confused about the B allele count

[lichen2018]

Dear author,
In function cell_by_gene_lefthap_counts in file get_snp_matrix.py, the phased alternative allele depth phased_AD.T is stored in cell_snp_Ballele,
def cell_by_gene_lefthap_counts(cellsnp_folder, eagle_folder, barcode_list):
......
......
phased_AD = np.where( (df_snp.GT.values == "0|1").reshape(-1,1), AD.A, (DP-AD).A )
phased_AD = scipy.sparse.csr_matrix(phased_AD)

# re-order based on barcode_list
index = np.array([barcode_mapper[x] for x in barcode_list if x in barcode_mapper])
DP = DP[:, index]
phased_AD = phased_AD[:, index]    

# returned matrix has shape (N_cells, N_snps), which is the transpose of the original matrix
return (DP-phased_AD).T, phased_AD.T, df_snp.snp_id.values

cell_snp_Aallele, cell_snp_Ballele, unique_snp_ids = cell_by_gene_lefthap_counts(args.cellsnplite_result_dir, args.eagle_out_dir, barcode_list)

while in function summarize_counts_for_blocks in utils_IO.py, the single_X which should contain BAF information store cell_snp_Aallele counts, is it right?

for b in range(df_block_contents.shape[0]):
    # BAF (SNPs)
    involved_snps_ids = [x for x in df_block_contents.snp_id.values[b] if not x is None]
    involved_snp_idx = np.array([map_snp_index[x] for x in involved_snps_ids])
    if len(involved_snp_idx) > 0:
        single_X[b, 1, :] = np.sum( cell_snp_Aallele[:, involved_snp_idx], axis=1 )
        single_total_bb_RD[b, :] = np.sum( cell_snp_Aallele[:, involved_snp_idx], axis=1 ) + np.sum( cell_snp_Ballele[:, involved_snp_idx], axis=1 )
    # RDR (genes)