def setUp(self):
for bundle_id, create_bundle in examples.tests:
logger.debug('Creating bundle: %s...' % bundle_id)
self.bundles[bundle_id] = create_bundle()
logger.debug('Saving bundle: %s...' % bundle_id)
pdbundle = save_bundle(self.bundles[bundle_id], bundle_id, __name__)
self.bundle_db_id_map[bundle_id]= pdbundle.pk
def createTripCreationGraph(self, userName, userEmail, tripId, tripLegIds, startTime, endTime):
"""Creates and stores the provenacne graph depecting the action of creating the trip"""
#startTime = datetime.datetime.strptime(startTime, "%a, %d %b %Y %H:%M:%S %Z")
#endTime = datetime.datetime.strptime(endTime, "%a, %d %b %Y %H:%M:%S %Z")
#the namespace of the project
cf = Namespace('cf', 'http://users.ecs.soton.ac.uk/pp6g11/ontology/carbonFooprints/')
# create a provenance _container
g = ProvBundle()
g.add_namespace("foaf", "http://xmlns.com/foaf/0.1/")
#create activity
g.activity(cf['tripCreation'], startTime, endTime)
#create entities.
g.entity(cf['trip-' + tripId])
#create trip leg entities
for tripLegId in tripLegIds:
tripLegId = str(tripLegId)
g.entity(cf['tripLeg-' + tripLegId])
g.wasGeneratedBy('cf:tripLeg-' + tripLegId, 'cf:tripCreation')
g.wasDerivedFrom('cf:trip-' + tripId, 'cf:tripLeg-' + tripLegId)
#add relations
g.wasGeneratedBy('cf:trip-' + tripId, 'cf:tripCreation')
#create agent
g.agent('cf:' + userName, {'prov:type': 'prov:Person', 'foaf:mbox': '<mailto:' + userEmail + '>'})
g.wasAssociatedWith('cf:tripCreation', 'cf:' + userName)
g.wasAttributedTo('cf:trip-' + tripId, 'cf:' + userName)
#save the graph
pdBundle = save_bundle(g)
#visualize the graph
path = tempfile.mkdtemp()
filepath = os.path.join(path, 'dot-test.png')
# Convert it to DOT
dot = graph.prov_to_dot(g)
dot.set_dpi(120)
# Write it to a temporary PNG file
#dot.write_png(filepath)
# Display it using matplotlib
#img = mpimg.imread(filepath)
##imgplot = plt.imshow(img)
#plt.show()
#os.remove(filepath)
return pdBundle
def createTripLegEmissionGraph(self, tripLegEmissionId, methodId, transportMeanId, transportMeanType, emissionFactorId, \
emissionFactorSourceId, drivingDistance, tripLegId, startAddressId, endAddressId, startTime, endTime):
"""Creates and stores the provenacne graph depecting the action of calculating carbon emissions of a trip leg"""
cf = Namespace('cf', 'http://users.ecs.soton.ac.uk/pp6g11/ontology/carbonFooprints/')
#define the entity, activity and agent identifiers
tripLegEmission = cf['tripLegEmission-' + str(tripLegEmissionId)]
transportMean = cf['transportMean-' + transportMeanType + '-' + str(transportMeanId)]
emissionFactor = cf['emissionFactor-' + str(emissionFactorId)]
emissionFactorSource = cf['emissionFactorSource-' + str(emissionFactorSourceId)]
tripLeg = cf['tripLeg-' + str(tripLegId)]
tripLegDrivingDistance = cf['tripLegDrivingDistance-' + str(tripLegId)]
tripLegStartAddress = cf['tripLegStartAddress-' + str(startAddressId)]
tripLegEndAddress = cf['tripLegEndAddress-' + str(endAddressId)]
calculationMethod = cf['calculationMetdod-' + str(methodId)]
# load the bundle that contains this trip leg. The one that has the trip creation graph
pdBundle = TripLeg.objects.get(id=tripLegId).trip.provBundle
# pdBundle = PDBundle.objects.get(id=284) #PDRecord.objects.get(bundle_id=60).bundle
#get the in memmory model of that bundle
g = pdBundle.get_prov_bundle()
#get the trip leg entity that is already stored
tripLegEntity = g.get_record(tripLeg)
#define the activities
g.activity(cf['tripLegCarbonEmissionsCalculation'], startTime, endTime)
g.activity(cf['drivingDistanceCalculation'])
#define the entities
g.entity(tripLegEmission)
g.entity(transportMean)
g.entity(emissionFactor)
g.entity(emissionFactorSource)
g.entity(tripLegDrivingDistance, {'prov:value': drivingDistance})
g.entity(tripLegStartAddress)
g.entity(tripLegEndAddress)
g.entity(calculationMethod)
#create agent
g.agent('cf:CarbonEmissionCalculator', {'prov:type': 'prov:SoftwareAgent'})
g.agent('cf:BingApi', {'prov:type': 'prov:SoftwareAgent'})
#relations
g.wasAttributedTo(tripLegEmission, 'cf:CarbonEmissionCalculator')
g.wasGeneratedBy(tripLegEmission, 'cf:tripLegCarbonEmissionsCalculation')
g.wasAssociatedWith('cf:tripLegCarbonEmissionsCalculation', 'cf:CarbonEmissionCalculator')
g.wasAssociatedWith('cf:drivingDistanceCalculation', 'cf:BingApi')
g.used('cf:tripLegCarbonEmissionsCalculation', emissionFactor)
g.used('cf:tripLegCarbonEmissionsCalculation', transportMean)
g.used('cf:tripLegCarbonEmissionsCalculation', calculationMethod)
g.used('cf:tripLegCarbonEmissionsCalculation', tripLegDrivingDistance)
g.wasDerivedFrom(transportMean, tripLegEntity)
g.wasDerivedFrom(tripLegStartAddress, tripLegEntity)
g.wasDerivedFrom(tripLegEndAddress, tripLegEntity)
g.wasDerivedFrom(tripLegDrivingDistance, tripLegStartAddress)
g.wasDerivedFrom(tripLegDrivingDistance, tripLegEndAddress)
g.wasGeneratedBy(tripLegDrivingDistance, 'cf:drivingDistanceCalculation')
g.used('cf:drivingDistanceCalculation', tripLegStartAddress)
g.used('cf:drivingDistanceCalculation', tripLegEndAddress)
#g.hadPrimarySource(emissionFactor, emissionFactorSource)
#visualize the graph
#path = tempfile.mkdtemp()
#filepath = os.path.join(path, 'dot-test.png')
# Convert it to DOT
#dot = graph.prov_to_dot(g)
#dot.set_dpi(120)
# Write it to a temporary PNG file
#dot.write_png(filepath)
# Display it using matplotlib
#img = mpimg.imread(filepath)
#imgplot = plt.imshow(img)
#plt.show()
#os.remove(filepath)
#small demo of how to encode the bundle into a dictionary and ultimately into json
json = g._encode_JSON_container()
entities = json['entity'].keys()
#save the graph (bundle)
return save_bundle(g)