def readObjects(self, file):
"""Use the class specific read function to create darts base on reading them from file.
file should be a handle to the file where darts are stored.
"""
self._collection = readScores(file)
def readScorePairs(scoresFN,geneNames,scoreType):
'''Read through a scores file, and separate into all pairwise
comparisons. Return as dict.'''
pairD = {}
scoresO = scores.readScores(scoresFN,geneNames=None)
for gn1,gn2 in scoresO.iterateEdgesByEndNodes():
sc = scoresO.getScoreByEndNodes(gn1,gn2,scoreType)
sp1 = geneNames.numToStrainName(gn1)
sp2 = geneNames.numToStrainName(gn2)
key = tuple(sorted([sp1,sp2]))
if key in pairD:
pairD[key].append(sc)
else:
pairD[key] = [sc]
return pairD
paramD = parameters.loadParametersD(paramFN)
## load data structures we'll use below
tree, strainStr2NumD, strainNum2StrD = trees.readTree(paramD['treeFN'])
# an object for gene name conversions
geneNames = genomes.geneNames(paramD['geneOrderFN'], strainStr2NumD,
strainNum2StrD)
subtreeL = trees.createSubtreeL(tree)
subtreeL.sort()
geneOrderT = genomes.createGeneOrderTs(paramD['geneOrderFN'], geneNames,
subtreeL, strainStr2NumD)
## read scores
scoresO = scores.readScores(paramD['scoresFN'], geneNames)
## make gene families
familyIslandFormationSummaryF = open(
paramD['familyIslandFormationSummaryFN'], 'w')
familyL = families.families(
tree, subtreeL, geneNames, scoresO, paramD['minNormThresh'],
paramD['minCoreSynThresh'], paramD['minSynThresh'],
paramD['synAdjustThresh'], paramD['synAdjustExtent'],
paramD['familyFN'], strainNum2StrD, familyIslandFormationSummaryF)
## group gene families into islands
islands.makeIslands(geneOrderT, geneNames, subtreeL, tree,
paramD['proxThreshL'], familyL, paramD['numThreads'],
strainStr2NumD, strainNum2StrD,
paramD['rootFocalClade'], paramD['islandOutFN'],
import parameters,genbank,trees,genomes,scores,families,islands
## Does island making without family making (i.e. the second half of
## what xenoGI.py does).
if __name__ == "__main__":
paramFN=sys.argv[1]
paramD = parameters.loadParametersD(paramFN)
## load data structures we'll use below
tree,strainStr2NumD,strainNum2StrD = trees.readTree(paramD['treeFN'])
# an object for gene name conversions
geneNames = genomes.geneNames(paramD['geneOrderFN'],strainStr2NumD,strainNum2StrD)
subtreeL=trees.createSubtreeL(tree)
subtreeL.sort()
geneOrderT=genomes.createGeneOrderTs(paramD['geneOrderFN'],geneNames,subtreeL,strainStr2NumD)
## read scores
scoresO = scores.readScores(paramD['scoresFN'],geneNames)
## load gene families
familyL = families.readFamilies(paramD['familyFN'],tree,geneNames,strainStr2NumD)
## group gene families into islands
outputSummaryF = open(paramD['outputSummaryFN'],'w')
islands.makeIslands(geneOrderT,geneNames,subtreeL,tree,paramD['proxThreshL'],familyL,paramD['numThreads'],strainStr2NumD,strainNum2StrD,paramD['rootFocalClade'],paramD['islandOutFN'],outputSummaryF)
outputSummaryF.close()
results.append(test_score(maxHit, finish, standard, [0, 1, 2], file))
results.append(test_score(no_cigar, unusual, standard, [0, 1, 2], file))
#Reversed
print('Testing reversely sorted darts')
results.append(test_score(gutter, board, minHit, [2, 1, 0], file))
results.append(test_score(minHit, almost, unbiased, [2, 1, 0], file))
results.append(test_score(no_cigar, eyes, maxHit, [2, 1, 0], file))
results.append(test_score(minHit, unusual, maxHit, [2, 1, 0], file))
results.append(test_score(standard, finish, maxHit, [2, 1, 0], file))
results.append(test_score(standard, unusual, no_cigar, [2, 1, 0], file))
#Random order
print('Testing randomly ordered darts')
results.append(test_score(board, gutter, minHit, [1, 2, 0], file))
results.append(test_score(minHit, unbiased, almost, [2, 0, 1], file))
results.append(test_score(maxHit, no_cigar, eyes, [0, 2, 1], file))
results.append(test_score(maxHit, minHit, unusual, [0, 2, 1], file))
results.append(test_score(standard, maxHit, finish, [2, 0, 1], file))
results.append(test_score(unusual, no_cigar, standard, [1, 0, 2], file))
#Print summary
printTests(results)
#Load scores from file
file = open(FILENAME, 'r')
scores = readScores(file)
for s in scores:
print(str(s))
