def main(nameFilename,
debug=False,
dataFilename=None,
learningPaths={},
students=None,
period=None,
heatMapColor="jet",
functions=None,
filterQuickClicks=False,
filesToSave={
"metaData": True,
"nodes": True
},
conceptHitsParams=None,
heatMapParams=None,
studentGroups=None,
**restArgs):
Visualisation.init(nameFilename)
settings = {}
settings['learningpaths'] = learningPaths
settings['students'] = students if not students is None else {
"whitelist": False,
"list": []
}
settings['period'] = period if not period is None else {"usePeriod": False}
if dataFilename is None:
dataFilename = [
x for x in input(
"which file would you like to use?(please enter the name of the excel file "
"or files seperated by commas)\n").split(',')
]
sample = {
'learningpaths': {},
'students': {
'whitelist':
True,
'list': [{
'type': 'text',
'value': '*****@*****.**'
}, {
'type': 'text',
'value': '*****@*****.**'
}, {
'type': 'text',
'value': '*****@*****.**'
}, {
'type': 'text',
'value': '*****@*****.**'
}, {
'type': 'text',
'value': '*****@*****.**'
}, {
'type': 'text',
'value': '*****@*****.**'
}, {
'type': 'text',
'value': '*****@*****.**'
}, {
'type': 'text',
'value': '*****@*****.**'
}]
},
'period': {
'usePeriod': False,
'startDate': datetime.datetime(2019, 9, 1, 0, 0),
'endDate': datetime.datetime(2019, 12, 13, 0, 0)
}
}
print(settings == sample)
data = FilterData.filterAndExtractData(dataFilename, settings, debug=debug)
if debug: print("done extracting data")
# Annonymisation.annonymiseExtracted(data)
# if debug: print("done making data anonymous")
lookup = {}
with open("inputFiles/studentsEncoded.csv", 'r') as studsEncode:
reader = csv.reader(studsEncode)
for name, number in reader:
lookup[name] = number
Annonymisation.alternateAnonymiseExtracted(data, lookup)
output = DataProcessing.processDataExtracted(data,
settings['learningpaths'],
filterQuickClicks,
filesToSave=filesToSave,
timeOnPageCalc=True)
# ToDo if visualisation's input is fixed, output['nodes'] can be used instead of loading nodes.json each time
firstHit = []
try:
os.mkdir("outputs/hitsperday")
except:
pass
try:
os.mkdir("outputs/hoursperday")
except:
pass
# for user in output["users"]:
# print(user)
# try:
# os.mkdir("outputs/user" + user)
# except:
# pass
# firstHit.append(Visualisation.hitsPerDayPerUser(output["users"], user, output["nodes"], settings))
# Visualisation.hoursPerDayPerUser(output['users'], user, output['nodes'], settings)
# print(max(firstHit))
for studentGroup in studentGroups:
print(studentGroup)
try:
os.mkdir("outputs/hoursPerDayPerStudent/")
except:
pass
try:
os.mkdir("outputs/hoursPerDayPerStudent/" + studentGroup)
except:
pass
print(studentGroup)
for student in studentGroups[studentGroup]:
student = "student " + str(student)
Visualisation.hoursPerDayPerUserNoConcepts(
output['users'],
student,
output['nodes'],
settings,
givenName="outputs/hoursPerDayPerStudent/" + studentGroup +
"/" + student)
# for path in settings['learningpaths']:
# Visualisation.learningpathFlowthrough(settings['learningpaths'][path])
# Visualisation.hitsPerDayPerLearningPath(pathId=path, settings=settings)
# Visualisation.heatMapOfGivenNodes(givenNodes=settings['learningpaths'][path]['list'],
# filename="heatmapPath" + str(path), colors=heatMapColor)
# if debug: print("done for path " + str(path))
if debug: print(settings)
DataProcessing.csvExports(nameFilename,
learningPaths=settings['learningpaths'],
functions=functions)
# if not functions is None:
# if ("all" in functions or "allHitsPerDayPerConceptGraph" in functions) and conceptHitsParams:
# if debug: print("HitsPerDayPerConceptGraph same scale")
# Visualisation.generateSetOfPathVisits(conceptHitsParams, settings=settings,
# debug=debug, users=False, specificConcept=True)
# if "HitsPerDayPerConceptGraph" in functions and conceptHitsParams:
# if debug: print("HitsPerDayPerConceptGraph varying scales")
# for conceptId in conceptHitsParams:
# Visualisation.hitsPerDay(nodeId=conceptId)
# if "usersPerDayPerLearningPath" in functions: # not all, because if we want all, they should be on the same scale
# if debug: print("usersPerDayPerLearningPath varying scales")
# for path in settings['learningpaths']:
# Visualisation.usersPerDayPerLearningPath(path, settings=settings)
# if "all" in functions or "allUsersPerDayPerLearningPath" in functions:
# if debug: print("UsersPerDayPerLearningPath same scale")
# Visualisation.generateSetOfPathVisits(pathId=list(settings['learningpaths']), settings=settings,
# debug=debug, users=True)
# if "all" in functions or "allHitsPerDayPerLearningPath" in functions:
# if debug: print("HitsPerDayPerLearningPath same scale")
# Visualisation.generateSetOfPathVisits(pathId=list(settings['learningpaths']), settings=settings,
# debug=debug)
# if "all" in functions or "allNodesFlowthrough" in functions:
# if debug: print("allNodesFlowthrough")
# Visualisation.allNodesFlowthrough(debug=debug) # ToDo there is currently no way to properly display this
# if ("all" in functions or "allNodesHeatMap" in functions) and heatMapParams:
# if debug: print("allNodesHeatmap")
# Visualisation.heatMapOfGivenNodes(**heatMapParams)
# ToDo nodes.json could be saved in such a way that the same nodes.json is not generated twice for the same settings
if "all" not in filesToSave: # remove any unwanted files
if "metaData" not in filesToSave:
if debug: print("removing metadata.json")
os.remove("outputs/metaData.json")
if "nodes" not in filesToSave:
if debug: print("removing nodes.json")
os.remove("outputs/nodes.json")
