How to use the biolib.common.alphanumeric_sort function in biolib

output_file : str
            Output file.
        """

        fout = open(output_file, 'w')
        fout.write('Genome id\tLength (bp)\t# sequences')
        for rank in self.rank_labels:
            fout.write('\t' + rank + ': taxa')
            fout.write('\t' + rank + ': percent of bps')
            fout.write('\t' + rank + ': percent of sequences')
            fout.write('\t' + rank + ': avg. evalue')
            fout.write('\t' + rank + ': avg. perc identity')
            fout.write('\t' + rank + ': avg. align length (AA)')
        fout.write('\n')

        sorted_genome_ids = alphanumeric_sort(self.profiles.keys())
        for genome_id in sorted_genome_ids:
            self.profiles[genome_id].write_genome_summary(fout)

        fout.close()

Output file.
        """

        fout = open(output_file, 'w')
        fout.write('Genome id\t# scaffolds\t# genes\tCoding bases')
        for rank in Taxonomy.rank_labels:
            fout.write('\t' + rank + ': taxon')
            fout.write('\t' + rank + ': % of scaffolds')
            fout.write('\t' + rank + ': % of genes')
            fout.write('\t' + rank + ': % of coding bases')
            fout.write('\t' + rank + ': avg. e-value')
            fout.write('\t' + rank + ': avg. % identity')
            fout.write('\t' + rank + ': avg. align. length (aa)')
        fout.write('\n')

        sorted_genome_ids = alphanumeric_sort(self.profiles.keys())
        for genome_id in sorted_genome_ids:
            self.profiles[genome_id].write_genome_summary(fout)

        fout.close()
        

def create_html_index(self, plot_dir, genome_plots):
        """Create HTML index for navigating outlier plots.

        Parameters
        ----------
        plot_dir : str
          Directory containing plots.
        genome_plots : d[genome_id] -> [(plot_type, plot_filename), ...]
          Hash indicating the plot types and filenames for each genome of interest.
        """

        sorted_genome_ids = alphanumeric_sort(genome_plots.keys())

        starting_plot_filename = genome_plots[sorted_genome_ids[0]][0][1]
        starting_plot_str = sorted_genome_ids[0] + '<br>' + genome_plots[sorted_genome_ids[0]][0][0]

        fout = open(os.path.join(plot_dir, 'index.html'), 'w')
        fout.write('\n')
        fout.write('')
        fout.write('<title>RefineM outlier plots</title>\n')
        fout.write('\n')
        fout.write('\n')
        fout.write('\n')
        fout.write('\n' % starting_plot_filename)
        fout.write('\n')
        fout.write('\n')
        fout.close()

Parameters
        ----------
        output_file : str
            Name of output file.
        """

        fout = open(output_file, 'w')
        fout.write('Genome id\tGenome size (bp)')
        fout.write('\tMean GC\tMedian GC')
        fout.write('\tMean scaffold length (bp)\tMedian scaffold length (bp)')
        fout.write('\tMean: ' + '\tMean: '.join(self.coverage_headers))
        fout.write('\tMedian: ' + '\tMedian: '.join(self.coverage_headers))
        fout.write('\t' + '\t'.join(self.signature_headers))
        fout.write('\n')

        for genome_id in alphanumeric_sort(self.genome_stats.keys()):
            stats = self.genome_stats[genome_id]

            fout.write(genome_id)
            fout.write('\t%d' % stats.genome_size)
            fout.write('\t%.2f' % stats.mean_gc)
            fout.write('\t%.2f' % stats.median_gc)
            fout.write('\t%.2f' % stats.mean_scaffold_length)
            fout.write('\t%.2f' % stats.median_scaffold_length)

            for cov in stats.mean_coverage:
                fout.write('\t%.2f' % cov)
                
            for cov in stats.median_coverage:
                fout.write('\t%.2f' % cov)

            for freq in stats.mean_signature:

genomes.add(fields[0])
                genomes.add(fields[2])
                try:
                    data[fields[0]][fields[2]] = [float(fields[5]), float(fields[7])]
                except KeyError:
                    data[fields[0]] = {}
                    data[fields[0]][fields[2]] = [float(fields[5]), float(fields[7])]
                except IndexError as e:
                    print(fields)
                    raise e

        self.perc_ids = np_zeros([len(genomes), len(genomes)])
        self.perc_aln = np_zeros([len(genomes), len(genomes)])
        genome_to_index = {}
        self.genomes = [None] * len(genomes)
        for n, g in enumerate(alphanumeric_sort(genomes)):
            genome_to_index[g] = n
            self.genomes[n] = g

        self.genomes = np_array(self.genomes)
        for g1, g2 in permutations(genomes, 2):
            try:
                self.perc_ids[genome_to_index[g1]][genome_to_index[g2]] = 100.0 - data[g1][g2][0]
                self.perc_aln[genome_to_index[g1], genome_to_index[g2]] = data[g1][g2][1]
            except:
                self.perc_ids[genome_to_index[g1]][genome_to_index[g2]] = 100.0 - data[g2][g1][0]
                self.perc_aln[genome_to_index[g1], genome_to_index[g2]] = data[g2][g1][1]