def MulOp(x, y): # (* x = x * y *)
global RH
if (x.mode == ORB.Const) and (y.mode == ORB.Const):
x.a = x.a * y.a
elif (y.mode == ORB.Const) and (y.a >= 2) and (log2(y.a) == 1):
load(x)
Put1(Lsl, x.r, x.r, log2(y.a))
elif y.mode == ORB.Const:
load(x)
Put1a(Mul, x.r, x.r, y.a)
elif (x.mode == ORB.Const) and (x.a >= 2) and (log2(x.a) == 1):
load(y)
Put1(Lsl, y.r, y.r, log2(x.a))
x.mode = Reg
x.r = y.r
elif x.mode == ORB.Const:
load(y)
Put1a(Mul, y.r, y.r, x.a)
x.mode = Reg
x.r = y.r
else:
load(x)
load(y)
Put0(Mul, RH - 2, x.r, y.r)
RH -= 1
x.r = RH - 1
def _main(f):
"""
>>> _main('abaab')
unigram: nbits < 7.906891
bigram: nbits < 7.584963
>>> _main('bababa')
unigram: nbits < 9.129283
bigram: nbits < 6.584963
"""
text = ''.join(l.strip() for l in f)
A = len(set(text))
k_unigram = defaultdict(int)
logprob_unigram = 0
for (n, ai) in enumerate(text):
p = (k_unigram[ai] + 1) / (n + A)
assert 0 <= p <= 1, 'probabilities must be in [0,1]'
logprob_unigram += log2(p)
k_unigram[ai] += 1
print 'unigram: nbits < %f' % (2 - logprob_unigram)
k_bigram = defaultdict(int)
njs = defaultdict(int)
logprob_bigram = log2(1.0 / A)
for (aj, ai) in bigrams(text):
kij = k_bigram[(ai, aj)]
nj = njs[aj]
p = (kij + 1) / (nj + A)
assert 0 <= p <= 1, 'probabilities must be in [0,1]'
logprob_bigram += log2(p)
k_bigram[(ai, aj)] += 1
njs[aj] += 1
print 'bigram: nbits < %f' % (2 - logprob_bigram)
def MulOp(x, y): # (* x = x * y *)
global RH
if (x.mode == ORB.Const) and (y.mode == ORB.Const):
x.a = x.a * y.a
elif (y.mode == ORB.Const) and (y.a >= 2) and (log2(y.a) == 1):
load(x)
Put1(Lsl, x.r, x.r, log2(y.a))
elif y.mode == ORB.Const:
load(x)
Put1a(Mul, x.r, x.r, y.a)
elif (x.mode == ORB.Const) and (x.a >= 2) and (log2(x.a) == 1):
load(y)
Put1(Lsl, y.r, y.r, log2(x.a))
x.mode = Reg
x.r = y.r
elif x.mode == ORB.Const:
load(y)
Put1a(Mul, y.r, y.r, x.a)
x.mode = Reg
x.r = y.r
else:
load(x)
load(y)
Put0(Mul, RH-2, x.r, y.r)
RH -= 1
x.r = RH-1
def setup(label, ps):
progress(label, "starting setup")
try:
with open(jar(label), "rb") as brine:
ps = pickle.load(brine)
except IOError:
progress(label, "generating distributions")
secret_l2_dist = ps.secret_l2_distribution()
progress(label, "done secret l2 dist")
query_l2_dist = ps.query_l2_distribution()
progress(label, "done query l2 dist")
e3_dist = ps.e3_distribution()
progress(label, "done e3 dist")
one_shot_dist = ps.one_shot_distribution()
progress(label, "done one shot dist")
f = tail_probability(one_shot_dist, ps.threshold())
p(label, "oneshot", float(-log2(f)))
p(label, "max_abs_e3", max(dist_absolute(e3_dist)))
with open(jar(label), "wb") as brine:
pickle.dump(ps, brine)
progress(label, "done setup")
def volume_estimate(ps, query_l2_dist, alpha, optimize_e3=False):
dim = ps.inner_product_dimension()
threshold = ps.threshold()
abs_e3_dist = dist_absolute(ps.e3_distribution())
def crunch(cutoff):
e3_cutoff = sorted(abs_e3_dist)[cutoff]
t = threshold - e3_cutoff
f = partial(queries, dim=dim, t=t, alpha=alpha)
result = expectation(query_l2_dist, f)
return result
cutoff = sorted(abs_e3_dist).index(min(top_quantile(abs_e3_dist, 100)))
result = crunch(cutoff)
e3_cutoff = sorted(abs_e3_dist)[cutoff]
if optimize_e3: # Optimize e3_cutoff
step = 16 #XXX: arbitrary
while step > 0:
decreasing = True
while (len(abs_e3_dist) + cutoff - step > 0) and decreasing:
candidate = crunch(cutoff - step)
decreasing = candidate < result
if decreasing:
result = candidate
e3_cutoff = sorted(abs_e3_dist)[cutoff - step]
cutoff -= step
step //= 2
result *= 2 # Account for absolute value bars
return -log2(result), e3_cutoff
def do(label, lgsq, lgeq):
with open(jar(label), "rb") as brine:
ps = pickle.load(brine)
progress(label, "starting s/{}/e/{}".format(lgsq, lgeq))
f = tail_probability(ps.one_shot_s_quantile(lgsq), ps.threshold())
p(label, "s/{}/e/{}/cost".format(lgsq, lgeq), float(-log2(f)))
progress(label, "done s/{}/e/{}".format(lgsq, lgeq))
def calc_gain(lNums, p_iSum=None):
if p_iSum is None: p_iSum = sum(lNums)
fSum = float(p_iSum)
fResult = 0
for num in lNums:
value = (num / fSum)
fResult += -value * log2(value)
return fResult
def DivOp(op, x, y): # (* x = x op y *)
global RH
e = log2(y.a) # note: shadows math.e
if op == ORS.div:
if (x.mode == ORB.Const) and (y.mode == ORB.Const):
if y.a > 0:
x.a = x.a / y.a
else:
ORS.Mark("bad divisor")
elif (y.mode == ORB.Const) and (y.a >= 2) and (e == 1):
load(x)
Put1(Asr, x.r, x.r, e)
elif y.mode == ORB.Const:
if y.a > 0:
load(x)
Put1a(Div, x.r, x.r, y.a)
else:
ORS.Mark("bad divisor")
else:
load(y)
if check:
Trap(LE, 6)
load(x)
Put0(Div, RH - 2, x.r, y.r)
RH -= 1
x.r = RH - 1
else: # (*op == ORS.mod*)
if (x.mode == ORB.Const) and (y.mode == ORB.Const):
if y.a > 0:
x.a = x.a % y.a
else:
ORS.Mark("bad modulus")
elif (y.mode == ORB.Const) and (y.a >= 2) and (e == 1):
load(x)
if e <= 16:
Put1(And, x.r, x.r, y.a - 1)
else:
Put1(Lsl, x.r, x.r, 32 - e)
Put1(Ror, x.r, x.r, 32 - e)
elif y.mode == ORB.Const:
if y.a > 0:
load(x)
Put1a(Div, x.r, x.r, y.a)
Put0(Mov + U, x.r, 0, 0)
else:
ORS.Mark("bad modulus")
else:
load(y)
if check:
Trap(LE, 6)
load(x)
Put0(Div, RH - 2, x.r, y.r)
Put0(Mov + U, RH - 2, 0, 0)
RH -= 1
x.r = RH - 1
def DivOp(op, x, y): # (* x = x op y *)
global RH
e = log2(y.a) # note: shadows math.e
if op == ORS.div:
if (x.mode == ORB.Const) and (y.mode == ORB.Const):
if y.a > 0:
x.a = x.a / y.a
else:
ORS.Mark("bad divisor")
elif (y.mode == ORB.Const) and (y.a >= 2) and (e == 1):
load(x)
Put1(Asr, x.r, x.r, e)
elif y.mode == ORB.Const:
if y.a > 0:
load(x)
Put1a(Div, x.r, x.r, y.a)
else:
ORS.Mark("bad divisor")
else:
load(y);
if check:
Trap(LE, 6)
load(x)
Put0(Div, RH-2, x.r, y.r)
RH -= 1
x.r = RH-1
else: # (*op == ORS.mod*)
if (x.mode == ORB.Const) and (y.mode == ORB.Const):
if y.a > 0:
x.a = x.a % y.a
else:
ORS.Mark("bad modulus")
elif (y.mode == ORB.Const) and (y.a >= 2) and (e == 1):
load(x);
if e <= 16:
Put1(And, x.r, x.r, y.a-1)
else:
Put1(Lsl, x.r, x.r, 32-e)
Put1(Ror, x.r, x.r, 32-e)
elif y.mode == ORB.Const:
if y.a > 0:
load(x)
Put1a(Div, x.r, x.r, y.a)
Put0(Mov+U, x.r, 0, 0)
else:
ORS.Mark("bad modulus")
else:
load(y);
if check:
Trap(LE, 6)
load(x)
Put0(Div, RH-2, x.r, y.r)
Put0(Mov+U, RH-2, 0, 0)
RH -= 1
x.r = RH-1
def __init__(self, n, q=None, improper=False):
self.n = n
if q is None:
self.q = int(2**round(0.5 + 3.5 + log2(n)))
else:
self.q = q
self.improper = improper
self.cache_dist_1 = None
self.cache_dist_2 = None
self.cache_dist_3 = None
def run(settings, load_cb=None):
global _running
_running = True
# actual init of the UI is done via this callback,
# which is posted to the MessageLoop at the end of this function
def do_init():
# create them...
resources = Resources(settings, ndbg.get_basedir())
global _mc
mw = MainWindow(settings, resources)
def run_load_cb():
log2("UI init: running on_load callback")
if load_cb:
load_cb(_mc)
return False # ensure the timeout is a one-time thing
def on_ready(*args):
log2("UI init: window shown, scheduling load in 200ms")
MessageLoop.add_delayed_message(run_load_cb, 200)
if load_cb:
mw.connect('show', on_ready)
settings.set_delayed_save(True)
_mc = MainControl(settings, mw)
# Go! :)
MessageLoop.add_message(do_init)
MessageLoop.run()
# cleanup
_running = False
if _mc:
_mc.destroy()
log2("ui.run done")
def run(settings, load_cb=None):
global _running
_running = True
# actual init of the UI is done via this callback,
# which is posted to the MessageLoop at the end of this function
def do_init():
# create them...
resources = Resources(settings, ndbg.get_basedir())
global _mc
mw = MainWindow(settings, resources)
def run_load_cb():
log2("UI init: running on_load callback")
if load_cb:
load_cb(_mc)
return False # ensure the timeout is a one-time thing
def on_ready(*args):
log2("UI init: window shown, scheduling load in 200ms")
MessageLoop.add_delayed_message(run_load_cb, 200)
if load_cb:
mw.connect('show', on_ready)
settings.set_delayed_save(True)
_mc = MainControl(settings, mw)
# Go! :)
MessageLoop.add_message(do_init)
MessageLoop.run()
# cleanup
_running = False
if _mc:
_mc.destroy()
log2("ui.run done")
def setup(label, ps):
progress(label, "starting setup")
try:
with open(jar(label), "rb") as brine:
ps = pickle.load(brine)
except IOError:
progress(label, "generating distributions")
secret_l2_dist = ps.secret_l2_distribution()
query_l2_dist = ps.query_l2_distribution()
one_shot_dist = ps.one_shot_distribution()
f = tail_probability(one_shot_dist, ps.threshold())
p(label, "oneshot", float(-log2(f)))
with open(jar(label), "wb") as brine:
pickle.dump(ps, brine)
def log_cap(dim, theta):
return -0.5 * log2(2 * mp.pi * dim) - log2(
mp.cos(theta)) + (dim - 1) * log2(mp.sin(theta))
def on_ready(*args):
log2("UI init: window shown, scheduling load in 200ms")
MessageLoop.add_delayed_message(run_load_cb, 200)
def run_load_cb():
log2("UI init: running on_load callback")
if load_cb:
load_cb(_mc)
return False # ensure the timeout is a one-time thing
import util
if __name__ == '__main__':
print(util.log2(1024))
util.test_util()
def run_load_cb():
log2("UI init: running on_load callback")
if load_cb:
load_cb(_mc)
return False # ensure the timeout is a one-time thing
def on_ready(*args):
log2("UI init: window shown, scheduling load in 200ms")
MessageLoop.add_delayed_message(run_load_cb, 200)
