def fast_calc_distances_task(alignment_file):
rec = Alignment(alignment_file, 'phylip', True)
rec.fast_compute_distances()
result = dict(distances=rec.get_distances().tolist(),
variances=rec.get_variances().tolist(),
tree=rec.get_bionj_tree())
return result
def fast_calc_distances_task(alignment_file):
rec = Alignment(alignment_file, 'phylip', True)
rec.fast_compute_distances()
result = dict(distances=rec.get_distances().tolist(),
variances=rec.get_variances().tolist(),
tree=rec.get_bionj_tree())
return result
def alignment(self):
al = Alignment([self.collection[i] for i in self.indices])
al.fast_compute_distances()
return al
def mrp_tree(self):
trees = [
tree.newick if hasattr('newick', tree) else tree
for tree in self.trees
]
return Alignment().get_mrp_supertree(trees)
def alignment(self):
al = Alignment([self.collection[i] for i in self.indices])
al.fast_compute_distances()
return al
def calc_distances_task(pll_dict, alignment_file, model=None):
rec = Alignment(alignment_file, 'phylip', True)
freqs = smooth_freqs(pll_dict['partitions'][0]['frequencies'])
alpha = pll_dict['partitions'][0]['alpha']
if model is None:
rec.set_substitution_model('GTR' if rec.is_dna() else 'LG08+F')
else:
rec.set_substitution_model(model)
rec.set_gamma_rate_model(4, alpha)
rec.set_frequencies(freqs)
if rec.is_dna():
rec.set_rates(pll_dict['partitions'][0]['rates'], 'ACGT')
rec.compute_distances()
result = dict(distances=rec.get_distances().tolist(),
variances=rec.get_variances().tolist())
pll_dict['partitions'][0].update(result)
pll_dict['nj_tree'] = rec.get_bionj_tree()
return pll_dict
def simulate_task(n, model, frequencies, alpha, tree, rates=None):
rec = Alignment()
rec.set_substitution_model(model)
rec.set_frequencies(frequencies)
rec.set_gamma_rate_model(4, alpha)
if rates is not None:
try:
rec.set_rates(rates, 'acgt')
except RuntimeError:
pass
rec.set_simulator(tree)
return rec.simulate(n)
def simulate_task(n, model, frequencies, alpha, tree, rates=None):
rec = Alignment()
rec.set_substitution_model(model)
rec.set_frequencies(frequencies)
rec.set_gamma_rate_model(4, alpha)
if rates is not None:
try:
rec.set_rates(rates, 'acgt')
except RuntimeError:
pass
rec.set_simulator(tree)
return rec.simulate(n)
def calc_distances_task(pll_dict, alignment_file, model=None):
rec = Alignment(alignment_file, 'phylip', True)
freqs = smooth_freqs(pll_dict['partitions'][0]['frequencies'])
alpha = pll_dict['partitions'][0]['alpha']
if model is None:
rec.set_substitution_model('GTR' if rec.is_dna() else 'LG08+F')
else:
rec.set_substitution_model(model)
rec.set_gamma_rate_model(4, alpha)
rec.set_frequencies(freqs)
if rec.is_dna():
rec.set_rates(pll_dict['partitions'][0]['rates'], 'ACGT')
rec.compute_distances()
result = dict(distances=rec.get_distances().tolist(),
variances=rec.get_variances().tolist())
pll_dict['partitions'][0].update(result)
pll_dict['nj_tree'] = rec.get_bionj_tree()
return pll_dict
