def collate(filenames):
answer = {}
for fname in filenames:
newList = []
f = open(fname, 'r')
for line in f:
try:
d = ast.literal_eval(line)
except:
print 'failed ast.literal_eval'
continue
temp = fname.split('_')
probName = temp[0].split('/')[-1]
questionName = temp[1]
grader = criteria.createGrader(allCriteria[(probName,
questionName)])
username = d['username']
data = d['data']
if data == '{}': continue
grade, feedback = grader.grade(util.GraphData(data))
newList.append((username, grade, feedback))
f.close()
newList.sort(key=lambda x: x[1])
answer[fname] = newList
return answer
def generate(visualOptions, criteriaOptions, generatorFunc, quantity=2):
if isinstance(visualOptions,basestring):
visualOptions = convertStringToDict(visualOptions)
if isinstance(criteriaOptions, basestring):
criteriaOptions = convertStringToDict(criteriaOptions)
#extract axis data
axisData = {}
axisData['xaxis'] = visualOptions['xaxis']
axisData['xaxis']['pixels'] = axisData['xaxis'].pop('pixelDim')
axisData['yaxis'] = visualOptions['yaxis']
axisData['yaxis']['pixels'] = axisData['yaxis'].pop('pixelDim')
#extract grader
grader = criteria.createGrader(criteriaOptions)
answers = []
for i in range(quantity):
genData = generatorFunc(axisData, grader)
(score, feedback) = grader.grade(util.GraphData(json.dumps(genData)))
answers.append({'data':genData,'score':score, 'feedback':feedback})
return answers
def collate(filenames):
answer = {}
for fname in filenames:
newList = []
f = open(fname, 'r')
for line in f:
try:
d = ast.literal_eval(line)
except:
print 'failed ast.literal_eval'
continue
temp = fname.split('_')
probName = temp[0].split('/')[-1]
questionName = temp[1]
grader = criteria.createGrader(allCriteria[(probName,questionName)])
username = d['username']
data = d['data']
if data == '{}': continue
grade, feedback = grader.grade(util.GraphData(data))
newList.append((username, grade, feedback))
f.close()
newList.sort(key=lambda x: x[1])
answer[fname] = newList
return answer
def gradeGivenCriteria(data, criteriaJSON):
critList = json.loads(criteriaJSON)
grader = criteria.createGrader(critList)
graphData = util.GraphData(data)
grade = grader.grade(graphData)
return (grade[0]*100, [grade[1]])
def gradeGivenCriteria(data, criteriaJSON):
critList = json.loads(criteriaJSON)
grader = criteria.createGrader(critList)
graphData = util.GraphData(data)
grade = grader.grade(graphData)
return (grade[0] * 100, [grade[1]])