code: def init_arrays(data):
      
  
      ## get stats from step6 h5 and create new h5
      co5 = h5py.File(data.clust_database, 'r')
      io5 = h5py.File(data.database, 'w')
  
      ## get maxlen and chunk len
      maxlen = data._hackersonly["max_fragment_length"] + 20
      chunks = co5["seqs"].attrs["chunksize"][0]
      nloci = co5["seqs"].shape[0]
  
      ## make array for snp string, 2 cols, - and *
      snps = io5.create_dataset("snps", (nloci, maxlen, 2),
                                dtype=np.bool,
                                chunks=(chunks, maxlen, 2),
                                compression='gzip')
      snps.attrs["chunksize"] = chunks
      snps.attrs["names"] = ["-", "*"]
  
      ## array for filters that will be applied in step7
      filters = io5.create_dataset("filters", (nloci, 6), dtype=np.bool)
      filters.attrs["filters"] = ["duplicates", "max_indels",
                                  "max_snps", "max_shared_hets",
                                  "min_samps", "max_alleles"]
  
      ## array for edgetrimming
      edges = io5.create_dataset("edges", (nloci, 5),
                                 dtype=np.uint16,
                                 chunks=(chunks, 5),
                                 compression="gzip")
      edges.attrs["chunksize"] = chunks
      edges.attrs["names"] = ["R1_L", "R1_R", "R2_L", "R2_R", "sep"]
  
      ## xfer data from clustdb to finaldb
      edges[:, 4] = co5["splits"][:]
      filters[:, 0] = co5["duplicates"][:]
  
      ## close h5s
      io5.close()
      co5.close()
docs: Create database file for storing final filtered snps data as hdf5 array.
      Copies splits and duplicates info from clust_database to database.