Python qutils.label_from_fpath函数代码示例

def save_features_in_contigs(output_dirpath, contigs_fpaths, feature_name, features_in_contigs, ref_features_num):
    return save(join(output_dirpath, feature_name + in_contigs_suffix_fn), {
        'filenames': [qutils.label_from_fpath(label) for label in contigs_fpaths],
        feature_name + '_in_contigs': dict((qutils.label_from_fpath(contigs_fpath), feature_amounts)
                                           for (contigs_fpath, feature_amounts) in features_in_contigs.items()),
        'ref_' + feature_name + '_number': ref_features_num,
    })

def draw_coverage_histograms(coverage_dict, contigs_fpaths, output_dirpath):
    total_len = dict()
    contigs_dict = dict()

    contigs_with_coverage = [contigs_fpath for contigs_fpath in contigs_fpaths if coverage_dict[contigs_fpath]]
    for contigs_fpath in contigs_fpaths:
        total_len[contigs_fpath] = reporting.get(contigs_fpath).get_field(reporting.Fields.TOTALLEN)
        contigs_dict[contigs_fpath] = reporting.get(contigs_fpath).get_field(reporting.Fields.CONTIGS)
    cov_values = [coverage_dict[contigs_fpath] for contigs_fpath in contigs_with_coverage]
    num_contigs = [contigs_dict[contigs_fpath] for contigs_fpath in contigs_with_coverage]

    common_coverage_values, bin_size, low_threshold, high_threshold, max_cov = binning_coverage(cov_values, num_contigs)
    histogram_title = 'Coverage histogram (bin size: ' + str(bin_size) + 'x)'
    plotter.coverage_histogram(contigs_with_coverage, common_coverage_values, output_dirpath + '/coverage_histogram',
                               histogram_title, bin_size=bin_size, max_cov=max_cov, low_threshold=low_threshold, high_threshold=high_threshold)
    for contigs_fpath in contigs_with_coverage:
        coverage_values, bin_size, low_threshold, high_threshold, max_cov = binning_coverage([coverage_dict[contigs_fpath]],
                                                                                             [contigs_dict[contigs_fpath]])
        label = qutils.label_from_fpath(contigs_fpath)
        corr_label = qutils.label_from_fpath_for_fname(contigs_fpath)
        histogram_title = label + ' coverage histogram (bin size: ' + str(bin_size) + 'x)'
        histogram_fpath = os.path.join(output_dirpath, corr_label + '_coverage_histogram')
        plotter.coverage_histogram([contigs_fpath], coverage_values, histogram_fpath,
                                   histogram_title, draw_bars=True, bin_size=bin_size, max_cov=max_cov,
                                   low_threshold=low_threshold, high_threshold=high_threshold)

def save_contigs_lengths(output_dirpath, contigs_fpaths, lists_of_lengths):
    lists_of_lengths = [sorted(list, reverse=True) for list in lists_of_lengths]

    return save(join(output_dirpath, contigs_lengths_fn), {
        'filenames': [qutils.label_from_fpath(label) for label in contigs_fpaths],
        'lists_of_lengths': lists_of_lengths
    })

def save_coord(output_dirpath, coord_x, coord_y, name_coord, contigs_fpaths):
    coord_fn = name_coord + suffix_fn
    return save(join(output_dirpath, coord_fn), {
        'coord_x': coord_x,
        'coord_y': coord_y,
        'filenames': [qutils.label_from_fpath(label) for label in contigs_fpaths]
    })

def get_assemblies_data(contigs_fpaths, icarus_dirpath, stdout_pattern, nx_marks):
    assemblies_n50 = defaultdict(dict)
    assemblies_data = ''
    assemblies_data += 'var assemblies_links = {};\n'
    assemblies_data += 'var assemblies_len = {};\n'
    assemblies_data += 'var assemblies_contigs = {};\n'
    assemblies_data += 'var assemblies_misassemblies = {};\n'
    assemblies_data += 'var assemblies_n50 = {};\n'
    assemblies_contig_size_data = ''
    for contigs_fpath in contigs_fpaths:
        assembly_label = qutils.label_from_fpath(contigs_fpath)
        report = reporting.get(contigs_fpath)
        l = report.get_field(reporting.Fields.TOTALLEN)
        contigs = report.get_field(reporting.Fields.CONTIGS)
        n50 = report.get_field(reporting.Fields.N50)
        if stdout_pattern:
            contig_stdout_fpath = stdout_pattern % qutils.label_from_fpath_for_fname(contigs_fpath) + '.stdout'
            contig_stdout_fpath = qutils.relpath(contig_stdout_fpath, icarus_dirpath)
            assemblies_data += 'assemblies_links["' + assembly_label + '"] = "' + contig_stdout_fpath + '";\n'
        assemblies_contig_size_data += 'assemblies_len["' + assembly_label + '"] = ' + str(l) + ';\n'
        assemblies_contig_size_data += 'assemblies_contigs["' + assembly_label + '"] = ' + str(contigs) + ';\n'
        assemblies_contig_size_data += 'assemblies_n50["' + assembly_label + '"] = "' + str(n50) + '";\n'
        for nx in nx_marks:
            assemblies_n50[assembly_label][nx] = report.get_field(nx)
    return assemblies_data, assemblies_contig_size_data, assemblies_n50

def get_color_and_ls(fpath, label=None):
    from quast_libs import qutils
    if not label:
        label = qutils.label_from_fpath(fpath)
    if not dict_color_and_ls:
        return None, None
    """
    Returns tuple: color, line style
    """
    return dict_color_and_ls[label]

def parallel_partition_contigs(asm, assemblies_by_ref, corrected_dirpath, alignments_fpath_template):
    assembly_label = qutils.label_from_fpath(asm.fpath)
    corr_assembly_label = qutils.label_from_fpath_for_fname(asm.fpath)
    logger.info('  ' + 'processing ' + assembly_label)
    added_ref_asm = []
    not_aligned_fname = corr_assembly_label + '_not_aligned_anywhere.fasta'
    not_aligned_fpath = os.path.join(corrected_dirpath, not_aligned_fname)
    contigs = {}
    aligned_contig_names = set()
    aligned_contigs_for_each_ref = {}
    contigs_seq = fastaparser.read_fasta_one_time(asm.fpath)
    alignments_fpath = alignments_fpath_template % corr_assembly_label
    if os.path.exists(alignments_fpath):
        with open(alignments_fpath) as f:
            for line in f:
                values = line.split()
                if values[0] in contigs_analyzer.ref_labels_by_chromosomes.keys():
                    ref_name = contigs_analyzer.ref_labels_by_chromosomes[values[0]]
                    ref_contigs_names = values[1:]
                    ref_contigs_fpath = os.path.join(
                        corrected_dirpath, corr_assembly_label + '_to_' + ref_name + '.fasta')
                    if ref_name not in aligned_contigs_for_each_ref:
                        aligned_contigs_for_each_ref[ref_name] = []

                    for (cont_name, seq) in contigs_seq:
                        if not cont_name in contigs:
                            contigs[cont_name] = seq

                        if cont_name in ref_contigs_names and cont_name not in aligned_contigs_for_each_ref[ref_name]:
                            # Collecting all aligned contigs names in order to further extract not aligned
                            aligned_contig_names.add(cont_name)
                            aligned_contigs_for_each_ref[ref_name].append(cont_name)
                            fastaparser.write_fasta(ref_contigs_fpath, [(cont_name, seq)], 'a')

                    ref_asm = Assembly(ref_contigs_fpath, assembly_label)
                    if ref_asm.name not in added_ref_asm:
                        if ref_name in assemblies_by_ref:
                            assemblies_by_ref[ref_name].append(ref_asm)
                            added_ref_asm.append(ref_asm.name)
        if qconfig.space_efficient:
            os.remove(alignments_fpath)

    # Extraction not aligned contigs
    all_contigs_names = set(contigs.keys())
    not_aligned_contigs_names = all_contigs_names - aligned_contig_names
    fastaparser.write_fasta(not_aligned_fpath, [(name, contigs[name]) for name in not_aligned_contigs_names])

    not_aligned_asm = Assembly(not_aligned_fpath, asm.label)
    return assemblies_by_ref, not_aligned_asm

def do(contigs_fpaths, gene_lengths, out_dirpath):
    logger.print_timestamp()
    logger.main_info('Running GlimmerHMM...')

    tool_dirpath = os.path.join(qconfig.LIBS_LOCATION, 'glimmer')
    tmp_dirpath = os.path.join(out_dirpath, 'tmp')
    tool_exec_fpath = compile_glimmer(logger)
    if not tool_exec_fpath:
        return

    if not os.path.isdir(out_dirpath):
        os.makedirs(out_dirpath)
    if not os.path.isdir(tmp_dirpath):
        os.makedirs(tmp_dirpath)

    n_jobs = min(len(contigs_fpaths), qconfig.max_threads)
    if is_python2():
        from joblib import Parallel, delayed
    else:
        from joblib3 import Parallel, delayed
    if qconfig.memory_efficient:
        results = Parallel(n_jobs=n_jobs)(delayed(predict_genes)(
            index, contigs_fpath, gene_lengths, out_dirpath, tool_dirpath, tmp_dirpath)
            for index, contigs_fpath in enumerate(contigs_fpaths))
    else:
        results = [predict_genes(index, contigs_fpath, gene_lengths, out_dirpath, tool_dirpath, tmp_dirpath)
                   for index, contigs_fpath in enumerate(contigs_fpaths)]

    genes_by_labels = dict()
    # saving results
    for i, contigs_fpath in enumerate(contigs_fpaths):
        report = reporting.get(contigs_fpath)
        label = qutils.label_from_fpath(contigs_fpath)
        genes_by_labels[label], unique, full_genes, partial_genes = results[i]
        if unique is not None:
            report.add_field(reporting.Fields.PREDICTED_GENES_UNIQUE, unique)
        if full_genes is not None:
            genes = ['%s + %s part' % (full_cnt, partial_cnt) for full_cnt, partial_cnt in zip(full_genes, partial_genes)]
            report.add_field(reporting.Fields.PREDICTED_GENES, genes)
        if unique is None and full_genes is None:
            logger.error(
                'Glimmer failed running Glimmer for %s. ' + ('Run with the --debug option'
                ' to see the command line.' if not qconfig.debug else '') % label)

    if not qconfig.debug:
        shutil.rmtree(tmp_dirpath)

    logger.main_info('Done.')
    return genes_by_labels

def correct_assemblies(contigs_fpaths, output_dirpath, labels):
    corrected_dirpath = os.path.join(output_dirpath, qconfig.corrected_dirname)
    # we need correction but do not need min-contig filtration
    min_contig = qconfig.min_contig
    qconfig.min_contig = 0
    corrected_contigs_fpaths, old_contigs_fpaths = qutils.correct_contigs(contigs_fpaths, corrected_dirpath, labels, reporting=None)
    qconfig.min_contig = min_contig
    assemblies = [Assembly(fpath, qutils.label_from_fpath(fpath)) for fpath in old_contigs_fpaths]
    corrected_labels = [asm.label for asm in assemblies]

    if qconfig.draw_plots or qconfig.html_report:
        corr_fpaths = [asm.fpath for asm in assemblies]
        corr_labels = [asm.label for asm in assemblies]
        plotter_data.save_colors_and_ls(corr_fpaths, labels=corr_labels)
    return assemblies, corrected_labels

def save_colors(results_dirpath, contigs_fpaths, dict_colors, meta=False):  # coordinates for Nx, NAx, NGx, NGAX
    if meta:
        html_fpath = os.path.join(results_dirpath, report_fname)
        with open(html_fpath) as f_html:
            html_text = f_html.read()
        html_text = re.sub('{{ ' + 'colors' + ' }}', 'standard_colors', html_text)
        html_text = re.sub('{{ ' + 'broken_scaffolds' + ' }}', '[]', html_text)
        with open(html_fpath, 'w') as f_html:
            f_html.write(html_text)
    else:
        contig_labels = [qutils.label_from_fpath(contigs_fpath) for contigs_fpath in contigs_fpaths]
        colors_and_ls = [dict_colors[contig_label] for contig_label in contig_labels]
        colors = [color_and_ls[0] for color_and_ls in colors_and_ls]
        colors_for_html = [html_colors[plotter_data.colors.index(color)] for color in colors]
        save_record(results_dirpath, 'colors', colors_for_html)
        broken_contig_names = [label for i, label in enumerate(contig_labels) if colors_and_ls[i][1] == secondary_line_style]
        save_record(results_dirpath, 'broken_scaffolds', broken_contig_names)

def calculate_ave_read_support(combined_output_dirpath, assemblies):
    unique_contigs_fpath = os.path.join(combined_output_dirpath, 'contigs_reports', qconfig.unique_contigs_fname_pattern)
    for assembly in assemblies:
        aligned_contigs_by_ref = dict()
        assembly_label = qutils.label_from_fpath(assembly.fpath)
        corr_assembly_label = qutils.label_from_fpath_for_fname(assembly.fpath)
        with open(unique_contigs_fpath % corr_assembly_label) as in_f:
            for line in in_f:
                ref_name, contig_len, contig_cov = line.strip().split('\t')
                aligned_contigs_by_ref.setdefault(ref_name, []).append((float(contig_len), float(contig_cov)))
        for ref_name, contigs in aligned_contigs_by_ref.items():
            ref_cov = sum(contig_cov * aligned_len for (aligned_len, contig_cov) in contigs)
            ref_cov /= sum(aligned_len for (aligned_len, contig_cov) in contigs)
            corr_assembly_label = qutils.label_from_fpath_for_fname(assembly.fpath)
            ref_contigs_fpath = os.path.join(
                        os.path.dirname(assembly.fpath), corr_assembly_label + '_to_' + ref_name + '.fasta')
            qconfig.assembly_labels_by_fpath[ref_contigs_fpath] = assembly_label
            report = reporting.get(ref_contigs_fpath, ref_name=ref_name)
            report.add_field(reporting.Fields.AVE_READ_SUPPORT, '%.2f' % ref_cov)

def do(contigs_fpaths, gene_lengths, out_dirpath):
    logger.print_timestamp()
    logger.main_info('Running GlimmerHMM...')

    tool_dirpath = os.path.join(qconfig.LIBS_LOCATION, 'glimmer')
    tmp_dirpath = os.path.join(out_dirpath, 'tmp')
    tool_exec_fpath = compile_glimmer(logger)
    if not tool_exec_fpath:
        return

    if not os.path.isdir(out_dirpath):
        os.makedirs(out_dirpath)
    if not os.path.isdir(tmp_dirpath):
        os.makedirs(tmp_dirpath)

    n_jobs = min(len(contigs_fpaths), qconfig.max_threads)
    parallel_args = [(index, contigs_fpath, gene_lengths, out_dirpath, tool_dirpath, tool_exec_fpath, tmp_dirpath)
                     for index, contigs_fpath in enumerate(contigs_fpaths)]
    genes_list, unique, full_genes, partial_genes = run_parallel(predict_genes, parallel_args, n_jobs)

    genes_by_labels = dict()
    # saving results
    for i, contigs_fpath in enumerate(contigs_fpaths):
        report = reporting.get(contigs_fpath)
        label = qutils.label_from_fpath(contigs_fpath)
        genes_by_labels[label] = genes_list[i]
        if unique[i] is not None:
            report.add_field(reporting.Fields.PREDICTED_GENES_UNIQUE, unique[i])
        if full_genes[i] is not None:
            genes = ['%s + %s part' % (full_cnt, partial_cnt) for full_cnt, partial_cnt in zip(full_genes[i], partial_genes[i])]
            report.add_field(reporting.Fields.PREDICTED_GENES, genes)
        if unique[i] is None and full_genes[i] is None:
            logger.error(
                'Failed running Glimmer for %s. ' % label + ('Run with the --debug option'
                ' to see the command line.' if not qconfig.debug else ''))

    if not qconfig.debug:
        shutil.rmtree(tmp_dirpath)

    logger.main_info('Done.')
    return genes_by_labels

def save_total_report(output_dirpath, min_contig, ref_fpath):
    from quast_libs import reporting
    asm_names = [qutils.label_from_fpath(this) for this in reporting.assembly_fpaths]
    report = reporting.table(reporting.Fields.grouped_order)
    subreports = []
    ref_names = []
    if qconfig.is_combined_ref and ref_labels_by_chromosomes:
        ref_names = sorted(list(set([ref for ref in ref_labels_by_chromosomes.values()])))
        subreports = [reporting.table(reporting.Fields.grouped_order, ref_name=ref_name) for ref_name in ref_names]
    t = datetime.datetime.now()

    return save(join(output_dirpath, total_report_fname), {
        'date': t.strftime('%d %B %Y, %A, %H:%M:%S'),
        'assembliesNames': asm_names,
        'referenceName': qutils.name_from_fpath(ref_fpath) if ref_fpath else '',
        'order': [i for i, _ in enumerate(asm_names)],
        'report': report,
        'subreferences': ref_names,
        'subreports': subreports,
        'minContig': min_contig
    })

def main(args):
    check_dirpath(qconfig.QUAST_HOME, 'You are trying to run it from ' + str(qconfig.QUAST_HOME) + '.\n' +
                  'Please, put QUAST in a different directory, then try again.\n', exit_code=3)

    if not args:
        qconfig.usage(stream=sys.stderr)
        sys.exit(1)

    metaquast_path = [os.path.realpath(__file__)]
    quast_py_args, contigs_fpaths = parse_options(logger, metaquast_path + args)
    output_dirpath, ref_fpaths, labels = qconfig.output_dirpath, qconfig.reference, qconfig.labels
    html_report = qconfig.html_report
    test_mode = qconfig.test

    # Directories
    output_dirpath, _, _ = qutils.set_up_output_dir(
        output_dirpath, None, not output_dirpath,
        save_json=False)

    corrected_dirpath = os.path.join(output_dirpath, qconfig.corrected_dirname)

    qconfig.set_max_threads(logger)
    qutils.logger = logger

    ########################################################################

    from quast_libs import reporting
    try:
        import imp
        imp.reload(reporting)
    except:
        reload(reporting)
    from quast_libs import plotter

    if os.path.isdir(corrected_dirpath):
        shutil.rmtree(corrected_dirpath)
    os.mkdir(corrected_dirpath)

    # PROCESSING REFERENCES
    if ref_fpaths:
        logger.main_info()
        logger.main_info('Reference(s):')

        corrected_ref_fpaths, combined_ref_fpath, chromosomes_by_refs, ref_names =\
            correct_meta_references(ref_fpaths, corrected_dirpath)

    # PROCESSING CONTIGS
    logger.main_info()
    logger.main_info('Contigs:')
    qconfig.no_check_meta = True
    assemblies, labels = correct_assemblies(contigs_fpaths, output_dirpath, labels)
    if not assemblies:
        logger.error("None of the assembly files contains correct contigs. "
                     "Please, provide different files or decrease --min-contig threshold.")
        return 4

    # Running QUAST(s)
    if qconfig.gene_finding:
        quast_py_args += ['--mgm']
    if qconfig.min_IDY is None: # special case: user not specified min-IDY, so we need to use MetaQUAST default value
        quast_py_args += ['--min-identity', str(qconfig.META_MIN_IDY)]

    downloaded_refs = False

    # SEARCHING REFERENCES
    if not ref_fpaths:
        logger.main_info()
        if qconfig.max_references == 0:
            logger.notice("Maximum number of references (--max-ref-number) is set to 0, search in SILVA 16S rRNA database is disabled")
        else:
            if qconfig.references_txt:
                logger.main_info("List of references was provided, starting to download reference genomes from NCBI...")
            else:
                logger.main_info("No references are provided, starting to search for reference genomes in SILVA 16S rRNA database "
                        "and to download them from NCBI...")
            downloaded_dirpath = os.path.join(output_dirpath, qconfig.downloaded_dirname)
            if not os.path.isdir(downloaded_dirpath):
                os.mkdir(downloaded_dirpath)
            corrected_dirpath = os.path.join(output_dirpath, qconfig.corrected_dirname)
            ref_fpaths = search_references_meta.do(assemblies, labels, downloaded_dirpath, corrected_dirpath, qconfig.references_txt)
            if ref_fpaths:
                search_references_meta.is_quast_first_run = True
                if not qconfig.references_txt:
                    downloaded_refs = True
                logger.main_info()
                logger.main_info('Downloaded reference(s):')
                corrected_ref_fpaths, combined_ref_fpath, chromosomes_by_refs, ref_names =\
                    correct_meta_references(ref_fpaths, corrected_dirpath, downloaded_refs=True)
            elif test_mode and not ref_fpaths:
                logger.error('Failed to download or setup SILVA 16S rRNA database for working without '
                             'references on metagenome datasets!', to_stderr=True, exit_with_code=4)

    if not ref_fpaths:
        # No references, running regular quast with MetaGenemark gene finder
        logger.main_info()
        logger.notice('No references are provided, starting regular QUAST with MetaGeneMark gene finder')
        assemblies = [Assembly(fpath, qutils.label_from_fpath(fpath)) for fpath in contigs_fpaths]
        _start_quast_main(quast_py_args, assemblies=assemblies, output_dirpath=output_dirpath, run_regular_quast=True)
        exit(0)

#.........这里部分代码省略.........

def save_combined_ref_stats(results, contigs_fpaths, ref_labels_by_chromosomes, output_dir, logger):
    istranslocations_by_asm = [result['istranslocations_by_refs'] if result else None for result in results]
    misassemblies_by_asm = [result['misassemblies_by_ref'] if result else None for result in results]
    all_refs = []
    for ref in ref_labels_by_chromosomes.values():
        if ref not in all_refs:
            all_refs.append(ref)
    if not qconfig.use_input_ref_order:
        all_refs.sort()
    misassemblies_by_refs_rows = []
    row = {'metricName': 'References', 'values': all_refs}
    misassemblies_by_refs_rows.append(row)
    if not istranslocations_by_asm:
        return
    for i, fpath in enumerate(contigs_fpaths):
        label = qutils.label_from_fpath(fpath)
        row = {'metricName': label, 'values': []}
        misassemblies_by_refs_rows.append(row)
        istranslocations_by_ref = istranslocations_by_asm[i]
        intergenomic_misassemblies_by_asm[label] = defaultdict(list)
        for ref in all_refs:
            intergenomic_misassemblies_by_asm[label][ref] = misassemblies_by_asm[i][ref] if misassemblies_by_asm[i] else []
        if istranslocations_by_ref:
            assembly_name = qutils.name_from_fpath(fpath)
            all_rows = []
            row = {'metricName': 'References', 'values': [ref_num + 1 for ref_num in range(len(all_refs))]}
            all_rows.append(row)
            for ref in all_refs:
                row = {'metricName': ref, 'values': []}
                for second_ref in all_refs:
                    if ref == second_ref or second_ref not in istranslocations_by_ref:
                        row['values'].append(None)
                    else:
                        row['values'].append(istranslocations_by_ref[ref][second_ref])
                possible_misassemblies = 0
                misassemblies_by_ref = misassemblies_by_asm[i]
                if misassemblies_by_ref:
                    possible_misassemblies = misassemblies_by_ref[ref].count(Misassembly.POSSIBLE_MISASSEMBLIES)
                istranslocations = max(0, sum([r for r in row['values'] if r]))
                misassemblies_by_refs_rows[-1]['values'].append(istranslocations + possible_misassemblies)
                all_rows.append(row)
            misassembly_by_ref_fpath = os.path.join(output_dir, 'interspecies_translocations_by_refs_%s.info' % assembly_name)
            with open(misassembly_by_ref_fpath, 'w') as misassembly_by_ref_file:
                misassembly_by_ref_file.write('Number of interspecies translocations by references: \n')
            print_file(all_rows, misassembly_by_ref_fpath, append_to_existing_file=True)

            with open(misassembly_by_ref_fpath, 'a') as misassembly_by_ref_file:
                misassembly_by_ref_file.write('References:\n')
                for ref_num, ref in enumerate(all_refs):
                    misassembly_by_ref_file.write(str(ref_num + 1) + ' - ' + ref + '\n')
            logger.info('  Information about interspecies translocations by references for %s is saved to %s' %
                        (assembly_name, misassembly_by_ref_fpath))
    misassemblies = []
    if qconfig.draw_plots:
        from quast_libs import plotter

        aligned_contigs_labels = []
        for row in misassemblies_by_refs_rows[1:]:
            if row['values']:
                aligned_contigs_labels.append(row['metricName'])
            else:
                misassemblies_by_refs_rows.remove(row)
        for i in range(len(all_refs)):
            cur_results = []
            for row in misassemblies_by_refs_rows[1:]:
                if row['values']:
                    cur_results.append(row['values'][i])
            misassemblies.append(cur_results)
        is_translocations_plot_fpath = os.path.join(output_dir, 'intergenomic_misassemblies')
        plotter.draw_meta_summary_plot('', output_dir, aligned_contigs_labels, all_refs,
                                       misassemblies, is_translocations_plot_fpath,
                                       title='Intergenomic misassemblies (found and supposed)', reverse=False,
                                       yaxis_title=None, print_all_refs=True, logger=logger)