def test_aa():
print '\n START TEST AMINO-ACIDS'
print ' **********************\n\n'
errors = []
data = '/home/francisco/Box/utils/pmodeltest/examples/protein.phy'
models = ['LG', 'WAG', 'JTT', 'MtREV', 'Dayhoff', 'DCMut',
'RtREV', 'CpREV', 'VT', 'Blosum62', 'MtMam',
'MtArt', 'HIVw', 'HIVb']
job_list = pmt.get_job_list(data, models, speed=True, protein=True,
verbose=False) # here verbose prints all command lines
job_list = pmt.run_jobs(job_list, nprocs=2, refresh=0.01)
job_list = pmt.parse_jobs(job_list, data)
pmt.clean_all (job_list, data)
job_list, ord_aic = pmt.aic_calc(job_list, True, verbose=True)
if not ord_aic == ['Dayhoff+G','DCMut+G','Dayhoff+I+G','DCMut+I+G',
'Dayhoff+I','DCMut+I','Dayhoff+G+F','DCMut+G+F',
'LG+G+F','Dayhoff+I+G+F','DCMut+I+G+F','LG+I+G+F',
'Dayhoff+I+F','DCMut+I+F','LG+I+F','WAG+G','WAG+I+G',
'WAG+I','Dayhoff','DCMut','WAG+G+F','RtREV+G+F','LG+G',
'WAG+I+G+F','WAG+I+F','RtREV+I+G+F','LG+I+G','RtREV+I+F',
'JTT+G+F','JTT+I+G+F','LG+I','JTT+I+F','JTT+G','JTT+I+G',
'Dayhoff+F','DCMut+F','CpREV+G+F','LG+F','JTT+I',
'CpREV+I+G+F','CpREV+I+F','WAG','WAG+F','MtArt+G+F',
'MtArt+I+G+F','RtREV+F','MtREV+G+F','JTT+F','MtREV+I+G+F',
'LG','HIVb+G+F','HIVb+I+G+F','MtREV+I+F','Blosum62+G+F',
'MtArt+I+F','JTT','Blosum62+I+G+F','Blosum62+I+F','CpREV+F',
'RtREV+G','HIVb+I+F','RtREV+I+G','CpREV+G','Blosum62+G',
'VT+G','RtREV+I','CpREV+I+G','Blosum62+I+G','VT+G+F',
'VT+I+G','CpREV+I','Blosum62+I','VT+I+G+F','VT+I','VT+I+F',
'MtMam+G+F','MtMam+I+G+F','Blosum62+F','MtREV+F','Blosum62',
'RtREV','MtMam+I+F','VT+F','VT','CpREV','MtArt+F','HIVb+F',
'HIVb+G','HIVb+I+G','HIVb+I','HIVw+G+F','HIVw+I+G+F',
'MtMam+F','HIVw+I+F','HIVb','MtREV+G','MtREV+I+G','MtArt+G','MtArt+I+G','MtREV+I','HIVw+F','MtArt+I','MtMam+G','MtMam+I+G','MtREV','HIVw+G','HIVw+I+G','MtMam+I','HIVw+I','MtArt','HIVw','MtMam']:
print 'Test ordering models: ERROR'
errors.append('ordering models')
else:
print 'Test ordering models: OK'
job_list = pmt.re_run(job_list, data, cutoff=0.95, refresh=0.01, nprocs=2, verbose=True)
job_list = pmt.parse_jobs(job_list, data)
pmt.clean_all (job_list, data)
if sorted(job_list.keys()) == sorted(['Dayhoff+G', 'DCMut+I+G', 'DCMut+G', 'Dayhoff+I+G']):
print 'Test better models: OK'
else:
print 'Test better models: ERROR'
errors.append('better models')
job_list, ord_aic = pmt.aic_calc(job_list, False)
if ord_aic == ['Dayhoff+G', 'DCMut+G', 'Dayhoff+I+G', 'DCMut+I+G']:
print 'Test ordering better models: OK'
else:
print 'Test ordering better models: ERROR'
errors.append('ordering better models')
expected = {'DCMut+G' : 3389.69506,
'DCMut+I+G' : 3391.46964,
'Dayhoff+G' : 3389.14838,
'Dayhoff+I+G': 3390.9257}
for j in expected:
if not round(expected[j],2) == round(job_list[j]['AIC'],2):
print 'Test AIC values: ERROR'
print j, job_list[j]['AIC'], round(job_list[j]['AIC'],2)
errors.append('AIC values')
break
else:
print 'Test AIC values: OK'
tree = pmt.re_run_best(ord_aic[0], job_list[ord_aic[0]]['cmd'], data, verbose=True)
pmt.clean_all ({ord_aic[0]: job_list[ord_aic[0]]}, data)
expected_tree = '((human:0.0563158672,(rat:0.2056794657,rabbit:0.0839307491)0.7670000000:0.0369524233)0.6450000000:0.0289065340,marsupial:0.2993530194,cow:0.1082479462);\n'
expected_tree = sub('(:[0-9]+\.[0-9]{3})[0-9]*','\\1', expected_tree)
expected_tree = sub('(\))[0-9]+\.[0-9]*','\\1', expected_tree)
tree = sub('(:[0-9]+\.[0-9]{3})[0-9]*','\\1', tree)
tree = sub('(\))[0-9]+\.[0-9]*','\\1', tree)
if expected_tree == tree:
print 'Testing final topology: OK'
else:
print 'Testing final topology: ERROR'
errors.append('Different final trees')
print expected_tree
print tree
print '\n\n\n TEST PROTEIN FINISHED\n\n'
if errors:
print 'ERROR founds:'
for e in errors:
print e
else:
print ' -> ALL TEST OK'
print '\n\nas last check, have a look to jmodeltest result in test folder'
def test_aa():
print('\n START TEST AMINO-ACIDS')
print(' **********************\n\n')
errors = []
data = 'examples/protein.phy'
models = [
'LG', 'WAG', 'JTT', 'MtREV', 'Dayhoff', 'DCMut', 'RtREV', 'CpREV',
'VT', 'Blosum62', 'MtMam', 'MtArt', 'HIVw', 'HIVb'
]
job_list = pmt.get_job_list(
data, models, speed=True, protein=True,
verbose=False) # here verbose prints all command lines
job_list = pmt.run_jobs(job_list, nprocs=2, refresh=0.01)
job_list = pmt.parse_jobs(job_list, data)
pmt.clean_all(job_list, data)
job_list, ord_aic = pmt.aic_calc(job_list, True, verbose=True)
if not ord_aic == [
'Dayhoff+G', 'DCMut+G', 'Dayhoff+I+G', 'DCMut+I+G', 'Dayhoff+I',
'DCMut+I', 'Dayhoff+G+F', 'DCMut+G+F', 'LG+G+F', 'Dayhoff+I+G+F',
'DCMut+I+G+F', 'LG+I+G+F', 'Dayhoff+I+F', 'DCMut+I+F', 'LG+I+F',
'WAG+G', 'WAG+I+G', 'WAG+I', 'Dayhoff', 'DCMut', 'WAG+G+F',
'RtREV+G+F', 'LG+G', 'WAG+I+G+F', 'WAG+I+F', 'RtREV+I+G+F',
'LG+I+G', 'RtREV+I+F', 'JTT+G+F', 'JTT+I+G+F', 'LG+I', 'JTT+I+F',
'JTT+G', 'JTT+I+G', 'Dayhoff+F', 'DCMut+F', 'CpREV+G+F', 'LG+F',
'JTT+I', 'CpREV+I+G+F', 'CpREV+I+F', 'WAG', 'WAG+F', 'MtArt+G+F',
'MtArt+I+G+F', 'RtREV+F', 'MtREV+G+F', 'JTT+F', 'MtREV+I+G+F',
'LG', 'HIVb+G+F', 'HIVb+I+G+F', 'MtREV+I+F', 'Blosum62+G+F',
'MtArt+I+F', 'JTT', 'Blosum62+I+G+F', 'Blosum62+I+F', 'CpREV+F',
'RtREV+G', 'HIVb+I+F', 'RtREV+I+G', 'CpREV+G', 'Blosum62+G',
'VT+G', 'RtREV+I', 'CpREV+I+G', 'Blosum62+I+G', 'VT+G+F', 'VT+I+G',
'CpREV+I', 'Blosum62+I', 'VT+I+G+F', 'VT+I', 'VT+I+F', 'MtMam+G+F',
'MtMam+I+G+F', 'Blosum62+F', 'MtREV+F', 'Blosum62', 'RtREV',
'MtMam+I+F', 'VT+F', 'VT', 'CpREV', 'MtArt+F', 'HIVb+F', 'HIVb+G',
'HIVb+I+G', 'HIVb+I', 'HIVw+G+F', 'HIVw+I+G+F', 'MtMam+F',
'HIVw+I+F', 'HIVb', 'MtREV+G', 'MtREV+I+G', 'MtArt+G', 'MtArt+I+G',
'MtREV+I', 'HIVw+F', 'MtArt+I', 'MtMam+G', 'MtMam+I+G', 'MtREV',
'HIVw+G', 'HIVw+I+G', 'MtMam+I', 'HIVw+I', 'MtArt', 'HIVw', 'MtMam'
]:
print('Test ordering models: ERROR')
errors.append('ordering models')
else:
print('Test ordering models: OK')
job_list = pmt.re_run(job_list,
data,
cutoff=0.95,
refresh=0.01,
nprocs=2,
verbose=True)
job_list = pmt.parse_jobs(job_list, data)
pmt.clean_all(job_list, data)
if sorted(job_list.keys()) == sorted(
['Dayhoff+G', 'DCMut+I+G', 'DCMut+G', 'Dayhoff+I+G']):
print('Test better models: OK')
else:
print('Test better models: ERROR')
errors.append('better models')
job_list, ord_aic = pmt.aic_calc(job_list, False)
if ord_aic == ['Dayhoff+G', 'DCMut+G', 'Dayhoff+I+G', 'DCMut+I+G']:
print('Test ordering better models: OK')
else:
print('Test ordering better models: ERROR')
errors.append('ordering better models')
expected = {
'DCMut+G': 3389.69506,
'DCMut+I+G': 3391.46964,
'Dayhoff+G': 3389.14838,
'Dayhoff+I+G': 3390.9257
}
for j in expected:
if not round(expected[j], 2) == round(job_list[j]['AIC'], 2):
print('Test AIC values: ERROR')
print(j, job_list[j]['AIC'], round(job_list[j]['AIC'], 2))
errors.append('AIC values')
break
else:
print('Test AIC values: OK')
tree = pmt.re_run_best(ord_aic[0],
job_list[ord_aic[0]]['cmd'],
data,
verbose=True)
pmt.clean_all({ord_aic[0]: job_list[ord_aic[0]]}, data)
expected_tree = '((human:0.0563158672,(rat:0.2056794657,rabbit:0.0839307491)0.7670000000:0.0369524233)0.6450000000:0.0289065340,marsupial:0.2993530194,cow:0.1082479462);\n'
expected_tree = sub('(:[0-9]+\.[0-9]{3})[0-9]*', '\\1', expected_tree)
expected_tree = sub('(\))[0-9]+\.[0-9]*', '\\1', expected_tree)
tree = sub('(:[0-9]+\.[0-9]{3})[0-9]*', '\\1', tree)
tree = sub('(\))[0-9]+\.[0-9]*', '\\1', tree)
if expected_tree == tree:
print('Testing final topology: OK')
else:
print('Testing final topology: ERROR')
errors.append('Different final trees')
print(expected_tree)
print(tree)
print('\n\n\n TEST PROTEIN FINISHED\n\n')
if errors:
print('ERROR founds:')
for e in errors:
print(e)
else:
print(' -> ALL TEST OK')
print('\n\nas last check, have a look to jmodeltest result in test folder')
def test_nt():
print '\n START TEST NUCLEOTIDS'
print ' *********************\n\n'
errors = []
data = '/home/francisco/Box/utils/pmodeltest/examples/dna.phy'
models = ['JC', 'K80', 'TrNef', 'TPM1', 'TPM2', 'TPM3',
'TIM1ef', 'TIM2ef', 'TIM3ef', 'TVMef', 'SYM',
'F81', 'HKY', 'TrN', 'TPM1uf', 'TPM2uf', 'TPM3uf',
'TIM1', 'TIM2', 'TIM3', 'TVM', 'GTR']
job_list = pmt.get_job_list(data, models, speed=True, protein=False,
verbose=False)
job_list = pmt.run_jobs(job_list, nprocs=2, refresh=0.01)
job_list = pmt.parse_jobs(job_list, data)
pmt.clean_all (job_list, data)
job_list, ord_aic = pmt.aic_calc(job_list, True, verbose=True)
if not ord_aic == ['TPM1uf+G+F','TPM3uf+G+F','TIM1+G+F','TPM1uf+I+G+F',
'TIM3+G+F','HKY+G+F','TPM3uf+I+G+F','TVM+G+F',
'TIM1+I+G+F','TrN+G+F','TIM3+I+G+F','HKY+I+G+F',
'TPM2uf+G+F','GTR+G+F','TVM+I+G+F','TPM1uf+I+F',
'TPM3uf+I+F','TrN+I+G+F','TIM2+G+F','TPM2uf+I+G+F',
'GTR+I+G+F','TIM1+I+F','TIM3+I+F','HKY+I+F','TIM2+I+G+F',
'TVM+I+F','TrN+I+F','TPM2uf+I+F','GTR+I+F','TIM2+I+F',
'TPM3uf+F','TPM1uf+F','HKY+F','TIM3+F','TIM1+F','TVM+F',
'TrN+F','TPM2uf+F','GTR+F','TIM2+F','F81+G+F',
'F81+I+G+F','SYM+G','SYM+I+G','TVMef+G','TVMef+I+G',
'SYM+I','TIM2ef+G','TIM2ef+I+G','TVMef+I','TPM2+G',
'TPM2+I+G','TIM3ef+G','TIM2ef+I','TIM1ef+G','TIM3ef+I+G',
'TIM1ef+I+G','TPM2+I','TPM3+G','TPM1+G','TIM3ef+I',
'TPM3+I+G','TPM1+I+G','TIM1ef+I','TrNef+G','TrNef+I+G',
'F81+I+F','TPM3+I','TPM1+I','K80+G','TrNef+I','K80+I+G',
'K80+I','F81+F','SYM','TIM2ef','TVMef','TIM3ef','TIM1ef',
'TPM2','TrNef','TPM3','TPM1','K80','JC+G','JC+I+G','JC+I','JC']:
print 'Test ordering models: ERROR'
errors.append('ordering models')
else:
print 'Test ordering models: OK'
job_list = pmt.re_run(job_list, data, cutoff=0.95, refresh=0.01, nprocs=2,
verbose=True)
job_list = pmt.parse_jobs(job_list, data)
pmt.clean_all (job_list, data)
if sorted(job_list.keys()) == sorted(['GTR+G+F','HKY+G+F','HKY+I+G+F','TIM1+G+F',
'TIM1+I+G+F','TIM3+G+F','TIM3+I+G+F',
'TPM1uf+G+F','TPM1uf+I+F','TPM1uf+I+G+F',
'TPM2uf+G+F','TPM3uf+G+F','TPM3uf+I+F',
'TPM3uf+I+G+F','TVM+G+F','TVM+I+G+F',
'TrN+G+F','TrN+I+G+F']):
print 'Test better models: OK'
else:
print 'Test better models: ERROR'
errors.append('better models')
job_list, ord_aic = pmt.aic_calc(job_list, False)
if ord_aic == ['TPM1uf+G+F','TPM3uf+G+F','TIM1+G+F','TPM1uf+I+G+F','TIM3+G+F',
'HKY+G+F','TPM3uf+I+G+F','TVM+G+F','TIM1+I+G+F','TrN+G+F',
'TIM3+I+G+F','HKY+I+G+F','TPM2uf+G+F','GTR+G+F','TVM+I+G+F',
'TPM1uf+I+F','TPM3uf+I+F','TrN+I+G+F']:
print 'Test ordering better models: OK'
else:
print 'Test ordering better models: ERROR'
errors.append('ordering better models')
expected = {'TrN+I+G+F' : 6051.92212,
'TPM1uf+I+G+F' : 6047.98258,
'TVM+I+G+F' : 6051.17612,
'TIM1+I+G+F' : 6049.6176 ,
'TVM+G+F' : 6049.37942,
'HKY+G+F' : 6048.42828,
'TPM3uf+G+F' : 6046.7577 ,
'TIM3+G+F' : 6048.40978,
'TPM3uf+I+G+F' : 6048.5627 ,
'TIM3+I+G+F' : 6050.20106,
'GTR+G+F' : 6051.01224,
'TrN+G+F' : 6050.122 ,
'TPM2uf+G+F' : 6050.421 ,
'TPM1uf+G+F' : 6046.19414,
'TPM3uf+I+F' : 6051.40916,
'TIM1+G+F' : 6047.84258,
'HKY+I+G+F' : 6050.24122,
'TPM1uf+I+F' : 6051.35094}
for j in expected:
if not round(expected[j],2) == round(job_list[j]['AIC'],2):
print 'Test AIC values: ERROR'
errors.append('AIC values')
break
else:
print 'Test AIC values: OK'
tree = pmt.re_run_best(ord_aic[0], job_list[ord_aic[0]]['cmd'], data, verbose=True)
job_list = pmt.parse_jobs({ord_aic[0]: job_list[ord_aic[0]]}, data)
pmt.clean_all ({ord_aic[0]: job_list[ord_aic[0]]}, data)
expected_tree = '((((((Macaca_mulatta:0.0117313526,(Alouata_seniculus:0.0190656000,(Pongo_pygmaeus_old_3:0.0030481589,Gorilla_gorilla:0.0020294397)0.9770000000:0.0075362735)0.0000000000:0.0004306512)0.9960000000:0.0172550253,Pan_troglodytes:0.0223821735)0.8640000000:0.0093079991,Trachypithecus_johnii:0.0229373226)1.0000000000:0.0776907115,Procolobus_badius:0.1966057310)0.9970000000:0.0650031999,Trachypithecus_geii:0.0048258029)0.8290000000:0.0030733844,Semnopithecus_entellus:0.0052455542,Callithrix_jacchus:0.0081475480);\n'
expected_tree = sub('(:[0-9]+\.[0-9]{3})[0-9]*','\\1', expected_tree)
expected_tree = sub('(\))[0-9]+\.[0-9]*','\\1', expected_tree)
tree = sub('(:[0-9]+\.[0-9]{3})[0-9]*','\\1', tree)
tree = sub('(\))[0-9]+\.[0-9]*','\\1', tree)
if expected_tree == tree:
print 'Testing final topology: OK'
else:
print 'Testing final topology: ERROR'
errors.append('Different final trees')
print expected_tree
print tree
print '\n\n\n TEST NUCLEOTIDES FINISHED\n\n'
if errors:
print 'ERROR founds:'
for e in errors:
print e
else:
print ' -> ALL TEST OK'
print '\n\nas last check, have a look to jmodeltest result in test folder'
def test_nt():
print('\n START TEST NUCLEOTIDS')
print(' *********************\n\n')
errors = []
data = 'examples/dna.phy'
models = [
'JC', 'K80', 'TrNef', 'TPM1', 'TPM2', 'TPM3', 'TIM1ef', 'TIM2ef',
'TIM3ef', 'TVMef', 'SYM', 'F81', 'HKY', 'TrN', 'TPM1uf', 'TPM2uf',
'TPM3uf', 'TIM1', 'TIM2', 'TIM3', 'TVM', 'GTR'
]
job_list = pmt.get_job_list(data,
models,
speed=True,
protein=False,
verbose=False)
job_list = pmt.run_jobs(job_list, nprocs=2, refresh=0.01)
job_list = pmt.parse_jobs(job_list, data)
pmt.clean_all(job_list, data)
job_list, ord_aic = pmt.aic_calc(job_list, True, verbose=True)
if not ord_aic == [
'TPM1uf+G+F', 'TPM3uf+G+F', 'TIM1+G+F', 'TPM1uf+I+G+F', 'TIM3+G+F',
'HKY+G+F', 'TPM3uf+I+G+F', 'TVM+G+F', 'TIM1+I+G+F', 'TrN+G+F',
'TIM3+I+G+F', 'HKY+I+G+F', 'TPM2uf+G+F', 'GTR+G+F', 'TVM+I+G+F',
'TPM1uf+I+F', 'TPM3uf+I+F', 'TrN+I+G+F', 'TIM2+G+F',
'TPM2uf+I+G+F', 'GTR+I+G+F', 'TIM1+I+F', 'TIM3+I+F', 'HKY+I+F',
'TIM2+I+G+F', 'TVM+I+F', 'TrN+I+F', 'TPM2uf+I+F', 'GTR+I+F',
'TIM2+I+F', 'TPM3uf+F', 'TPM1uf+F', 'HKY+F', 'TIM3+F', 'TIM1+F',
'TVM+F', 'TrN+F', 'TPM2uf+F', 'GTR+F', 'TIM2+F', 'F81+G+F',
'F81+I+G+F', 'SYM+G', 'SYM+I+G', 'TVMef+G', 'TVMef+I+G', 'SYM+I',
'TIM2ef+G', 'TIM2ef+I+G', 'TVMef+I', 'TPM2+G', 'TPM2+I+G',
'TIM3ef+G', 'TIM2ef+I', 'TIM1ef+G', 'TIM3ef+I+G', 'TIM1ef+I+G',
'TPM2+I', 'TPM3+G', 'TPM1+G', 'TIM3ef+I', 'TPM3+I+G', 'TPM1+I+G',
'TIM1ef+I', 'TrNef+G', 'TrNef+I+G', 'F81+I+F', 'TPM3+I', 'TPM1+I',
'K80+G', 'TrNef+I', 'K80+I+G', 'K80+I', 'F81+F', 'SYM', 'TIM2ef',
'TVMef', 'TIM3ef', 'TIM1ef', 'TPM2', 'TrNef', 'TPM3', 'TPM1',
'K80', 'JC+G', 'JC+I+G', 'JC+I', 'JC'
]:
print('Test ordering models: ERROR')
errors.append('ordering models')
else:
print('Test ordering models: OK')
job_list = pmt.re_run(job_list,
data,
cutoff=0.95,
refresh=0.01,
nprocs=2,
verbose=True)
job_list = pmt.parse_jobs(job_list, data)
pmt.clean_all(job_list, data)
if sorted(job_list.keys()) == sorted([
'GTR+G+F', 'HKY+G+F', 'HKY+I+G+F', 'TIM1+G+F', 'TIM1+I+G+F',
'TIM3+G+F', 'TIM3+I+G+F', 'TPM1uf+G+F', 'TPM1uf+I+F',
'TPM1uf+I+G+F', 'TPM2uf+G+F', 'TPM3uf+G+F', 'TPM3uf+I+F',
'TPM3uf+I+G+F', 'TVM+G+F', 'TVM+I+G+F', 'TrN+G+F', 'TrN+I+G+F'
]):
print('Test better models: OK')
else:
print('Test better models: ERROR')
errors.append('better models')
job_list, ord_aic = pmt.aic_calc(job_list, False)
if ord_aic == [
'TPM1uf+G+F', 'TPM3uf+G+F', 'TIM1+G+F', 'TPM1uf+I+G+F', 'TIM3+G+F',
'HKY+G+F', 'TPM3uf+I+G+F', 'TVM+G+F', 'TIM1+I+G+F', 'TrN+G+F',
'TIM3+I+G+F', 'HKY+I+G+F', 'TPM2uf+G+F', 'GTR+G+F', 'TVM+I+G+F',
'TPM1uf+I+F', 'TPM3uf+I+F', 'TrN+I+G+F'
]:
print('Test ordering better models: OK')
else:
print('Test ordering better models: ERROR')
errors.append('ordering better models')
expected = {
'TrN+I+G+F': 6051.92212,
'TPM1uf+I+G+F': 6047.98258,
'TVM+I+G+F': 6051.17612,
'TIM1+I+G+F': 6049.6176,
'TVM+G+F': 6049.37942,
'HKY+G+F': 6048.42828,
'TPM3uf+G+F': 6046.7577,
'TIM3+G+F': 6048.40978,
'TPM3uf+I+G+F': 6048.5627,
'TIM3+I+G+F': 6050.20106,
'GTR+G+F': 6051.01224,
'TrN+G+F': 6050.122,
'TPM2uf+G+F': 6050.421,
'TPM1uf+G+F': 6046.19414,
'TPM3uf+I+F': 6051.40916,
'TIM1+G+F': 6047.84258,
'HKY+I+G+F': 6050.24122,
'TPM1uf+I+F': 6051.35094
}
for j in expected:
if not round(expected[j], 2) == round(job_list[j]['AIC'], 2):
print('Test AIC values: ERROR')
errors.append('AIC values')
break
else:
print('Test AIC values: OK')
tree = pmt.re_run_best(ord_aic[0],
job_list[ord_aic[0]]['cmd'],
data,
verbose=True)
job_list = pmt.parse_jobs({ord_aic[0]: job_list[ord_aic[0]]}, data)
pmt.clean_all({ord_aic[0]: job_list[ord_aic[0]]}, data)
expected_tree = '((((((Macaca_mulatta:0.0117313526,(Alouata_seniculus:0.0190656000,(Pongo_pygmaeus_old_3:0.0030481589,Gorilla_gorilla:0.0020294397)0.9770000000:0.0075362735)0.0000000000:0.0004306512)0.9960000000:0.0172550253,Pan_troglodytes:0.0223821735)0.8640000000:0.0093079991,Trachypithecus_johnii:0.0229373226)1.0000000000:0.0776907115,Procolobus_badius:0.1966057310)0.9970000000:0.0650031999,Trachypithecus_geii:0.0048258029)0.8290000000:0.0030733844,Semnopithecus_entellus:0.0052455542,Callithrix_jacchus:0.0081475480);\n'
expected_tree = sub('(:[0-9]+\.[0-9]{3})[0-9]*', '\\1', expected_tree)
expected_tree = sub('(\))[0-9]+\.[0-9]*', '\\1', expected_tree)
tree = sub('(:[0-9]+\.[0-9]{3})[0-9]*', '\\1', tree)
tree = sub('(\))[0-9]+\.[0-9]*', '\\1', tree)
if expected_tree == tree:
print('Testing final topology: OK')
else:
print('Testing final topology: ERROR')
errors.append('Different final trees')
print(expected_tree)
print(tree)
print('\n\n\n TEST NUCLEOTIDES FINISHED\n\n')
if errors:
print('ERROR founds:')
for e in errors:
print(e)
else:
print(' -> ALL TEST OK')
print('\n\nas last check, have a look to jmodeltest result in test folder')