"""
parser.add_argument("-o", "--output_file", action="store", dest="output", default="stdout",
help="Output file. Default: stdout")
"""
args = parser.parse_args()
# run after scripts/expansion/compare_cluster.py
# out_fd = sys.stdout if args.output == "stdout" else open(args.output, "w")
species_syn_dict = TwoLvlDict()
for species in args.species_list:
species_syn_dict[species] = read_synonyms_dict("%s%s/all.t" %
(args.species_dir, species))
species_syn_dict.write("families_all_species.t", absent_symbol=".")
not_assembled = species_syn_dict.filter_by_line(is_assembled)
species_syn_dict.write("correctly_assembled_families_species.t",
absent_symbol=".")
assembled_ids = IdSet(species_syn_dict.sl_keys())
assembled_ids.write("assembled_families.ids")
not_assembled_ids = IdSet(not_assembled.sl_keys())
not_assembled_ids.write("non_assembled_families.ids")
"""
if args.output != "stdout":
out_fd.close()
"""
for alignment_file in args.input:
alignment_name_list = FileRoutines.split_filename(alignment_file)
output_prefix = "%s/%s.unique_positions" % (args.output_dir,
alignment_name_list[1])
unique_position_dict[alignment_name_list[
1]] = MultipleAlignmentRoutines.count_unique_positions_per_sequence_from_file(
alignment_file,
output_prefix,
format=args.format,
gap_symbol="-",
return_mode="relative",
verbose=False)
species_list = unique_position_dict.sl_keys()
data_dict = OrderedDict()
for species in species_list:
data_dict[species] = []
for alignment in unique_position_dict:
data_dict[species].append(unique_position_dict[alignment][species])
data_list = [data_dict[species] for species in data_dict]
MatplotlibRoutines.extended_percent_histogram(data_list,
args.histogram_output,
input_mode="percent",
label=species_list)