def modelSumLabelUpdate(modelSum, labels, data, problem, txn):
model = db.Model(data['user'], data['hub'], data['track'],
problem['chrom'], problem['chromStart'],
modelSum['penalty']).get(txn=txn)
return calculateModelLabelError(model, labels, problem,
modelSum['penalty'])
def getModels(data):
problems = Tracks.getProblems(data)
output = []
for problem in problems:
modelSummaries = db.ModelSummaries(data['user'], data['hub'],
data['track'], problem['chrom'],
problem['chromStart']).get()
if len(modelSummaries.index) < 1:
lopartOutput = generateLOPARTModel(data, problem)
output.extend(lopartOutput)
continue
nonZeroRegions = modelSummaries[modelSummaries['regions'] > 0]
if len(nonZeroRegions.index) < 1:
lopartOutput = generateLOPARTModel(data, problem)
output.extend(lopartOutput)
continue
withPeaks = nonZeroRegions[nonZeroRegions['numPeaks'] > 0]
if len(withPeaks.index) < 1:
lopartOutput = generateLOPARTModel(data, problem)
output.extend(lopartOutput)
continue
noError = withPeaks[withPeaks['errors'] < 1]
if len(noError.index) < 1:
lopartOutput = generateLOPARTModel(data, problem)
output.extend(lopartOutput)
continue
elif len(noError.index) > 1:
# Select which model to display from modelSums with 0 error
noError = whichModelToDisplay(data, problem, noError)
penalty = noError['penalty'].iloc[0]
minErrorModel = db.Model(data['user'], data['hub'], data['track'],
problem['chrom'], problem['chromStart'],
penalty)
model = minErrorModel.getInBounds(data['ref'], data['start'],
data['end'])
onlyPeaks = model[model['annotation'] == 'peak']
# Organize the columns
onlyPeaks = onlyPeaks[modelColumns]
onlyPeaks.columns = jbrowseModelColumns
output.extend(onlyPeaks.to_dict('records'))
return output
def putModel(data):
modelData = pd.read_json(data['modelData'])
modelData.columns = modelColumns
modelInfo = data['modelInfo']
problem = modelInfo['problem']
penalty = data['penalty']
user = modelInfo['user']
hub = modelInfo['hub']
track = modelInfo['track']
txn = db.getTxn()
db.Model(user, hub, track, problem['chrom'], problem['chromStart'],
penalty).put(modelData, txn=txn)
labels = db.Labels(user, hub, track, problem['chrom']).get()
errorSum = calculateModelLabelError(modelData, labels, problem, penalty)
db.ModelSummaries(user, hub, track, problem['chrom'],
problem['chromStart']).add(errorSum, txn=txn)
txn.commit()
return modelInfo