def runAssembler(snpRate, typeOfGen, detail, parameterRobot):
#N, G, L, p,K,snpRate, typeOfGen, detail = 100, 100, 10000, 0.01,30,0.001, 'r', "1000"
motherGen, reads, noisyReads = dataGen.generateData(
typeOfGen, detail, parameterRobot)
motherGen, reads, noisyReads = logging.rawDataLoad(
parameterRobot.defaultFolder + "UnitTest", parameterRobot.G,
parameterRobot.N, parameterRobot.L, "dn")
f1 = cluster.groupIndelNoisyKmers(noisyReads, parameterRobot)
G1, startList, f1 = graphForm.getSeqGraph(f1, noisyReads, parameterRobot)
f2, G2 = branchClear.clearResidual(f1, G1, parameterRobot)
G3 = bridgeResolve.resolveRepeats(f2, G2, parameterRobot)
G4 = alignmentBridge.MSAresolve(f2, G3, noisyReads, snpRate,
parameterRobot)
#G4 = G3
recovSeq = eulerCycle.findEC(G4)
recovGen = readAns.reportRecovSeq(recovSeq, f2, noisyReads, parameterRobot)
numMistakes, success = compare.subAlignCompare(recovGen, motherGen,
parameterRobot)
#numMistakes, success = 0 , 0
return numMistakes, success
# Target of the new code : Fast Assemble and assembly in optimal amount of information
#t0 = time.time()
#N, G, L, p,snpRate, typeOfGen, detail = 1000, 10000,200, 0.015, 0.001 ,'m', "500-300-50"
#runAssembler(N, G, L, p,snpRate, typeOfGen, detail)
#print "Time (sec) :", time.time() - t0
def runAssembler(snpRate, typeOfGen, detail,parameterRobot):
#N, G, L, p,K,snpRate, typeOfGen, detail = 100, 100, 10000, 0.01,30,0.001, 'r', "1000"
motherGen, reads, noisyReads = dataGen.generateData(typeOfGen, detail,parameterRobot)
motherGen, reads, noisyReads = logging.rawDataLoad(parameterRobot.defaultFolder+"UnitTest",parameterRobot.G,parameterRobot.N,parameterRobot.L, "dn")
f1 = cluster.groupIndelNoisyKmers(noisyReads,parameterRobot)
G1,startList, f1 = graphForm.getSeqGraph(f1,noisyReads, parameterRobot)
f2, G2 = branchClear.clearResidual(f1, G1,parameterRobot)
G3 = bridgeResolve.resolveRepeats(f2, G2,parameterRobot)
G4 = alignmentBridge.MSAresolve(f2, G3, noisyReads, snpRate,parameterRobot )
#G4 = G3
recovSeq = eulerCycle.findEC(G4)
recovGen = readAns.reportRecovSeq(recovSeq, f2, noisyReads,parameterRobot)
numMistakes, success = compare.subAlignCompare(recovGen, motherGen,parameterRobot)
#numMistakes, success = 0 , 0
return numMistakes, success
# Target of the new code : Fast Assemble and assembly in optimal amount of information
#t0 = time.time()
#N, G, L, p,snpRate, typeOfGen, detail = 1000, 10000,200, 0.015, 0.001 ,'m', "500-300-50"
#runAssembler(N, G, L, p,snpRate, typeOfGen, detail)
#print "Time (sec) :", time.time() - t0
def clusterUnitTest2():
# Unit Test 1 : Generate 30 reads with 10 copies with noise , length being 20
motherGen, reads, noisyReads = logging.rawDataLoad("clusterReadsUnitTest",
10, 300, 40, "dn")
parameterRobot = logging.parameterObj()
parameterRobot.N = 300
parameterRobot.L = 40
parameterRobot.G = 10000
parameterRobot.liid = 30
parameterRobot.K = 30
parameterRobot.threshold = 5
parameterRobot.p = 0.01
parameterRobot.indel = True
cluster.groupIndelNoisyKmers(noisyReads, parameterRobot, "fast")
def clusterUnitTest2():
# Unit Test 1 : Generate 30 reads with 10 copies with noise , length being 20
motherGen, reads, noisyReads = logging.rawDataLoad("clusterReadsUnitTest",10,300,40,"dn")
parameterRobot = logging.parameterObj()
parameterRobot.N = 300
parameterRobot.L = 40
parameterRobot.G = 10000
parameterRobot.liid = 30
parameterRobot.K = 30
parameterRobot.threshold = 5
parameterRobot.p = 0.01
parameterRobot.indel = True
cluster.groupIndelNoisyKmers(noisyReads, parameterRobot, "fast")
def graphFormUnitTest(N, G, L, folderName =""):
print "dataGenUnitTest"
dummyParameters = logging.parameterObj()
dummyParameters.defaultFolder = folderName
dummyParameters.liid = 40
dummyParameters.K = 40
dummyParameters.threshold = 6
dummyParameters.p = 0.015
dummyParameters.indel = True
dummyParameters.N, dummyParameters.G, dummyParameters.L, dummyParameters.p, typeOfGen, detail = N, G, L, 0.015, 'm', "500-200-50"
# motherGen, reads, noisyReads = dataGen.generateData( typeOfGen,detail,dummyParameters)
motherGen, reads, noisyReads = logging.rawDataLoad(dummyParameters.defaultFolder+"UnitTest",dummyParameters.G,dummyParameters.N,dummyParameters.L, "dn")
returnfmapping= cluster.groupIndelNoisyKmers(noisyReads, dummyParameters, "fast")
def graphFormUnitTest(N, G, L, folderName=""):
print "dataGenUnitTest"
dummyParameters = logging.parameterObj()
dummyParameters.defaultFolder = folderName
dummyParameters.liid = 40
dummyParameters.K = 40
dummyParameters.threshold = 6
dummyParameters.p = 0.015
dummyParameters.indel = True
dummyParameters.N, dummyParameters.G, dummyParameters.L, dummyParameters.p, typeOfGen, detail = N, G, L, 0.015, 'm', "500-200-50"
# motherGen, reads, noisyReads = dataGen.generateData( typeOfGen,detail,dummyParameters)
motherGen, reads, noisyReads = logging.rawDataLoad(
dummyParameters.defaultFolder + "UnitTest", dummyParameters.G,
dummyParameters.N, dummyParameters.L, "dn")
returnfmapping = cluster.groupIndelNoisyKmers(noisyReads, dummyParameters,
"fast")