def final_4d_metric(blocks_shifts_x):
count = 0
start = 0
#embedding = numpy.zeros() #TODO : Preallocate memory for the embedding
embedding_size = 4 * len(blocks_shifts_x) * sum(
[R_vals[i] * possible_s[i] for i in xrange(len(possible_s))])
embedding = numpy.zeros((embedding_size))
for block_id in xrange(len(blocks_shifts_x)):
for s_id in xrange(len(blocks_shifts_x[block_id])):
count += 1
#print count
s = possible_s[s_id]
I_arr = random_s_block[block_id][s_id]
r = len(I_arr)
for u in xrange(r):
'''
psi_u_all_v = []
STR = []
for j in xrange(s):
for ri in I_arr[u]:
try:
STR.append(blocks_shifts_x[block_id][s_id][j][ri])
psi_u_all_v.append(''.join(STR))
except:
print j, ri
raise
'''
psi_u_all_v = numpy.bincount([
randomness.custom_hash(
s, u, ''.join([
blocks_shifts_x[block_id][s_id][j][ri]
for ri in I_arr[u]
])) for j in xrange(s)
])[1:] * 1.0 / (2 * r)
embedding[start:(start + psi_u_all_v.shape[0])] = psi_u_all_v
start += 4 * s
'''
if count == 1:
embedding = numpy.zeros((4*s))
embedding[:psi_u_all_v.shape[0]] = psi_u_all_v
else:
temp = numpy.zeros((4*s))
temp[:psi_u_all_v.shape[0]] = psi_u_all_v
embedding = numpy.concatenate((embedding, temp))
'''
return embedding
def final_4d_metric(blocks_shifts_x):
count = 0
start = 0
#embedding = numpy.zeros() #TODO : Preallocate memory for the embedding
embedding_size = 4*len(blocks_shifts_x)*sum([R_vals[i]*possible_s[i]
for i in xrange(len(possible_s))])
embedding = numpy.zeros((embedding_size))
for block_id in xrange(len(blocks_shifts_x)):
for s_id in xrange(len(blocks_shifts_x[block_id])):
count += 1
#print count
s = possible_s[s_id]
I_arr = random_s_block[block_id][s_id]
r = len(I_arr)
for u in xrange(r):
'''
psi_u_all_v = []
STR = []
for j in xrange(s):
for ri in I_arr[u]:
try:
STR.append(blocks_shifts_x[block_id][s_id][j][ri])
psi_u_all_v.append(''.join(STR))
except:
print j, ri
raise
'''
psi_u_all_v = numpy.bincount([
randomness.custom_hash(s, u, ''.join([blocks_shifts_x[block_id][s_id][j][ri]
for ri in I_arr[u]]))
for j in xrange(s)])[1:] * 1.0 / (2 * r)
embedding[start:(start+psi_u_all_v.shape[0])] = psi_u_all_v
start += 4*s
'''
if count == 1:
embedding = numpy.zeros((4*s))
embedding[:psi_u_all_v.shape[0]] = psi_u_all_v
else:
temp = numpy.zeros((4*s))
temp[:psi_u_all_v.shape[0]] = psi_u_all_v
embedding = numpy.concatenate((embedding, temp))
'''
return embedding
def final_4d_metric(blocks_shifts_x, R_vals, possible_s, random_s_block):
count = 0
start = 0
embedding_size = 4 * len(blocks_shifts_x) * sum([R_vals[i] * possible_s[i]
for i in xrange(len(possible_s))])
embedding = numpy.zeros((embedding_size))
for block_id in xrange(len(blocks_shifts_x)):
for s_id in xrange(len(blocks_shifts_x[block_id])):
count += 1
s = possible_s[s_id]
I_arr = random_s_block[block_id][s_id]
r = len(I_arr)
for u in xrange(r):
psi_u_all_v = numpy.bincount([randomness.custom_hash(s, u, ''.join([blocks_shifts_x[block_id][s_id][
j][ri] for ri in I_arr[u]])) for j in xrange(s)])[1:] * 1.0 / (2 * r)
embedding[start:(start + psi_u_all_v.shape[0])] = psi_u_all_v
start += 4 * s
return embedding
def final_4d_metric(blocks_shifts_x):
count = 0
start = 0
#embedding = numpy.zeros() #TODO : Preallocate memory for the embedding
embedding_size = 4*len(blocks_shifts_x)*sum([R_vals[i]*possible_s[i]
for i in xrange(len(possible_s))])
embedding = numpy.zeros((embedding_size))
for block_id in xrange(len(blocks_shifts_x)):
for s_id in xrange(len(blocks_shifts_x[block_id])):
count += 1
#print count
s = possible_s[s_id]
I_arr = random_s_block[block_id][s_id]
r = len(I_arr)
for u in xrange(r):
psi_u_all_v = numpy.bincount([
randomness.custom_hash(s, u, ''.join([blocks_shifts_x[block_id][s_id][j][ri]
for ri in I_arr[u]]))
for j in xrange(s)])[1:] * 1.0 / (2 * r)
embedding[start:(start+psi_u_all_v.shape[0])] = psi_u_all_v
start += 4*s
return embedding
