowerBoundSubstitutionCost()), "lbrc",
str(graph.lowerBoundRearrangementCost()), "ubsc",
str(graph.upperBoundSubstitutionCost()), "ubrc",
str(graph.upperBoundRearrangementCost())
])
#Report the starting point
reportGraph(avg, "H", "n/a", "n/a")
assert avg.validate()
#Write stuff about G
reportGraph(baseGraph, "G", "n/a", "n/a")
assert baseGraph.validate()
for iteration in range(iterationNumber):
print "Starting iteration", iteration
graph = copy.copy(baseGraph)
#Undo the ambiguity
lBSC = graph.lowerBoundSubstitutionCost()
lBRC = graph.lowerBoundRearrangementCost()
step = 1
while graph.ambiguity():
reportGraph(graph, "G'", iteration, step)
c1EL = listCase1(graph)
c2EL = listCase2(graph)
#print "There are %s labeling extensions and %s bond extensions" % (len(c1EL), len(c2EL))
chosenExtension = random.choice(c1EL + c2EL)
chosenExtension.function(chosenExtension.args)
assert graph.validate()
assert lBSC <= graph.lowerBoundSubstitutionCost()
assert lBRC <= graph.lowerBoundRearrangementCost()
lBSC = graph.lowerBoundSubstitutionCost()
lBRC = graph.lowerBoundRearrangementCost()
step += 1
#Report final AVG
reportGraph(graph, "G'", iteration, step)
assert graph.validate()
assert graph.lowerBoundSubstitutionCost(
) == graph.upperBoundSubstitutionCost()
assert graph.lowerBoundRearrangementCost(
) == graph.upperBoundRearrangementCost()
for m in graph.modules():
assert m.isSimple()
experiment += 1
def main():
experimentNumber = 10
iterationNumber = 2000
startTime = time.time()
last = startTime
results = []
experiment = 0
segmentNumber = 5
epochs = 4
outputDir = "results"
system("mkdir %s" % outputDir)
while experiment < experimentNumber:
#Create a random history
history = RandomHistory(segmentNumber, epochs)
avg = history.avg()
def breakAllHomologousSides(side, graph):
if side.bond != None:
graph.deleteBond(side)
for child in side.children():
breakAllHomologousSides(child, graph)
def homologousSidesHaveOnlyTrivialLifts(side):
if side.bond != None and len(side.nonTrivialLiftedBonds()) > 0:
return False
for child in side.children():
if not homologousSidesHaveOnlyTrivialLifts(child):
return False
return True
sidesToBreak = [ side for side in avg.sides() if side.parent() == None and homologousSidesHaveOnlyTrivialLifts(side) ]
if len(sidesToBreak) > 0:
breakAllHomologousSides(sidesToBreak[0], avg)
#Undo stuff in the first graph
baseGraph = deAVG(avg)
assert avg.substitutionAmbiguity() == 0
assert avg.rearrangementAmbiguity() == 0
assert avg.lowerBoundRearrangementCost() == avg.upperBoundRearrangementCost()
assert baseGraph.lowerBoundRearrangementCost() <= avg.lowerBoundRearrangementCost()
#Selection of histories with what we want
if avg.lowerBoundRearrangementCost() == 0 or avg.lowerBoundSubstitutionCost() == 0 or baseGraph.substitutionAmbiguity() == 0 or baseGraph.rearrangementAmbiguity() == 0 or len([ segment for segment in baseGraph.segments if len(segment.children) == 0 ]) <= 3*segmentNumber:
continue
print avg.lowerBoundRearrangementCost(), avg.lowerBoundSubstitutionCost(), baseGraph.substitutionAmbiguity(), baseGraph.rearrangementAmbiguity(), len([ segment for segment in baseGraph.segments if len(segment.children) == 0 ]), 2*segmentNumber
def reportGraph(graph, graphName, iteration, step):
graph = copy.copy(graph)
graph.addFreeRoots()
return { "graphName":graphName,
"experiment":experiment,
"iteration":iteration,
"step":step, "ambiguity":graph.ambiguity(),
"u_s":graph.substitutionAmbiguity(),
"u_r":graph.rearrangementAmbiguity(),
"lbsc":graph.lowerBoundSubstitutionCost(),
"lbrc":int(graph.lowerBoundRearrangementCost()),
"ubsc":graph.upperBoundSubstitutionCost(),
"ubrc":int(graph.upperBoundRearrangementCost()),
"dot":("%s\n" % graph.dot()) }
#Report the starting point
results.append(reportGraph(avg, "H", "n/a", "n/a"))
#assert avg.validate()
#Write stuff about G
results.append(reportGraph(baseGraph, "G", "n/a", "n/a"))
#assert baseGraph.validate()
for iteration in range(iterationNumber):
print "Starting iteration", iteration
graph = copy.copy(baseGraph)
#Undo the ambiguity
#lBSC = graph.lowerBoundSubstitutionCost()
#lBRC = graph.lowerBoundRearrangementCost()
step = 1
while graph.ambiguity():
results.append(reportGraph(graph, "G'", iteration, step))
c1EL = listCase1(graph)
c2EL = listCase2(graph)
c3EL = listCase3(graph)
#print "There are %s labeling extensions and %s bond extensions" % (len(c1EL), len(c2EL))
chosenExtension = random.choice(c1EL + c2EL + c3EL)
chosenExtension.function(chosenExtension.args)
#assert graph.validate()
#assert lBSC <= graph.lowerBoundSubstitutionCost()
#assert lBRC <= graph.lowerBoundRearrangementCost()
#lBSC = graph.lowerBoundSubstitutionCost()
#lBRC = graph.lowerBoundRearrangementCost()
step += 1
#Report final AVG
for segment in list(graph.segments): #Get rid of useless nodes
if segment.label == None and segment.left.bond == None and segment.right.bond == None:
segment.disconnect()
graph.segments.remove(segment)
# Recompute the event graph from scratch
graph.eventGraph, graph.segmentThreads = graph.threads()
graph.timeEventGraph()
results.append(reportGraph(graph, "G'", iteration, step))
#assert graph.validate()
#assert graph.lowerBoundSubstitutionCost() == graph.upperBoundSubstitutionCost()
#assert graph.lowerBoundRearrangementCost() == graph.upperBoundRearrangementCost()
#for m in graph.modules():
# assert m.isSimple()
experiment += 1
print 'EXPERIMENT', experiment, time.time() - last
last = time.time()
#print "results", results
###Now format results for printing
#Print table with following fields
#Experiment, s(H), r(H), lbsc(G), ubsc(G), lbrc(G), ubrc(G), min_G' s(G'), min_G' r(G'), max_G' s(G'), max_G' r(G'), med_G' s(G'), med_G' s(G')
print "Making summary tables latex"
def fn(statFn, term):
return int(statFn([ row[term] for row in gPRows ]))
def med(l):
l = l[:]
l.sort()
if len(l) % 2 == 1:
return l[len(l)/2]
return (l[len(l)/2] + l[len(l)/2 - 1])/2.0
def getRows():
experimentResults = [ row for row in results if row["experiment"] == experiment ]
return [ row for row in experimentResults if row["graphName"] == "H" ][0], [ row for row in experimentResults if row["graphName"] == "G" ][0], [ row for row in experimentResults if row["graphName"] == "G'" and row["ambiguity"] == 0 ]
rTable = [ [ "exp.", "$r(H)$", "$u_r(G)$", "$lbrc(G)$", "$ubrc(G)$", "$r(G_{rmin}')$", "$r(G_{rmax}')$", "$r(G_{rmed}')$" ] ]
for experiment in range(experimentNumber):
historyRow, gRow, gPRows = getRows()
rTable.append([ str(i) for i in [ experiment, historyRow["lbrc"], gRow["u_r"], gRow["lbrc"], gRow["ubrc"], fn(min, "lbrc"), fn(max, "lbrc"), fn(med, "lbrc") ] ])
sTable = [ [ "exp.", "$s(H)$", "$u_s(G)$", "$lbsc(G)$", "$ubsc(G)$", "$s(G_{smin}')$", "$s(G_{smax}')$", "$s(G_{smed}')$" ] ]
for experiment in range(experimentNumber):
historyRow, gRow, gPRows = getRows()
sTable.append([ str(i) for i in [ experiment, historyRow["lbsc"], gRow["u_s"], gRow["lbsc"], gRow["ubsc"], fn(min, "lbsc"), fn(max, "lbsc"), fn(med, "lbsc")] ])
def writeLatexTable(table, fileName, tableLabel, caption=""):
fH = open(os.path.join(outputDir, fileName), 'w')
writeDocumentPreliminaries(fH)
writePreliminaries(8, fH)
for line in table:
writeRow(line, fH)
writeEnd(fH, tableLabel, caption)
writeDocumentEnd(fH)
fH.close()
writeLatexTable(sTable, "aggregateSubs.tex", "subsExpTable", "Results for substitution ambiguity and cost. Starting for an initial evolutionary history H we randomly removed elements to create G and then, by G-bounded extension operations, created a G-bounded AVG G'. Each row represents a separate initial evolutionary history. For each evolutionary history we created 1000 $G$-bounded AVG extensions. $G'_{smin}$, $G'_{smax}$ and $G'_{smax}$ are, respectively, the $G$-bounded extension with minimum, maximum and median substitution cost.")
writeLatexTable(rTable, "aggregateRearrangements.tex", "rearrangeExpTable", "Follows format of Table \\ref{subsExpTable}.")
def writeTSVTable(table, fileName):
fH = open(os.path.join(outputDir, fileName), 'w')
for line in table:
fH.write("\t".join(line) + "\n")
fH.close()
writeTSVTable(sTable, "aggregateSubs.tsv")
writeTSVTable(rTable, "aggregateRearrangements.tsv")
print "Making step-wise .tsv files"
#Write .tsv files showing the change in the bounds during extension from G to G' during an iteration
def writeStepFile(argName, fn):
fH = open(os.path.join(outputDir, "%s.%s.steps.tsv" % (experiment, argName)), 'w')
historyRow = getRows()[0]
fH.write("#TSV showing %s value, original history had %s value \n" % (argName, fn(historyRow)))
experimentResults = [ row for row in results if row["experiment"] == experiment and row["graphName"] == "G'" ]
experimentResultsByIteration = [ [] for i in range(iterationNumber) ]
for row in experimentResults:
experimentResultsByIteration[row["iteration"]].append(row)
#Print row for scale
fH.write("\t".join([ str(j) for j in range(max([ len(i) for i in experimentResultsByIteration ])) ]) + "\n")
for it in xrange(iterationNumber):
itRows = experimentResultsByIteration[it]
fH.write("%s\n" % "\t".join([ str(fn(row)) for row in itRows]))
fH.close()
for experiment in range(experimentNumber):
writeStepFile("lbrc", lambda row : row["lbrc"])
writeStepFile("ubrc", lambda row : row["ubrc"])
writeStepFile("ubrc-lbrc", lambda row : row["ubrc"] - row["lbrc"])
writeStepFile("lbsc", lambda row : row["lbsc"])
writeStepFile("ubsc", lambda row : row["ubsc"])
writeStepFile("lbsc-ubsc", lambda row : row["ubsc"] - row["lbsc"])
print "Making graphviz plots"
#Write the dot files of the H, G and G_min, G_max and G_med for each experiment
for experiment in range(experimentNumber):
historyRow, gRow, gPRows = getRows()
dirName = os.path.join(outputDir, "%s_graphViz" % experiment)
system("mkdir %s" % dirName)
def fn(statFn, term):
i = statFn([ row[term] for row in gPRows ])
return [ row for row in gPRows if int(row[term]) == i ][0]
def writeDot(fileName, row):
fileName = os.path.join(dirName, fileName)
fH = open(fileName, 'w')
fH.write("%s\n" % row["dot"])
fH.close()
system("dot %s -Tpdf > %s.pdf" % (fileName, fileName))
writeDot("history", historyRow)
writeDot("g", gRow)
writeDot("gPRRMin" , fn(min, "ubrc"))
writeDot("gPRRMax", fn(max, "ubrc"))
writeDot("gPRSMin" , fn(min, "ubsc"))
writeDot("gPRSMax", fn(max, "ubsc"))
print "Simulations took %s seconds" % (time.time() - startTime)
def testCases_random(self):
experimentNumber = 10
iterationNumber = 10
last = time.time()
experiment = 0
while experiment < experimentNumber:
print 'EXPERIMENT', experiment, time.time() - last
last = time.time()
#Create a random history
history = RandomHistory(3, 3)
avg = history.avg()
#Undo stuff in the first graph
baseGraph = deAVG(avg)
if baseGraph.substitutionAmbiguity() == 0 or baseGraph.rearrangementAmbiguity() == 0:
continue
def reportGraph(graph, graphName, iteration, step):
graph = copy.copy(graph)
graph.addFreeRoots()
print "\t".join([ "graphName", graphName,
"experiment", str(experiment),
"iteration", str(iteration),
"step", str(step),
"ambiguity", str(graph.ambiguity()),
"u_s", str(graph.substitutionAmbiguity()),
"u_r", str(graph.rearrangementAmbiguity()),
"lbsc", str(graph.lowerBoundSubstitutionCost()),
"lbrc", str(graph.lowerBoundRearrangementCost()),
"ubsc", str(graph.upperBoundSubstitutionCost()),
"ubrc", str(graph.upperBoundRearrangementCost()) ])
#Report the starting point
reportGraph(avg, "H", "n/a", "n/a")
assert avg.validate()
#Write stuff about G
reportGraph(baseGraph, "G", "n/a", "n/a")
assert baseGraph.validate()
for iteration in range(iterationNumber):
print "Starting iteration", iteration
graph = copy.copy(baseGraph)
#Undo the ambiguity
lBSC = graph.lowerBoundSubstitutionCost()
lBRC = graph.lowerBoundRearrangementCost()
step = 1
while graph.ambiguity():
reportGraph(graph, "G'", iteration, step)
c1EL = listCase1(graph)
c2EL = listCase2(graph)
#print "There are %s labeling extensions and %s bond extensions" % (len(c1EL), len(c2EL))
chosenExtension = random.choice(c1EL + c2EL)
chosenExtension.function(chosenExtension.args)
assert graph.validate()
assert lBSC <= graph.lowerBoundSubstitutionCost()
assert lBRC <= graph.lowerBoundRearrangementCost()
lBSC = graph.lowerBoundSubstitutionCost()
lBRC = graph.lowerBoundRearrangementCost()
step += 1
#Report final AVG
reportGraph(graph, "G'", iteration, step)
assert graph.validate()
assert graph.lowerBoundSubstitutionCost() == graph.upperBoundSubstitutionCost()
assert graph.lowerBoundRearrangementCost() == graph.upperBoundRearrangementCost()
for m in graph.modules():
assert m.isSimple()
experiment += 1
def main():
experimentNumber = 10
iterationNumber = 2000
startTime = time.time()
last = startTime
results = []
experiment = 0
segmentNumber = 5
epochs = 4
outputDir = "results"
system("mkdir %s" % outputDir)
while experiment < experimentNumber:
#Create a random history
history = RandomHistory(segmentNumber, epochs)
avg = history.avg()
def breakAllHomologousSides(side, graph):
if side.bond != None:
graph.deleteBond(side)
for child in side.children():
breakAllHomologousSides(child, graph)
def homologousSidesHaveOnlyTrivialLifts(side):
if side.bond != None and len(side.nonTrivialLiftedBonds()) > 0:
return False
for child in side.children():
if not homologousSidesHaveOnlyTrivialLifts(child):
return False
return True
sidesToBreak = [
side for side in avg.sides() if side.parent() == None
and homologousSidesHaveOnlyTrivialLifts(side)
]
if len(sidesToBreak) > 0:
breakAllHomologousSides(sidesToBreak[0], avg)
#Undo stuff in the first graph
baseGraph = deAVG(avg)
assert avg.substitutionAmbiguity() == 0
assert avg.rearrangementAmbiguity() == 0
assert avg.lowerBoundRearrangementCost(
) == avg.upperBoundRearrangementCost()
assert baseGraph.lowerBoundRearrangementCost(
) <= avg.lowerBoundRearrangementCost()
#Selection of histories with what we want
if avg.lowerBoundRearrangementCost(
) == 0 or avg.lowerBoundSubstitutionCost(
) == 0 or baseGraph.substitutionAmbiguity(
) == 0 or baseGraph.rearrangementAmbiguity() == 0 or len([
segment
for segment in baseGraph.segments if len(segment.children) == 0
]) <= 3 * segmentNumber:
continue
print avg.lowerBoundRearrangementCost(
), avg.lowerBoundSubstitutionCost(), baseGraph.substitutionAmbiguity(
), baseGraph.rearrangementAmbiguity(), len([
segment for segment in baseGraph.segments
if len(segment.children) == 0
]), 2 * segmentNumber
def reportGraph(graph, graphName, iteration, step):
graph = copy.copy(graph)
graph.addFreeRoots()
return {
"graphName": graphName,
"experiment": experiment,
"iteration": iteration,
"step": step,
"ambiguity": graph.ambiguity(),
"u_s": graph.substitutionAmbiguity(),
"u_r": graph.rearrangementAmbiguity(),
"lbsc": graph.lowerBoundSubstitutionCost(),
"lbrc": int(graph.lowerBoundRearrangementCost()),
"ubsc": graph.upperBoundSubstitutionCost(),
"ubrc": int(graph.upperBoundRearrangementCost()),
"dot": ("%s\n" % graph.dot())
}
#Report the starting point
results.append(reportGraph(avg, "H", "n/a", "n/a"))
#assert avg.validate()
#Write stuff about G
results.append(reportGraph(baseGraph, "G", "n/a", "n/a"))
#assert baseGraph.validate()
for iteration in range(iterationNumber):
print "Starting iteration", iteration
graph = copy.copy(baseGraph)
#Undo the ambiguity
#lBSC = graph.lowerBoundSubstitutionCost()
#lBRC = graph.lowerBoundRearrangementCost()
step = 1
while graph.ambiguity():
results.append(reportGraph(graph, "G'", iteration, step))
c1EL = listCase1(graph)
c2EL = listCase2(graph)
c3EL = listCase3(graph)
#print "There are %s labeling extensions and %s bond extensions" % (len(c1EL), len(c2EL))
chosenExtension = random.choice(c1EL + c2EL + c3EL)
chosenExtension.function(chosenExtension.args)
#assert graph.validate()
#assert lBSC <= graph.lowerBoundSubstitutionCost()
#assert lBRC <= graph.lowerBoundRearrangementCost()
#lBSC = graph.lowerBoundSubstitutionCost()
#lBRC = graph.lowerBoundRearrangementCost()
step += 1
#Report final AVG
for segment in list(graph.segments): #Get rid of useless nodes
if segment.label == None and segment.left.bond == None and segment.right.bond == None:
segment.disconnect()
graph.segments.remove(segment)
# Recompute the event graph from scratch
graph.eventGraph, graph.segmentThreads = graph.threads()
graph.timeEventGraph()
results.append(reportGraph(graph, "G'", iteration, step))
#assert graph.validate()
#assert graph.lowerBoundSubstitutionCost() == graph.upperBoundSubstitutionCost()
#assert graph.lowerBoundRearrangementCost() == graph.upperBoundRearrangementCost()
#for m in graph.modules():
# assert m.isSimple()
experiment += 1
print 'EXPERIMENT', experiment, time.time() - last
last = time.time()
#print "results", results
###Now format results for printing
#Print table with following fields
#Experiment, s(H), r(H), lbsc(G), ubsc(G), lbrc(G), ubrc(G), min_G' s(G'), min_G' r(G'), max_G' s(G'), max_G' r(G'), med_G' s(G'), med_G' s(G')
print "Making summary tables latex"
def fn(statFn, term):
return int(statFn([row[term] for row in gPRows]))
def med(l):
l = l[:]
l.sort()
if len(l) % 2 == 1:
return l[len(l) / 2]
return (l[len(l) / 2] + l[len(l) / 2 - 1]) / 2.0
def getRows():
experimentResults = [
row for row in results if row["experiment"] == experiment
]
return [row for row in experimentResults
if row["graphName"] == "H"][0], [
row for row in experimentResults if row["graphName"] == "G"
][0], [
row for row in experimentResults
if row["graphName"] == "G'" and row["ambiguity"] == 0
]
rTable = [[
"exp.", "$r(H)$", "$u_r(G)$", "$lbrc(G)$", "$ubrc(G)$",
"$r(G_{rmin}')$", "$r(G_{rmax}')$", "$r(G_{rmed}')$"
]]
for experiment in range(experimentNumber):
historyRow, gRow, gPRows = getRows()
rTable.append([
str(i) for i in [
experiment, historyRow["lbrc"], gRow["u_r"], gRow["lbrc"],
gRow["ubrc"],
fn(min, "lbrc"),
fn(max, "lbrc"),
fn(med, "lbrc")
]
])
sTable = [[
"exp.", "$s(H)$", "$u_s(G)$", "$lbsc(G)$", "$ubsc(G)$",
"$s(G_{smin}')$", "$s(G_{smax}')$", "$s(G_{smed}')$"
]]
for experiment in range(experimentNumber):
historyRow, gRow, gPRows = getRows()
sTable.append([
str(i) for i in [
experiment, historyRow["lbsc"], gRow["u_s"], gRow["lbsc"],
gRow["ubsc"],
fn(min, "lbsc"),
fn(max, "lbsc"),
fn(med, "lbsc")
]
])
def writeLatexTable(table, fileName, tableLabel, caption=""):
fH = open(os.path.join(outputDir, fileName), 'w')
writeDocumentPreliminaries(fH)
writePreliminaries(8, fH)
for line in table:
writeRow(line, fH)
writeEnd(fH, tableLabel, caption)
writeDocumentEnd(fH)
fH.close()
writeLatexTable(
sTable, "aggregateSubs.tex", "subsExpTable",
"Results for substitution ambiguity and cost. Starting for an initial evolutionary history H we randomly removed elements to create G and then, by G-bounded extension operations, created a G-bounded AVG G'. Each row represents a separate initial evolutionary history. For each evolutionary history we created 1000 $G$-bounded AVG extensions. $G'_{smin}$, $G'_{smax}$ and $G'_{smax}$ are, respectively, the $G$-bounded extension with minimum, maximum and median substitution cost."
)
writeLatexTable(rTable, "aggregateRearrangements.tex", "rearrangeExpTable",
"Follows format of Table \\ref{subsExpTable}.")
def writeTSVTable(table, fileName):
fH = open(os.path.join(outputDir, fileName), 'w')
for line in table:
fH.write("\t".join(line) + "\n")
fH.close()
writeTSVTable(sTable, "aggregateSubs.tsv")
writeTSVTable(rTable, "aggregateRearrangements.tsv")
print "Making step-wise .tsv files"
#Write .tsv files showing the change in the bounds during extension from G to G' during an iteration
def writeStepFile(argName, fn):
fH = open(
os.path.join(outputDir, "%s.%s.steps.tsv" % (experiment, argName)),
'w')
historyRow = getRows()[0]
fH.write("#TSV showing %s value, original history had %s value \n" %
(argName, fn(historyRow)))
experimentResults = [
row for row in results
if row["experiment"] == experiment and row["graphName"] == "G'"
]
experimentResultsByIteration = [[] for i in range(iterationNumber)]
for row in experimentResults:
experimentResultsByIteration[row["iteration"]].append(row)
#Print row for scale
fH.write("\t".join([
str(j)
for j in range(max([len(i) for i in experimentResultsByIteration]))
]) + "\n")
for it in xrange(iterationNumber):
itRows = experimentResultsByIteration[it]
fH.write("%s\n" % "\t".join([str(fn(row)) for row in itRows]))
fH.close()
for experiment in range(experimentNumber):
writeStepFile("lbrc", lambda row: row["lbrc"])
writeStepFile("ubrc", lambda row: row["ubrc"])
writeStepFile("ubrc-lbrc", lambda row: row["ubrc"] - row["lbrc"])
writeStepFile("lbsc", lambda row: row["lbsc"])
writeStepFile("ubsc", lambda row: row["ubsc"])
writeStepFile("lbsc-ubsc", lambda row: row["ubsc"] - row["lbsc"])
print "Making graphviz plots"
#Write the dot files of the H, G and G_min, G_max and G_med for each experiment
for experiment in range(experimentNumber):
historyRow, gRow, gPRows = getRows()
dirName = os.path.join(outputDir, "%s_graphViz" % experiment)
system("mkdir %s" % dirName)
def fn(statFn, term):
i = statFn([row[term] for row in gPRows])
return [row for row in gPRows if int(row[term]) == i][0]
def writeDot(fileName, row):
fileName = os.path.join(dirName, fileName)
fH = open(fileName, 'w')
fH.write("%s\n" % row["dot"])
fH.close()
system("dot %s -Tpdf > %s.pdf" % (fileName, fileName))
writeDot("history", historyRow)
writeDot("g", gRow)
writeDot("gPRRMin", fn(min, "ubrc"))
writeDot("gPRRMax", fn(max, "ubrc"))
writeDot("gPRSMin", fn(min, "ubsc"))
writeDot("gPRSMax", fn(max, "ubsc"))
print "Simulations took %s seconds" % (time.time() - startTime)
