b=existing_files, c=sample_files)) output_dict[sample_name] = sample_files output_dict = dict(sorted(output_dict.items())) return output_dict # Create sampledata for Illumina raw reads raw_reads_dict = create_sampledata_dict(raw_reads_dirs) raw_reads_dict = { k: raw_reads_dict[k] for k in raw_reads_dict if "HP" in k and not os.path.isfile( "/data2/bio/Metagenomes/HG19/Unmapped_reads/{}_no_hg19.1.gz".format(k)) } Utilities.dump_2d_array([[k] + raw_reads_dict[k] for k in raw_reads_dict], file=projectDescriber.sampledata) # Prepare deploy charts launchGuideLiner = LaunchGuideLiner( charts_dir="{}{}/charts/".format( Utilities.ends_with_slash(projectDescriber.directory), "hg19"), deploy_prefix=projectDescriber.owner + "-hg19", nodes_number=7, threads_number="half", sampledata_file=projectDescriber.sampledata, refdata_file="/data/reference/homo_sapiens/hg/hg19/hg19.refdata", output_mask="hg19", output_dir="/data2/bio/Metagenomes/HG19") launchGuideLiner.generate_config() launchGuideLiner.get_deploy_guide() """
def dump_counter(counter: Counter, file: str): Utilities.dump_2d_array([("keyword", "occurrences")] + counter.most_common(), file=file)
def dump_groupdata_dict(groupdata: dict, file: str): array = [[j, k] for k in groupdata for j in groupdata[k] if len(groupdata[k]) > 0] Utilities.dump_2d_array(array=array, file=file)