def printBasicNoteStats(user):
notes = Note.objects.filter(owner=user)
print "# Notes:", notes.count()
noteLen = map(lambda x:len(x.contents), notes)
noteLines = map(lambda x:len(x.contents.split('\n')), notes)
print "Ave #Chars:", mean(noteLen), ", Ave Var:", variance(noteLen)
print "Ave #Lines:", mean(noteLines), ", Ave Var:", variance(noteLines)
def printBasicNoteStats(user):
notes = Note.objects.filter(owner=user)
print "# Notes:", notes.count()
noteLen = map(lambda x: len(x.contents), notes)
noteLines = map(lambda x: len(x.contents.split('\n')), notes)
print "Ave #Chars:", mean(noteLen), ", Ave Var:", variance(noteLen)
print "Ave #Lines:", mean(noteLines), ", Ave Var:", variance(noteLines)
def user_mean_dead(userid):
global _walk_cache
if userid not in _walk_cache:
_walk_cache[userid] = userWalk(User.objects.filter(id=userid)[0])
totDays,activeDays,adeadtotal,adeadgained = _walk_cache[userid]
#for alive,dead in adeadtotal: print alive,",",dead
return ca.make_feature('mean_alive_notes',mean( [dead for alive,dead in adeadtotal ] ))
def user_mean_day_del(userid):
global _walk_cache
if userid not in _walk_cache:
_walk_cache[userid] = userWalk(User.objects.filter(id=userid)[0])
totDays, activeDays, adeadtotal, adeadgained = _walk_cache[userid]
return ca.make_feature('mean_del_notes_per_day',
mean([dead for alive, dead in adeadgained]))
def user_mean_dead(userid):
global _walk_cache
if userid not in _walk_cache:
_walk_cache[userid] = userWalk(User.objects.filter(id=userid)[0])
totDays, activeDays, adeadtotal, adeadgained = _walk_cache[userid]
#for alive,dead in adeadtotal: print alive,",",dead
return ca.make_feature('mean_alive_notes',
mean([dead for alive, dead in adeadtotal]))
def user_mean_change(userid):
global _walk_cache
if userid not in _walk_cache:
_walk_cache[userid] = userWalk(User.objects.filter(id=userid)[0])
totDays,activeDays,adeadtotal,adeadgained = _walk_cache[userid]
delta = [(new - dead) for new,dead in adeadgained]
#print [(new,dead) for new,dead in adeadgained]
#print delta
return ca.make_feature('mean_change', mean(delta))
def user_mean_change(userid):
global _walk_cache
if userid not in _walk_cache:
_walk_cache[userid] = userWalk(User.objects.filter(id=userid)[0])
totDays, activeDays, adeadtotal, adeadgained = _walk_cache[userid]
delta = [(new - dead) for new, dead in adeadgained]
#print [(new,dead) for new,dead in adeadgained]
#print delta
return ca.make_feature('mean_change', mean(delta))
def user_mean_day_del(userid):
global _walk_cache
if userid not in _walk_cache:
_walk_cache[userid] = userWalk(User.objects.filter(id=userid)[0])
totDays,activeDays,adeadtotal,adeadgained = _walk_cache[userid]
return ca.make_feature('mean_del_notes_per_day',mean([dead for alive,dead in adeadgained ] ))
def var(v):
ev = mean(v)
return sum([(x-ev)**2 for x in v ])/(1.0*len(v)-1)
def s(counts):
print "min:%g max:%g mode:%g mean:%g median:%g var:%g" % (min(counts),max(counts),mode(counts),mean(counts),median(counts),var(counts))
return (min(counts),max(counts),mode(counts),mean(counts),median(counts),var(counts))
def var(v):
ev = mean(v)
return sum([(x - ev)**2 for x in v]) / (1.0 * len(v) - 1)
def s(counts):
print "min:%g max:%g mode:%g mean:%g median:%g var:%g" % (
min(counts), max(counts), mode(counts), mean(counts), median(counts),
var(counts))
return (min(counts), max(counts), mode(counts), mean(counts),
median(counts), var(counts))
