def testChildTreeJob(self):
"""Check that the ChildTreeJob class runs all children."""
numChildren = 100
flagDir = getTempDirectory()
options = Job.Runner.getDefaultOptions(getTempDirectory())
shutil.rmtree(options.jobStore)
with Toil(options) as toil:
toil.start(CTTestParent(flagDir, numChildren))
# Check that all jobs ran
for i in xrange(numChildren):
self.assertTrue(os.path.exists(os.path.join(flagDir, str(i))))
shutil.rmtree(flagDir)
def testChildTreeJob(self):
"""Check that the ChildTreeJob class runs all children."""
numChildren = 100
flagDir = getTempDirectory()
options = Job.Runner.getDefaultOptions(getTempDirectory())
shutil.rmtree(options.jobStore)
with Toil(options) as toil:
toil.start(CTTestParent(flagDir, numChildren))
# Check that all jobs ran
for i in range(numChildren):
self.assertTrue(os.path.exists(os.path.join(flagDir, str(i))))
shutil.rmtree(flagDir)
def scriptTree_SortTest(testNo, batchSystem, lines=10000, maxLineLength=10, N=10000):
"""Tests scriptTree/jobTree by sorting a file in parallel.
"""
for test in xrange(testNo):
tempDir = getTempDirectory(os.getcwd())
tempFile = getTempFile(rootDir=tempDir)
jobTreeDir = os.path.join(tempDir, "testJobTree")
makeFileToSort(tempFile, lines=lines, maxLineLength=maxLineLength)
#First make our own sorted version
fileHandle = open(tempFile, 'r')
l = fileHandle.readlines()
l.sort()
fileHandle.close()
#Sort the file
while True:
command = "scriptTreeTest_Sort.py --jobTree %s --logLevel=DEBUG --fileToSort=%s --N %i --batchSystem %s --jobTime 1.0 --maxCpus 20 --retryCount 2" % (jobTreeDir, tempFile, N, batchSystem) #, retryCount)
system(command)
try:
system("jobTreeStatus --jobTree %s --failIfNotComplete" % jobTreeDir)
break
except:
print "The jobtree failed and will be restarted"
#raise RuntimeError()
continue
#Now check the file is properly sorted..
#Now get the sorted file
fileHandle = open(tempFile, 'r')
l2 = fileHandle.readlines()
fileHandle.close()
checkEqual(l, l2)
system("rm -rf %s" % tempDir)
def run(self, fileStore):
sequenceFiles1 = [
fileStore.readGlobalFile(fileID)
for fileID in self.sequenceFileIDs1
]
chunks = runGetChunks(
sequenceFiles=sequenceFiles1,
chunksDir=getTempDirectory(rootDir=fileStore.getLocalTempDir()),
chunkSize=self.blastOptions.chunkSize,
overlapSize=self.blastOptions.overlapSize)
assert len(chunks) > 0
logger.info(
"Broken up the sequence files into individual 'chunk' files")
chunkIDs = [
fileStore.writeGlobalFile(chunk, cleanup=True) for chunk in chunks
]
diagonalResultsID = self.addChild(
MakeSelfBlasts(self.blastOptions, chunkIDs)).rv()
offDiagonalResultsID = self.addChild(
MakeOffDiagonalBlasts(self.blastOptions, chunkIDs)).rv()
logger.debug("Collating the blasts after blasting all-against-all")
return self.addFollowOn(
CollateBlasts(self.blastOptions,
[diagonalResultsID, offDiagonalResultsID])).rv()
def runComparisonOfBlastScriptVsNaiveBlast(self, blastMode):
"""We compare the output with a naive run of the blast program, to check the results are nearly
equivalent.
"""
encodeRegions = [ "ENm00" + str(i) for i in xrange(1,2) ] #, 2) ] #Could go to six
species = ("human", "mouse", "dog")
#Other species to try "rat", "monodelphis", "macaque", "chimp"
for encodeRegion in encodeRegions:
regionPath = os.path.join(self.encodePath, encodeRegion)
for i in xrange(len(species)):
species1 = species[i]
for species2 in species[i+1:]:
seqFile1 = os.path.join(regionPath, "%s.%s.fa" % (species1, encodeRegion))
seqFile2 = os.path.join(regionPath, "%s.%s.fa" % (species2, encodeRegion))
#Run simple blast
runNaiveBlast(seqFile1, seqFile2, self.tempOutputFile, self.tempDir)
logger.info("Ran the naive blast okay")
#Run cactus blast pipeline
toilDir = os.path.join(getTempDirectory(self.tempDir), "toil")
if blastMode == "allAgainstAll":
runCactusBlast(sequenceFiles=[ seqFile1, seqFile2 ],
alignmentsFile=self.tempOutputFile2, toilDir=toilDir,
chunkSize=500000, overlapSize=10000)
else:
runCactusBlast(sequenceFiles=[ seqFile1 ], alignmentsFile=self.tempOutputFile2,
toilDir=toilDir, chunkSize=500000, overlapSize=10000,
targetSequenceFiles=[ seqFile2 ])
logger.info("Ran cactus_blast okay")
logger.critical("Comparing cactus_blast and naive blast; using mode: %s" % blastMode)
checkCigar(self.tempOutputFile)
checkCigar(self.tempOutputFile2)
compareResultsFile(self.tempOutputFile, self.tempOutputFile2)
def runWorkflow_multipleExamples(inputGenFunction,
testNumber=1,
testRestrictions=(TestStatus.TEST_SHORT, TestStatus.TEST_MEDIUM, \
TestStatus.TEST_LONG, TestStatus.TEST_VERY_LONG,),
inverseTestRestrictions=False,
batchSystem="single_machine",
buildAvgs=False, buildReference=False,
buildReferenceSequence=False,
buildCactusPDF=False, buildAdjacencyPDF=False,
buildReferencePDF=False,
makeCactusTreeStats=False, makeMAFs=False,
configFile=None, buildJobTreeStats=False):
"""A wrapper to run a number of examples.
"""
if (inverseTestRestrictions and TestStatus.getTestStatus() not in testRestrictions) or \
(not inverseTestRestrictions and TestStatus.getTestStatus() in testRestrictions):
for test in xrange(testNumber):
tempDir = getTempDirectory(os.getcwd())
sequences, newickTreeString = inputGenFunction(regionNumber=test,
tempDir=tempDir)
runWorkflow_TestScript(sequences,
newickTreeString,
batchSystem=batchSystem,
buildAvgs=buildAvgs,
buildReference=buildReference,
buildCactusPDF=buildCactusPDF,
buildAdjacencyPDF=buildAdjacencyPDF,
makeCactusTreeStats=makeCactusTreeStats,
makeMAFs=makeMAFs,
configFile=configFile,
buildJobTreeStats=buildJobTreeStats)
system("rm -rf %s" % tempDir)
logger.info("Finished random test %i" % test)
def testBlastRandom(self):
"""Make some sequences, put them in a file, call blast with random parameters
and check it runs okay.
"""
tempSeqFile = os.path.join(self.tempDir, "tempSeq.fa")
self.tempFiles.append(tempSeqFile)
for test in xrange(self.testNo):
seqNo = random.choice(xrange(0, 10))
seq = getRandomSequence(8000)[1]
fileHandle = open(tempSeqFile, 'w')
for fastaHeader, seq in [(str(i),
mutateSequence(seq,
0.3 * random.random()))
for i in xrange(seqNo)]:
if random.random() > 0.5:
seq = reverseComplement(seq)
fastaWrite(fileHandle, fastaHeader, seq)
fileHandle.close()
chunkSize = random.choice(xrange(500, 9000))
overlapSize = random.choice(xrange(2, 100))
toilDir = os.path.join(getTempDirectory(self.tempDir), "toil")
runCactusBlast([tempSeqFile], self.tempOutputFile, toilDir,
chunkSize, overlapSize)
#runToilStatusAndFailIfNotComplete(toilDir)
if getLogLevelString() == "DEBUG":
system("cat %s" % self.tempOutputFile)
system("rm -rf %s " % toilDir)
def setUp(self):
unittest.TestCase.setUp(self)
self.testNo = TestStatus.getTestSetup(1, 2, 10, 10)
self.tempDir = getTempDirectory(os.getcwd())
self.jobTreeDir = os.path.join(
self.tempDir,
"testJobTree") #A directory for the job tree to be created in
def runComparisonOfBlastScriptVsNaiveBlast(self, blastMode):
"""We compare the output with a naive run of the blast program, to check the results are nearly
equivalent.
"""
encodeRegions = [ "ENm00" + str(i) for i in xrange(1,2) ] #, 2) ] #Could go to six
species = ("human", "mouse", "dog")
#Other species to try "rat", "monodelphis", "macaque", "chimp"
for encodeRegion in encodeRegions:
regionPath = os.path.join(self.encodePath, encodeRegion)
for i in xrange(len(species)):
species1 = species[i]
for species2 in species[i+1:]:
seqFile1 = os.path.join(regionPath, "%s.%s.fa" % (species1, encodeRegion))
seqFile2 = os.path.join(regionPath, "%s.%s.fa" % (species2, encodeRegion))
#Run simple blast
runNaiveBlast(seqFile1, seqFile2, self.tempOutputFile, self.tempDir)
logger.info("Ran the naive blast okay")
#Run cactus blast pipeline
toilDir = os.path.join(getTempDirectory(self.tempDir), "toil")
if blastMode == "allAgainstAll":
runCactusBlast(sequenceFiles=[ seqFile1, seqFile2 ],
alignmentsFile=self.tempOutputFile2, toilDir=toilDir,
chunkSize=500000, overlapSize=10000)
else:
runCactusBlast(sequenceFiles=[ seqFile1 ], alignmentsFile=self.tempOutputFile2,
toilDir=toilDir, chunkSize=500000, overlapSize=10000,
targetSequenceFiles=[ seqFile2 ])
logger.info("Ran cactus_blast okay")
logger.critical("Comparing cactus_blast and naive blast; using mode: %s" % blastMode)
checkCigar(self.tempOutputFile)
checkCigar(self.tempOutputFile2)
compareResultsFile(self.tempOutputFile, self.tempOutputFile2)
def testCactusSetup(self):
"""Creates a bunch of random inputs and then passes them to cactus setup.
"""
for test in xrange(self.testNo):
tempDir = os.path.relpath(getTempDirectory(os.getcwd()))
sequenceNumber = random.choice(xrange(100))
sequences, newickTreeString = getCactusInputs_random(
tempDir=tempDir, sequenceNumber=sequenceNumber)
#Setup the flower disk.
experiment = getCactusWorkflowExperimentForTest(
sequences, newickTreeString,
os.path.join('/data', os.path.relpath(tempDir)))
cactusDiskDatabaseString = experiment.getDiskDatabaseString()
cactusSequencesPath = os.path.join(experiment.getDbDir(),
"cactusSequences")
runCactusSetup(cactusDiskDatabaseString=cactusDiskDatabaseString,
cactusSequencesPath=cactusSequencesPath,
sequences=sequences,
newickTreeString=newickTreeString)
runCactusSetup(cactusDiskDatabaseString=cactusDiskDatabaseString,
cactusSequencesPath=cactusSequencesPath,
sequences=sequences,
newickTreeString=newickTreeString)
experiment.cleanupDb()
system("rm -rf %s" % tempDir)
logger.info("Finished test %i of cactus_setup.py", test)
def run(self, fileStore):
logger.info("Preparing sequence for preprocessing")
inSequence = fileStore.readGlobalFile(self.inSequenceID)
if self.prepOptions.chunkSize <= 0:
# In this first case we don't need to break up the sequence
chunked = False
inChunkList = [inSequence]
else:
# chunk it up
chunked = True
inChunkDirectory = getTempDirectory(
rootDir=fileStore.getLocalTempDir())
inChunkList = runGetChunks(sequenceFiles=[inSequence],
chunksDir=inChunkDirectory,
chunkSize=self.prepOptions.chunkSize,
overlapSize=0)
inChunkList = [os.path.abspath(path) for path in inChunkList]
logger.info("Chunks = %s" % inChunkList)
inChunkIDList = [
fileStore.writeGlobalFile(chunk, cleanup=True)
for chunk in inChunkList
]
outChunkIDList = []
#For each input chunk we create an output chunk, it is the output chunks that get concatenated together.
if not self.chunksToCompute:
self.chunksToCompute = list(range(len(inChunkList)))
for i in self.chunksToCompute:
#Calculate the number of chunks to use
inChunkNumber = int(
max(
1,
math.ceil(
len(inChunkList) *
self.prepOptions.proportionToSample)))
assert inChunkNumber <= len(inChunkList) and inChunkNumber > 0
#Now get the list of chunks flanking and including the current chunk
j = max(0, i - inChunkNumber // 2)
inChunkIDs = inChunkIDList[j:j + inChunkNumber]
if len(
inChunkIDs
) < inChunkNumber: #This logic is like making the list circular
inChunkIDs += inChunkIDList[:inChunkNumber - len(inChunkIDs)]
assert len(inChunkIDs) == inChunkNumber
outChunkIDList.append(
self.addChild(
self.getChunkedJobForCurrentStage(
inChunkIDs,
float(inChunkNumber) / len(inChunkIDList),
inChunkIDList[i])).rv())
if chunked:
# Merge results of the chunking process back into a genome-wide file
return self.addFollowOn(
MergeChunks(self.prepOptions, outChunkIDList)).rv()
else:
# Didn't chunk--we have a genome-wide fasta file
return outChunkIDList[0]
def run(self, fileStore):
sequenceFiles1 = [
fileStore.readGlobalFile(fileID)
for fileID in self.sequenceFileIDs1
]
if self.blastOptions.gpuLastz == True:
# wga-gpu has a 3G limit.
self.blastOptions.chunkSize = 3000000000
chunks = runGetChunks(
sequenceFiles=sequenceFiles1,
chunksDir=getTempDirectory(rootDir=fileStore.getLocalTempDir()),
chunkSize=self.blastOptions.chunkSize,
overlapSize=self.blastOptions.overlapSize)
if len(chunks) == 0:
raise Exception(
"no chunks produced for files: {} ".format(sequenceFiles1))
logger.info(
"Broken up the sequence files into individual 'chunk' files")
chunkIDs = [
fileStore.writeGlobalFile(chunk, cleanup=True) for chunk in chunks
]
diagonalResultsID = self.addChild(
MakeSelfBlasts(self.blastOptions, chunkIDs)).rv()
offDiagonalResultsID = self.addChild(
MakeOffDiagonalBlasts(self.blastOptions, chunkIDs)).rv()
logger.debug("Collating the blasts after blasting all-against-all")
return self.addFollowOn(
CollateBlasts(self.blastOptions,
[diagonalResultsID, offDiagonalResultsID])).rv()
def setUp(self):
unittest.TestCase.setUp(self)
self.encodeRegion = "ENm001"
self.encodePath = os.path.join(TestStatus.getPathToDataSets(), "MAY-2005")
self.regionPath = os.path.join(self.encodePath, self.encodeRegion)
self.tempDir = getTempDirectory(os.getcwd())
self.tempOutputFile = os.path.join(self.tempDir, "results1.txt")
def testKeepingCoverageOnIngroups(self):
"""Tests whether the --ingroupCoverageDir option works as
advertised."""
encodeRegion = "ENm001"
ingroups = ["human", "cow"]
outgroups = ["macaque", "rabbit", "dog"]
regionPath = os.path.join(self.encodePath, encodeRegion)
ingroupPaths = map(lambda x: os.path.join(regionPath, x + "." + encodeRegion + ".fa"), ingroups)
outgroupPaths = map(lambda x: os.path.join(regionPath, x + "." + encodeRegion + ".fa"), outgroups)
# Run blast in "ingroup vs outgroups" mode, requesting to keep
# the bed files that show outgroup coverage on the ingroup.
toilDir = os.path.join(self.tempDir, "tmp_toil")
outgroupFragmentPaths = [getTempFile(rootDir=self.tempDir) for outgroup in outgroups]
ingroupCoveragePaths = [getTempFile(rootDir=self.tempDir) for ingroup in ingroups]
runCactusBlastIngroupsAndOutgroups(ingroups=ingroupPaths, outgroups=outgroupPaths, alignmentsFile=self.tempOutputFile, outgroupFragmentPaths=outgroupFragmentPaths, ingroupCoveragePaths=ingroupCoveragePaths, toilDir=toilDir)
for i, ingroupPath in enumerate(ingroupPaths):
# Get the coverage from the outgroups independently and
# check that it's the same as the file in
# ingroupCoverageDir
otherIngroupPath = ingroupPaths[1] if i == 0 else ingroupPaths[0]
# To filter out alignments from the other ingroup and
# self-alignments we need to create a fasta with all the
# outgroup fragments in it.
outgroupsCombined = getTempFile(rootDir=self.tempDir)
for outgroupFragmentPath in outgroupFragmentPaths:
system("cat %s >> %s" % (outgroupFragmentPath, outgroupsCombined))
independentCoverageFile = getTempFile(rootDir=self.tempDir)
coverageWorkDir = getTempDirectory(rootDir=self.tempDir)
calculateCoverage(work_dir=coverageWorkDir, fromGenome=outgroupsCombined, sequenceFile=ingroupPath, cigarFile=self.tempOutputFile, outputFile=independentCoverageFile)
# find the coverage file cactus_blast kept (should be
# named according to the basename of the ingroup path
# file)
keptCoverageFile = ingroupCoveragePaths[i]
self.assertTrue(filecmp.cmp(independentCoverageFile, keptCoverageFile))
def runWorkflow_multipleExamples(inputGenFunction,
testNumber=1,
testRestrictions=(TestStatus.TEST_SHORT, TestStatus.TEST_MEDIUM, \
TestStatus.TEST_LONG, TestStatus.TEST_VERY_LONG,),
inverseTestRestrictions=False,
batchSystem="single_machine",
buildAvgs=False, buildReference=False,
buildReferenceSequence=False,
buildCactusPDF=False, buildAdjacencyPDF=False,
buildReferencePDF=False,
makeCactusTreeStats=False, makeMAFs=False,
configFile=None, buildJobTreeStats=False):
"""A wrapper to run a number of examples.
"""
if (inverseTestRestrictions and TestStatus.getTestStatus() not in testRestrictions) or \
(not inverseTestRestrictions and TestStatus.getTestStatus() in testRestrictions):
for test in xrange(testNumber):
tempDir = getTempDirectory(os.getcwd())
sequences, newickTreeString = inputGenFunction(regionNumber=test, tempDir=tempDir)
runWorkflow_TestScript(sequences, newickTreeString,
batchSystem=batchSystem,
buildAvgs=buildAvgs, buildReference=buildReference,
buildCactusPDF=buildCactusPDF, buildAdjacencyPDF=buildAdjacencyPDF,
makeCactusTreeStats=makeCactusTreeStats, makeMAFs=makeMAFs, configFile=configFile,
buildJobTreeStats=buildJobTreeStats)
system("rm -rf %s" % tempDir)
logger.info("Finished random test %i" % test)
def run(self):
#----------------------------------------
# Run cactus_workflow.py and report time#
#----------------------------------------
logger.info("CactusWorkflowWrapper: going to issue cactus run for simulation %s, parameter %s\n" %(self.simulation, self.paraFile))
tempDir = getTempDirectory(self.outDir)
flowerdisk = os.path.join(tempDir, "cactusDisk")
jobtreeDir = os.path.join(tempDir, "jobTree")
#batchSystem = "single_machine"
batchSystem = "parasol"
retryCount = 0
command = "cactus_workflow.py --speciesTree='%s' %s --configFile %s --buildTrees --setupAndBuildAlignments --cactusDisk %s --logDebug --job=JOB_FILE" %(self.tree, self.sequenceFiles, self.paraFile, flowerdisk)
starttime = time.time()
runJobTree(command, jobtreeDir, "DEBUG", retryCount, batchSystem, None)
#runCactusWorkflow(flowerdisk, self.sequenceFiles, self.tree, jobtreeDir, "DEBUG", 0, batchSystem, None, True, True, False, False, self.config)
runtime = time.time() - starttime
logger.info("Done cactus_workflow for simulation %s, config %s\n" %(self.simulation, self.paraFile))
#-----------------------
# Run cactus_treeStats #
#-----------------------
#statsFile = os.path.join(self.outDir, "stats", "%s.xml" % self.simNum)
statsFile = os.path.join(self.outDir, "stats", "%s.xml" % self.simName)
runCactusTreeStats(outputFile=statsFile, cactusDisk=flowerdisk)
#self.addChildCommand(command)
#------------------- Adding child ------------------------#
#self.addChildTarget(CactusMAFGeneratorWrapper(self.outDir, tempDir, self.simNum, runtime))
self.addChildTarget(CactusMAFGeneratorWrapper(self.outDir, tempDir, self.simTrueMafDir, self.simName, runtime))
logger.info("Added child CactusMAFGeneratorWrapper at %s\n" % self.outDir)
#------------------- Cleaning up -------------------------#
self.setFollowOnTarget(CactusWorkflowWrapperCleanup(tempDir))
def setUp(self):
#This is the number of random problems to solve, handed to the test code
self.testNo = TestStatus.getTestSetup(shortTestNo=1, mediumTestNo=5,
longTestNo=10, veryLongTestNo=100)
self.tempFiles = []
self.tempDir = getTempDirectory(os.getcwd())
self.tempBlossomDirectory = self.tempDir + "/tempBlossom"
unittest.TestCase.setUp(self)
def run(self, fileStore):
sequenceFiles1 = [fileStore.readGlobalFile(fileID) for fileID in self.sequenceFileIDs1]
sequenceFiles2 = [fileStore.readGlobalFile(fileID) for fileID in self.sequenceFileIDs2]
chunks1 = runGetChunks(sequenceFiles=sequenceFiles1, chunksDir=getTempDirectory(rootDir=fileStore.getLocalTempDir()), chunkSize=self.blastOptions.chunkSize, overlapSize=self.blastOptions.overlapSize)
chunks2 = runGetChunks(sequenceFiles=sequenceFiles2, chunksDir=getTempDirectory(rootDir=fileStore.getLocalTempDir()), chunkSize=self.blastOptions.chunkSize, overlapSize=self.blastOptions.overlapSize)
chunkIDs1 = [fileStore.writeGlobalFile(chunk, cleanup=True) for chunk in chunks1]
chunkIDs2 = [fileStore.writeGlobalFile(chunk, cleanup=True) for chunk in chunks2]
resultsIDs = []
#Make the list of blast jobs.
for chunkID1 in chunkIDs1:
for chunkID2 in chunkIDs2:
#TODO: Make the compression work
self.blastOptions.compressFiles = False
resultsIDs.append(self.addChild(RunBlast(self.blastOptions, chunkID1, chunkID2)).rv())
logger.info("Made the list of blasts")
#Set up the job to collate all the results
return self.addFollowOn(CollateBlasts(self.blastOptions, resultsIDs)).rv()
def run(self, fileStore):
sequenceFiles1 = [fileStore.readGlobalFile(fileID) for fileID in self.sequenceFileIDs1]
sequenceFiles2 = [fileStore.readGlobalFile(fileID) for fileID in self.sequenceFileIDs2]
chunks1 = runGetChunks(sequenceFiles=sequenceFiles1, chunksDir=getTempDirectory(rootDir=fileStore.getLocalTempDir()), chunkSize=self.blastOptions.chunkSize, overlapSize=self.blastOptions.overlapSize)
chunks2 = runGetChunks(sequenceFiles=sequenceFiles2, chunksDir=getTempDirectory(rootDir=fileStore.getLocalTempDir()), chunkSize=self.blastOptions.chunkSize, overlapSize=self.blastOptions.overlapSize)
chunkIDs1 = [fileStore.writeGlobalFile(chunk, cleanup=True) for chunk in chunks1]
chunkIDs2 = [fileStore.writeGlobalFile(chunk, cleanup=True) for chunk in chunks2]
resultsIDs = []
#Make the list of blast jobs.
for chunkID1 in chunkIDs1:
for chunkID2 in chunkIDs2:
#TODO: Make the compression work
self.blastOptions.compressFiles = False
resultsIDs.append(self.addChild(RunBlast(self.blastOptions, chunkID1, chunkID2)).rv())
logger.info("Made the list of blasts")
#Set up the job to collate all the results
return self.addFollowOn(CollateBlasts(self.blastOptions, resultsIDs)).rv()
def setUp(self):
#This is the number of random problems to solve, handed to the test code
self.testNo = TestStatus.getTestSetup(shortTestNo=1, mediumTestNo=5,
longTestNo=10, veryLongTestNo=100)
self.tempFiles = []
self.tempDir = getTempDirectory(os.getcwd())
self.tempMatchGraphDirectory = self.tempDir + "/tempMatchGraph"
unittest.TestCase.setUp(self)
def progressiveFunction(self, experimentFile, toilDir,
batchSystem, buildAvgs,
buildReference,
buildHal,
buildFasta,
toilStats,
subtreeRoot=None):
tempDir = getTempDirectory(os.getcwd())
tempExperimentDir = os.path.join(tempDir, "exp")
runCreateMultiCactusProject(experimentFile,
tempExperimentDir,
fixNames=False,
root=subtreeRoot)
logger.info("Put the temporary files in %s" % tempExperimentDir)
runCactusProgressive(os.path.join(tempExperimentDir, "exp_project.xml"),
toilDir,
batchSystem=batchSystem,
buildAvgs=buildAvgs,
toilStats=toilStats)
# Check that the headers and sequences in the output are the
# same as the sequences in the input (minus differences in
# repeat-masking)
exp = ExperimentWrapper(ET.parse(experimentFile).getroot())
seqMap = exp.buildSequenceMap()
# Maps genome name -> headers in fasta
headers = {}
for genomeName, inputSequencePath in seqMap.items():
if os.path.isdir(inputSequencePath):
# Some "input sequence paths" are actually provided as
# directories containing multiple FASTAs
concatenatedPath = getTempFile()
system("cat %s/* > %s" % (inputSequencePath, concatenatedPath))
inputSequencePath = concatenatedPath
headers[genomeName] = list(map(itemgetter(0), fastaRead(inputSequencePath)))
# check headers inside .c2h output
for expPath in glob.glob('%s/*/*_experiment.xml' % (tempExperimentDir)):
subExp = ExperimentWrapper(ET.parse(expPath).getroot())
outgroups = subExp.getOutgroupEvents()
c2hPath = subExp.getHALPath()
with open(c2hPath) as f:
for line in f:
fields = line.split('\t')
if fields[0] == 's':
# Sequence line
genome = fields[1][1:-1]
header = fields[2][1:-1]
if genome in headers and genome not in outgroups:
# This genome is an input genome
self.assertTrue(header in headers[genome],
'Header %s from output c2h %s not found in input fa %s'
' for genome %s' % (header, c2hPath, seqMap[genome], genome))
runToilStatusAndFailIfNotComplete(toilDir)
system("rm -rf %s" % tempDir)
def setUp(self):
self.testNo = TestStatus.getTestSetup(1, 5, 10, 100)
self.tempDir = getTempDirectory(os.getcwd())
self.tempFiles = []
unittest.TestCase.setUp(self)
self.tempOutputFile = os.path.join(self.tempDir, "results1.txt")
self.tempFiles.append(self.tempOutputFile)
self.tempOutputFile2 = os.path.join(self.tempDir, "results2.txt")
self.tempFiles.append(self.tempOutputFile2)
self.encodePath = os.path.join(TestStatus.getPathToDataSets(), "MAY-2005")
def repeat_masking_job(job, input_fasta, species):
temp_dir = getTempDirectory()
os.chdir(temp_dir)
local_fasta = os.path.join(temp_dir, 'input.fa')
job.fileStore.readGlobalFile(input_fasta, local_fasta, cache=False)
system("chmod a+rw %s" % local_fasta)
system("RepeatMasker -pa 10 -species {species} {input}".format(species=species, input=local_fasta))
output_path = local_fasta + '.out'
masked_out = job.fileStore.writeGlobalFile(output_path)
return masked_out
def setUp(self):
unittest.TestCase.setUp(self)
self.encodeRegion = "ENm001"
self.encodePath = os.path.join(TestStatus.getPathToDataSets(), "MAY-2005")
self.regionPath = os.path.join(self.encodePath, self.encodeRegion)
self.tempDir = getTempDirectory(os.getcwd())
self.tempOutputFile = os.path.join(self.tempDir, "results1.txt")
self.toilDir = os.path.join(self.tempDir, "toil")
self.toilOptions = Job.Runner.getDefaultOptions(self.toilDir)
self.toilOptions.disableCaching = True
def setUp(self):
self.testNo = TestStatus.getTestSetup(1, 5, 10, 100)
self.tempDir = getTempDirectory(os.getcwd())
self.tempFiles = []
unittest.TestCase.setUp(self)
self.tempOutputFile = os.path.join(self.tempDir, "results1.txt")
self.tempFiles.append(self.tempOutputFile)
self.tempOutputFile2 = os.path.join(self.tempDir, "results2.txt")
self.tempFiles.append(self.tempOutputFile2)
self.encodePath = os.path.join(TestStatus.getPathToDataSets(), "MAY-2005")
def setUp(self):
unittest.TestCase.setUp(self)
self.trees = randomTreeSet()
self.mcTrees = []
self.tempDir = getTempDirectory(os.getcwd())
self.tempFa = os.path.join(self.tempDir, "seq.fa")
with open(self.tempFa, "w") as f:
f.write(">temp\nNNNNNNNCNNNNAAAAAAAAAAAAAAANNNNNNN\n")
self.dummySeqMaps = []
for tree in self.trees:
if tree.size() < 50:
mcTree = MultiCactusTree(tree)
seqMap = dict()
for i in mcTree.breadthFirstTraversal():
mcTree.setName(i, "Node%s" % str(i))
seqMap["Node%s" % str(i)] = self.tempFa
mcTree.computeSubtreeRoots()
mcTree.nameUnlabeledInternalNodes()
self.mcTrees.append(mcTree)
self.dummySeqMaps.append(seqMap)
# Boreoeutherian tree
borTree = '((((HUMAN:0.006969,CHIMP:0.009727)Anc7:0.025291,BABOON:0.044568)Anc6:0.11,(MOUSE:0.072818,RAT:0.081244)Anc5:0.260342)Anc4:0.023260,((DOG:0.07,CAT:0.07)Anc3:0.087381,(PIG:0.06,COW:0.06)Anc2:0.104728)Anc1:0.04)Anc0;'
self.borMcTree = MultiCactusTree(NXNewick().parseString(
borTree, addImpliedRoots=False))
self.borMcTree.computeSubtreeRoots()
self.borMcTree.nameUnlabeledInternalNodes()
self.mcTrees.append(self.borMcTree)
# Eutherian backbone tree
backbone = '(((((((((((Homo_sapiens:0.00655,Pan_troglodytes:0.00684):0.00422,Gorilla_gorilla_gorilla:0.008964):0.009693,Pongo_abelii:0.01894):0.015511,Macaca_mulatta:0.043601):0.08444,Aotus_nancymaae:0.08):0.08,Microcebus_murinus:0.10612):0.043494,Galeopterus_variegatus:0.134937):0.04,((((Jaculus_jaculus:0.1,(Microtus_ochrogaster:0.14,(Mus_musculus:0.084509,Rattus_norvegicus:0.091589):0.047773):0.06015):0.122992,(Heterocephalus_glaber:0.1,(Cavia_porcellus:0.065629,(Chinchilla_lanigera:0.06,Octodon_degus:0.1):0.06):0.05):0.06015):0.05,Marmota_marmota:0.1):0.05,Oryctolagus_cuniculus:0.21569):0.04):0.040593,(((Sus_scrofa:0.12,(Orcinus_orca:0.069688,(Bos_taurus:0.04,Capra_hircus:0.04):0.09):0.045488):0.02,((Equus_caballus:0.109397,(Felis_catus:0.098612,(Canis_lupus_familiaris:0.052458,Mustela_putorius_furo:0.08):0.02):0.049845):0.02,(Pteropus_alecto:0.1,Eptesicus_fuscus:0.08):0.033706):0.03):0.025,Erinaceus_europaeus:0.278178):0.021227):0.023664,(((Loxodonta_africana:0.022242,Procavia_capensis:0.145358):0.076687,Chrysochloris_asiatica:0.04):0.05,Dasypus_novemcinctus:0.169809):0.02)backbone_root:0.234728,(Monodelphis_domestica:0.125686,Sarcophilus_harrisii:0.12):0.2151);'
self.backboneTree = MultiCactusTree(NXNewick().parseString(
backbone, addImpliedRoots=False))
self.backboneTree.computeSubtreeRoots()
self.backboneTree.nameUnlabeledInternalNodes()
self.mcTrees.append(self.backboneTree)
seqLens = dict()
seqLens["HUMAN"] = 57553
seqLens["CHIMP"] = 57344
seqLens["BABOON"] = 58960
seqLens["MOUSE"] = 32750
seqLens["RAT"] = 38436
seqLens["DOG"] = 54187
seqLens["CAT"] = 50283
seqLens["PIG"] = 54843
seqLens["COW"] = 55508
self.blanchetteSeqMap = dict()
for event, seqLen in seqLens.items():
p = os.path.join(self.tempDir, event + ".fa")
with open(p, "w") as f:
f.write(">%s\n" % event)
f.write(''.join(['A'] * seqLen))
f.write('\n')
self.blanchetteSeqMap[event] = p
def run(self, fileStore):
sequenceFiles1 = [fileStore.readGlobalFile(fileID) for fileID in self.sequenceFileIDs1]
chunks = runGetChunks(sequenceFiles=sequenceFiles1, chunksDir=getTempDirectory(rootDir=fileStore.getLocalTempDir()), chunkSize = self.blastOptions.chunkSize, overlapSize=self.blastOptions.overlapSize)
assert len(chunks) > 0
logger.info("Broken up the sequence files into individual 'chunk' files")
chunkIDs = [fileStore.writeGlobalFile(chunk, cleanup=True) for chunk in chunks]
diagonalResultsID = self.addChild(MakeSelfBlasts(self.blastOptions, chunkIDs)).rv()
offDiagonalResultsID = self.addChild(MakeOffDiagonalBlasts(self.blastOptions, chunkIDs)).rv()
logger.debug("Collating the blasts after blasting all-against-all")
return self.addFollowOn(CollateBlasts(self.blastOptions, [diagonalResultsID, offDiagonalResultsID])).rv()
def testSort(self):
for test in xrange(self.testNo):
tempDir = getTempDirectory(os.getcwd())
tempFile1 = getTempFile(rootDir=tempDir)
makeFileToSort(tempFile1)
lines1 = loadFile(tempFile1)
lines1.sort()
sort(tempFile1)
lines2 = loadFile(tempFile1)
checkEqual(lines1, lines2)
system("rm -rf %s" % tempDir)
def repeat_masking_job(job, input_fasta, species):
temp_dir = getTempDirectory()
os.chdir(temp_dir)
local_fasta = os.path.join(temp_dir, 'input.fa')
job.fileStore.readGlobalFile(input_fasta, local_fasta, cache=False)
system("chmod a+rw %s" % local_fasta)
system("RepeatMasker -pa 10 -species {species} {input}".format(
species=species, input=local_fasta))
output_path = local_fasta + '.out'
masked_out = job.fileStore.writeGlobalFile(output_path)
return masked_out
def testAddingOutgroupsImprovesResult(self):
"""Run blast on "ingroup" and "outgroup" encode regions, and ensure
that adding an extra outgroup only adds alignments if
possible, and doesn't lose any
"""
encodeRegions = [ "ENm00" + str(i) for i in xrange(1,2) ]
ingroups = ["human", "macaque"]
outgroups = ["rabbit", "dog", "rat", "platypus", "xenopus", "fugu"]
# subselect 4 random ordered outgroups
outgroups = [outgroups[i] for i in sorted(random.sample(xrange(len(outgroups)), 4))]
for encodeRegion in encodeRegions:
regionPath = os.path.join(self.encodePath, encodeRegion)
ingroupPaths = map(lambda x: os.path.join(regionPath, x + "." + encodeRegion + ".fa"), ingroups)
outgroupPaths = map(lambda x: os.path.join(regionPath, x + "." + encodeRegion + ".fa"), outgroups)
results = []
for numOutgroups in xrange(1,5):
# Align w/ increasing numbers of outgroups
subResults = getTempFile()
subOutgroupPaths = outgroupPaths[:numOutgroups]
print "aligning %s vs %s" % (",".join(ingroupPaths), ",".join(subOutgroupPaths))
tmpToil = os.path.join(self.tempDir, "outgroupToil")
runCactusBlastIngroupsAndOutgroups(ingroupPaths, subOutgroupPaths, alignmentsFile=subResults, toilDir=tmpToil)
results.append(subResults)
# Print diagnostics about coverage
for i, subResults in enumerate(results):
for ingroup, ingroupPath in zip(ingroups, ingroupPaths):
ingroupCoverage = getTempFile(rootDir=self.tempDir)
coverageWorkDir = getTempDirectory(rootDir=self.tempDir)
calculateCoverage(work_dir=coverageWorkDir, sequenceFile=ingroupPath, cigarFile=subResults, outputFile=ingroupCoverage)
coveredBases = popenCatch("cat %s | awk '{ total += $3 - $2 } END { print total }'" % ingroupCoverage)
print "covered bases on %s using %d outgroups: %s" % (ingroup, i + 1, coveredBases)
resultsSets = map(lambda x : loadResults(x), results)
for i, moreOutgroupsResults in enumerate(resultsSets[1:]):
# Make sure the results from (n+1) outgroups are
# (very nearly) a superset of the results from n outgroups
print "Using %d addl outgroup(s):" % (i + 1)
comparator = ResultComparator(resultsSets[0], moreOutgroupsResults)
print comparator
self.assertTrue(comparator.sensitivity >= 0.99)
# Ensure that the new alignments don't cover more than
# x% of already existing alignments to human
for i in xrange(1, len(resultsSets)):
prevResults = resultsSets[i-1][0]
curResults = resultsSets[i][0]
prevResultsHumanPos = set(map(lambda x: (x[0], x[1]) if "human" in x[0] else (x[2], x[3]), filter(lambda x: "human" in x[0] or "human" in x[2], prevResults)))
newAlignments = curResults.difference(prevResults)
newAlignmentsHumanPos = set(map(lambda x: (x[0], x[1]) if "human" in x[0] else (x[2], x[3]), filter(lambda x: "human" in x[0] or "human" in x[2], newAlignments)))
print "addl outgroup %d:" % i
print "bases re-covered: %f (%d)" % (len(newAlignmentsHumanPos.intersection(prevResultsHumanPos))/float(len(prevResultsHumanPos)), len(newAlignmentsHumanPos.intersection(prevResultsHumanPos)))
for subResult in results:
os.remove(subResult)
def runCactusProgressive(options):
with Toil(options) as toil:
importSingularityImage()
#Run the workflow
if options.restart:
halID = toil.restart()
else:
options.cactusDir = getTempDirectory()
#Create the progressive cactus project
projWrapper = ProjectWrapper(options)
projWrapper.writeXml()
pjPath = os.path.join(
options.cactusDir, ProjectWrapper.alignmentDirName,
'%s_project.xml' % ProjectWrapper.alignmentDirName)
assert os.path.exists(pjPath)
project = MultiCactusProject()
if not os.path.isdir(options.cactusDir):
os.makedirs(options.cactusDir)
project.readXML(pjPath)
#import the sequences
for genome, seq in project.inputSequenceMap.items():
if os.path.isdir(seq):
tmpSeq = getTempFile()
catFiles([
os.path.join(seq, subSeq) for subSeq in os.listdir(seq)
], tmpSeq)
seq = tmpSeq
seq = makeURL(seq)
project.inputSequenceIDMap[genome] = toil.importFile(seq)
#import cactus config
if options.configFile:
cactusConfigID = toil.importFile(makeURL(options.configFile))
else:
cactusConfigID = toil.importFile(
makeURL(project.getConfigPath()))
project.setConfigID(cactusConfigID)
project.syncToFileStore(toil)
configNode = ET.parse(project.getConfigPath()).getroot()
configWrapper = ConfigWrapper(configNode)
configWrapper.substituteAllPredefinedConstantsWithLiterals()
project.writeXML(pjPath)
halID = toil.start(
RunCactusPreprocessorThenProgressiveDown(
options, project, memory=configWrapper.getDefaultMemory()))
toil.exportFile(halID, makeURL(options.outputHal))
def setUp(self):
unittest.TestCase.setUp(self)
self.trees = randomTreeSet()
self.mcTrees = []
self.tempDir = getTempDirectory(os.getcwd())
self.tempFa = os.path.join(self.tempDir, "seq.fa")
with open(self.tempFa, "w") as f:
f.write(">temp\nNNNNNNNCNNNNAAAAAAAAAAAAAAANNNNNNN\n")
self.dummySeqMaps = []
for tree in self.trees:
if tree.size() < 50:
mcTree = MultiCactusTree(tree, tree.degree())
seqMap = dict()
for i in mcTree.breadthFirstTraversal():
mcTree.setName(i, "Node%s" % str(i))
seqMap["Node%s" % str(i)] = self.tempFa
mcTree.computeSubtreeRoots()
mcTree.nameUnlabeledInternalNodes()
self.mcTrees.append(mcTree)
self.dummySeqMaps.append(seqMap)
# Boreoeutherian tree
borTree = '((((HUMAN:0.006969,CHIMP:0.009727)Anc7:0.025291,BABOON:0.044568)Anc6:0.11,(MOUSE:0.072818,RAT:0.081244)Anc5:0.260342)Anc4:0.023260,((DOG:0.07,CAT:0.07)Anc3:0.087381,(PIG:0.06,COW:0.06)Anc2:0.104728)Anc1:0.04)Anc0;'
self.borMcTree = MultiCactusTree(NXNewick().parseString(borTree, addImpliedRoots=False))
self.borMcTree.computeSubtreeRoots()
self.borMcTree.nameUnlabeledInternalNodes()
self.mcTrees.append(self.borMcTree)
# Eutherian backbone tree
backbone = '(((((((((((Homo_sapiens:0.00655,Pan_troglodytes:0.00684):0.00422,Gorilla_gorilla_gorilla:0.008964):0.009693,Pongo_abelii:0.01894):0.015511,Macaca_mulatta:0.043601):0.08444,Aotus_nancymaae:0.08):0.08,Microcebus_murinus:0.10612):0.043494,Galeopterus_variegatus:0.134937):0.04,((((Jaculus_jaculus:0.1,(Microtus_ochrogaster:0.14,(Mus_musculus:0.084509,Rattus_norvegicus:0.091589):0.047773):0.06015):0.122992,(Heterocephalus_glaber:0.1,(Cavia_porcellus:0.065629,(Chinchilla_lanigera:0.06,Octodon_degus:0.1):0.06):0.05):0.06015):0.05,Marmota_marmota:0.1):0.05,Oryctolagus_cuniculus:0.21569):0.04):0.040593,(((Sus_scrofa:0.12,(Orcinus_orca:0.069688,(Bos_taurus:0.04,Capra_hircus:0.04):0.09):0.045488):0.02,((Equus_caballus:0.109397,(Felis_catus:0.098612,(Canis_lupus_familiaris:0.052458,Mustela_putorius_furo:0.08):0.02):0.049845):0.02,(Pteropus_alecto:0.1,Eptesicus_fuscus:0.08):0.033706):0.03):0.025,Erinaceus_europaeus:0.278178):0.021227):0.023664,(((Loxodonta_africana:0.022242,Procavia_capensis:0.145358):0.076687,Chrysochloris_asiatica:0.04):0.05,Dasypus_novemcinctus:0.169809):0.02)backbone_root:0.234728,(Monodelphis_domestica:0.125686,Sarcophilus_harrisii:0.12):0.2151);'
self.backboneTree = MultiCactusTree(NXNewick().parseString(backbone, addImpliedRoots=False))
self.backboneTree.computeSubtreeRoots()
self.backboneTree.nameUnlabeledInternalNodes()
self.mcTrees.append(self.backboneTree)
seqLens = dict()
seqLens["HUMAN"] = 57553
seqLens["CHIMP"] = 57344
seqLens["BABOON"] = 58960
seqLens["MOUSE"] = 32750
seqLens["RAT"] = 38436
seqLens["DOG"] = 54187
seqLens["CAT"] = 50283
seqLens["PIG"] = 54843
seqLens["COW"] = 55508
self.blanchetteSeqMap = dict()
for event, seqLen in seqLens.items():
p = os.path.join(self.tempDir, event +".fa")
with open(p, "w") as f:
f.write(">%s\n" % event)
f.write(''.join(['A'] * seqLen))
f.write('\n')
self.blanchetteSeqMap[event] = p
def setUp(self):
unittest.TestCase.setUp(self)
self.tempDir = getTempDirectory(os.getcwd())
self.tempFiles = []
unittest.TestCase.setUp(self)
self.tempOutputFile = os.path.join(self.tempDir, "results1.txt")
self.tempFiles.append(self.tempOutputFile)
self.tempOutputFile2 = os.path.join(self.tempDir, "results2.txt")
self.tempFiles.append(self.tempOutputFile2)
self.encodePath = os.path.join(TestStatus.getPathToDataSets(), "MAY-2005")
self.defaultLastzArguments = "--ambiguous=iupac"
self.defaultRealignArguments = ""
def testAddingOutgroupsImprovesResult(self):
"""Run blast on "ingroup" and "outgroup" encode regions, and ensure
that adding an extra outgroup only adds alignments if
possible, and doesn't lose any
"""
encodeRegions = [ "ENm00" + str(i) for i in xrange(1,2) ]
ingroups = ["human", "macaque"]
outgroups = ["rabbit", "dog", "rat", "platypus", "xenopus", "fugu"]
# subselect 4 random ordered outgroups
outgroups = [outgroups[i] for i in sorted(random.sample(xrange(len(outgroups)), 4))]
for encodeRegion in encodeRegions:
regionPath = os.path.join(self.encodePath, encodeRegion)
ingroupPaths = map(lambda x: os.path.join(regionPath, x + "." + encodeRegion + ".fa"), ingroups)
outgroupPaths = map(lambda x: os.path.join(regionPath, x + "." + encodeRegion + ".fa"), outgroups)
results = []
for numOutgroups in xrange(1,5):
# Align w/ increasing numbers of outgroups
subResults = getTempFile()
subOutgroupPaths = outgroupPaths[:numOutgroups]
tmpJobTree = getTempDirectory()
print "aligning %s vs %s" % (",".join(ingroupPaths), ",".join(subOutgroupPaths))
system("cactus_blast.py --ingroups %s --outgroups %s --cigars %s --jobTree %s/jobTree" % (",".join(ingroupPaths), ",".join(subOutgroupPaths), subResults, tmpJobTree))
system("rm -fr %s" % (tmpJobTree))
results.append(subResults)
# Print diagnostics about coverage
for i, subResults in enumerate(results):
for ingroup, ingroupPath in zip(ingroups, ingroupPaths):
coveredBases = popenCatch("cactus_coverage %s %s | awk '{ total += $3 - $2 } END { print total }'" % (ingroupPath, subResults))
print "covered bases on %s using %d outgroups: %s" % (ingroup, i + 1, coveredBases)
resultsSets = map(lambda x : loadResults(x), results)
for i, moreOutgroupsResults in enumerate(resultsSets[1:]):
# Make sure the results from (n+1) outgroups are
# (very nearly) a superset of the results from n outgroups
print "Using %d addl outgroup(s):" % (i + 1)
comparator = ResultComparator(resultsSets[0], moreOutgroupsResults)
print comparator
self.assertTrue(comparator.sensitivity >= 0.99)
# Ensure that the new alignments don't cover more than
# x% of already existing alignments to human
for i in xrange(1, len(resultsSets)):
prevResults = resultsSets[i-1][0]
curResults = resultsSets[i][0]
prevResultsHumanPos = set(map(lambda x: (x[0], x[1]) if "human" in x[0] else (x[2], x[3]), filter(lambda x: "human" in x[0] or "human" in x[2], prevResults)))
newAlignments = curResults.difference(prevResults)
newAlignmentsHumanPos = set(map(lambda x: (x[0], x[1]) if "human" in x[0] else (x[2], x[3]), filter(lambda x: "human" in x[0] or "human" in x[2], newAlignments)))
print "addl outgroup %d:" % i
print "bases re-covered: %f (%d)" % (len(newAlignmentsHumanPos.intersection(prevResultsHumanPos))/float(len(prevResultsHumanPos)), len(newAlignmentsHumanPos.intersection(prevResultsHumanPos)))
for subResult in results:
os.remove(subResult)
def testGetMidPoint(self):
for test in xrange(self.testNo):
tempDir = getTempDirectory(os.getcwd())
tempFile = getTempFile(rootDir=tempDir)
makeFileToSort(tempFile)
l = open(tempFile, 'r').read()
fileSize = os.path.getsize(tempFile)
midPoint = getMidPoint(tempFile, 0, fileSize)
print "the mid point is %i of a file of %i bytes woth byte" % (midPoint, fileSize)
assert midPoint < fileSize
assert l[midPoint] == '\n'
assert midPoint >= 0
system("rm -rf %s" % tempDir)
def setUp(self):
self.batchSystem = "singleMachine"
if getBatchSystem() != None:
self.batchSystem = getBatchSystem()
unittest.TestCase.setUp(self)
self.useOutgroup = False
self.doSelfAlignment = False
#Load the config file, turn on the checks.
configWrapper = ConfigWrapper(ET.parse(os.path.join(cactusRootPath(), "cactus_progressive_config.xml")).getroot())
configWrapper.turnAllModesOn()
self.tempDir = getTempDirectory(os.getcwd())
self.configFile = os.path.join(self.tempDir, "tempConfig.xml")
configWrapper.writeXML(self.configFile)
def setUp(self):
self.batchSystem = "singleMachine"
if getBatchSystem() != None:
self.batchSystem = getBatchSystem()
unittest.TestCase.setUp(self)
self.useOutgroup = False
self.doSelfAlignment = False
#Load the config file, turn on the checks.
configWrapper = ConfigWrapper(ET.parse(os.path.join(cactusRootPath(), "cactus_progressive_config.xml")).getroot())
configWrapper.turnAllModesOn()
configWrapper.turnOffHeaderChecks()
self.tempDir = getTempDirectory(os.getcwd())
self.configFile = os.path.join(self.tempDir, "tempConfig.xml")
configWrapper.writeXML(self.configFile)
def testCopySubRangeOfFile(self):
for test in xrange(self.testNo):
tempDir = getTempDirectory(os.getcwd())
tempFile = getTempFile(rootDir=tempDir)
outputFile = getTempFile(rootDir=tempDir)
makeFileToSort(tempFile)
fileSize = os.path.getsize(tempFile)
assert fileSize > 0
fileStart = random.choice(xrange(0, fileSize))
fileEnd = random.choice(xrange(fileStart, fileSize))
copySubRangeOfFile(tempFile, fileStart, fileEnd, outputFile)
l = open(outputFile, 'r').read()
l2 = open(tempFile, 'r').read()[fileStart:fileEnd]
checkEqual(l, l2)
system("rm -rf %s" % tempDir)
def run(self, fileStore):
logger.info("Preparing sequence for preprocessing")
# chunk it up
inSequence = fileStore.readGlobalFile(self.inSequenceID)
inChunkDirectory = getTempDirectory(
rootDir=fileStore.getLocalTempDir())
inChunkList = runGetChunks(sequenceFiles=[inSequence],
chunksDir=inChunkDirectory,
chunkSize=self.prepOptions.chunkSize,
overlapSize=0)
inChunkList = [os.path.abspath(path) for path in inChunkList]
logger.info("Chunks = %s" % inChunkList)
logger.info("Chunks dir = %s" % os.listdir(inChunkDirectory))
inChunkIDList = [
fileStore.writeGlobalFile(chunk) for chunk in inChunkList
]
outChunkIDList = []
#For each input chunk we create an output chunk, it is the output chunks that get concatenated together.
if not self.chunksToCompute:
self.chunksToCompute = range(len(inChunkList))
for i in self.chunksToCompute:
#Calculate the number of chunks to use
inChunkNumber = int(
max(
1,
math.ceil(
len(inChunkList) *
self.prepOptions.proportionToSample)))
assert inChunkNumber <= len(inChunkList) and inChunkNumber > 0
#Now get the list of chunks flanking and including the current chunk
j = max(0, i - inChunkNumber / 2)
inChunkIDs = inChunkIDList[j:j + inChunkNumber]
if len(
inChunkIDs
) < inChunkNumber: #This logic is like making the list circular
inChunkIDs += inChunkIDList[:inChunkNumber - len(inChunkIDs)]
assert len(inChunkIDs) == inChunkNumber
outChunkIDList.append(
self.addChild(
PreprocessChunk(self.prepOptions, inChunkIDs,
float(inChunkNumber) / len(inChunkIDList),
inChunkIDList[i])).rv())
# follow on to merge chunks
return self.addFollowOn(MergeChunks(self.prepOptions,
outChunkIDList)).rv()
def testCactusSetup(self):
"""Creates a bunch of random inputs and then passes them to cactus setup.
"""
for test in xrange(self.testNo):
tempDir = getTempDirectory(os.getcwd())
sequenceNumber = random.choice(xrange(100))
sequences, newickTreeString = getCactusInputs_random(tempDir=tempDir, sequenceNumber=sequenceNumber)
#Setup the flower disk.
experiment = getCactusWorkflowExperimentForTest(sequences, newickTreeString, tempDir)
cactusDiskDatabaseString = experiment.getDiskDatabaseString()
runCactusSetup(cactusDiskDatabaseString, sequences, newickTreeString)
runCactusSetup(cactusDiskDatabaseString, sequences, newickTreeString)
experiment.cleanupDb()
system("rm -rf %s" % tempDir)
logger.info("Finished test %i of cactus_setup.py", test)
def testCPecanEmMultipleTrials(self):
"""Runs uns cPecanEm with multiple different trials.
"""
for seqFile1, seqFile2 in seqFilePairGenerator():
tempDir = getTempDirectory(rootDir=os.getcwd())
jobTreeDir = os.path.join(tempDir, "jobTree")
alignmentsFile = os.path.join(tempDir, "alignments.cigars")
computeAlignments(seqFile1, seqFile2, alignmentsFile)
logger.info("Computed alignments for seqs %s and %s" % (seqFile1, seqFile2))
outputModelFile = os.path.join(tempDir, "outputModel.txt")
outputModelXMLFile = os.path.join(tempDir, "outputModel.xml")
outputBlastFile = os.path.join(tempDir, "outputBlast.txt")
#First run the script to generate a model and do one iteration of EM to
#get the likelihood to compare with the final likelihood
trials=3
runCPecanEm(sequenceFiles=[ seqFile1, seqFile2 ],
alignmentsFile=alignmentsFile, outputModelFile=outputModelFile,
jobTreeDir=jobTreeDir,
trials=trials,
outputTrialHmms=True,
iterations=5, randomStart=True, logLevel=getLogLevelString(),
optionsToRealign="--diagonalExpansion=6 --splitMatrixBiggerThanThis=100",
outputXMLModelFile=outputModelXMLFile,
blastScoringMatrixFile=outputBlastFile)
trialHmms = [ Hmm.loadHmm(outputModelFile + ("_%i" % i)) for i in xrange(trials) ]
hmm = Hmm.loadHmm(outputModelFile)
node = ET.parse(outputModelXMLFile).getroot()
logger.info("After multiple trials and iterations of EM the best likelihood found was %s, the likelihoods of the variants were: %s" %
(hmm.likelihood, " ".join(map(lambda x : str(x.likelihood), trialHmms))))
matchProbs, gapOpen, gapExtend = makeBlastScoringMatrix(hmm, ("ACTG",))
logger.info("Gap open: %s, Gap extend: %s, Match probs %s" % (gapOpen, gapExtend, " ".join(map(str, matchProbs))))
self.assertTrue(float(node.attrib["maxLikelihood"]) == hmm.likelihood)
#Now use the blast file to compute a new matrix
computeAlignments(seqFile1, seqFile2, alignmentsFile, lastzArguments=("--ambiguous=iupac --scores=%s" % outputBlastFile))
#Run modifyHmm to check it works
system("cPecanModifyHmm %s %s --gcContent=0.5 --substitutionRate=0.05 --setFlatIndelEmissions" % (outputModelFile, outputModelFile))
hmm = Hmm.loadHmm(outputModelFile)
node = ET.parse(outputModelXMLFile).getroot()
system("rm -rf %s" % tempDir)
def runWorkflow_multipleExamples(testId,
inputGenFunction,
testNumber=1,
batchSystem="single_machine",
buildAvgs=False,
configFile=None,
buildToilStats=False,
useConstraints=False,
cactusWorkflowFunction=runCactusWorkflow,
logLevel=None,
buildHal=False,
buildFasta=False,
progressive=False):
"""A wrapper to run a number of examples.
The testId parameter is used to allocate a unique port so that tests
can run in parallel.
"""
if logLevel is None:
logLevel = _LOG_LEVEL
for test in range(testNumber):
tempDir = getTempDirectory(os.getcwd())
if useConstraints:
sequences, newickTreeString, constraints = inputGenFunction(
regionNumber=test, tempDir=tempDir)
else:
sequences, newickTreeString = inputGenFunction(regionNumber=test,
tempDir=tempDir)
constraints = None
runWorkflow_TestScript(testId,
sequences,
newickTreeString,
outputDir=tempDir,
batchSystem=batchSystem,
buildAvgs=buildAvgs,
buildHal=buildHal,
buildFasta=buildFasta,
configFile=configFile,
buildToilStats=buildToilStats,
constraints=constraints,
progressive=progressive,
cactusWorkflowFunction=cactusWorkflowFunction,
logLevel=logLevel)
system("rm -rf %s" % tempDir)
logger.info("Finished random test %i" % test)
def testCactus_Random_fixedAncestor(self):
"""Tests that cactus doesn't crash when aligning to a fixed ancestral sequence."""
sequences, _ = getCactusInputs_random(treeLeafNumber=3)
rootSeq = sequences.pop()
# Create a star tree
tree = '(%s)root;' % ",".join([str(x) + ":1.0" for x in range(len(sequences))])
outputDir = getTempDirectory()
experiment = getCactusWorkflowExperimentForTest(sequences, tree,
outputDir,
progressive=True)
experiment.setSequenceID("root", rootSeq)
experiment.setRootReconstructed(False)
experimentFile = os.path.join(outputDir, "experiment.xml")
experiment.writeXML(experimentFile)
jobTreeDir = os.path.join(outputDir, "jobTree")
self.progressiveFunction(experimentFile, jobTreeDir, 'singleMachine',
False, True, True, False)
def testJobTreeStats_SortSimple(self):
"""Tests the jobTreeStats utility using the scriptTree_sort example.
"""
for test in xrange(self.testNo):
tempDir = getTempDirectory(os.getcwd())
tempFile = getTempFile(rootDir=tempDir)
outputFile = getTempFile(rootDir=tempDir)
jobTreeDir = os.path.join(tempDir, "jobTree")
lines=100000
maxLineLength=10
N=1000
makeFileToSort(tempFile, lines, maxLineLength)
#Sort the file
command = "scriptTreeTest_Sort.py --jobTree %s --logLevel=DEBUG --fileToSort=%s --N %s --stats --jobTime 0.5" % (jobTreeDir, tempFile, N)
system(command)
#Now get the stats
system("jobTreeStats --jobTree %s --outputFile %s" % (jobTreeDir, outputFile))
#Cleanup
system("rm -rf %s" % tempDir)
def run(self, fileStore):
logger.info("Preparing sequence for preprocessing")
inSequence = fileStore.readGlobalFile(self.inSequenceID)
if self.prepOptions.chunkSize <= 0:
# In this first case we don't need to break up the sequence
chunked = False
inChunkList = [inSequence]
else:
# chunk it up
chunked = True
inChunkDirectory = getTempDirectory(rootDir=fileStore.getLocalTempDir())
inChunkList = runGetChunks(sequenceFiles=[inSequence], chunksDir=inChunkDirectory,
chunkSize=self.prepOptions.chunkSize,
overlapSize=0)
inChunkList = [os.path.abspath(path) for path in inChunkList]
logger.info("Chunks = %s" % inChunkList)
inChunkIDList = [fileStore.writeGlobalFile(chunk, cleanup=True) for chunk in inChunkList]
outChunkIDList = []
#For each input chunk we create an output chunk, it is the output chunks that get concatenated together.
if not self.chunksToCompute:
self.chunksToCompute = range(len(inChunkList))
for i in self.chunksToCompute:
#Calculate the number of chunks to use
inChunkNumber = int(max(1, math.ceil(len(inChunkList) * self.prepOptions.proportionToSample)))
assert inChunkNumber <= len(inChunkList) and inChunkNumber > 0
#Now get the list of chunks flanking and including the current chunk
j = max(0, i - inChunkNumber/2)
inChunkIDs = inChunkIDList[j:j+inChunkNumber]
if len(inChunkIDs) < inChunkNumber: #This logic is like making the list circular
inChunkIDs += inChunkIDList[:inChunkNumber-len(inChunkIDs)]
assert len(inChunkIDs) == inChunkNumber
outChunkIDList.append(self.addChild(self.getChunkedJobForCurrentStage(inChunkIDs, float(inChunkNumber)/len(inChunkIDList), inChunkIDList[i])).rv())
if chunked:
# Merge results of the chunking process back into a genome-wide file
return self.addFollowOn(MergeChunks(self.prepOptions, outChunkIDList)).rv()
else:
# Didn't chunk--we have a genome-wide fasta file
return outChunkIDList[0]
def runCactusGraphMapJoin(options):
with Toil(options) as toil:
importSingularityImage(options)
#Run the workflow
if options.restart:
wf_output = toil.restart()
else:
options.cactusDir = getTempDirectory()
#load cactus config
configNode = ET.parse(options.configFile).getroot()
config = ConfigWrapper(configNode)
config.substituteAllPredefinedConstantsWithLiterals()
# load up the vgs
vg_ids = []
for vg_path in options.vg:
logger.info("Importing {}".format(vg_path))
vg_ids.append(toil.importFile(makeURL(vg_path)))
# tack on the decoys
if options.decoyGraph:
logger.info("Importing decoys {}".format(options.decoyGraph))
vg_ids.append(toil.importFile(makeURL(options.decoyGraph)))
# we'll treat it like any other graph downstream, except clipping
# where we'll check first using the path name
options.vg.append(options.decoyGraph)
# load up the hals
hal_ids = []
for hal_path in options.hal:
logger.info("Importing {}".format(hal_path))
hal_ids.append(toil.importFile(makeURL(hal_path)))
# run the workflow
wf_output = toil.start(
Job.wrapJobFn(graphmap_join_workflow, options, config, vg_ids,
hal_ids))
#export the split data
export_join_data(toil, options, wf_output[0], wf_output[1],
wf_output[2])
def runWorkflow_multipleExamples(inputGenFunction,
testNumber=1,
testRestrictions=(TestStatus.TEST_SHORT, TestStatus.TEST_MEDIUM, \
TestStatus.TEST_LONG, TestStatus.TEST_VERY_LONG,),
inverseTestRestrictions=False,
batchSystem="single_machine",
buildAvgs=False, buildReference=False,
configFile=None, buildToilStats=False,
useConstraints=False,
cactusWorkflowFunction=runCactusWorkflow,
buildHal=False,
buildFasta=False,
progressive=False):
"""A wrapper to run a number of examples.
"""
if (inverseTestRestrictions and TestStatus.getTestStatus() not in testRestrictions) or \
(not inverseTestRestrictions and TestStatus.getTestStatus() in testRestrictions):
for test in xrange(testNumber):
tempDir = getTempDirectory(os.getcwd())
if useConstraints:
sequences, newickTreeString, constraints = inputGenFunction(
regionNumber=test, tempDir=tempDir)
else:
sequences, newickTreeString = inputGenFunction(
regionNumber=test, tempDir=tempDir)
constraints = None
runWorkflow_TestScript(
sequences,
newickTreeString,
outputDir=tempDir,
batchSystem=batchSystem,
buildAvgs=buildAvgs,
buildReference=buildReference,
buildHal=buildHal,
buildFasta=buildFasta,
configFile=configFile,
buildToilStats=buildToilStats,
constraints=constraints,
progressive=progressive,
cactusWorkflowFunction=cactusWorkflowFunction)
system("rm -rf %s" % tempDir)
logger.info("Finished random test %i" % test)
def testCPecanEm(self):
"""Runs cPecanEm.
"""
trial = 0
for modelType in ("fiveState", "fiveStateAsymmetric", "threeState", "threeStateAsymmetric"):
for seqFile1, seqFile2 in seqFilePairGenerator():
tempDir = getTempDirectory(rootDir=os.getcwd())
jobTreeDir = os.path.join(tempDir, "jobTree")
alignmentsFile = os.path.join(tempDir, "alignments.cigars")
computeAlignments(seqFile1, seqFile2, alignmentsFile)
logger.info("Computed alignments for seqs %s and %s" % (seqFile1, seqFile2))
outputModelFile = os.path.join(tempDir, "outputModel.txt")
#First run the script to generate a model and do one iteration of EM to
#get the likelihood to compare with the final likelihood
runCPecanEm(sequenceFiles=[ seqFile1, seqFile2 ],
alignmentsFile=alignmentsFile, outputModelFile=outputModelFile,
modelType=modelType,
jobTreeDir=jobTreeDir,
iterations=1, trials=1, randomStart=False, logLevel=getLogLevelString(),
setJukesCantorStartingEmissions=0.2,
#useDefaultModelAsStart=,
trainEmissions=True,
tieEmissions=True,
optionsToRealign="--diagonalExpansion=6 --splitMatrixBiggerThanThis=100")
hmm = Hmm.loadHmm(outputModelFile)
system("rm -rf %s" % jobTreeDir) #Cleanup the old jobTree
logger.info("For trial %s the likelihood after 1 iteration of EM is %s" % (trial, hmm.likelihood))
iterations = 5
runCPecanEm(sequenceFiles=[ seqFile1, seqFile2 ],
alignmentsFile=alignmentsFile, outputModelFile=outputModelFile, jobTreeDir=jobTreeDir,
optionsToRealign="--diagonalExpansion=6 --splitMatrixBiggerThanThis=100",
iterations=iterations, inputModelFile=outputModelFile, logLevel=getLogLevelString(),
maxAlignmentLengthPerJob=10000) #, updateTheBand=True)
hmm2 = Hmm.loadHmm(outputModelFile)
logger.info("For trial %s the likelihood after a further %s iterations of EM is %s" % (trial, iterations, hmm2.likelihood))
self.assertTrue(hmm.likelihood < hmm2.likelihood)
hmm2.normalise()
logger.info("Final transitions: %s" % " ".join(map(str, hmm2.transitions)))
logger.info("Final emissions: %s" % " ".join(map(str, hmm2.emissions)))
system("rm -rf %s" % tempDir)
trial += 1
def progressiveFunction(self, experimentFile, jobTreeDir,
batchSystem, buildAvgs,
buildReference,
buildHal,
buildFasta,
jobTreeStats,
subtreeRoot=None):
tempDir = getTempDirectory(os.getcwd())
tempExperimentDir = os.path.join(tempDir, "exp")
runCactusCreateMultiCactusProject(experimentFile,
tempExperimentDir,
fixNames=False,
root=subtreeRoot)
logger.info("Put the temporary files in %s" % tempExperimentDir)
runCactusProgressive(os.path.join(tempExperimentDir, "exp_project.xml"),
jobTreeDir,
batchSystem=batchSystem,
buildAvgs=buildAvgs,
jobTreeStats=jobTreeStats)
runJobTreeStatusAndFailIfNotComplete(jobTreeDir)
system("rm -rf %s" % tempDir)
def run(self):
#----------------------------------------
# Run cactus_workflow.py and report time#
#----------------------------------------
logger.info(
"CactusWorkflowWrapper: going to issue cactus run for simulation %s, parameter %s\n"
% (self.simulation, self.paraFile))
tempDir = getTempDirectory(self.outDir)
flowerdisk = os.path.join(tempDir, "cactusDisk")
jobtreeDir = os.path.join(tempDir, "jobTree")
#batchSystem = "single_machine"
batchSystem = "parasol"
retryCount = 0
command = "cactus_workflow.py --speciesTree='%s' %s --configFile %s --buildTrees --setupAndBuildAlignments --cactusDisk %s --logDebug --job=JOB_FILE" % (
self.tree, self.sequenceFiles, self.paraFile, flowerdisk)
starttime = time.time()
runJobTree(command, jobtreeDir, "DEBUG", retryCount, batchSystem, None)
#runCactusWorkflow(flowerdisk, self.sequenceFiles, self.tree, jobtreeDir, "DEBUG", 0, batchSystem, None, True, True, False, False, self.config)
runtime = time.time() - starttime
logger.info("Done cactus_workflow for simulation %s, config %s\n" %
(self.simulation, self.paraFile))
#-----------------------
# Run cactus_treeStats #
#-----------------------
#statsFile = os.path.join(self.outDir, "stats", "%s.xml" % self.simNum)
statsFile = os.path.join(self.outDir, "stats", "%s.xml" % self.simName)
runCactusTreeStats(outputFile=statsFile, cactusDisk=flowerdisk)
#self.addChildCommand(command)
#------------------- Adding child ------------------------#
#self.addChildTarget(CactusMAFGeneratorWrapper(self.outDir, tempDir, self.simNum, runtime))
self.addChildTarget(
CactusMAFGeneratorWrapper(self.outDir, tempDir, self.simTrueMafDir,
self.simName, runtime))
logger.info("Added child CactusMAFGeneratorWrapper at %s\n" %
self.outDir)
#------------------- Cleaning up -------------------------#
self.setFollowOnTarget(CactusWorkflowWrapperCleanup(tempDir))
def setUp(self):
unittest.TestCase.setUp(self)
self.trees = randomTreeSet()
self.mcTrees = []
self.tempDir = getTempDirectory(os.getcwd())
self.tempFa = os.path.join(self.tempDir, "seq.fa")
with open(self.tempFa, "w") as f:
f.write(">temp\nNNNNNNNCNNNNAAAAAAAAAAAAAAANNNNNNN\n")
self.dummySeqMaps = []
for tree in self.trees:
if tree.size() < 500:
mcTree = MultiCactusTree(tree, tree.degree())
seqMap = dict()
for i in mcTree.breadthFirstTraversal():
mcTree.setName(i, "Node%s" % str(i))
seqMap["Node%s" % str(i)] = self.tempFa
mcTree.computeSubtreeRoots()
self.mcTrees.append(mcTree)
self.dummySeqMaps.append(seqMap)
seqLens = dict()
seqLens["HUMAN"] = 57553
seqLens["CHIMP"] = 57344
seqLens["BABOON"] = 58960
seqLens["MOUSE"] = 32750
seqLens["RAT"] = 38436
seqLens["DOG"] = 54187
seqLens["CAT"] = 50283
seqLens["PIG"] = 54843
seqLens["COW"] = 55508
self.blanchetteSeqMap = dict()
for event, seqLen in seqLens.items():
p = os.path.join(self.tempDir, event +".fa")
with open(p, "w") as f:
f.write(">%s\n" % event)
f.write(''.join(['A'] * seqLen))
f.write('\n')
self.blanchetteSeqMap[event] = p
def runWorkflow_multipleExamples(inputGenFunction,
testNumber=1,
testRestrictions=(TestStatus.TEST_SHORT, TestStatus.TEST_MEDIUM, \
TestStatus.TEST_LONG, TestStatus.TEST_VERY_LONG,),
inverseTestRestrictions=False,
batchSystem="single_machine",
buildAvgs=False, buildReference=False,
configFile=None, buildJobTreeStats=False,
useConstraints=False,
cactusWorkflowFunction=runCactusWorkflow,
buildHal=False,
buildFasta=False,
progressive=False):
"""A wrapper to run a number of examples.
"""
if (inverseTestRestrictions and TestStatus.getTestStatus() not in testRestrictions) or \
(not inverseTestRestrictions and TestStatus.getTestStatus() in testRestrictions):
for test in xrange(testNumber):
tempDir = getTempDirectory(os.getcwd())
if useConstraints:
sequences, newickTreeString, constraints = inputGenFunction(regionNumber=test, tempDir=tempDir)
else:
sequences, newickTreeString = inputGenFunction(regionNumber=test, tempDir=tempDir)
constraints = None
experiment = runWorkflow_TestScript(sequences, newickTreeString,
outputDir=tempDir,
batchSystem=batchSystem,
buildAvgs=buildAvgs, buildReference=buildReference,
buildHal=buildHal,
buildFasta=buildFasta,
configFile=configFile,
buildJobTreeStats=buildJobTreeStats,
constraints=constraints,
progressive=progressive,
cactusWorkflowFunction=cactusWorkflowFunction)
experiment.cleanupDb()
system("rm -rf %s" % tempDir)
logger.info("Finished random test %i" % test)
def scriptTree_SortTest(testNo, batchSystem, lines=100000, maxLineLength=10, N=1000):
"""Tests scriptTree/jobTree by sorting a file in parallel.
"""
for test in xrange(testNo):
tempDir = getTempDirectory(os.getcwd())
tempFile = getTempFile(rootDir=tempDir)
jobTreeDir = os.path.join(tempDir, "jobTree")
makeFileToSort(tempFile, lines=lines, maxLineLength=maxLineLength)
#First make our own sorted version
fileHandle = open(tempFile, 'r')
l = fileHandle.readlines()
l.sort()
fileHandle.close()
#Sort the file
command = "scriptTreeTest_Sort.py --jobTree %s --logLevel=DEBUG --fileToSort=%s --N %i --batchSystem %s --jobTime 1.0 --maxJobs 20" % (jobTreeDir, tempFile, N, batchSystem)
system(command)
#Now check the file is properly sorted..
#Now get the sorted file
fileHandle = open(tempFile, 'r')
l2 = fileHandle.readlines()
fileHandle.close()
checkEqual(l, l2)
system("rm -rf %s" % tempDir)
def testBlastRandom(self):
"""Make some sequences, put them in a file, call blast with random parameters
and check it runs okay.
"""
tempSeqFile = os.path.join(self.tempDir, "tempSeq.fa")
self.tempFiles.append(tempSeqFile)
for test in xrange(self.testNo):
seqNo = random.choice(xrange(0, 10))
seq = getRandomSequence(8000)[1]
fileHandle = open(tempSeqFile, 'w')
for fastaHeader, seq in [ (str(i), mutateSequence(seq, 0.3*random.random())) for i in xrange(seqNo) ]:
if random.random() > 0.5:
seq = reverseComplement(seq)
fastaWrite(fileHandle, fastaHeader, seq)
fileHandle.close()
chunkSize = random.choice(xrange(500, 9000))
overlapSize = random.choice(xrange(2, 100))
toilDir = os.path.join(getTempDirectory(self.tempDir), "toil")
runCactusBlast([ tempSeqFile ], self.tempOutputFile, toilDir, chunkSize, overlapSize)
#runToilStatusAndFailIfNotComplete(toilDir)
if getLogLevelString() == "DEBUG":
system("cat %s" % self.tempOutputFile)
system("rm -rf %s " % toilDir)
def main(argv=None):
if argv is None:
argv = sys.argv
seed = random.randint(0, 2**31)
parser = argparse.ArgumentParser(description='Run little hal test')
parser.add_argument('--preset', type=str,
help='halGenRandom preset to use [small, medium, big, large]', default='small')
args = parser.parse_args()
rval = 0
print "chunk, comp, time(gen), time(cons), fsize(k)"
try:
for chunkSize in [10000, 100000, 1000000, 10000000]:
for compression in [0, 2, 5, 7, 9]:
try:
tempDir = getTempDirectory(rootDir="./")
tempFile = getTempFile(suffix=".h5", rootDir=tempDir)
except:
traceback.print_exc(file=sys.stdout)
return 1
t = time.time()
runHalGen(args.preset, seed, chunkSize, compression, tempFile)
fsize = os.path.getsize(tempFile)
th = time.time() - t
runHalCons(tempFile, getTempFile(rootDir=tempDir))
tc = time.time() - th - t
print "%d, %d, %f.3, %f.3, %f.2" % (
chunkSize, compression, th, tc, fsize / 1024.)
except:
traceback.print_exc(file=sys.stdout)
return 1
system("rm -rf %s" % tempDir)
return rval
