with open('DAS28data.csv', 'rt') as csvfile:
file = csv.reader(csvfile, delimiter=',')
DAS28scores = list(file)
for row in UL_PD_scores[1:]:
file = row[filename]
name = file[3:5]
date = row[contentdate]
joint = row[joint_scanned]
if joint in Session.jointNames:
if dateDict.get(date) is None:
sess = Session()
sess.name = name
sess.add_file(file, joint, int(row[score]))
dateDict[date] = [sess]
sess.calc_avg()
else:
if dateDict[date][len(dateDict[date]) - 1].name != name:
dateDict[date].append(Session())
currentSess = dateDict[date][len(dateDict[date]) - 1]
currentSess.name = name
currentSess.add_file(file, joint, int(row[score]))
currentSess.calc_avg()
DAS28scores.sort(key=lambda x:
(float(x[0]), (float(x[2]) - 0.36 * np.log(float(x[1]) + 1))))
last_date = ""
DAS28_date_dict = dict()
