def main():
tTree = raw_input("Write down the file name of the taxonomic tree in the folder \"meta\" [ without the extension .tree ]\n")
if (tTree == ""):
tTree = "GGdb2015"
oMatrix = raw_input("Write down the CSV file name of the occurrence matrix in the folder \"meta\" [ without the extension .csv ]\n")
if (oMatrix == ""):
oMatrix = "MGAcount_complete"
iMatrix = raw_input("Write down the CSV file name of the data matrix in the folder \"meta\" [ without the extension .csv ]\n")
if (iMatrix == ""):
iMatrix = "Info"
print "/!\ Data getting parsed..."
try:
samplesInfoList,infoList = parseInfo(iMatrix)
sampleIDList = getSampleIDList(samplesInfoList)
except IOError:
print "\nERROR: Maybe the filename",iMatrix,".csv does not exist in \"meta\" folder\n"
s.exit(0)
print "..."
try:
samplesOccList,speciesList = parseMatrix(oMatrix)
except IOError:
print "\nERROR: Maybe the filename",oMatrix,".csv does not exist in \"meta\" folder\n"
s.exit(0)
print "..."
try:
paths,n,nodesList = parseTree(tTree)
except IOError:
print "\nERROR: Maybe the filename",tTree,".tree does not exist in \"meta\" folder\n"
s.exit(0)
print "-- End of parsing\n"
print "/!\ Constructing the whole annotated taxonomic tree"
print "[ You may have to wait for a few seconds... ]"
taxoTree = TaxoTree("Root").addNode(paths,nodesList,samplesOccList)
print "-- End of construction\n"
dataArray = [samplesInfoList,infoList,samplesOccList,speciesList,paths,n,nodesList,taxoTree,sampleIDList]
answer = ""
while not ((answer == "exit") or (answer == "exit()") or (answer == "quit")):
try:
print "What do you want to do?"
print "[Write down the number matching with the action required. Details are in README file]"
print " 1: Run the program"
print " 2: Print the taxonomic tree"
print "[To quit, write down exit]"
answer = raw_input("Your answer?\n")
if (answer =="1"):
runAct(dataArray)
print "-- End \n"
elif (answer == "2"):
printTreeAct(dataArray)
print "-- End \n"
elif not ((answer == "exit") or (answer == "exit()") or (answer == "quit")):
print "/!\ ERROR: Please enter a number between 1 and 2 included, or 'exit' if you want to quit."
raise ValueError
except ValueError:
print "/!\ ERROR: Please look at the line above."
print "/!\ ERROR: If the line above is blank, it may be an uncatched ValueError.\n"
def expectMatrix(matrix,n,m):
exp = 0
if not n or not m:
print "\n/!\ ERROR: Math problem (Division by zero)."
raise ValueError
for i in range(n):
for j in range(m):
try:
#All values are theoretically non-negative
#Since we have to deal only with integers (numpy module in Python...)
#-1 signifies infinite value (see computeDiscriminatoryDistance.py)
#We ignore these infinite values in the calculus of the expectation
if not (matrix[i][j] == inf):
exp += matrix[i][j]/(n*m)
except IndexError:
print "BUG"
print matrix[i],matrix[j]
from misc import getSampleIDList
from parsingInfo import parseInfo
sampleInfoList,_ = parseInfo("Info")
sampleIDList = getSampleIDList(sampleInfoList)
print sampleIDList[i],sampleIDList[j]
print "END BUG"
return exp
def main():
tTree = raw_input("Write down the file name of the taxonomic tree in the folder \"meta\" [ without the extension .tree ]\n")
if (tTree == ""):
tTree = "GGdb2015"
oMatrix = raw_input("Write down the CSV file name of the occurrence matrix in the folder \"meta\" [ without the extension .csv ]\n")
if (oMatrix == ""):
oMatrix = "MGAcount_complete"
iMatrix = raw_input("Write down the CSV file name of the data matrix in the folder \"meta\" [ without the extension .csv ]\n")
if (iMatrix == ""):
iMatrix = "Info"
print "/!\ Data getting parsed..."
try:
samplesInfoList,infoList = parseInfo(iMatrix)
sampleIDList = getSampleIDList(samplesInfoList)
except IOError:
print "\nERROR: Maybe the filename",iMatrix,".csv does not exist in \"meta\" folder\n"
s.exit(0)
print "..."
try:
samplesOccList,speciesList = parseMatrix(oMatrix)
except IOError:
print "\nERROR: Maybe the filename",oMatrix,".csv does not exist in \"meta\" folder\n"
s.exit(0)
print "..."
try:
paths,n,nodesList = parseTree(tTree)
except IOError:
print "\nERROR: Maybe the filename",tTree,".tree does not exist in \"meta\" folder\n"
s.exit(0)
print "-- End of parsing\n"
print "/!\ Constructing the whole annotated taxonomic tree"
print "[ You may have to wait for a few seconds... ]"
taxoTree = TaxoTree("Root").addNode(paths,nodesList,samplesOccList)
print "-- End of construction\n"
dataArray = [samplesInfoList,infoList,samplesOccList,speciesList,paths,n,nodesList,taxoTree,sampleIDList]
answer = ""
while not ((answer == "exit") or (answer == "exit()") or (answer == "quit")):
try:
print "What do you want to do?"
print "[Write down the number matching with the action required. Details are in README file]"
print " 1: Total ratio and Diff ratio"
print " 2: Pattern ratio"
print " 3: Percentage of assignments in a certain group of bacterias depending on metadata"
print " 4: Pearson correlation coefficient"
print " 5: Microbial diversity in samples"
print " 6: Similarity coefficients between patients"
print " 7: Print the taxonomic tree"
print " 8: Plot a graph, or a pie chart"
print " 9: Compute total distance between two samples"
print "[To quit, write down exit]"
answer = raw_input("Your answer?\n")
if (answer =="1"):
totalDiffRatioAct(dataArray)
print "-- End \n"
elif (answer == "2"):
patternRatioAct(dataArray)
print "-- End \n"
elif (answer == "3"):
percentageAct(dataArray)
print "-- End \n"
elif (answer == "4"):
pearsonAct(dataArray)
print "-- End \n"
elif (answer == "5"):
diversityAct(dataArray)
print "-- End\n"
elif (answer == "6"):
matrixSim = similarityAct(dataArray,iMatrix)
dataArray.append(matrixSim)
print "-- End \n"
elif (answer == "7"):
printTreeAct(dataArray)
print "-- End \n"
elif (answer == "8"):
plottingAct(dataArray)
print "-- End \n"
elif (answer == "9"):
distanceAct(dataArray)
print "-- End \n"
elif not ((answer == "exit") or (answer == "exit()") or (answer == "quit")):
print "\n/!\ ERROR: Please enter a number between 1 and 9 included, or 'exit' if you want to quit."
raise ValueError
except ValueError:
print "/!\ ERROR: Please look at the line above."
print "/!\ ERROR: If the line above is blank, it may be an uncatched ValueError.\n"