#########################################################################
# MacSyFinder - Detection of macromolecular systems in protein dataset #
# using systems modelling and similarity search. #
# Authors: Sophie Abby, Bertrand Neron #
# Copyright (c) 2014-2023 Institut Pasteur (Paris) and CNRS. #
# See the COPYRIGHT file for details #
# #
# This file is part of MacSyFinder package. #
# #
# MacSyFinder is free software: you can redistribute it and/or modify #
# it under the terms of the GNU General Public License as published by #
# the Free Software Foundation, either version 3 of the License, or #
# (at your option) any later version. #
# #
# MacSyFinder is distributed in the hope that it will be useful, #
# but WITHOUT ANY WARRANTY; without even the implied warranty of #
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the #
# GNU General Public License for more details . #
# #
# You should have received a copy of the GNU General Public License #
# along with MacSyFinder (COPYING). #
# If not, see <https://www.gnu.org/licenses/>. #
#########################################################################
"""
Module to manage both default values and configuration needed by macsyfinder
"""
import os
import shutil
from time import strftime
import logging
from configparser import ConfigParser, ParsingError
from macsypy.model_conf_parser import ModelConfParser
_log = logging.getLogger(__name__)
[docs]class MacsyDefaults(dict):
"""
Handle all default values for macsyfinder.
the default values must be defined here, **NOT** in argument parser nor in config
the argument parser or config must use a MacsyDefaults object
"""
[docs] def __init__(self, **kwargs):
"""
:param kwargs: allow to overwrite a default value.
It mainly used in unit tests
To define a new default value just add an attribute with the default value
"""
super().__init__()
self.__dict__ = self
common_path = os.path.join('share', 'macsyfinder', 'models')
virtual_env = os.environ.get('VIRTUAL_ENV')
if virtual_env:
system_models_dir = os.path.join(virtual_env, common_path)
else:
system_models_dir = '' # os.path.exists('') -> False
prefixes = ('/', os.path.join('/', 'usr', 'local'))
for root_prefix in prefixes:
root_path = os.path.join(root_prefix, common_path)
if os.path.exists(root_path) and os.path.isdir(root_path):
system_models_dir = root_path
# depending on distrib it's installed in /share or /usr/local/share
# if it's installed with --user
# install models in ~/.macsyfinder instead of ~/.local/share/macsyfinder
self.cfg_file = kwargs.get('cfg_file', None)
self.coverage_profile = kwargs.get('coverage_profile', 0.5)
self.e_value_search = kwargs.get('e_value_search', 0.1)
self.cut_ga = kwargs.get('cut_ga', True)
self.db_type = kwargs.get('db_type', None)
self.hmmer = kwargs.get('hmmer', shutil.which('hmmsearch'))
self.i_evalue_sel = kwargs.get('i_evalue_sel', 0.001)
self.idx = kwargs.get('idx', False)
self.index_dir = kwargs.get('index_dir', None)
self.inter_gene_max_space = kwargs.get('inter_gene_max_space', None)
self.log_level = kwargs.get('log_level', logging.INFO)
self.log_file = kwargs.get('log_file', 'macsyfinder.log')
self.max_nb_genes = kwargs.get('max_nb_genes', None)
self.min_genes_required = kwargs.get('min_genes_required', None)
self.min_mandatory_genes_required = kwargs.get('min_mandatory_genes_required', None)
self.models = kwargs.get('models', [])
self.system_models_dir = kwargs.get('system_models_dir', [path for path in
(system_models_dir,
os.path.join(os.path.expanduser('~'),
'.macsyfinder', 'models'))
if os.path.exists(path)]
)
self.models_dir = kwargs.get('models_dir', None)
self.multi_loci = kwargs.get('multi_loci', set())
self.mute = kwargs.get('mute', False)
self.out_dir = kwargs.get('out_dir', None)
self.previous_run = kwargs.get('previous_run', None)
self.profile_suffix = kwargs.get('profile_suffix', '.hmm')
self.quiet = kwargs.get('quiet', 0)
self.relative_path = kwargs.get('relative_path', False)
self.replicon_topology = kwargs.get('replicon_topology', 'circular')
self.res_extract_suffix = kwargs.get('res_extract_suffix', '.res_hmm_extract')
self.res_search_dir = kwargs.get('res_search_dir', '.')
self.res_search_suffix = kwargs.get('res_search_suffix', '.search_hmm.out')
self.sequence_db = kwargs.get('sequence_db', None)
self.topology_file = kwargs.get('topology_file', None)
self.verbosity = kwargs.get('verbosity', 0)
self.worker = kwargs.get('worker', 1)
self.mandatory_weight = kwargs.get('mandatory_weight', 1.0)
self.accessory_weight = kwargs.get('accessory_weight', .5)
self.neutral_weight = kwargs.get('neutral_weight', 0.0)
self.exchangeable_weight = kwargs.get('exchangeable_weight', .8)
self.out_of_cluster_weight = kwargs.get('out_of_cluster_weight', .7)
self.itself_weight = kwargs.get('itself_weight', 1.0)
self.redundancy_penalty = kwargs.get('redundancy_penalty', 1.5)
self.timeout = kwargs.get('timeout', 0)
self.force_run = kwargs.get('force_run', False)
[docs]class Config:
"""
Handle configuration values for macsyfinder.
This values come from default and ar superseded by the configuration files, then the command line settings.
"""
cfg_opts = [('base', ('db_type', 'idx', 'replicon_topology', 'sequence_db', 'topology_file')),
('models_opt', ('inter_gene_max_space', 'max_nb_genes', 'min_mandatory_genes_required',
'min_genes_required', 'multi_loci')),
('models', tuple()),
('hmmer', ('coverage_profile', 'e_value_search', 'cut_ga', 'i_evalue_sel', 'hmmer')),
('score_opt', ('mandatory_weight', 'accessory_weight', 'neutral_weight', 'exchangeable_weight',
'itself_weight', 'redundancy_penalty', 'out_of_cluster_weight')),
('directories', ('models_dir', 'system_models_dir', 'out_dir', 'profile_suffix', 'res_search_dir',
'res_search_suffix', 'res_extract_suffix', 'index_dir')),
('general', ('cfg_file', 'log_file', 'log_level', 'previous_run', 'relative_path',
'verbosity', 'quiet', 'mute', 'worker', 'timeout', 'force_run')),
]
model_opts = ('itself', 'exchangeable', 'mandatory', 'accessory', 'neutral',
'out_of_cluster', 'redundancy_penalty',
'e_value_search', 'e_value_sel', 'coverage_profile', 'cut_ga')
path_opts = ('sequence_db', 'topology_file', 'cfg_file', 'log_file', 'models_dir', 'system_models_dir', 'out_dir',
'profile_suffix', 'res_search_dir', 'res_search_suffix', 'res_extract_suffix', 'index_dir')
[docs] def __init__(self, defaults, parsed_args):
"""
Store macsyfinder configuration options and propose an interface to access to them.
The config object is populated in several steps, the rules of precedence are
system wide conf < user home conf < model conf < (project conf | previous run) < command line
system wide conf = etc/macsyfinder/macsyfinder.conf
user home conf = ~/.macsyfinder/macsyfinder.conf
model conf = model_conf.xml at the root of the model package
project conf = macsyfinder.conf where the analysis is run
previous run = macsyfinder.conf in previous run results dir
command line = the options set on the command line
:param defaults:
:type defaults: a :class:`MacsyDefaults` object
:param parsed_args: the command line arguments parsed
:type parsed_args: a :class:`argspace.Namescape` object
"""
self._defaults = defaults
self.cfg_name = "macsyfinder.conf"
virtual_env = os.environ.get('VIRTUAL_ENV')
if virtual_env:
system_wide_config_file = os.path.join(virtual_env, 'etc', 'macsyfinder', self.cfg_name)
else:
# not in virtual_env
var_env = os.environ.get('MACSY_CONF')
if var_env:
system_wide_config_file = var_env
else:
system_wide_config_file = os.path.join('/', 'etc', 'macsyfinder', self.cfg_name)
self._options = {}
self._tmp_opts = {}
self._set_default_config()
if os.path.exists(system_wide_config_file):
self._set_system_wide_config(system_wide_config_file)
user_wide_config_file = os.path.join(os.path.expanduser('~'), '.macsyfinder', self.cfg_name)
if os.path.exists(user_wide_config_file):
self._set_user_wide_config(user_wide_config_file)
project_config_file = os.path.join(os.getcwd(), 'macsyfinder.conf')
if os.path.exists(project_config_file):
self._set_project_config_file(project_config_file)
if hasattr(parsed_args, 'cfg_file') and parsed_args.cfg_file:
user_config_file = parsed_args.cfg_file
if os.path.exists(user_config_file):
self._set_user_config_file(user_config_file)
else:
raise ValueError(f"Config file {user_config_file} not found.")
previous_run = False
if hasattr(parsed_args, 'previous_run') and parsed_args.previous_run:
prev_config = os.path.normpath(os.path.join(parsed_args.previous_run, self.cfg_name))
previous_run = True
if not os.path.exists(prev_config):
raise ValueError(f"No config file found in dir {parsed_args.previous_run}")
self._set_previous_run_config(prev_config)
if previous_run:
if hasattr(parsed_args, 'sequence_db') and parsed_args.sequence_db:
_log.warning(f"ignore sequence_db '{parsed_args.sequence_db}' use sequence_db "
f"from previous_run '{parsed_args.previous_run}'.")
parsed_args.sequence_db = None
self._set_command_line_config(parsed_args)
models = self.models()
if models:
# the config is also used for macsydata
# in this case the models are not necessary
model_family_root, _ = models
# create list of model_root respecting precedence
model_family_root_path = [os.path.join(p, model_family_root) for p in self.models_dir()]
model_family_root_path = [p for p in model_family_root_path if os.path.exists(p)]
# check if the last model_family_root_path (with higher precedence) as a model config file
if model_family_root_path:
model_config_file = os.path.join(model_family_root_path[-1], 'model_conf.xml')
if os.path.exists(model_config_file):
self._set_model_config(model_config_file)
# superseed options (potentially in model_conf)
# by the values provided by previous-run, project conf, the users on the commandline
self._options.update(self._tmp_opts)
# check that hmmsearch exists
if not self.hmmer():
msg = "'hmmsearch' NOT found in your PATH, Please specify hmmsearch path with --hmmer opt " \
"or install 'hmmer' package."
_log.critical(msg)
raise ValueError(msg)
[docs] def _set_options(self, options):
"""
set key, value in the general config
:param options: the options to specify in general config
:type options: a dictionary with option name as keys and values as values
"""
for opt, val in options.items():
if val not in (None, [], set()):
met_name = f'_set_{opt}'
if hasattr(self, met_name):
# config has a specific method to parse and store the value
# for this option
getattr(self, met_name)(val)
else:
# config has no method defined to set this option
self._options[opt] = val
[docs] def _set_default_config(self):
"""
set the value comming from MacsyDefaults
"""
# the special methods are not used to fill with defaults values
self._options = self._defaults.copy()
# except for loglevel because log_level can accept int and string as value
# need conversion in int which is the internal format
self._options['log_level'] = self._convert_log_level(self._defaults.log_level)
[docs] def _set_system_wide_config(self, config_path):
"""
set the options from the system wide configuration file
:param str config_path:
"""
system_wide_config = self._config_file_2_dict(config_path)
if 'models_dir' in system_wide_config:
# models_dir cannot be modified in general configuration
# set system_model_dir instead
del system_wide_config['models_dir']
self._set_options(system_wide_config)
[docs] def _set_user_wide_config(self, config_path):
"""
Set the options from the ~/.macsyfinder/macsyfinder.conf file
:param str config_path: The path to the ~/.macsyfinder/macsyfinder.conf
"""
user_wide_config = self._config_file_2_dict(config_path)
self._set_options(user_wide_config)
[docs] def _set_model_config(self, model_conf_path):
"""
Set the options from the model package model_conf.xml file
:param str model_conf_path: The path to the model_conf.xml file
"""
mcp = ModelConfParser(model_conf_path)
model_conf = mcp.parse()
self._set_options(model_conf)
[docs] def _set_project_config_file(self, config_path):
"""
Set the options from the macsyfinder.conf present in the current directory
:param str config_path: the path to the configuration file
"""
project_config = self._config_file_2_dict(config_path)
for opt in self.model_opts:
if opt in project_config:
self._tmp_opts[opt] = project_config[opt]
del project_config[opt]
self._set_options(project_config)
[docs] def _set_user_config_file(self, config_path):
"""
Set the options specified by the user on the command line via the --cfg-file option
:param str config_path: The path to the configuration path
"""
user_config = self._config_file_2_dict(config_path)
for opt in self.model_opts:
if opt in user_config:
self._tmp_opts[opt] = user_config[opt]
del user_config[opt]
self._set_options(user_config)
[docs] def _set_previous_run_config(self, prev_config_path):
"""
Set the options specified by the user on the command line via --previous-run
:param prev_config_path:
"""
previous_conf = self._config_file_2_dict(prev_config_path)
if 'out_dir' in previous_conf:
# set the out_dir from the previous_run is a non sense
del previous_conf['out_dir']
for opt in self.model_opts:
if opt in previous_conf:
self._tmp_opts[opt] = previous_conf[opt]
del previous_conf[opt]
self._set_options(previous_conf)
[docs] def _set_command_line_config(self, parsed_args):
"""
:param parsed_args: the argument set on the command line
:type parsed_args: :class:`argparse.Namespace` object.
"""
# do not iter on args special attribute
# do not set option if the value is None (not specified on command line)
args_dict = {k: v for k, v in vars(parsed_args).items() if not k.startswith('__') and v is not None}
for opt in self.model_opts:
if opt in args_dict:
self._tmp_opts[opt] = args_dict[opt]
del args_dict[opt]
self._set_options(args_dict)
[docs] def _config_file_2_dict(self, file):
"""
Parse a configuration file in ini format in dictionnary
:param str file: path to the configuration file
:return: the parsed options
:rtype: dict
"""
parser = ConfigParser()
parse_meth = {int: parser.getint,
float: parser.getfloat,
bool: parser.getboolean
}
try:
parser.read([file])
_log.debug(f"Configuration file {file} parsed.")
except ParsingError as err:
raise ParsingError(f"The macsyfinder configuration file '{file}' is not well formed: {err}") from None
opts = {}
sections = list(parser.sections())
for section in sections:
for option in parser.options(section):
opt_type = type(self._defaults.get(option, None))
if option == 'log_level':
self._set_log_level(parser.get(section, option))
else:
try:
opt_value = parse_meth.get(opt_type, parser.get)(section, option)
except (ValueError, TypeError) as err:
raise ValueError(f"Invalid value in config_file for option '{option}': {err}")
opts[option] = opt_value
return opts
def __getattr__(self, option_name):
# some getter return just a value they can be transformed in property
# but some other need extra argument so they cannot be a property, they must be methods
# to have something generic and with the same behavior
# that mean need to call all of them
# for generic getter, that mean no code in config
# I simulate a function (lambda) which can be called without argument
if option_name in self._options:
return lambda: self._options[option_name]
else:
raise AttributeError(f"config object has no attribute '{option_name}'")
[docs] def _str_2_tuple(self, value):
"""
transform a string with syntax {model_fqn int} in list of tuple
:param str value: the string to parse
:return:
:rtype: [(model_fqn, int), ...]
"""
try:
it = iter(value.split())
res = [(a, next(it)) for a in it]
return res
except StopIteration:
raise ValueError(f"You must provide a list of model name and value separated by spaces: {value}")
[docs] def save(self, path_or_buf=None):
"""
save itself in a file in ini format.
.. note::
the undefined options (set to None) are omitted
:param path_or_buf: where to serialize itself.
:type path_or_buf: str or file like object
"""
def serialize():
conf_str = ''
for section, options in self.cfg_opts:
conf_str += f"[{section}]\n"
if section == 'models':
# [(model_family, (def_name1, ...)), ... ]
model_family, model_names = self.models()
conf_str += f"models = {model_family} {' '.join(model_names)}\n"
else:
for opt in options:
opt_value = self._options[opt]
if opt_value in (None, [], set()):
continue
elif isinstance(opt_value, dict):
value = ""
for model, v in opt_value.items():
value += f"{model} {v} "
opt_value = value
elif isinstance(opt_value, (set, list)):
opt_value = ', '.join(opt_value)
elif opt_value in self.path_opts and self.relative_path:
opt_value = os.path.relpath(opt_value)
conf_str += f"{opt} = {opt_value}\n"
return conf_str
if path_or_buf is None:
path_or_buf = os.path.join(self.out_dir(), self.cfg_name)
if isinstance(path_or_buf, str):
with open(path_or_buf, 'w') as cfg_file:
print(serialize(), file=cfg_file)
else:
print(serialize(), file=path_or_buf)
[docs] def _set_db_type(self, value):
"""
set value for 'db_type' option
:param str value: the value for db_type, allowed values are :
'ordered_replicon', 'gembase', 'unordered'
:raise ValueError: if value is not allowed
"""
auth_values = ('ordered_replicon', 'gembase', 'unordered')
if value in auth_values:
self._options['db_type'] = value
else:
raise ValueError(f"db_type as unauthorized value : '{value}'.")
[docs] def _set_inter_gene_max_space(self, value):
"""
set value for 'inter_gene_max_space' option
:param str value: the string parse representing the model fully qualified name
and it's associated value and so on
the model_fqn is a string, the associated value must be cast in int
:raise ValueError: if value is not well formed
"""
opt = {}
if isinstance(value, str):
try:
value = self._str_2_tuple(value)
except ValueError as err:
raise ValueError(f"Invalid syntax for 'inter_gene_max_space': {err}.")
for model_fqn, quorum in value:
try:
opt[model_fqn] = int(quorum)
except ValueError:
raise ValueError(f"The value for 'inter_gene_max_space' option for model {model_fqn} must be an integer"
f", but you provided {quorum}")
self._options['inter_gene_max_space'] = opt
[docs] def inter_gene_max_space(self, model_fqn):
"""
:param str model_fqn: the model fully qualifed name
:return: the gene_max_space for the model_fqn or None if it's does not specify
:rtype: int or None
"""
if self._options['inter_gene_max_space']:
return self._options['inter_gene_max_space'].get(model_fqn, None)
else:
return None
[docs] def _set_max_nb_genes(self, value):
"""
set value for 'max_nb_genes' option
:param str value: the string parse representing the model fully qualified name
and it's associated value and so on
the model_fqn is a string, the associated value must be cast in int
:raise ValueError: if value is not well formed
"""
opt = {}
if isinstance(value, str):
try:
value = self._str_2_tuple(value)
except ValueError as err:
raise ValueError(f"Invalid syntax for 'max_nb_genes': {err}.")
for model_fqn, quorum in value:
try:
opt[model_fqn] = int(quorum)
except ValueError:
raise ValueError(f"The value for 'max_nb_genes' option for model {model_fqn} must be an integer, "
f"but you provided {quorum}")
self._options['max_nb_genes'] = opt
[docs] def max_nb_genes(self, model_fqn):
"""
:param str model_fqn: the model fully qualifed name
:return: the max_nb_genes for the model_fqn or None if it's does not specify
:rtype: int or None
"""
if self._options['max_nb_genes']:
return self._options['max_nb_genes'].get(model_fqn, None)
else:
return None
[docs] def _set_min_genes_required(self, value):
"""
set value for 'min_genes_required' option
:param str value: the string parse representing the model fully qualified name
and it's associated value and so on
the model_fqn is a string, the associated value must be cast in int
:raise ValueError: if value is not well formed
"""
opt = {}
if isinstance(value, str):
try:
value = self._str_2_tuple(value)
except ValueError as err:
raise ValueError(f"Invalid syntax for 'min_genes_required': {err}.")
for model_fqn, quorum in value:
try:
opt[model_fqn] = int(quorum)
except ValueError:
raise ValueError(f"The value for 'min_genes_required' option for model {model_fqn} must be an integer, "
f"but you provided {quorum}")
self._options['min_genes_required'] = opt
[docs] def min_genes_required(self, model_fqn):
"""
:param str model_fqn: the model fully qualifed name
:return: the min_genes_required for the model_fqn or None if it's does not specify
:rtype: int or None
"""
if self._options['min_genes_required']:
return self._options['min_genes_required'].get(model_fqn, None)
else:
return None
[docs] def _set_min_mandatory_genes_required(self, value):
"""
set value for 'min_mandatory_genes_required' option
:param str value: the string parse representing the model fully qualified name
and it's associated value and so on
the model_fqn is a string, the associated value must be cast in int
:raise ValueError: if value is not well formed
"""
opt = {}
if isinstance(value, str):
try:
value = self._str_2_tuple(value)
except ValueError as err:
raise ValueError(f"Invalid syntax for 'min_mandatory_genes_required': {err}.")
for model_fqn, quorum in value:
try:
opt[model_fqn] = int(quorum)
except ValueError:
raise ValueError(f"The value for 'min_mandatory_genes_required' option "
f"for model {model_fqn} must be an integer, but you provided {quorum}")
self._options['min_mandatory_genes_required'] = opt
[docs] def min_mandatory_genes_required(self, model_fqn):
"""
:param str model_fqn: the model fully qualifed name
:return: the min_mandatory_genes_required for the model_fqn or None if it's does not specify
:rtype: int or None
"""
if self._options['min_mandatory_genes_required']:
return self._options['min_mandatory_genes_required'].get(model_fqn, None)
else:
return None
[docs] def _set_models(self, value):
"""
:param value: The models to search as return by the command line parsing or
the configuration files
if value come from command_line
['model1', 'def1', 'def2', 'def3']
if value come from config file
['set_1', 'T9SS T3SS T4SS_typeI')]
[(model_family, [def_name1, ...]), ... ]
"""
if isinstance(value, str):
# it comes from a config_file
# value = model_family_name model1 model2
model_family_name, *models_name = value.split()
else:
# it come from the command line
# value = ['model_family_name', 'model1', 'model2']
model_family_name = value[0]
models_name = value[1:]
if model_family_name and not models_name:
models_name = ['all']
self._options['models'] = (model_family_name, models_name)
[docs] def out_dir(self):
"""
:return: the path to the directory where the results are stored
"""
out_dir = self._options['out_dir']
if out_dir:
return out_dir
else:
out_dir = os.path.join(self._options['res_search_dir'],
f"macsyfinder-{strftime('%Y%m%d_%H-%M-%S')}")
self._options['out_dir'] = out_dir
return out_dir
[docs] def working_dir(self):
"""
alias to :py:meth:`config.Config.out_dir`
"""
return self.out_dir()
[docs] def _set_replicon_topology(self, value):
"""
set the default replicon topology
:param str value: 'circular' or 'linear'
"""
auth_values = ('linear', 'circular')
value_low = value.lower()
new_topo = None
for topo in auth_values:
if topo.startswith(value_low):
new_topo = topo
break
if new_topo is not None:
self._options['replicon_topology'] = new_topo
else:
raise ValueError(f"replicon_topology as unauthorized value : '{value}'.")
[docs] def _set_sequence_db(self, path):
"""
:param str path: set the path to the sequence file (in fasta format) to analysed
"""
if os.path.exists(path) and os.path.isfile(path):
self._options['sequence_db'] = path
else:
raise ValueError(f"sequence_db '{path}' does not exists or is not a file.")
[docs] def _set_topology_file(self, path):
"""
test if the path exists and set it in config
:param str path: the path to the topology file
"""
if os.path.exists(path) and os.path.isfile(path):
self._options['topology_file'] = path
else:
raise ValueError(f"topology_file '{path}' does not exists or is not a file.")
[docs] def _set_system_models_dir(self, value):
"""
:param value: the path of the models dir set by the system (vs set by the user)
:type value: list of string or a single string
:return:
"""
if isinstance(value, str):
# it comes from a config_file
# value = path1, path2
value = value.split(', ')
self._options['system_models_dir'] = value
[docs] def _set_models_dir(self, path):
"""
:param str path: the path to the models (definitions + profiles) are stored.
"""
# if models_dir is provide by the user this value mask canonical ones
# prefix_data, 'models'
# os.path.expanduser('~'), '.macsyfinder', 'data'
# models_dir must return a list of path
if os.path.exists(path) and os.path.isdir(path):
self._options['models_dir'] = [path]
else:
raise ValueError(f"models_dir '{path}' does not exists or is not a directory.")
[docs] def _set_multi_loci(self, value):
"""
:param str value: the models fqn list separated by comma of multi loc models
"""
models_fqn = {v for v in [v.strip() for v in value.split(',')] if v}
self._options['multi_loci'] = set(models_fqn)
def _convert_log_level(self, value):
try:
log_level = int(value)
except ValueError:
value = value.upper()
try:
log_level = getattr(logging, value)
except AttributeError:
raise ValueError(f"Invalid value for log_level: {value}.") from None
return log_level
[docs] def _set_log_level(self, value):
"""
:param value:
:return:
"""
self._options['log_level'] = self._convert_log_level(value)
[docs] def _set_no_cut_ga(self, value):
"""
:param value:
:type value:
:return:
:rtype:
"""
self._options['cut_ga'] = not value
[docs] def models_dir(self):
"""
:return: list of models dir path
:rtype: list of str
"""
if self._options['models_dir']:
# the models_dir has been set by user
return self._options['models_dir']
else:
# use canonical location
return self._options['system_models_dir']
[docs] def multi_loci(self, model_fqn):
"""
:param str model_fqn: the model fully qualified name
:return: True if the model is multi loci, False otherwise
:rtype: bool
"""
return model_fqn in self._options['multi_loci']
[docs] def hmmer_dir(self):
"""
:return: The name of the directory containing the hmmsearch results (output, error, parsing)
"""
return 'hmmer_results'
[docs] def hit_weights(self):
"""
:return: the options used in scoring systems (mandatory_weight, accessory_weight, itself_weight,
exchangeable_weight, out_of_cluster_weight)
:rtype: dict
"""
return {'mandatory': self._options['mandatory_weight'],
'accessory': self._options['accessory_weight'],
'neutral': self._options['neutral_weight'],
'itself': self._options['itself_weight'],
'exchangeable': self._options['exchangeable_weight'],
'out_of_cluster': self._options['out_of_cluster_weight']
}
[docs] def log_level(self):
"""
:return: the verbosity output level
:rtype: int
"""
level = self._options['log_level'] - (10 * self.verbosity()) + (10 * self.quiet())
level = min(50, max(10, level))
return level
[docs]class NoneConfig:
"""
Minimalist Config object just use in some special case wher config is require by api
but not used for instance in :class:`macsypy.package.Package`
"""
def __getattr__(self, prop):
if prop in ('multi_loci', 'min_mandatory_genes_required', 'max_nb_genes',
'inter_gene_max_space', 'min_genes_required'):
return lambda x: None
else:
return lambda: None
