def update_distance_matrix(config_dict, args):
logger = logging.getLogger('snapperdb.snpdb.update_distance_matrix')
logger.info('Inititialising SnpDB Class')
snpdb = SNPdb(config_dict)
snpdb.parse_config_dict(config_dict)
snpdb._connect_to_snpdb()
logger.info('Getting strains')
strain_list, update_strain, all_strains = snpdb.get_strains()
# # get_all_good_ids from snpdb2 takes a snp cutoff as well, here, we don't have a SNP cutoff so we set it arbitrarily high.
snp_co = '1000000'
if all_strains or len(update_strain) > 1:
if update_strain:
print "### Populating distance matrix: " + str(
datetime.datetime.now())
snpdb.parse_args_for_update_matrix(snp_co, strain_list)
if args.hpc == 'N':
print '### Launching serial update_distance_matrix ' + str(
datetime.datetime.now())
snpdb.check_matrix(strain_list, update_strain)
snpdb.update_clusters()
else:
print '### Launching parallel update_distance_matrix ' + str(
datetime.datetime.now())
present_stains = list(set(strain_list) - set(update_strain))
for idx, one_strain in enumerate(
chunks(list(update_strain), int(args.hpc))):
snpdb.write_qsubs_to_check_matrix(
args, idx, one_strain, present_stains,
config_dict['snpdb_name'])
snpdb.check_matrix(update_strain, update_strain)
else:
print '### Nothing to update ' + str(datetime.datetime.now())
else:
print '### Nothing to update ' + str(datetime.datetime.now())
def update_clusters(config_dict):
snpdb = SNPdb(config_dict)
snpdb.parse_config_dict(config_dict)
snpdb._connect_to_snpdb()
snpdb.update_clusters()