def test_write_adder(self, qty=1000):
for i in range(qty):
a = Hardlocation()
b = Bitstring()
a.write(b)
self.assertEqual([ b.bitsign(i) for i in xrange(sdm.get_dimension()) ], a.adder)
a.write(b)
self.assertEqual([ 2*b.bitsign(i) for i in xrange(sdm.get_dimension()) ], a.adder)
def test_write_adder(self, qty=1000):
for i in range(qty):
a = Hardlocation()
b = Bitstring()
a.write(b)
self.assertEqual([ b.bitsign(i) for i in xrange(sdm.get_dimension()) ], a.adder)
a.write(b)
self.assertEqual([ 2*b.bitsign(i) for i in xrange(sdm.get_dimension()) ], a.adder)
def sample_radius(rounds=1, verbose=0):
if verbose > 0:
print 'Initializing SDM'
sdm.initialize()
dimension = sdm.get_dimension()
v = []
for i in xrange(rounds):
if verbose > 0:
print 'Round #%d' % (i+1)
addr = Bitstring()
dist = sdm.distance(addr)
if verbose > 0:
print ' Processing results'
w = [0]*(dimension+1)
for d in dist:
w[d] += 1
u = [0]*(dimension+1)
for d, n in enumerate(w):
for j in range(d, dimension+1):
u[j] += n
v.append(u)
sdm.free()
return v
def test_mean_distance(self, qty=10):
#sdm.initialize()
for i in range(qty):
a = Bitstring()
arr = array(sdm.distance(a))
value = abs(arr.mean()-sdm.get_dimension()/2.)/arr.std()
self.assertTrue(value <= 1.5)
def sample_radius(rounds=1, verbose=0):
if verbose > 0:
print 'Initializing SDM'
sdm.initialize()
dimension = sdm.get_dimension()
v = []
for i in xrange(rounds):
if verbose > 0:
print 'Round #%d' % (i + 1)
addr = Bitstring()
dist = sdm.distance(addr)
if verbose > 0:
print ' Processing results'
w = [0] * (dimension + 1)
for d in dist:
w[d] += 1
u = [0] * (dimension + 1)
for d, n in enumerate(w):
for j in range(d, dimension + 1):
u[j] += n
v.append(u)
sdm.free()
return v
def test_random_swap(self, qty=1000):
for i in range(qty):
a = Bitstring()
b = a.copy()
self.assertEqual(a.distance_to(b), 0)
dist = random.randint(0, sdm.get_dimension())
b.bitrandomswap(dist)
self.assertEqual(a.distance_to(b), dist)
def sample():
print 'Initializing SDM'
sdm.initialize()
dimension = sdm.get_dimension()
addr = Bitstring()
dist = sdm.distance(addr)
sdm.free()
return dist
def sample():
print 'Initializing SDM'
sdm.initialize()
dimension = sdm.get_dimension()
addr = Bitstring()
dist = sdm.distance(addr)
sdm.free()
return dist
def test_bitset(self):
dim = sdm.get_dimension()
a = Bitstring(zero=True)
for i in range(dim):
a.bitset(i)
s = str(a)
s1 = sum([ 1 for x in s[:dim-i-1] if x == '0' ])
s2 = sum([ 1 for x in s[-i-1:] if x == '1' ])
self.assertEqual(s1+s2, dim)
def test_uniform_distribution(qty=10000):
n = sdm.get_dimension()
v = [0]*n
for i in xrange(qty):
a = Bitstring()
for j in range(n):
v[j] += a.bitsign(j)
import pylab
pylab.hist(v, bins=15)
return v
def test_uniform_distribution(qty=10000):
n = sdm.get_dimension()
v = [0] * n
for i in xrange(qty):
a = Bitstring()
for j in range(n):
v[j] += a.bitsign(j)
import pylab
pylab.hist(v, bins=15)
return v
def table_7_1():
n = sdm.get_dimension()
a = Bitstring()
v = []
for i in range(550):
b = a.copy()
b.bitrandomswap(i)
v.append([ i, sdm.thread_radius_count_intersect(a, b) ])
print i
sys.stdout.flush()
return v
def table_7_1():
n = sdm.get_dimension()
a = Bitstring()
v = []
for i in range(550):
b = a.copy()
b.bitrandomswap(i)
v.append([i, sdm.thread_radius_count_intersect(a, b)])
print i
sys.stdout.flush()
return v
def scan_for_distances(numwrites=1):
import time, cPickle;
#Configure execution
numwrites_string = '_x_at_x_'+str(numwrites)+'_writes'
sdm.initialize()
v = sdm.Bitstring()
for i in range(numwrites):
sdm.thread_write(v,v)
for i in range (1000,2000,1000):
print 'Registering '+str(i)+' new items in SDM'
#add 1000 itens to memory
mem_write_x_at_x(1000)
print 'Computing the distances to these items'
a = sdm_utils.critical_distance2(0, sdm.get_dimension(), 1, v, iterated_reading=6, read=sdm.thread_read_cubed,debug=0)
#save new distance values in a
picklename = 'N=256_iter_read=2_'+str(i)+'saved items'+numwrites_string+'_DrK_cubed.cPickle'
cPickle.dump(a, open (picklename, 'wb'))
print 'saved '+picklename
sdm.free()
def chart_sample_radius(rounds=1, verbose=0):
import pylab
data = sample_radius(rounds=rounds, verbose=verbose)
#for i in range(sdm.get_dimension()+1):
# data[-1][i] += 100000
dist = range(sdm.get_dimension()+1)
args = []
kwargs = { 'linewidth': 1.0 }
for v in data:
args.extend([ dist, v, 'k-' ])
pylab.plot(*args, **kwargs)
pylab.xlabel('distance')
pylab.ylabel('qty of hardlocations')
pylab.title('Qty of hardlocations around random address')
pylab.grid(True)
pylab.show()
arr = array(zip(*data))
stat = [ (i, m, v) for i, (m, v) in enumerate(zip(arr.mean(axis=1), arr.std(axis=1))) ]
return data, stat
def chart_sample_radius(rounds=1, verbose=0):
import pylab
data = sample_radius(rounds=rounds, verbose=verbose)
#for i in range(sdm.get_dimension()+1):
# data[-1][i] += 100000
dist = range(sdm.get_dimension() + 1)
args = []
kwargs = {'linewidth': 1.0}
for v in data:
args.extend([dist, v, 'k-'])
pylab.plot(*args, **kwargs)
pylab.xlabel('distance')
pylab.ylabel('qty of hardlocations')
pylab.title('Qty of hardlocations around random address')
pylab.grid(True)
pylab.show()
arr = array(zip(*data))
stat = [(i, m, v)
for i, (m, v) in enumerate(zip(arr.mean(axis=1), arr.std(axis=1)))]
return data, stat