def load_jobs(self):
conf = self.conf
for m in self.models:
args = self.args.copy()
args["--model"] = m
bionj_job = Job(conf["app"]["phyml"], args,
parent_ids=[self.nodeid])
bionj_job.jobname += "-bionj-" + m
bionj_job.jobcat = "bionj"
bionj_job.add_input_file(self.alg_phylip_file, bionj_job.jobdir)
self.jobs.append(bionj_job)
if self.lk_mode == "raxml":
raxml_args = {
"-f": "e",
"-s": pjoin(bionj_job.jobdir, self.alg_phylip_file),
"-m": "PROTGAMMA%s" % m,
"-n": self.alg_phylip_file+"."+m,
"-t": pjoin(bionj_job.jobdir,
self.alg_phylip_file+"_phyml_tree.txt")
}
raxml_job = Job(conf["app"]["raxml"], raxml_args,
parent_ids=[bionj_job.jobid])
raxml_job.jobname += "-lk-optimize"
raxml_job.dependencies.add(bionj_job)
raxml_job.model = m
raxml_job.jobcat = "raxml"
self.jobs.append(raxml_job)
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 app_wrapper(func, args):
global NCURSES
base_dir = GLOBALS.get("scratch_dir", GLOBALS["basedir"])
lock_file = pjoin(base_dir, "alive")
if not args.enable_ui:
NCURSES = False
if not pexist(lock_file) or args.clearall:
open(lock_file, "w").write(time.ctime())
else:
clear_env()
print >>sys.stderr, '\nThe same process seems to be running. Use --clearall or remove the lock file "alive" within the output dir'
sys.exit(-1)
try:
if NCURSES:
curses.wrapper(main, func, args)
else:
main(None, func, args)
except ConfigError, e:
if GLOBALS.get('_background_scheduler', None):
GLOBALS['_background_scheduler'].terminate()
print >>sys.stderr, "\nConfiguration Error:", e
clear_env()
sys.exit(-1)
def load_jobs(self):
appname = self.conf[self.confname]["_app"]
args = self.args.copy()
args["-in"] = pjoin(GLOBALS["input_dir"], self.alg_fasta_file)
args["-out"] = "clean.alg.fasta"
job = Job(self.conf["app"][appname], args, parent_ids=[self.nodeid])
job.add_input_file(self.alg_fasta_file)
self.jobs.append(job)
def load_jobs(self):
# Only one Muscle job is necessary to run this task
appname = self.conf[self.confname]["_app"]
args = OrderedDict(self.args)
args[""] = "%s %s" % (pjoin(GLOBALS["input_dir"], self.multiseq_file), "alg.fasta")
job = Job(self.conf["app"][appname], args, parent_ids=[self.nodeid])
job.add_input_file(self.multiseq_file)
self.jobs.append(job)
def load_jobs(self):
appname = self.conf[self.confname]["_app"]
# Only one Muscle job is necessary to run this task
args = OrderedDict(self.args)
args["-i"] = pjoin(GLOBALS["input_dir"], self.multiseq_file)
args["-o"] = "alg.fasta"
job = Job(self.conf["app"][appname], args, parent_ids=[self.nodeid])
job.cores = self.conf["threading"].get(appname, 1)
job.add_input_file(self.multiseq_file)
self.jobs.append(job)
def load_jobs(self):
args = self.args.copy()
try:
del args["-wag"]
except KeyError:
pass
if self.constrain_tree:
args["-constraints"] = pjoin(GLOBALS["input_dir"], self.constrain_tree)
args[pjoin(GLOBALS["input_dir"], self.alg_phylip_file)] = ""
appname = self.conf[self.confname]["_app"]
job = Job(self.conf["app"][appname], args, parent_ids=[self.nodeid])
job.cores = self.conf["threading"][appname]
if self.constrain_tree:
job.add_input_file(self.constrain_tree)
job.add_input_file(self.alg_phylip_file)
self.jobs.append(job)
def load_jobs(self):
args = self.args.copy()
args["-outfile"] = "mcoffee.fasta"
alg_paths = [pjoin(GLOBALS["input_dir"], algid)
for algid in self.all_alg_files]
args["-aln"] = ' '.join(alg_paths)
job = Job(self.conf["app"]["tcoffee"], args, parent_ids=self.parent_ids)
for key in self.all_alg_files:
job.add_input_file(key)
self.jobs.append(job)
def load_jobs(self):
appname = self.conf[self.confname]["_app"]
args = OrderedDict(self.args)
# Mafft redirects resulting alg to std.output. The order of
# arguments is important, input file must be the last
# one.
args[""] = pjoin(GLOBALS["input_dir"], self.multiseq_file)
job = Job(self.conf["app"][appname], args, parent_ids=[self.nodeid])
job.add_input_file(self.multiseq_file)
job.cores = self.conf["threading"][appname]
self.jobs.append(job)
def finish(self):
# Once executed, alignment is converted into relaxed
# interleaved phylip format.
alg = SeqGroup(os.path.join(self.jobs[0].jobdir, "mcoffee.fasta"))
fasta = alg.write(format="fasta")
phylip = alg.write(format="iphylip_relaxed")
alg_list_string = '\n'.join([pjoin(GLOBALS["input_dir"],
aname) for aname in self.all_alg_files])
db.add_task_data(self.taskid, DATATYPES.alg_list, alg_list_string)
AlgTask.store_data(self, fasta, phylip)
def clear_env():
try:
terminate_job_launcher()
except:
pass
base_dir = GLOBALS["basedir"]
lock_file = pjoin(base_dir, "alive")
try:
os.remove(lock_file)
except Exception:
print >>sys.stderr, "could not remove lock file %s" %lock_file
clear_tempdir()
def finish(self):
if self.conf[self.confname]["_alg_trimming"]:
# If trimming happened after mcoffee, let's save the
# resulting output
trim_job = self.jobs[-1]
alg = SeqGroup(pjoin(trim_job.jobdir, trim_job.alg_fasta_file))
fasta = alg.write(format="fasta")
phylip = alg.write(format="iphylip_relaxed")
AlgTask.store_data(self, fasta, phylip)
else:
# If no post trimming, output is just what Mcoffee
# produced, so we can recycle its data ids.
mc_task = self.jobs[-1]
fasta_id = db.get_dataid(mc_task.taskid, DATATYPES.alg_fasta)
phylip_id = db.get_dataid(mc_task.taskid, DATATYPES.alg_phylip)
db.register_task_data(self.taskid, DATATYPES.alg_fasta, fasta_id)
db.register_task_data(self.taskid, DATATYPES.alg_phylip, phylip_id)
def dump_tree_debug(msg, taskdir, mtree, ttree, target_seqs, out_seqs):
try:
if out_seqs is None: out_seqs = set()
if target_seqs is None: target_seqs = set()
if ttree:
for n in ttree.get_leaves():
if n.name in out_seqs:
n.name = n.name + " *__OUTGROUP__*"
if mtree:
for n in mtree.get_leaves():
if n.name in out_seqs:
n.name = n.name + " *__OUTGROUP__*"
if n.name in target_seqs:
n.name = n.name + " [ TARGET ]"
OUT = open(pjoin(taskdir, "__debug__"), "w")
print >>OUT, msg
print >>OUT, "MainTree:", mtree
print >>OUT, "TaskTree:", ttree
print >>OUT, "Expected outgroups:", out_seqs
OUT.close()
except Exception, e:
print e
def __init__(self, bin, args, jobname=None, parent_ids=None):
# Used at execution time
self.status = None
# How to run the app
self.bin = bin
# command line arguments
self.args = args
# Default number of cores used by the job. If more than 1,
# this attribute should be changed
self.cores = 1
self.exec_type = "insitu"
self.jobname = jobname
# generates the unique job identifier based on the params of
# the app. Some params include path names that can prevent
# recycling the job, so a clean it.
clean = lambda x: basename(x) if GLOBALS["basedir"] in x or GLOBALS["taskdir"] in x else x
parsed_id_string = ["%s %s" %(clean(str(pair[0])), clean(str(pair[1])))
for pair in self.args.iteritems()]
#print '\n'.join(map(str, self.args.items()))
self.jobid = md5(','.join(sorted([md5(e) for e in
parsed_id_string])))
# self.jobid = md5(','.join(sorted([md5(str(pair)) for pair in
# self.args.iteritems()])))
if parent_ids:
self.jobid = md5(','.join(sorted(parent_ids+[self.jobid])))
if not self.jobname:
self.jobname = re.sub("[^0-9a-zA-Z]", "-", basename(self.bin))
self.ifdone_cmd = ""
self.iffail_cmd = ""
self.set_jobdir(pjoin(GLOBALS["tasks_dir"], self.jobid))
self.input_files = {}
self.dependencies = set()
def finish(self):
# Once executed, alignment is converted into relaxed
# interleaved phylip format. Both files, fasta and phylip,
# remain accessible.
# Set Task specific attributes
main_job = self.jobs[0]
fasta_path = pjoin(main_job.jobdir, "clean.alg.fasta")
alg = SeqGroup(fasta_path)
if len(alg) != self.size:
log.warning("Trimming was to aggressive and it tried"
" to remove one or more sequences."
" Alignment trimming will be disabled for this dataset."
)
self.clean_alg_fasta_file = db.register_task_data(self.taskid, DATATYPES.clean_alg_fasta, self.alg_fasta_file)
self.clean_alg_phylip_file = db.register_task_data(self.taskid, DATATYPES.clean_alg_phylip, self.alg_phylip_file)
else:
for line in open(self.jobs[0].stdout_file):
line = line.strip()
if line.startswith("#ColumnsMap"):
kept_columns = map(int, line.split("\t")[1].split(","))
fasta = alg.write(format="fasta")
phylip = alg.write(format="iphylip_relaxed")
AlgCleanerTask.store_data(self, fasta, phylip, kept_columns)
def load_jobs(self):
readal_bin = self.conf["app"]["readal"]
trimal_bin = self.conf["app"]["trimal"]
input_dir = GLOBALS["input_dir"]
multiseq_file = pjoin(input_dir, self.multiseq_file)
multiseq_file_r = pjoin(input_dir, self.multiseq_file+"_reversed")
first = seq_reverser_job(multiseq_file, multiseq_file_r,
[self.nodeid], readal_bin)
#print self.multiseq_file
first.add_input_file(self.multiseq_file)
self.jobs.append(first)
all_alg_names = []
mcoffee_parents = []
for aligner_name in self.conf[self.confname]["_aligners"]:
aligner_name = aligner_name[1:]
_classname = APP2CLASS[self.conf[aligner_name]["_app"]]
_module = __import__(CLASS2MODULE[_classname], globals(), locals(), [], -1)
_aligner = getattr(_module, _classname)
# Normal alg
task1 = _aligner(self.nodeid, self.multiseq_file, self.seqtype,
self.conf, aligner_name)
task1.size = self.size
self.jobs.append(task1)
all_alg_names.append(task1.alg_fasta_file)
# Alg of the reverse
task2 = _aligner(self.nodeid, self.multiseq_file+"_reversed",
self.seqtype, self.conf, aligner_name)
task2.size = self.size
task2.dependencies.add(first)
self.jobs.append(task2)
# Restore reverse alg
reverse_out = pjoin(input_dir, task2.alg_fasta_file)
task3 = seq_reverser_job(reverse_out,
reverse_out+"_restored",
[task2.taskid], readal_bin)
task3.dependencies.add(task2)
task3.add_input_file(task2.alg_fasta_file)
all_alg_names.append(reverse_out+"_restored")
self.jobs.append(task3)
mcoffee_parents.extend([task1.taskid, task2.taskid])
# Combine signal from all algs using Mcoffee
mcoffee_task = MCoffee(self.nodeid, self.seqtype, all_alg_names,
self.conf, self.confname, parent_ids=mcoffee_parents)
# reversed algs are not actually saved into db, but it should
# be present since the reverser job is always executed
mcoffee_task.dependencies.update(list(self.jobs))
self.jobs.append(mcoffee_task)
if self.conf[self.confname]["_alg_trimming"]:
trimming_cutoff = 1.0 / len(all_alg_names)
targs = {}
targs["-forceselect"] = pjoin(input_dir, mcoffee_task.alg_fasta_file)
targs["-compareset"] = pjoin(input_dir, mcoffee_task.alg_list_file)
targs["-out"] = "mcoffee.trimmed.fasta"
targs["-fasta"] = ""
targs["-ct"] = trimming_cutoff
trim_job = Job(trimal_bin, targs, parent_ids=[mcoffee_task.taskid])
trim_job.jobname = "McoffeeTrimming"
trim_job.dependencies.add(mcoffee_task)
trim_job.alg_fasta_file = targs["-out"]
for key in all_alg_names:
trim_job.add_input_file(key)
trim_job.add_input_file(mcoffee_task.alg_fasta_file)
trim_job.add_input_file(mcoffee_task.alg_list_file)
self.jobs.append(trim_job)
def load_jobs(self):
args = OrderedDict(self.args)
args["-s"] = pjoin(GLOBALS["input_dir"], self.alg_phylip_file)
args["-m"] = self.model_string
args["-n"] = self.alg_phylip_file
if self.constrain_tree:
log.log(24, "Using constrain tree %s" %self.constrain_tree)
args["-g"] = pjoin(GLOBALS["input_dir"], self.constrain_tree)
if self.partitions_file:
log.log(24, "Using alg partitions %s" %self.partitions_file)
args['-q'] = pjoin(GLOBALS["input_dir"], self.partitions_file)
tree_job = Job(self.raxml_bin, args, parent_ids=[self.nodeid])
tree_job.jobname += "-"+self.model_string
tree_job.cores = self.threads
# Register input files necessary to run the job
tree_job.add_input_file(self.alg_phylip_file)
if self.constrain_tree:
tree_job.add_input_file(self.constrain_tree)
if self.partitions_file:
tree_job.add_input_file(self.partitions_file)
self.jobs.append(tree_job)
self.out_tree_file = os.path.join(tree_job.jobdir,
"RAxML_bestTree." + self.alg_phylip_file)
if self.bootstrap == "alrt":
alrt_args = tree_job.args.copy()
if self.constrain_tree:
del alrt_args["-g"]
if self.partitions_file:
alrt_args["-q"] = args['-q']
alrt_args["-f"] = "J"
alrt_args["-t"] = self.out_tree_file
alrt_job = Job(self.raxml_bin, alrt_args,
parent_ids=[tree_job.jobid])
alrt_job.jobname += "-alrt"
alrt_job.dependencies.add(tree_job)
alrt_job.cores = self.threads
# Register necessary input files
alrt_job.add_input_file(self.alg_phylip_file)
if self.partitions_file:
alrt_job.add_input_file(self.partitions_file)
self.jobs.append(alrt_job)
self.alrt_job = alrt_job
elif self.bootstrap == "alrt_phyml":
alrt_args = {
"-o": "n",
"-i": self.alg_phylip_file,
"--bootstrap": "-2",
"-d": self.seqtype,
"-u": self.out_tree_file,
"--model": self.model,
"--quiet": "",
"--no_memory_check": "",
}
#if self.constrain_tree:
# alrt_args["--constraint_tree"] = self.constrain_tree
alrt_job = Job(self.conf["app"]["phyml"],
alrt_args, parent_ids=[tree_job.jobid])
alrt_job.add_input_file(self.alg_phylip_file, alrt_job.jobdir)
alrt_job.jobname += "-alrt"
alrt_job.dependencies.add(tree_job)
alrt_job.add_input_file(self.alg_phylip_file)
self.jobs.append(alrt_job)
self.alrt_job = alrt_job
else:
# Bootstrap calculation
boot_args = tree_job.args.copy()
boot_args["-n"] = "bootstraps."+boot_args["-n"]
boot_args["-N"] = int(self.bootstrap)
boot_args["-b"] = 31416
boot_job = Job(self.raxml_bin, boot_args,
parent_ids=[tree_job.jobid])
boot_job.jobname += "-%d-bootstraps" %(boot_args['-N'])
boot_job.dependencies.add(tree_job)
boot_job.cores = self.threads
# Register necessary input files
boot_job.add_input_file(self.alg_phylip_file)
if self.constrain_tree:
boot_job.add_input_file(self.constrain_tree)
if self.partitions_file:
boot_job.add_input_file(self.partitions_file)
self.jobs.append(boot_job)
# Bootstrap drawing on top of best tree
bootd_args = tree_job.args.copy()
if self.constrain_tree:
del bootd_args["-g"]
if self.partitions_file:
del bootd_args["-q"]
bootd_args["-n"] = "bootstrapped."+ tree_job.args["-n"]
bootd_args["-f"] = "b"
bootd_args["-t"] = self.out_tree_file
bootd_args["-z"] = pjoin(boot_job.jobdir, "RAxML_bootstrap." + boot_job.args["-n"])
bootd_job = Job(self.raxml_bin, bootd_args,
parent_ids=[tree_job.jobid])
bootd_job.jobname += "-bootstrapped"
bootd_job.dependencies.add(boot_job)
bootd_job.cores = self.threads
self.jobs.append(bootd_job)
self.boot_job = boot_job
self.bootd_job = bootd_job
e_obj = error[1] if error[1] else error[0]
error_path = e_obj.jobdir if isjob(e_obj) else e_obj.taskid
if e_obj is not error[0]:
error_lines.append(" -> %s" %e_obj)
error_lines.append(" -> %s" %error_path)
error_lines.append(" -> %s" %error[2])
for eline in error_lines:
log.error(eline)
pending_threads = set([ts.configid for ts in pending_tasks])
finished_threads = expected_threads - (pending_threads | set(thread_errors.keys()))
just_finished_lines = []
finished_lines = []
for configid in finished_threads:
# configid is the the same as threadid in master tasks
final_tree_file = pjoin(GLOBALS[configid]["_outpath"],
GLOBALS["inputname"] + ".final_tree")
threadname = GLOBALS[configid]["_name"]
if configid in past_threads:
log.log(28, "Done thread @@12:%s@@1: in %d iteration(s)",
threadname, past_threads[configid])
finished_lines.append("Finished %s in %d iteration(s)" %(
threadname, past_threads[configid]))
else:
log.log(28, "Assembling final tree...")
main_tree, treeiters = assembly_tree(configid)
past_threads[configid] = treeiters - 1
log.log(28, "Done thread @@12:%s@@1: in %d iteration(s)",
threadname, past_threads[configid])
def process_task(task, wkname, npr_conf, nodeid2info):
alignerconf, alignerclass = npr_conf.aligner
cleanerconf, cleanerclass = npr_conf.alg_cleaner
mtesterconf, mtesterclass = npr_conf.model_tester
treebuilderconf, treebuilderclass = npr_conf.tree_builder
if not treebuilderclass:
# Allows to dump algs in workflows with no tree tasks
treebuilderclass = DummyTree
splitterconf, splitterclass = npr_conf.tree_splitter
conf = GLOBALS[task.configid]
seqtype = task.seqtype
nodeid = task.nodeid
ttype = task.ttype
taskid = task.taskid
threadid = task.threadid
node_info = nodeid2info[nodeid]
size = task.size#node_info.get("size", 0)
target_seqs = node_info.get("target_seqs", [])
out_seqs = node_info.get("out_seqs", [])
if not treebuilderclass or size < 4:
# Allows to dump algs in workflows with no tree tasks or if tree
# inference does not make sense given the number of sequences. DummyTree
# will produce a fake fully collapsed newick tree.
treebuilderclass = DummyTree
mtesterclass = None
# If more than one outgroup are used, enable the use of constrain
if out_seqs and len(out_seqs) > 1:
constrain_id = nodeid
else:
constrain_id = None
new_tasks = []
if ttype == "msf":
# Register Tree constrains
constrain_tree = "(%s, (%s));" %(','.join(sorted(task.out_seqs)),
','.join(sorted(task.target_seqs)))
_outs = "\n".join(map(lambda name: ">%s\n0" %name, sorted(task.out_seqs)))
_tars = "\n".join(map(lambda name: ">%s\n1" %name, sorted(task.target_seqs)))
constrain_alg = '\n'.join([_outs, _tars])
db.add_task_data(nodeid, DATATYPES.constrain_tree, constrain_tree)
db.add_task_data(nodeid, DATATYPES.constrain_alg, constrain_alg)
db.dataconn.commit() # since the creation of some Task
# objects may require this info, I need
# to commit right now.
# Register node
db.add_node(task.threadid,
task.nodeid, task.cladeid,
task.target_seqs,
task.out_seqs)
nodeid2info[nodeid]["size"] = task.size
nodeid2info[nodeid]["target_seqs"] = task.target_seqs
nodeid2info[nodeid]["out_seqs"] = task.out_seqs
alg_task = alignerclass(nodeid, task.multiseq_file,
seqtype, conf, alignerconf)
alg_task.size = task.size
new_tasks.append(alg_task)
elif ttype == "alg" or ttype == "acleaner":
if ttype == "alg":
nodeid2info[nodeid]["alg_path"] = task.alg_fasta_file
elif ttype == "acleaner":
nodeid2info[nodeid]["alg_clean_path"] = task.clean_alg_fasta_file
alg_fasta_file = getattr(task, "clean_alg_fasta_file",
task.alg_fasta_file)
alg_phylip_file = getattr(task, "clean_alg_phylip_file",
task.alg_phylip_file)
# Calculate alignment stats
# cons_mean, cons_std = get_trimal_conservation(task.alg_fasta_file,
# conf["app"]["trimal"])
#
# max_identity = get_trimal_identity(task.alg_fasta_file,
# conf["app"]["trimal"])
# log.info("Conservation: %0.2f +-%0.2f", cons_mean, cons_std)
# log.info("Max. Identity: %0.2f", max_identity)
#import time
#t1 = time.time()
#mx, mn, mean, std = get_identity(task.alg_fasta_file)
#print time.time()-t1
#log.log(26, "Identity: max=%0.2f min=%0.2f mean=%0.2f +- %0.2f",
# mx, mn, mean, std)
#t1 = time.time()
if seqtype == "aa" and npr_conf.switch_aa_similarity < 1:
try:
alg_stats = db.get_task_data(taskid, DATATYPES.alg_stats)
except Exception, e:
alg_stats = {}
if ttype == "alg":
algfile = pjoin(GLOBALS["input_dir"], task.alg_phylip_file)
dataid = DATATYPES.alg_phylip
elif ttype == "acleaner":
algfile = pjoin(GLOBALS["input_dir"], task.clean_alg_phylip_file)
dataid = DATATYPES.clean_alg_phylip
if "i_mean" not in alg_stats:
log.log(24, "Calculating alignment stats...")
# dump data if necesary
algfile = pjoin(GLOBALS["input_dir"], task.alg_phylip_file)
if not pexist(algfile):
# dump phylip alg
open(algfile, "w").write(db.get_data(db.get_dataid(taskid, dataid)))
mx, mn, mean, std = get_statal_identity(algfile,
conf["app"]["statal"])
alg_stats = {"i_max":mx, "i_mean":mean, "i_min":mn, "i_std":std}
db.add_task_data(taskid, DATATYPES.alg_stats, alg_stats)
log.log(22, "Alignment stats (sequence similarity):")
log.log(22, " max: %(i_max)0.2f, min:%(i_min)0.2f, avg:%(i_mean)0.2f+-%(i_std)0.2f" %
(alg_stats))
else:
alg_stats = {"i_max":-1, "i_mean":-1, "i_min":-1, "i_std":-1}
#print time.time()-t1
#log.log(24, "Identity: max=%0.2f min=%0.2f mean=%0.2f +- %0.2f",
# mx, mn, mean, std)
task.max_ident = alg_stats["i_max"]
task.min_ident = alg_stats["i_min"]
task.mean_ident = alg_stats["i_mean"]
task.std_ident = alg_stats["i_std"]
next_task = None
if ttype == "alg" and cleanerclass:
next_task = cleanerclass(nodeid, seqtype, alg_fasta_file,
alg_phylip_file,
conf, cleanerconf)
else:
# Converts aa alignment into nt if necessary
if seqtype == "aa" and \
"nt" in GLOBALS["seqtypes"] and \
task.mean_ident >= npr_conf.switch_aa_similarity:
log.log(28, "@@2:Switching to codon alignment!@@1: amino-acid sequence similarity: %0.2f >= %0.2f" %\
(task.mean_ident, npr_conf.switch_aa_similarity))
alg_fasta_file = "%s.%s" %(taskid, DATATYPES.alg_nt_fasta)
alg_phylip_file = "%s.%s" %(taskid, DATATYPES.alg_nt_phylip)
try:
alg_fasta_file = db.get_dataid(taskid, DATATYPES.alg_nt_fasta)
alg_fasta_file = db.get_dataid(taskid, DATATYPES.alg_nt_phylip)
except ValueError:
log.log(22, "Calculating codon alignment...")
source_alg = pjoin(GLOBALS["input_dir"], task.alg_fasta_file)
if ttype == "alg":
kept_columns = []
elif ttype == "acleaner":
# if original alignment was trimmed, use it as reference
# but make the nt alignment only on the kept columns
kept_columns = db.get_task_data(taskid, DATATYPES.kept_alg_columns)
if not pexist(source_alg):
open(source_alg, "w").write(db.get_task_data(taskid, DATATYPES.alg_fasta))
nt_alg = switch_to_codon(source_alg, kept_columns=kept_columns)
db.add_task_data(taskid, DATATYPES.alg_nt_fasta, nt_alg.write())
db.add_task_data(taskid, DATATYPES.alg_nt_phylip, nt_alg.write(format='iphylip_relaxed'))
npr_conf = IterConfig(conf, wkname, task.size, "nt")
seqtype = "nt"
if mtesterclass:
next_task = mtesterclass(nodeid, alg_fasta_file,
alg_phylip_file,
constrain_id,
conf, mtesterconf)
elif treebuilderclass:
next_task = treebuilderclass(nodeid, alg_phylip_file,
constrain_id,
None, seqtype,
conf, treebuilderconf)
if next_task:
next_task.size = task.size
new_tasks.append(next_task)
def schedule(workflow_task_processor, pending_tasks, schedule_time, execution, debug, norender):
# Adjust debug mode
if debug == "all":
log.setLevel(10)
pending_tasks = set(pending_tasks)
## ===================================
## INITIALIZE BASIC VARS
execution, run_detached = execution
thread2tasks = defaultdict(list)
for task in pending_tasks:
thread2tasks[task.configid].append(task)
expected_threads = set(thread2tasks.keys())
past_threads = {}
thread_errors = defaultdict(list)
## END OF VARS AND SHORTCUTS
## ===================================
cores_total = GLOBALS["_max_cores"]
if cores_total > 0:
job_queue = Queue()
back_launcher = Process(target=background_job_launcher,
args=(job_queue, run_detached,
GLOBALS["launch_time"], cores_total))
back_launcher.start()
else:
job_queue = None
back_launcher = None
GLOBALS["_background_scheduler"] = back_launcher
GLOBALS["_job_queue"] = job_queue
# Captures Ctrl-C for debuging DEBUG
#signal.signal(signal.SIGINT, control_c)
last_report_time = None
BUG = set()
try:
# Enters into task scheduling
while pending_tasks:
wtime = schedule_time
# ask SGE for running jobs
if execution == "sge":
sgeid2jobs = db.get_sge_tasks()
qstat_jobs = sge.qstat()
else:
qstat_jobs = None
# Show summary of pending tasks per thread
thread2tasks = defaultdict(list)
for task in pending_tasks:
thread2tasks[task.configid].append(task)
set_logindent(0)
log.log(28, "@@13: Updating tasks status:@@1: (%s)" % (ctime()))
info_lines = []
for tid, tlist in thread2tasks.iteritems():
threadname = GLOBALS[tid]["_name"]
sizelist = ["%s" %getattr(_ts, "size", "?") for _ts in tlist]
info = "Thread @@13:%s@@1:: pending tasks: @@8:%s@@1: of sizes: %s" %(
threadname, len(tlist), ', '.join(sizelist))
info_lines.append(info)
for line in info_lines:
log.log(28, line)
if GLOBALS["email"] and last_report_time is None:
last_report_time = time()
send_mail(GLOBALS["email"], "Your NPR process has started", '\n'.join(info_lines))
## ================================
## CHECK AND UPDATE CURRENT TASKS
checked_tasks = set()
check_start_time = time()
to_add_tasks = set()
GLOBALS["cached_status"] = {}
for task in sorted(pending_tasks, sort_tasks):
# Avoids endless periods without new job submissions
elapsed_time = time() - check_start_time
#if not back_launcher and pending_tasks and \
# elapsed_time > schedule_time * 2:
# log.log(26, "@@8:Interrupting task checks to schedule new jobs@@1:")
# db.commit()
# wtime = launch_jobs(sorted(pending_tasks, sort_tasks),
# execution, run_detached)
# check_start_time = time()
# Enter debuging mode if necessary
if debug and log.level > 10 and task.taskid.startswith(debug):
log.setLevel(10)
log.debug("ENTERING IN DEBUGGING MODE")
thread2tasks[task.configid].append(task)
# Update tasks and job statuses
if task.taskid not in checked_tasks:
try:
show_task_info(task)
task.status = task.get_status(qstat_jobs)
db.dataconn.commit()
if back_launcher and task.status not in set("DE"):
for j, cmd in task.iter_waiting_jobs():
j.status = "Q"
GLOBALS["cached_status"][j.jobid] = "Q"
if j.jobid not in BUG:
if not os.path.exists(j.jobdir):
os.makedirs(j.jobdir)
for ifile, outpath in j.input_files.iteritems():
try:
_tid, _did = ifile.split(".")
_did = int(_did)
except (IndexError, ValueError):
dataid = ifile
else:
dataid = db.get_dataid(_tid, _did)
if not outpath:
outfile = pjoin(GLOBALS["input_dir"], ifile)
else:
outfile = pjoin(outpath, ifile)
if not os.path.exists(outfile):
open(outfile, "w").write(db.get_data(dataid))
log.log(24, " @@8:Queueing @@1: %s from %s" %(j, task))
job_queue.put([j.jobid, j.cores, cmd, j.status_file])
BUG.add(j.jobid)
update_task_states_recursively(task)
db.commit()
checked_tasks.add(task.taskid)
except TaskError, e:
log.error("Errors found in %s" %task)
import traceback
traceback.print_exc()
if GLOBALS["email"]:
threadname = GLOBALS[task.configid]["_name"]
send_mail(GLOBALS["email"], "Errors found in %s!" %threadname,
'\n'.join(map(str, [task, e.value, e.msg])))
pending_tasks.discard(task)
thread_errors[task.configid].append([task, e.value, e.msg])
continue
else:
# Set temporary Queued state to avoids launching
# jobs from clones
task.status = "Q"
if log.level < 24:
show_task_info(task)
if task.status == "D":
#db.commit()
show_task_info(task)
logindent(3)
# Log commands of every task
if 'cmd_log_file' not in GLOBALS[task.configid]:
GLOBALS[task.configid]['cmd_log_file'] = pjoin(GLOBALS[task.configid]["_outpath"], "cmd.log")
O = open(GLOBALS[task.configid]['cmd_log_file'], "w")
O.close()
cmd_lines = get_cmd_log(task)
CMD_LOG = open(GLOBALS[task.configid]['cmd_log_file'], "a")
print >>CMD_LOG, task
for c in cmd_lines:
print >>CMD_LOG, ' '+'\t'.join(map(str, c))
CMD_LOG.close()
#
try:
#wkname = GLOBALS[task.configid]['_name']
create_tasks = workflow_task_processor(task, task.target_wkname)
except TaskError, e:
log.error("Errors found in %s" %task)
pending_tasks.discard(task)
thread_errors[task.configid].append([task, e.value, e.msg])
continue
else:
logindent(-3)
to_add_tasks.update(create_tasks)
pending_tasks.discard(task)
elif task.status == "E":
log.error("task contains errors: %s " %task)
log.error("Errors found in %s")
pending_tasks.discard(task)
thread_errors[task.configid].append([task, None, "Found (E) task status"])
