def parse_spades_version(sample_name_):
log_file = [
i for i in Utilities.scan_whole_dir(
"/data1/bio/projects/vradchenko/lactobacillus_salivarius/pga-pe/log"
)
if i.endswith(".log") and all(j in i for j in ["spades", sample_name_])
][0]
log_lines = Utilities.load_list(log_file)
image_version_line = [
i for i in log_lines
if i.strip().startswith("Status: Image is up to date for ")
][0].strip()
spades_version = re.split("[\t ]+", image_version_line)[-1]
return spades_version
d["is_correlation_valid"] = True
return _process_out()
try:
print("Running on the node {}".format(os.uname()[1]))
except:
pass
sleep(np.random.randint(90))
print("Polling the queue")
remote_queue = os.path.join(ProjectDescriber.DATA_DIR, "correlation_data",
"group_datasets", "tables.txt")
correlation_tables = Utilities.remove_empty_values(
Utilities.load_list(remote_queue))
if len(correlation_tables) == 0:
print("Empty remote queue")
sys.exit(0)
Utilities.dump_list(correlation_tables[1:], remote_queue)
correlation_table = correlation_tables[0]
print("Now processing: '{}'".format(correlation_table))
group_name = os.path.splitext(os.path.basename(correlation_table))[0]
out_dir = os.path.join(ProjectDescriber.DATA_DIR, "correlation_data",
"group_results", group_name)
correlation_df = load_tsv(correlation_table).dropna(axis=0, how="any")
feature_groups = sorted(set([i.split("@")[0] for i in correlation_df.columns]))
