def test_final_summary(self):
pkl = os.path.join(self.testfiles_dir, AMPLE_PKL)
if not os.path.isfile(pkl): return
with open(pkl) as f:
d = cPickle.load(f)
summary = mrbump_util.finalSummary(d)
self.assertIsNotNone(summary)
def molecular_replacement(self, optd):
if not optd['mrbump_scripts']:
# MRBUMP analysis of the ensembles
logger.info('----- Running MRBUMP on ensembles--------\n\n')
if len(optd['ensembles']) < 1:
msg = "ERROR! Cannot run MRBUMP as there are no ensembles!"
exit_util.exit_error(msg)
if optd['mrbump_dir'] is None:
bump_dir = os.path.join(optd['work_dir'], 'MRBUMP')
optd['mrbump_dir'] = bump_dir
else:
bump_dir = optd['mrbump_dir']
if not os.path.exists(bump_dir):
os.mkdir(bump_dir)
optd['mrbump_results'] = []
logger.info("Running MRBUMP jobs in directory: %s", bump_dir)
# Set an ensemble-specific phaser_rms if required
if optd['phaser_rms'] == 'auto':
ensembler.set_phaser_rms_from_subcluster_score(optd)
# Sort the ensembles in a favourable way
logger.info("Sorting ensembles")
sort_keys = [
'cluster_num', 'truncation_level',
'subcluster_radius_threshold', 'side_chain_treatment'
]
ensemble_pdbs_sorted = ensembler.sort_ensembles(
optd['ensembles'],
optd['ensembles_data'],
keys=sort_keys,
prioritise=True)
# Create job scripts
logger.info("Generating MRBUMP runscripts")
optd['mrbump_scripts'] = mrbump_util.write_mrbump_files(
ensemble_pdbs_sorted,
optd,
job_time=mrbump_util.MRBUMP_RUNTIME,
ensemble_options=optd['ensemble_options'],
directory=bump_dir)
# Create function for monitoring jobs - static function decorator?
if self.ample_output:
def monitor():
r = mrbump_util.ResultsSummary()
r.extractResults(optd['mrbump_dir'], purge=bool(optd['purge']))
optd['mrbump_results'] = r.results
return self.ample_output.display_results(optd)
else:
monitor = None
# Save results here so that we have the list of scripts and mrbump directory set
ample_util.save_amoptd(optd)
# Change to mrbump directory before running
os.chdir(optd['mrbump_dir'])
ok = workers_util.run_scripts(
job_scripts=optd['mrbump_scripts'],
monitor=monitor,
check_success=mrbump_util.checkSuccess,
early_terminate=optd['early_terminate'],
nproc=optd['nproc'],
job_time=mrbump_util.MRBUMP_RUNTIME,
job_name='mrbump',
submit_cluster=optd['submit_cluster'],
submit_qtype=optd['submit_qtype'],
submit_queue=optd['submit_queue'],
submit_pe_lsf=optd['submit_pe_lsf'],
submit_pe_sge=optd['submit_pe_sge'],
submit_array=optd['submit_array'],
submit_max_array=optd['submit_max_array'])
if not ok:
msg = "An error code was returned after running MRBUMP on the ensembles!\n" + \
"For further information check the logs in directory: {0}".format(optd['mrbump_dir'])
logger.critical(msg)
# Collect the MRBUMP results
results_summary = mrbump_util.ResultsSummary()
optd['mrbump_results'] = results_summary.extractResults(
optd['mrbump_dir'], purge=bool(optd['purge']))
optd['success'] = results_summary.success
ample_util.save_amoptd(optd)
summary = mrbump_util.finalSummary(optd)
logger.info(summary)
def test_final_summary(self):
pkl = os.path.join(self.testfiles_dir, AMPLE_PKL)
if not os.path.isfile(pkl): return
with open(pkl) as f: d = pickle.load(f)
summary = mrbump_util.finalSummary(d)
self.assertIsNotNone(summary)
def molecular_replacement(self, optd):
mrbump_util.set_success_criteria(optd)
if not optd['mrbump_scripts']:
# MRBUMP analysis of the ensembles
logger.info('----- Running MRBUMP on ensembles--------\n\n')
if len(optd['ensembles']) < 1:
msg = "ERROR! Cannot run MRBUMP as there are no ensembles!"
exit_util.exit_error(msg)
if optd['mrbump_dir'] is None:
bump_dir = os.path.join(optd['work_dir'], 'MRBUMP')
optd['mrbump_dir'] = bump_dir
else:
bump_dir = optd['mrbump_dir']
if not os.path.exists(bump_dir):
os.mkdir(bump_dir)
optd['mrbump_results'] = []
logger.info("Running MRBUMP jobs in directory: %s", bump_dir)
# Set an ensemble-specific phaser_rms if required
if optd['phaser_rms'] == 'auto':
ensembler.set_phaser_rms_from_subcluster_score(optd)
# Sort the ensembles in a favourable way
logger.info("Sorting ensembles")
sort_keys = ['cluster_num', 'truncation_level', 'subcluster_radius_threshold', 'side_chain_treatment']
ensemble_pdbs_sorted = ensembler.sort_ensembles(
optd['ensembles'], optd['ensembles_data'], keys=sort_keys, prioritise=True)
# Create job scripts
logger.info("Generating MRBUMP runscripts")
optd['mrbump_scripts'] = mrbump_util.write_mrbump_files(
ensemble_pdbs_sorted,
optd,
job_time=mrbump_util.MRBUMP_RUNTIME,
ensemble_options=optd['ensemble_options'],
directory=bump_dir)
# Create function for monitoring jobs - static function decorator?
if self.ample_output:
def monitor():
r = mrbump_util.ResultsSummary()
r.extractResults(optd['mrbump_dir'], purge=bool(optd['purge']))
optd['mrbump_results'] = r.results
return self.ample_output.display_results(optd)
else:
monitor = None
# Save results here so that we have the list of scripts and mrbump directory set
ample_util.save_amoptd(optd)
# Change to mrbump directory before running
os.chdir(optd['mrbump_dir'])
ok = workers_util.run_scripts(
job_scripts=optd['mrbump_scripts'],
monitor=monitor,
check_success=mrbump_util.checkSuccess,
early_terminate=optd['early_terminate'],
nproc=optd['nproc'],
job_time=mrbump_util.MRBUMP_RUNTIME,
job_name='mrbump',
submit_cluster=optd['submit_cluster'],
submit_qtype=optd['submit_qtype'],
submit_queue=optd['submit_queue'],
submit_pe_lsf=optd['submit_pe_lsf'],
submit_pe_sge=optd['submit_pe_sge'],
submit_array=optd['submit_array'],
submit_max_array=optd['submit_max_array'])
if not ok:
msg = "An error code was returned after running MRBUMP on the ensembles!\n" + \
"For further information check the logs in directory: {0}".format(optd['mrbump_dir'])
logger.critical(msg)
# Collect the MRBUMP results
results_summary = mrbump_util.ResultsSummary()
optd['mrbump_results'] = results_summary.extractResults(optd['mrbump_dir'], purge=bool(optd['purge']))
optd['success'] = results_summary.success
ample_util.save_amoptd(optd)
summary = mrbump_util.finalSummary(optd)
logger.info(summary)