def convert_tables(self):
"""
Based on the confidence score, convert xmap file and two corresponding cmap files
into "pandas table".
"""
pd.set_option('display.width',200)
with open ('%s.table' % self.name, 'a') as xmap_table:
with open (self.xmap) as xmap:
for line in xmap:
if line.startswith('#h'):
hearder = line[3:]
xmap_table.write(hearder)
if line[0]!='#':
xmap_table.write(line)
with open ('%s.rtable' % self.name, 'a') as rcmap_table:
with open (self.rcmap) as rcmap:
for line in rcmap:
if line.startswith('#h'):
hearder = line[3:]
rcmap_table.write(hearder)
if line[0]!='#':
rcmap_table.write(line)
with open ('%s.qtable' % self.name, 'a') as qcmap_table:
with open (self.qcmap) as qcmap:
for line in qcmap:
if line.startswith('#h'):
hearder = line[3:]
qcmap_table.write(hearder)
if line[0]!='#':
qcmap_table.write(line)
self.XmapTable = pd.read_table('%s.table' % self.name)
headers_x = ['RefContigID','RefStartPos','RefEndPos','QryContigID','QryStartPos',
'QryEndPos','Orientation', 'Confidence','QryLen','RefLen', 'Alignment']
self.filtered_XmapTable = self.XmapTable[self.XmapTable['Confidence']>=self.confidence_score][headers_x].reset_index(drop=True)
headers_r = ['CMapId','ContigLength','NumSites','SiteID','Position']
self.RcmapTable = pd.read_table('%s.rtable' % self.name)[headers_r]
headers_q = ['CMapId','ContigLength','NumSites','SiteID','Position','Coverage']
self.QcmapTable = pd.read_table('%s.qtable' % self.name)[headers_q]
os.remove('%s.table' % self.name)
os.remove('%s.rtable' % self.name)
os.remove('%s.qtable' % self.name)
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