def finish(self):
lks = []
if self.lk_mode == "phyml":
for job in self.jobs:
if job.jobcat != "bionj": continue
phyml_job = job
tree_file = pjoin(phyml_job.jobdir,
self.alg_phylip_file+"_phyml_tree.txt")
stats_file = pjoin(phyml_job.jobdir,
self.alg_phylip_file+"_phyml_stats.txt")
tree = PhyloTree(tree_file)
m = re.search('Log-likelihood:\s+(-?\d+\.\d+)',
open(stats_file).read())
lk = float(m.groups()[0])
tree.add_feature("lk", lk)
tree.add_feature("model", phyml_job.args["--model"])
lks.append([float(tree.lk), tree.model, tree])
elif self.lk_mode == "raxml":
for job in self.jobs:
if job.jobcat != "raxml": continue
raxml_job = job
lk = open(pjoin(raxml_job.jobdir, "RAxML_log.%s"
%raxml_job.args["-n"])).readline().split()[1]
tree = PhyloTree(raxml_job.args["-t"])
tree.add_feature("lk", lk)
tree.add_feature("model", raxml_job.model)
lks.append([float(tree.lk), tree.model, tree])
# sort lks in ASC order
lks.sort()
# choose the model with higher likelihood, the lastone in the list
best_model = lks[-1][1]
best_tree = lks[-1][2]
log.log(22, "%s model selected from the following lk values:\n%s" %(best_model, '\n'.join(map(str, lks))))
ModelTesterTask.store_data(self, best_model, lks)
def __init__(self, nodeid, alg_fasta_file, alg_phylip_file,
constrain_tree, conf, confname):
GLOBALS["citator"].add(PHYML_CITE)
self.alg_phylip_file = alg_phylip_file
self.alg_fasta_file = alg_fasta_file
self.confname = confname
self.conf = conf
self.lk_mode = conf[confname]["_lk_mode"]
if self.lk_mode == "raxml":
phyml_optimization = "n"
elif self.lk_mode == "phyml":
phyml_optimization = "lr"
else:
raise ValueError("Choose a valid lk_mode value (raxml or phyml)")
base_args = {
"--datatype": "aa",
"--input": self.alg_phylip_file,
"--bootstrap": "0",
"-o": phyml_optimization,
"--model": None, # I will iterate over this value when
# creating jobs
"--quiet": ""
}
self.models = conf[confname]["_models"]
task_name = "Prottest-[%s]" %','.join(self.models)
ModelTesterTask.__init__(self, nodeid, "mchooser", task_name,
base_args, conf[confname])
self.best_model = None
self.seqtype = "aa"
self.init()
def finish(self):
# first job is the raxml tree
best_model = None
best_model_in_next_line = False
t = None
for line in open(self.jobs[-1].stdout_file, "rU"):
line = line.strip()
if best_model_in_next_line and line.startswith("Model"):
pass#best_model = line.split("=")[1].strip()
elif best_model_in_next_line and line.startswith("partition"):
best_model = line.split("=")[1].strip()
best_model_in_next_line = False
elif line.startswith("Model selected:"):
best_model_in_next_line = True
elif line.startswith("ML tree (NNI) for the best AIC model ="):
nw = line.replace("ML tree (NNI) for the best AIC model =", "")
t = PhyloTree(nw)
open(self.best_model_file, "w").write(best_model)
log.log(26, "Best model: %s" %best_model)
if self.ttype == "tree":
tree_job = self.jobs[-1]
tree_file = os.path.join(tree_job.jobdir,
"jModelTest_tree."+self.nodeid)
t.write(outfile=self.tree_file)
self.model = best_model
ModelTesterTask.finish(self)
def __init__(self, nodeid, alg_fasta_file, alg_phylip_file, conf):
GLOBALS["citator"].add(JMODELTEST_CITE)
self.conf = conf
base_args = {
'-d': alg_fasta_file,
}
args = self.conf["jmodeltest"]
if args.get("-t", "ML") == "ML":
task_type = "tree"
else:
task_type = "mchooser"
ModelTesterTask.__init__(self, nodeid, task_type, "Jmodeltest",
base_args, self.conf[confname])
# set app arguments and options
self.alg_fasta_file = alg_fasta_file
self.alg_phylip_file = alg_phylip_file
self.seqtype = "nt"
self.models = "see jmodeltest params"
self.init()
self.best_model_file = os.path.join(self.taskdir, "best_model.txt")
if task_type == "tree":
self.tree_file = os.path.join(self.taskdir, "final_tree.nw")
else:
self.tree_file = None
def finish(self):
lks = []
if self.lk_mode == "phyml":
for job in [j for j in self.jobs if j.flag == "phyml"]:
tree_file = os.path.join(job.jobdir,
self.alg_basename+"_phyml_tree.txt")
stats_file = os.path.join(j.jobdir,
self.alg_basename+"_phyml_stats.txt")
tree = PhyloTree(tree_file)
m = re.search('Log-likelihood:\s+(-?\d+\.\d+)',
open(stats_file).read())
lk = float(m.groups()[0])
tree.add_feature("lk", lk)
tree.add_feature("model", job.args["--model"])
lks.append([float(tree.lk), tree.model, tree])
elif self.lk_mode == "raxml":
for job in [j for j in self.jobs if j.flag == "raxml"]:
lk = open(os.path.join(job.jobdir, "RAxML_log.%s"
%job.args["-n"])).readline().split()[1]
tree = PhyloTree(job.args["-t"])
tree.add_feature("lk", lk)
tree.add_feature("model", job.model)
lks.append([lk, tree.model, tree])
lks.sort()
lks.reverse()
# choose the model with higher likelihood
best_model = lks[-1][1]
best_tree = lks[-1][2]
open(self.best_model_file, "w").write(best_model)
if self.tree_file:
tree.write(self.tree_file)
ModelTesterTask.finish(self)
def __init__(self, nodeid, alg_fasta_file, alg_phylip_file,
constrain_tree, conf):
self.alg_phylip_file = alg_phylip_file
self.alg_fasta_file = alg_fasta_file
self.alg_basename = basename(self.alg_phylip_file)
self.conf = conf
self.lk_mode = self.conf["prottest"]["_lk_mode"]
if self.lk_mode == "raxml":
phyml_optimization = "n"
elif self.lk_mode == "phyml":
phyml_optimization = "lr"
else:
raise ValueError("Choose a valid lk_mode value (raxml or phyml)")
base_args = {
"--datatype": "aa",
"--input": self.alg_basename,
"--bootstrap": "0",
"-o": phyml_optimization,
"--model": None, # I will iterate over this value when
# creating jobs
"--quiet": ""
}
ModelTesterTask.__init__(self, nodeid, "mchooser", "Prottest",
base_args, conf["prottest"])
self.best_model = None
self.seqtype = "aa"
self.models = self.conf["prottest"]["_models"]
self.init()
self.post_init()