def main():
args = parser.parse_args()
# Determine which mapping type was specified. If neither a default
# or custom mapping was specified then throw an error.
if args.map_type and args.custom_map_table:
sys.exit("Only one of \"--map_type\" or \"--custom_map_table\" can be "
"set. Please re-run the command with only one of these "
"options.")
elif args.map_type:
mapfile = default_map[args.map_type]
elif args.custom_map_table:
mapfile = args.custom_map_table
else:
sys.exit("A default mapping table needs to be specified with the "
"--map_type option, or alternatively a custom mapfile can "
"be specified with the --custom_map_table option")
tab_w_descrip = add_descrip_col(inputfile=args.input, mapfile=mapfile)
# Output the table to file.
make_output_dir_for_file(args.output)
tab_w_descrip.to_csv(path_or_buf=args.output,
sep="\t",
index=False,
compression="infer")
def main():
args = parser.parse_args()
# Determine which input trait table was specified. If neither a default
# or custom table was specified then throw an error.
if args.in_trait:
trait_table = default_tables[args.in_trait]
elif args.observed_trait_table:
trait_table = args.observed_trait_table
else:
raise RuntimeError(
"A default input trait table needs to be specified with the " +
"--in_trait option, or alternatively a custom table can be " +
"specified with the --observed_trait_table option")
# Check that input filenames exist.
check_files_exist([args.tree, trait_table])
# Methods for discrete trait prediction with CI enabled.
discrete_set = set(['emp_prob', 'mp'])
if args.confidence and args.hsp_method in discrete_set:
ci_setting = True
else:
ci_setting = False
count_outfile = args.output_prefix + ".tsv"
ci_outfile = args.output_prefix + "_ci.tsv"
hsp_table, ci_table = castor_hsp_workflow(tree_path=args.tree,
trait_table_path=trait_table,
hsp_method=args.hsp_method,
chunk_size=args.chunk_size,
calc_nsti=args.calculate_NSTI,
calc_ci=ci_setting,
check_input=args.check,
num_proc=args.processes,
ran_seed=args.seed)
# Output the table to file.
make_output_dir_for_file(count_outfile)
hsp_table.to_csv(path_or_buf=count_outfile,
index_label="sequence",
sep="\t")
# Output the CI file as well if option set.
if ci_setting:
make_output_dir_for_file(ci_outfile)
ci_table.to_csv(path_or_buf=ci_outfile,
index_label="sequence",
sep="\t")
def main():
args = parser.parse_args()
# Determine which mapping type was specified. If neither a default
# or custom mapping was specified then throw an error.
if args.map_type:
mapfile = default_map[args.map_type]
elif args.custom_map_table:
mapfile = args.custom_map_table
else:
sys.exit("A default mapping table needs to be specified with the " +
"--map_type option, or alternatively a custom mapfile can " +
"be specified with the --custom_map_table option")
tab_w_descrip = add_descrip_col(inputfile=args.input, mapfile=mapfile)
# Output the table to file.
make_output_dir_for_file(args.output)
tab_w_descrip.to_csv(path_or_buf=args.output, sep="\t", index=False)
def main():
args = parser.parse_args()
# Determine which input trait table was specified. If neither a default
# or custom table was specified then throw an error.
if args.in_trait:
trait_table = default_tables[args.in_trait]
elif args.observed_trait_table:
trait_table = args.observed_trait_table
else:
raise RuntimeError(
"A default input trait table needs to be specified with the " +
"--in_trait option, or alternatively a custom table can be " +
"specified with the --observed_trait_table option")
# Check that input filenames exist.
check_files_exist([args.tree, trait_table])
# No longer support outputting CIs with this script.
ci_setting = False
hsp_table, ci_table = castor_hsp_workflow(tree_path=args.tree,
trait_table_path=trait_table,
hsp_method=args.hsp_method,
chunk_size=args.chunk_size,
calc_nsti=args.calculate_NSTI,
calc_ci=ci_setting,
check_input=args.check,
num_proc=args.processes,
ran_seed=args.seed,
verbose=args.verbose)
# Output the table to file.
make_output_dir_for_file(args.output)
hsp_table.to_csv(path_or_buf=args.output,
index_label="sequence",
sep="\t",
compression="infer")
