def _lab_parser(prog="lab"):
parser = _base_parser(
prog=prog,
description=
"""ASReview LAB - Active learning for Systematic Reviews.""" # noqa
)
parser.add_argument("--clean_project",
default=None,
type=str,
help="Safe cleanup of temporary files in project.")
parser.add_argument(
"--clean_all_projects",
action='store_true',
help="Safe cleanup of temporary files in all projects.")
parser.add_argument("--ip",
default=HOST_NAME,
type=str,
help="The IP address the server will listen on.")
parser.add_argument("--port",
default=PORT_NUMBER,
type=int,
help="The port the server will listen on.")
return parser
def _simulate_parser(prog="simulate", description=DESCRIPTION_SIMULATE):
parser = _base_parser(prog=prog, description=description)
# Active learning parameters
# File path to the data.
parser.add_argument(
"dataset",
type=str,
nargs="*",
help="File path to the dataset or one of the built-in datasets.")
# Initial data (prior knowledge)
parser.add_argument("--n_prior_included",
default=DEFAULT_N_PRIOR_INCLUDED,
type=int,
help="Sample n prior included papers. "
"Only used when --prior_included is not given. "
f"Default {DEFAULT_N_PRIOR_INCLUDED}")
parser.add_argument("--n_prior_excluded",
default=DEFAULT_N_PRIOR_EXCLUDED,
type=int,
help="Sample n prior excluded papers. "
"Only used when --prior_excluded is not given. "
f"Default {DEFAULT_N_PRIOR_EXCLUDED}")
return parser
def _lab_parser(prog="lab"):
parser = _base_parser(
prog=prog,
description=
"""ASReview LAB - Active learning for Systematic Reviews.""" # noqa
)
parser.add_argument("--clean-project",
dest="clean_project",
default=None,
type=str,
help="Safe cleanup of temporary files in project.")
parser.add_argument(
"--clean-all-projects",
dest="clean_all_projects",
default=None,
action='store_true',
help="Safe cleanup of temporary files in all projects.")
parser.add_argument("--ip",
default=HOST_NAME,
type=str,
help="The IP address the server will listen on.")
parser.add_argument("--port",
default=PORT_NUMBER,
type=int,
help="The port the server will listen on.")
parser.add_argument(
"--no-browser",
dest="no_browser",
action='store_true',
help="Do not open ASReview LAB in a browser after startup.")
parser.add_argument("--port-retries",
dest="port_retries",
default=50,
type=int,
help="The number of additional ports to try if the"
"specified port is not available.")
parser.add_argument("--certfile",
default="",
type=str,
help="The full path to an SSL/TLS certificate file.")
parser.add_argument(
"--keyfile",
default="",
type=str,
help="The full path to a private key file for usage with SSL/TLS.")
return parser
def _lab_parser(prog="lab", description=DESCRIPTION_LAB):
parser = _base_parser(prog=prog, description=description)
# Active learning parameters
parser.add_argument("--ip",
default=HOST_NAME,
type=str,
help="The IP address the server will listen on.")
parser.add_argument("--port",
default=PORT_NUMBER,
type=int,
help="The port the server will listen on.")
return parser
def _lab_parser(prog="lab"):
parser = _base_parser(
prog=prog,
description="""ASReview LAB - Active learning for Systematic Reviews.""" # noqa
)
parser.add_argument(
"--ip",
default=HOST_NAME,
type=str,
help="The IP address the server will listen on.")
parser.add_argument(
"--port",
default=PORT_NUMBER,
type=int,
help="The port the server will listen on.")
return parser
def _simulate_parser(prog="simulate", description=DESCRIPTION_SIMULATE):
parser = _base_parser(prog=prog, description=description)
# Active learning parameters
# File path to the data.
parser.add_argument(
"dataset",
type=str,
nargs="*",
help="File path to the dataset or one of the built-in datasets.")
# Initial data (prior knowledge)
parser.add_argument("--n_prior_included",
default=DEFAULT_N_PRIOR_INCLUDED,
type=int,
help="Sample n prior included papers. "
"Only used when --prior_included is not given. "
f"Default {DEFAULT_N_PRIOR_INCLUDED}")
parser.add_argument("--n_prior_excluded",
default=DEFAULT_N_PRIOR_EXCLUDED,
type=int,
help="Sample n prior excluded papers. "
"Only used when --prior_excluded is not given. "
f"Default {DEFAULT_N_PRIOR_EXCLUDED}")
parser.add_argument("--prior_idx",
default=[],
nargs="*",
type=int,
help="Prior indices by id.")
parser.add_argument(
'--init_seed',
default=None,
type=int,
help="Seed for setting the prior indices if the --prior_idx option is "
"not used. If the option --prior_idx is used with one or more "
"index, this option is ignored.")
parser.add_argument("--verbose",
"-v",
default=0,
type=int,
help="Verbosity")
return parser
def _simulate_parser(prog="simulate", description=DESCRIPTION_SIMULATE):
parser = _base_parser(prog=prog, description=description)
# Active learning parameters
# File path to the data.
parser.add_argument(
"dataset",
type=str,
nargs="*",
help="File path to the dataset or one of the benchmark datasets."
)
# Initial data (prior knowledge)
parser.add_argument(
"--n_prior_included",
default=DEFAULT_N_PRIOR_INCLUDED,
type=int,
help="Sample n prior included papers. "
"Only used when --prior_idx is not given. "
f"Default {DEFAULT_N_PRIOR_INCLUDED}")
parser.add_argument(
"--n_prior_excluded",
default=DEFAULT_N_PRIOR_EXCLUDED,
type=int,
help="Sample n prior excluded papers. "
"Only used when --prior_idx is not given. "
f"Default {DEFAULT_N_PRIOR_EXCLUDED}")
parser.add_argument(
"--prior_idx",
default=[],
nargs="*",
type=int,
help="Prior indices by rownumber (0 is first rownumber)."
)
parser.add_argument(
"--prior_record_id",
default=[],
nargs="*",
type=int,
help="Prior indices by record_id."
)
parser.add_argument(
"--included_dataset",
default=[],
nargs="*",
type=str,
help="A dataset with papers that should be included"
"Can be used multiple times."
)
parser.add_argument(
"--excluded_dataset",
default=[],
nargs="*",
type=str,
help="A dataset with papers that should be excluded"
"Can be used multiple times."
)
parser.add_argument(
"--prior_dataset",
default=[],
nargs="*",
type=str,
help="A dataset with papers from prior studies."
)
# logging and verbosity
parser.add_argument(
"--state_file", "-s", "--log_file", "-l",
default=None,
type=str,
help="Location to store the state of the simulation."
)
parser.add_argument(
"-m", "--model",
type=str,
default=DEFAULT_MODEL,
help=f"The prediction model for Active Learning. "
f"Default: '{DEFAULT_MODEL}'.")
parser.add_argument(
"-q", "--query_strategy",
type=str,
default=DEFAULT_QUERY_STRATEGY,
help=f"The query strategy for Active Learning. "
f"Default: '{DEFAULT_QUERY_STRATEGY}'.")
parser.add_argument(
"-b", "--balance_strategy",
type=str,
default=DEFAULT_BALANCE_STRATEGY,
help="Data rebalancing strategy mainly for RNN methods. Helps against"
" imbalanced dataset with few inclusions and many exclusions. "
f"Default: '{DEFAULT_BALANCE_STRATEGY}'")
parser.add_argument(
"-e", "--feature_extraction",
type=str,
default=DEFAULT_FEATURE_EXTRACTION,
help="Feature extraction method. Some combinations of feature"
" extraction method and prediction model are impossible/ill"
" advised."
f"Default: '{DEFAULT_FEATURE_EXTRACTION}'"
)
parser.add_argument(
'--init_seed',
default=None,
type=int,
help="Seed for setting the prior indices if the --prior_idx option is "
"not used. If the option --prior_idx is used with one or more "
"index, this option is ignored."
)
parser.add_argument(
"--n_instances",
default=DEFAULT_N_INSTANCES,
type=int,
help="Number of papers queried each query."
f"Default {DEFAULT_N_INSTANCES}.")
parser.add_argument(
"--n_queries",
type=int,
default=None,
help="The number of queries. By default, the program "
"stops after all documents are reviewed or is "
"interrupted by the user."
)
parser.add_argument(
"-n", "--n_papers",
type=int,
default=None,
help="The number of papers to be reviewed. By default, "
"the program stops after all documents are reviewed or is "
"interrupted by the user."
)
parser.add_argument(
"--verbose", "-v",
default=0,
type=int,
help="Verbosity"
)
return parser
