def decrypt( self, data, base=0x1000084 ):
if isinstance(data, (ObjectWithStreamBigEndian, ObjectWithStream)):
data = data.getRawData()
data = scipy.fromstring(data, scipy.uint16)
data.byteswap(True)
data = self.decryptChunk(data, base)
data.byteswap(True)
data = scipy.bitwise_xor(data, data[-1])
return data.tostring()
def create_diploid_dataset(call_method_id=76,
file_name='/tmp/test.csv',
coding_type='normal'):
#Load parent list
parents = []
with open(env.env['data_dir'] + 'heterozygous_genotypes.csv') as f:
f.next()
for l in f:
parents.append(map(str.strip, l.split(',')))
snpsd = dp.load_snps_call_method(call_method_id)
l = zip(snpsd.accessions, range(len(snpsd.accessions)))
l.sort()
l = map(list, zip(*l))
acc_list = l[0]
orders = l[1]
sds = []
for i, sd in enumerate(snpsd.snpsDataList):
snps = sp.array(sd.snps, dtype='int8')
snps_list = []
p_list = []
for ps in parents:
f_id = bisect.bisect(acc_list, ps[0]) - 1
m_id = bisect.bisect(acc_list, ps[1]) - 1
if acc_list[f_id] == ps[0] and acc_list[m_id] == ps[1]:
f_gt = snps[:, orders[f_id]].flatten()
m_gt = snps[:, orders[m_id]].flatten()
if coding_type == 'normal':
o_gt = f_gt + m_gt
elif coding_type == 'dominant':
o_gt = sp.bitwise_xor(f_gt, m_gt)
snps_list.append(o_gt)
p_list.append('%s_%s' % (ps[0], ps[1]))
snps_list = sp.transpose(sp.array(snps_list, dtype='int8'))
snps = []
for s in snps_list:
snps.append(s)
sds.append(
snpsdata.SNPsData(snps,
sd.positions,
accessions=p_list,
chromosome=i + 1))
sd = snpsdata.SNPsDataSet(sds, [1, 2, 3, 4, 5])
sd.writeToFile(file_name)
def _energy_func(self, x, **kwargs):
x_signs = sp.signbit(x)
return sp.vstack((sp.bitwise_xor(x_signs[:-1], x_signs[1:]), [False] * x.shape[1]))
def _energy_func(self, x, **kwargs):
x_signs = sp.signbit(x)
return sp.vstack((sp.bitwise_xor(x_signs[:-1],
x_signs[1:]), [False] * x.shape[1]))