def extract(self, experiment, type, indiv):
filepath = GetAltFile.getAltTraceFile(experiment, type, indiv)
if filepath != False:
return TraceDistance.calcDistance(filepath)
else:
print "WARN: couldn't find alt trace file for experiment {}, indiv {}".format(experiment[0], indiv[0])
return ["NA"] * 4
def extract(self, experiment, type, indiv):
filepath = experiment[2] + os.path.sep + "traces_afterPP" + os.path.sep + indiv[0] + ".trace"
if os.path.isfile(filepath):
return TraceDistance.calcDistance(filepath)
else:
return ["NA"] * 4
def dataCollector(self):
listing = glob.glob(self.pattern)
td = TraceDistance()
dc = DistanceCalc()
with open(self.outputFile, "w") as csvfile:
headersWritten = False
print listing # Testing
for nestFile in listing:
print "Experiment folder: " + nestFile # Testing
expFolder = nestFile[-2:]
experimentNumber = str(expFolder)
popListing = glob.glob(nestFile + "/population/*.vxa")
for path in popListing:
indNumber = path[27:-8]
print "Population path: " + path # Testing
print "Ind. ID: " + indNumber # Testing
backupBasePath = nestFile + "/population_{condition}/" + indNumber + "_vox.vxa"
backup_path = os.path.abspath(backupBasePath.format(condition="beforePL"))
if not os.path.isfile(backup_path):
backup_path = os.path.abspath(backupBasePath.format(condition="MUT"))
if not os.path.isfile(backup_path):
backup_path = False
print "Backups path: " + backup_path # Testing
voxProbability, voxLifetime, voxCounts = self.voxCounter(experimentNumber, path, indNumber)
voxProb_orig, voxProbLife_orig, voxCounts_orig = self.voxCounter(
experimentNumber, backup_path, indNumber
)
traceFilename = os.path.abspath(nestFile + "/traces_afterPP/" + indNumber + ".trace")
mutatedBasePath = nestFile + "/traces_{condition}/" + indNumber + ".trace"
NOMUT_traceFilename = os.path.abspath(mutatedBasePath.format(condition="MUT"))
variant = "mut"
if not os.path.isfile(NOMUT_traceFilename):
NOMUT_traceFilename = os.path.abspath(mutatedBasePath.format(condition="NOMUT"))
variant = "nomut"
if not os.path.isfile(NOMUT_traceFilename):
NOMUT_traceFilename = False
if variant == "nomut":
fieldnames = [
"Ind_ID",
"birthtime",
"Exp_Num",
"probability",
"euclideanStep",
"manhattanStep",
"euclideanTotal",
"manhattanTotal",
"lifetime",
"size",
"totalMuscles",
"totalFat",
"totalBone",
"diseasedMuscle",
"diseasedFat",
"diseasedBone",
"diseasedEuclideanStep",
"diseasedManhattanStep",
"diseasedEuclideanTotal",
"diseasedManhattanTotal",
]
else:
fieldnames = [
"Ind_ID",
"birthtime",
"Exp_Num",
"probability",
"euclideanStep",
"manhattanStep",
"euclideanTotal",
"manhattanTotal",
"lifetime",
"size",
"totalMuscles",
"totalFat",
"totalBone",
"originalMuscle",
"originalFat",
"originalBone",
"originalEuclideanStep",
"originalManhattanStep",
"originalEuclideanTotal",
"originalManhattanTotal",
]
if not headersWritten:
writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
writer.writeheader()
headersWritten = True
if os.path.isfile(traceFilename):
distances = td.calcDistance(traceFilename)
birthtime = dc.getBirthTime(traceFilename)
if not birthtime:
birthtime = "NA"
print distances # Testing
print "Born at: " + str(birthtime)
else:
distances = ["NA", "NA", "NA", "NA", "NA"] # Batman
birthtime = ["NA"]
print indNumber + " trace file missing in /traces_afterPP/ of experiment " + experimentNumber
if NOMUT_traceFilename:
NOMUT_distances = td.calcDistance(NOMUT_traceFilename)
print NOMUT_distances
else:
NOMUT_distances = ["NA", "NA", "NA", "NA", "NA"] # Batman
print indNumber + " trace file missing in /traces_NOMUT/ of experiment " + experimentNumber
if variant == "mut":
columnNames = {
"Ind_ID": indNumber,
"birthtime": birthtime,
"Exp_Num": experimentNumber,
"probability": voxProbability,
"euclideanStep": distances[0],
"manhattanStep": distances[1],
"euclideanTotal": distances[2],
"manhattanTotal": distances[3],
"lifetime": voxLifetime,
"size": voxCounts[4],
"totalMuscles": voxCounts[3],
"totalFat": voxCounts[1],
"totalBone": voxCounts[2],
"originalMuscle": voxCounts_orig[3],
"originalFat": voxCounts_orig[1],
"originalBone": voxCounts_orig[2],
"originalEuclideanStep": NOMUT_distances[0],
"originalManhattanStep": NOMUT_distances[1],
"originalEuclideanTotal": NOMUT_distances[2],
"originalManhattanTotal": NOMUT_distances[3],
}
elif variant == "nomut":
columnNames = {
"Ind_ID": indNumber,
"birthtime": birthtime,
"Exp_Num": experimentNumber,
"probability": voxProbability,
"euclideanStep": distances[0],
"manhattanStep": distances[1],
"euclideanTotal": distances[2],
"manhattanTotal": distances[3],
"lifetime": voxLifetime,
"size": voxCounts[4],
"totalMuscles": voxCounts[3],
"totalFat": voxCounts[1],
"totalBone": voxCounts[2],
"diseasedMuscle": voxCounts_orig[3],
"diseasedFat": voxCounts_orig[1],
"diseasedBone": voxCounts_orig[2],
"diseasedEuclideanStep": NOMUT_distances[0],
"diseasedManhattanStep": NOMUT_distances[1],
"diseasedEuclideanTotal": NOMUT_distances[2],
"diseasedManhattanTotal": NOMUT_distances[3],
}
else:
print "File reading (mut/nomut) error!"
break
writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
writer.writerow(columnNames)
