def test_get_most_likely(self):
tree = EvolTree (WRKDIR + 'tree.nw')
tree.workdir = 'examples/evol/data/protamine/PRM1/paml/'
tree.link_to_evol_model (WRKDIR + 'paml/M1/M1.out', 'M1')
tree.link_to_evol_model (WRKDIR + 'paml/M2/M2.out', 'M2')
self.assertEqual(round(tree.get_most_likely ('M2','M1'),16),
round(6.3280740347111373e-10,16))
def test_call_histface(self):
tree = EvolTree (WRKDIR + 'tree.nw')
tree.workdir = 'examples/evol/data/protamine/PRM1/paml/'
tree.link_to_alignment (WRKDIR + 'alignments.fasta_ali')
tree.link_to_evol_model (WRKDIR + 'paml/M2/M2.out', 'M2.a')
col = {'NS' : 'grey', 'RX' : 'black',
'RX+': 'grey', 'CN' : 'black',
'CN+': 'grey', 'PS' : 'black', 'PS+': 'black'}
col2 = {'NS' : 'white', 'RX' : 'white',
'RX+': 'white', 'CN' : 'white',
'CN+': 'white', 'PS' : 'white', 'PS+': 'white'}
M2a = tree.get_evol_model('M2.a')
try:
import PyQt4
except ImportError:
pass
else:
M2a.set_histface (up=False, kind='stick', hlines=[1.0, 0.3],
hlines_col=['red','grey'], header='ugliest face')
M2a.set_histface (up=False, kind='curve', colors=col2,errors=True,
hlines = [2.5, 1.0, 4.0, 0.5],
header = 'Many lines, error boxes, background black',
hlines_col=['orange', 'yellow', 'red', 'cyan'])
M2a.set_histface (up=False, kind='bar', hlines = [1.0, 0.3],
hlines_col=['black','grey'],colors=col)
self.assertEqual(str(type(M2a.properties['histface'])),
"<class 'ete2.treeview.faces.SequencePlotFace'>")
def test_deep_copy(self):
tree = EvolTree (WRKDIR + 'tree.nw')
tree.workdir = 'examples/evol/data/protamine/PRM1/paml/'
tree.link_to_evol_model (WRKDIR + 'paml/fb/fb.out', 'fb')
fba = deepcopy (tree.get_evol_model('fb'))
tree._models['fb.a'] = fba
self.assertEqual(str(tree.get_evol_model('fb.a')),
str(tree.get_evol_model('fb'))
)
def test_pickling(self):
tree = EvolTree (WRKDIR + 'tree.nw')
tree.workdir = ETEPATH + '/examples/data/protamine/PRM1/paml/'
tree.link_to_alignment (WRKDIR + 'alignments.fasta_ali')
tree.link_to_evol_model (WRKDIR + 'paml/M2/M2.out', 'M2.a')
out = open('blip.pik', 'w')
dump (tree, out)
out.close()
out = open('blip.pik')
tree2 = load (out)
out.close()
os.remove('blip.pik')
self.assertEqual(str(tree2.get_evol_model('M2.a')),
str(tree.get_evol_model('M2.a'))
)
def test_load_model(self):
tree = EvolTree (WRKDIR + 'tree.nw')
tree.workdir = 'examples/evol/data/protamine/PRM1/paml/'
tree.link_to_evol_model (WRKDIR + 'paml/fb/fb.out', 'fb')
tree.link_to_evol_model (WRKDIR + 'paml/M1/M1.out', 'M1')
tree.link_to_evol_model (WRKDIR + 'paml/M2/M2.out', 'M2')
tree.link_to_evol_model (WRKDIR + 'paml/M7/M7.out', 'M7')
tree.link_to_evol_model (WRKDIR + 'paml/M8/M8.out', 'M8')
tree.link_to_alignment (WRKDIR + 'alignments.fasta_ali')
self.assertEqual(sorted(tree._models.keys()),
sorted(['fb', 'M1', 'M2', 'M7', 'M8']))
self.assertEqual(len (tree.get_evol_model('M2').branches), 194)
self.assertEqual(tree.get_evol_model('fb').lnL, -3265.316569)
self.assert_('proportions' in str(tree.get_evol_model('M2')))
self.assert_('p2=' in str(tree.get_evol_model('M2')))
self.assert_('proportions' not in str(tree.get_evol_model('fb')))
self.assert_(' #193' in str(tree.get_evol_model('fb')))
def test_labelling_tree(self):
tree = EvolTree (WRKDIR + 'tree.nw')
tree.workdir = 'examples/evol/data/protamine/PRM1/paml/'
random_swap(tree)
tree.link_to_evol_model (WRKDIR + 'paml/fb/fb.out', 'fb')
self.assert_(check_annotation (tree))
ALG_PATH = "./alignment_%s_measuring_evol.fasta" % (typ)
TREE_PATH = PATH + re.sub('\./', '', TREE_PATH)
ALG_PATH = PATH + re.sub('\./', '', ALG_PATH )
print T
print '\n ----> and an alignment from: \n'+ALG_PATH+'\n\n'
T.link_to_alignment(ALG_PATH)
raw_input(" ====> hit some key to see the Tree with alignment")
T.show()
###
# run free-branch model, and display result
print '\n\n\n ----> We define now our working directory, that will be created:', \
WORKING_PATH
T.workdir = (WORKING_PATH)
print '\n ----> and run the free-branch model with run_model function:\n\n%s\n%s\n%s\n'\
% ('*'*10 + ' doc ' + '*'*10, T.run_model.func_doc, '*'*30)
raw_input(" ====> Hit some key to start free-branch computation with codeml...\n")
T.run_model('fb')
T.show()
###
# run site model, and display result
print '\n\n\n ----> We are now goingn to run sites model M1 and M2 with run_model function:\n'
raw_input(" ====> hit some key to start")
for model in ['M1', 'M2']:
print 'running model ' + model
T.run_model(model)
