def test_profile_ct_bincounts(self):
""" Test the ability of sortseq_tools.profile_ct to count frequencies
"""
print '\nIn test_profile_ct_bincounts...'
library_files = glob.glob(self.input_dir+'library_*.txt')
library_files += glob.glob(self.input_dir+'dataset_*.txt')
good_bin_num = 2
bad_bin_num = 5
for file_name in library_files:
print '\t%s ='%file_name,
description = file_name.split('_')[-1].split('.')[0]
executable = lambda:\
profile_ct.main(io.load_dataset(file_name),bin=good_bin_num)
print '(bin=%d)'%good_bin_num,
# If bad or library, then profile_ct.main should raise SortSeqError
if ('_bad' in file_name) or ('library' in file_name):
try:
self.assertRaises(SortSeqError,executable)
print 'badtype,',
except:
print 'good (ERROR).'
raise
# If good, then profile_ct.main should produce a valid df
elif ('_good' in file_name) or ('dataset' in file_name):
try:
df = executable()
qc.validate_profile_ct(df)
out_file = self.output_dir+\
'profile_ct_bin_%s.txt'%description
io.write(df,out_file)
io.load_profile_ct(out_file)
print 'good,',
except:
print 'bad (ERROR).'
raise
# There are no other options
else:
raise SortSeqError('Unrecognized class of file_name.')
# Should always raise an error if bin num is too large
executable = lambda:\
profile_ct.main(io.load_dataset(file_name),bin=bad_bin_num)
print '(bin=%d)'%bad_bin_num,
try:
self.assertRaises(SortSeqError,executable)
print 'badtype.'
except:
print 'good (ERROR).'
raise
def test_profile_ct_totalcounts(self):
""" Test the ability of sortseq_tools.profile_ct to count frequencies based on total count values
"""
print '\nIn test_profile_ct_totalcounts...'
library_files = glob.glob(self.input_dir+'library_*.txt')
library_files += glob.glob(self.input_dir+'dataset_*.txt')
for file_name in library_files:
print '\t%s ='%file_name,
description = file_name.split('_')[-1].split('.')[0]
executable = lambda: profile_ct.main(io.load_dataset(file_name))
# If good, then profile_ct.main should produce a valid df
if '_good' in file_name:
try:
df = executable()
qc.validate_profile_ct(df)
out_file = self.output_dir+\
'profile_ct_total_%s.txt'%description
io.write(df,out_file)
io.load_profile_ct(out_file)
print 'good.'
except:
print 'bad (ERROR).'
raise
# If bad, then profile_ct.main should raise SortSeqError
elif '_bad' in file_name:
try:
self.assertRaises(SortSeqError,executable)
print 'badtype.'
except:
print 'good (ERROR).'
raise
# There are no other options
else:
raise SortSeqError('Unrecognized class of file_name.')
