code: def most_common_nucleotides(partitioned_read_sequences):
      
      counts, variant_column_indices = nucleotide_counts(
          partitioned_read_sequences)
      max_count_per_column = counts.max(axis=0)
  
      assert len(max_count_per_column) == counts.shape[1]
      max_nucleotide_index_per_column = np.argmax(counts, axis=0)
      assert len(max_nucleotide_index_per_column) == counts.shape[1]
      nucleotides = [
          index_to_dna_nucleotide[idx]
          for idx in max_nucleotide_index_per_column
      ]
      other_nucleotide_counts = counts.sum(axis=0) - max_count_per_column
      return "".join(nucleotides), max_count_per_column, other_nucleotide_counts
docs: Find the most common nucleotide at each offset to the left and
      right of a variant.
  
      Parameters
      ----------
      partitioned_read_sequences : list of tuples
          Each tuple has three elements:
              - sequence before mutant nucleotides
              - mutant nucleotides
              - sequence after mutant nucleotides
  
      Returns a tuple with the following elements:
          - nucleotide sequence from most common nucleotide at each offset
             relative to the variant
          - an array of counts indicating how many reads supported this nucleotide
          - an array of counts for all the *other* nucleotides at that position