def modelStats(request):
user = request.authenticated_userid
return {
'numModels': Models.numModels(),
'correctModels': Models.numCorrectModels(),
'user': user
}
def checkForMoreJobs(task):
txn = db.getTxn()
problem = task['problem']
modelSums = db.ModelSummaries(task['user'], task['hub'], task['track'],
problem['chrom'],
problem['chromStart']).get(txn=txn,
write=True)
Models.checkGenerateModels(modelSums, problem, task, txn=txn)
txn.commit()
def removeLabel(data):
toRemove = pd.Series({
'chrom': data['ref'],
'chromStart': data['start'],
'chromEnd': data['end']
})
txn = db.getTxn()
labels = db.Labels(data['user'], data['hub'], data['track'], data['ref'])
removed, after = labels.remove(toRemove, txn=txn)
db.Prediction('changes').increment(txn=txn)
Models.updateAllModelLabels(data, after)
txn.commit()
return removed.to_dict()
def updateLabel(data):
label = data['label']
updateLabel = pd.Series({
'chrom': data['ref'],
'chromStart': data['start'],
'chromEnd': data['end'],
'annotation': label
})
txn = db.getTxn()
labelDb = db.Labels(data['user'], data['hub'], data['track'], data['ref'])
item, labels = labelDb.add(updateLabel, txn=txn)
db.Prediction('changes').increment(txn=txn)
Models.updateAllModelLabels(data, labels)
txn.commit()
return item.to_dict()
def submitPregenWithData(doPregen, user, hub, track, coverageUrl, txn=None):
recs = doPregen.to_dict('records')
for problem in recs:
penalties = Models.getPrePenalties()
job = Jobs.PregenJob(user,
hub,
track['track'],
problem,
penalties,
trackUrl=coverageUrl)
job.putNewJob(checkExists=False)
def addLabel(data):
label = 'unknown'
for i in range(100):
print("#################################################")
print("THIS IS THE DATA", data)
for i in range(10):
print("#################################################")
# Duplicated because calls from updateLabel are causing freezing
newLabel = pd.Series({
'chrom': data['ref'],
'chromStart': data['start'],
'chromEnd': data['end'],
'annotation': label
})
txn = db.getTxn()
item, labels = db.Labels(data['user'], data['hub'], data['track'],
data['ref']).add(newLabel, txn=txn)
db.Prediction('changes').increment(txn=txn)
Models.updateAllModelLabels(data, labels)
txn.commit()
return data
def stats(request):
numLabeledChroms, numLabels = Labels.stats()
currentJobStats = Jobs.stats()
user = request.authenticated_userid
return {
'numModels': Models.numModels(),
'numLabeledChroms': numLabeledChroms,
'numLabels': numLabels,
'numJobs': currentJobStats['numJobs'],
'newJobs': currentJobStats['newJobs'],
'queuedJobs': currentJobStats['queuedJobs'],
'processingJobs': currentJobStats['processingJobs'],
'doneJobs': currentJobStats['doneJobs'],
'avgTime': currentJobStats['avgTime'],
'user': user
}