Source code for macsypy.system

#########################################################################
# MacSyFinder - Detection of macromolecular systems in protein dataset  #
#               using systems modelling and similarity search.          #
# Authors: Sophie Abby, Bertrand Neron                                  #
# Copyright (c) 2014-2021  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/>.                          #
#########################################################################

import abc
import itertools
import statistics
from itertools import chain
from operator import attrgetter
import logging
_log = logging.getLogger(__name__)

from.gene import GeneStatus
from .cluster import Cluster
from .hit import ValidHit
from .error import MacsypyError


[docs]class MatchMaker(metaclass=abc.ABCMeta): """ Is an abstract class for (Odered/Unordered)MatchMaker the `match` class method must be implemented in concrete classes """
[docs] def __init__(self, model): self._model = model # init my structures to count gene occurrences self.mandatory_counter = {g.name: 0 for g in model.mandatory_genes} self.exchangeable_mandatory = self._create_exchangeable_map(model.mandatory_genes) self.accessory_counter = {g.name: 0 for g in model.accessory_genes} self.exchangeable_accessory = self._create_exchangeable_map(model.accessory_genes) self.forbidden_counter = {g.name: 0 for g in model.forbidden_genes} self.exchangeable_forbidden = self._create_exchangeable_map(model.forbidden_genes) self.neutral_counter = {g.name: 0 for g in model.neutral_genes} self.exchangeable_neutral = self._create_exchangeable_map(model.neutral_genes)
[docs] def _create_exchangeable_map(self, genes): """ create a map between an exchangeable (formly homolog or analog) gene name and it's gene reference :param genes: The genes to get the exchangeable genes :type genes: list of :class:`macsypy.gene.ModelGene` objects :rtype: a dict with keys are the exchangeable gene_name and the value the reference gene name """ map = {} for gene in genes: for ex_gene in gene.exchangeables: map[ex_gene.name] = gene return map
[docs] def sort_hits_by_status(self, hits): """ sort :class:`macsypy.hit.Hit` according the the status of the gene the hit code for. :param hits: list of :class:`macsypy.hit.Hit` object :return: the valid hits according their status :rtype: a tuple of 4 lists * :class:`macsypy.hit.ValidHit` for MANDATORY genes * :class:`macsypy.hit.ValidHit` for ACCESSORY genes * :class:`macsypy.hit.ValidHit` for NEUTRAL genes * :class:`macsypy.hit.ValidHit` for FORBIDDEN genes """ mandatory_hits = [] accessory_hits = [] neutral_hits = [] forbidden_hits = [] for hit in hits: gene_name = hit.gene.name # the ValidHit need to be linked to the # gene of the model gene = self._model.get_gene(gene_name) if gene_name in self.mandatory_counter: self.mandatory_counter[hit.gene.name] += 1 mandatory_hits.append(ValidHit(hit, gene, GeneStatus.MANDATORY)) elif gene_name in self.exchangeable_mandatory: gene_ref = self.exchangeable_mandatory[gene_name] self.mandatory_counter[gene_ref.name] += 1 mandatory_hits.append(ValidHit(hit, gene, GeneStatus.MANDATORY)) elif gene_name in self.accessory_counter: self.accessory_counter[gene_name] += 1 accessory_hits.append(ValidHit(hit, gene, GeneStatus.ACCESSORY)) elif gene_name in self.exchangeable_accessory: gene_ref = self.exchangeable_accessory[gene_name] self.accessory_counter[gene_ref.name] += 1 accessory_hits.append(ValidHit(hit, gene, GeneStatus.ACCESSORY)) elif gene_name in self.neutral_counter: self.neutral_counter[gene_name] += 1 neutral_hits.append(ValidHit(hit, gene, GeneStatus.NEUTRAL)) elif gene_name in self.exchangeable_neutral: gene_ref = self.exchangeable_neutral[gene_name] self.neutral_counter[gene_ref.name] += 1 neutral_hits.append(ValidHit(hit, gene, GeneStatus.NEUTRAL)) elif gene_name in self.forbidden_counter: self.forbidden_counter[gene_name] += 1 forbidden_hits.append(ValidHit(hit, gene, GeneStatus.FORBIDDEN)) elif gene_name in self.exchangeable_forbidden: gene_ref = self.exchangeable_forbidden[gene_name] self.forbidden_counter[gene_ref.name] += 1 forbidden_hits.append(ValidHit(hit, gene, GeneStatus.FORBIDDEN)) return mandatory_hits, accessory_hits, neutral_hits, forbidden_hits
[docs] def present_genes(self): """ :return: the lists of genes name in model which are present replicon (included exchangeable) :rtype: tuple of 4 lists for mandatory, accessory, neutral and forbidden ([str gene_name, ...], [str gene_name], [str gene_name], [str gene_name]) """ mandatory_genes = [g_name for g_name, occ in self.mandatory_counter.items() if occ > 0] accessory_genes = [g_name for g_name, occ in self.accessory_counter.items() if occ > 0] neutral_genes = [g_name for g_name, occ in self.neutral_counter.items() if occ > 0] forbidden_genes = [g_name for g_name, occ in self.forbidden_counter.items() if occ > 0] return mandatory_genes, accessory_genes, neutral_genes, forbidden_genes
@abc.abstractmethod def match(self): pass
[docs]class OrderedMatchMaker(MatchMaker): """ check if a set of hits match the quorum for ordered replicons (ordered_replicon or gembase) """
[docs] def __init__(self, model, redundancy_penalty): self._redundancy_penalty = redundancy_penalty super().__init__(model)
[docs] def match(self, clusters): """ Check a set of clusters fill model constraints. If yes create a :class:`macsypy.system.System` otherwise create a :class:`macsypy.cluster.RejectedClusters`. :param clusters: The list of cluster to check if fit the model :type clusters: list of :class:`macsypy.cluster.Cluster` objects :return: either a System or a RejectedClusters :rtype: :class:`macsypy.system.System` or :class:`macsypy.cluster.RejectedClusters` object """ # count the hits # and track for each hit for which gene it counts for valid_clusters = [] forbidden_hits = [] for cluster in clusters: # sort hits between forbidden and the other # and transform hit in ValidHit *one_clst_allowed_hits, one_clst_forbidden_hits = self.sort_hits_by_status(cluster.hits) if one_clst_forbidden_hits: forbidden_hits.extend(one_clst_forbidden_hits) # create cluster of ValidHit one_clst_allowed_hits = [vh for st_hits in one_clst_allowed_hits for vh in st_hits] one_clst_allowed_hits.sort(key=attrgetter('position')) valid_clusters.append(Cluster(one_clst_allowed_hits + one_clst_forbidden_hits, self._model, cluster._hit_weights)) mandatory_genes, accessory_genes, neutral_genes, forbidden_genes = self.present_genes() # the count is finished # check if the quorum is reached # count how many different genes are represented in the clusters # the neutral genes belong to the cluster # but they do not count for the quorum _log.debug("#" * 50) _log.debug(f"mandatory_genes: {mandatory_genes}") _log.debug(f"accessory_genes: {accessory_genes}") _log.debug(f"neutral_genes: {neutral_genes}") _log.debug(f"forbidden_genes: {forbidden_genes}") reasons = [] is_a_system = True if forbidden_genes: is_a_system = False msg = f"There is {len(forbidden_hits)} forbidden genes occurrence(s):" \ f" {', '.join(h.gene.name for h in forbidden_hits)}" reasons.append(msg) _log.debug(msg) if len(mandatory_genes) < self._model.min_mandatory_genes_required: is_a_system = False msg = f'The quorum of mandatory genes required ({self._model.min_mandatory_genes_required}) is not reached: ' \ f'{len(mandatory_genes)}' reasons.append(msg) _log.debug(msg) if len(accessory_genes) + len(mandatory_genes) < self._model.min_genes_required: is_a_system = False msg = f'The quorum of genes required ({self._model.min_genes_required}) is not reached:' \ f' {len(accessory_genes) + len(mandatory_genes)}' reasons.append(msg) _log.debug(msg) if is_a_system: res = System(self._model, valid_clusters, self._redundancy_penalty) _log.debug("is a system") else: res = RejectedClusters(self._model, valid_clusters, reasons) _log.debug("#" * 50) return res
[docs]class UnorderedMatchMaker(MatchMaker):
[docs] def match(self, hits): """ :param hits: :return: """ # count the hits # and track for each hit for which gene it counts for mandatory_hits, accessory_hits, neutral_hits, forbidden_hits = self.sort_hits_by_status(hits) # the count is finished # check if the quorum is reached # count how many different genes are represented in the clusters # the neutral genes belong to the cluster # but they do not count for the quorum mandatory_genes, accessory_genes, neutral_genes, forbidden_genes = self.present_genes() _log.debug("#" * 50) _log.debug(f"mandatory_genes: {mandatory_genes}") _log.debug(f"accessory_genes: {accessory_genes}") _log.debug(f"neutral_genes: {neutral_genes}") _log.debug(f"forbidden_genes: {forbidden_genes}") is_a_potential_system = True reasons = [] if forbidden_genes: msg = f"There is {len(forbidden_hits)} forbidden genes occurrence(s):" \ f" {', '.join(h.gene.name for h in forbidden_hits)}" _log.debug(msg) if len(mandatory_genes) < self._model.min_mandatory_genes_required: is_a_potential_system = False msg = f'The quorum of mandatory genes required ({self._model.min_mandatory_genes_required}) is not reached: ' \ f'{len(mandatory_genes)}' reasons.append(msg) _log.debug(msg) if len(accessory_genes) + len(mandatory_genes) < self._model.min_genes_required: is_a_potential_system = False msg = f'The quorum of genes required ({self._model.min_genes_required}) is not reached:' \ f' {len(accessory_genes) + len(mandatory_genes)}' reasons.append(msg) _log.debug(msg) if is_a_potential_system: res = LikelySystem(self._model, mandatory_hits, accessory_hits, neutral_hits, forbidden_hits) _log.debug("There is a genetic potential for a system") elif any((mandatory_hits, accessory_hits, neutral_hits)): res = UnlikelySystem(self._model, mandatory_hits, accessory_hits, neutral_hits, forbidden_hits, reasons) else: res = None _log.debug("#" * 50) return res
[docs]class HitSystemTracker(dict): """ track in which system is implied each hit """
[docs] def __init__(self, systems): super(HitSystemTracker, self).__init__() for system in systems: v_hits = system.hits for v_hit in v_hits: hit = v_hit.hit if hit not in self: self[hit] = set() self[hit].add(system)
[docs]class ClusterSystemTracker(dict): """ track in which system is implied each cluster """
[docs] def __init__(self, systems): super(ClusterSystemTracker, self).__init__() for system in systems: clusters = system.clusters for clst in clusters: if clst not in self: self[clst] = set() self[clst].add(system)
[docs]class MetaSetOfHits(abc.ABCMeta): """ This metaclass control the AbstractSetOfHits class creation. In this metaclass we inject on the fly several attributes and properties two private attributes and one public property corresponding to each value of _supported_status class attribute defined in the concrete classes. for instance for System class * the attributes * self._mandatory * self._mandatory_occ * self._accessory * self._accessory_occ * self._neutral * self._neutral_occ * and the properties * mandatory * accessory * neutral are automatically injected The value for attributes `_<status>_occ` are filled by the `count` method which is defined in AbstractSetOfHits """
[docs] def getter_maker(status): """ Create a property which allow to access to the gene corresponding of the cat of the model :param str cat: the type of gene category to which we create the getter :return: unbound method """ def getter(self): occ = getattr(self, f"_{status}_occ") return {k: v for k, v in occ.items()} return getter
[docs] def __call__(cls, *args, **kwargs): new_system_inst = super().__call__(*args, **kwargs) # print() # print("##################### MetaSystem __call__ #################") # print("### new_system_inst", new_system_inst) # print("### new_system_inst._supported_status", new_system_inst._supported_status) for status in [str(s) for s in new_system_inst._supported_status]: # set the private attribute in the Model instance setattr(new_system_inst, f"_{status}_occ", {}) # set the public property in the Model class setattr(cls, f"{status}_occ", property(MetaSetOfHits.getter_maker(status))) # count fill _mandatory_occ, accessory_occ, ... attributes new_system_inst.count() return new_system_inst
[docs]class AbstractSetOfHits(metaclass=MetaSetOfHits): """ Is the mother class of System, RejectedCluster, LikelySystems UnlikelySystem, ... """
[docs] def __init__(self, model, replicon_name): self.model = model
def _sort_hits(self, hits): hits = sorted(hits, key=attrgetter('position')) return hits @property @abc.abstractmethod def hits(self): pass @property def replicon_name(self): """ :return: The name of the replicon :rtype: str """ return self._replicon_name @property def position(self): """ :return: The position of the first and last hit, excluded the hit coding for loners. If the system is composed only by loners, used loners to compute position :rtype: tuple (start: int, end:int) """ # hits are sorted by their positions hits = [h.position for h in self.hits if not h.gene_ref.loner] if hits: hits.sort() pos = hits[0], hits[-1] else: # there are only loners # take them pos = self.hits[0].position, self.hits[-1].position return pos
[docs] def count(self): """ fill structures one for supported status mandatory, accessory, ... each structure count how many hit for each gene of the model mandatory_occ = { gene_name : [ValidHit, ...] :return: None """ for status in [str(s) for s in self._supported_status]: setattr(self, f"_{status}_occ", {g.name: [] for g in getattr(self.model, f"{status}_genes")} ) # all the hits are ValidHit for hit in self.hits: name = hit.gene_ref.alternate_of().name status = str(hit.status) # transform gene status in lower string try: getattr(self, f"_{status}_occ")[name].append(hit) except AttributeError: pass except KeyError: raise MacsypyError(f"gene '{name}' does not belong to '{status}' genes in model '{self.model.name}'")
@property def wholeness(self): """ :return: a score indicating the genes ratio of the model which have at least one hit by default full system is mandatory + accessory ('neutral' genes do not count) but for special corner case it can be sepcified in model definition (xml) or on the command line :rtype: float """ # model completude # the neutral hit do not participate to the model completude score = sum([1 for hits in chain(self._mandatory_occ.values(), self._accessory_occ.values()) if hits]) / \ self.model.max_nb_genes return score
[docs]class System(AbstractSetOfHits): """ Modelize as system. a system is an occurrence of a given model on a replicon. """ _supported_status = (GeneStatus.MANDATORY, GeneStatus.ACCESSORY, GeneStatus.NEUTRAL) _id = itertools.count(1)
[docs] def __init__(self, model, clusters, redundancy_penalty=1.5): """ :param model: The model which has ben used to build this system :type model: :class:`macsypy.model.Model` object :param clusters: The list of cluster that form this system :type clusters: list of :class:`macsypy.cluster.Cluster` objects """ self._replicon_name = clusters[0].replicon_name self.id = f"{self.replicon_name}_{model.name}_{next(self._id)}" self.clusters = clusters self.redundancy_penalty = redundancy_penalty self._score = None super().__init__(model, self._replicon_name)
@property def score(self): """ :return: a score take in account * if a hit match for the gene or it is an exchangeable gene * if a hit is duplicated and already present in the system or the cluster * if a hit match for mandatory/accessory gene of the model :rtype: float """ if self._score is not None: # The score of the system is called for each clique # So to avoid computation we cached it return self._score def clst_func(clsts): """ :param clsts: list of clusters :return: return the list of functions which are represented in these clusters. :rtype: set of str """ func_in_clst = {} for clst in clsts: for v_hit in clst.hits: func = v_hit.gene_ref.alternate_of().name if func in func_in_clst: func_in_clst[func].append(clst) else: func_in_clst[func] = [clst] return func_in_clst _log.debug(f"=================== score computation for system {self.id} ===================") # split clusters in 2 # the clusters loners multi systems # and the others (regular) regular_clsts = [] loner_multi_syst_clsts = [] for clst in self.clusters: if clst.loner and clst.hits[0].multi_system: loner_multi_syst_clsts.append(clst) else: regular_clsts.append(clst) # Compute score of regular clusters clst_scores = [clst.score for clst in regular_clsts] score = sum(clst_scores) _log.debug(f"regular clusters scores sum({clst_scores}) = {score}") for gene in self.model.mandatory_genes + self.model.accessory_genes: _log.debug("compute penalty redundancy") # it cannot be forbidden gene in System instance # the neutral genes do not play a role in score (only to build clusters) clst_having_hit = sum([1 for clst in regular_clsts if clst.fulfilled_function(gene)]) _log.debug(f"nb of clusters which fulfill function of {gene.name} = {clst_having_hit}") if clst_having_hit: clst_penalty = (clst_having_hit - 1) * self.redundancy_penalty _log.debug(f"clst_penalty {- clst_penalty}") score -= clst_penalty # compute score of loners multi systems loners_multi_syst_functions = clst_func(loner_multi_syst_clsts) regular_functions = set(clst_func(regular_clsts)) _log.debug("compute score of loner multi systems") for funct in loners_multi_syst_functions: if not funct in regular_functions: loners_score = max(c.score for c in loners_multi_syst_functions[funct]) _log.debug(f"score for {funct} = {loners_score}") score += loners_score else: # if the biological funct is already encoded by regular clusters # we do not increase the score _log.debug(f"{funct} is already in regular clusters") pass self._score = score _log.debug(f"score of system {self.id} = {score:.2f}") return score
[docs] def occurrence(self): """ sometimes several systems collocates so they form only one cluster so macsyfinder build only one system the occurrence is an indicator of how many systems are it's based on the number of occurrence of each mandatory genes The multi_system genes are not take in account. :return: a predict number of biologic systems """ genes = {g.name: g for g in self.model.genes} occ_per_gene = [len(hits) for gene_name, hits in self._mandatory_occ.items() if not genes[gene_name].multi_system] # if a systems contains 5 gene with occ of 1 and 5 gene with 0 occ # the median is 0.5 # round(0.5) = 0 # so I fix a floor value at 1 return max(1, round(statistics.median(occ_per_gene)))
@property def hits(self): """ :return: The list of all hits that compose this system :rtype: [:class:`macsypy.hit.ValidHits` , ... ] """ hits = self._sort_hits([h for cluster in self.clusters for h in cluster.hits]) return hits @property def loci_num(self): """ :return: the number of the corresponding locus for each cluster the cluster made of only one hit reprenting a loner is not considered as a loci so these clusters have the locus_num = 0 :rtype: list of int """ loci = [] loci_num = 0 loners_num = 0 # we do not take loners in account for clst in self.clusters: if not clst.loner: loci_num += 1 loci.append(loci_num) else: loners_num -= 1 loci.append(loners_num) return loci @property def loci_nb(self): """ :return: The number of loci of this system (loners are not considered) :rtype: int >= 0 """ loci_nb = len([1 for c in self.clusters if not c.loner]) return loci_nb @property def multi_loci(self): """ :return: True if the systems is encoded in multiple loci. False otherwise :rtype: bool """ return self.loci_nb > 1
[docs] def is_compatible(self, other): """ :param other: the other systems to test compatibility :type other: :class:`macsypy.system.System` object :return: True if other system is compatible with this one. False otherwise. Two systems are compatible if they do not share :class:`macsypy.hit.Hit` except hit corresponding to a multi_system gene in the model. .. note:: This method is used to compute the best combination of systems. """ other_hits = {vh.hit for vh in other.hits if not vh.multi_system} my_hits = {vh.hit for vh in self.hits if not vh.multi_system} return not (my_hits & other_hits)
[docs]class RejectedClusters(AbstractSetOfHits): """ Handle a set of clusters which has been rejected during the :func:`macsypy.system.match` step This clusters (can be one) does not fill the requirements or contains forbidden genes. """ _supported_status = (GeneStatus.MANDATORY, GeneStatus.ACCESSORY, GeneStatus.NEUTRAL, GeneStatus.FORBIDDEN)
[docs] def __init__(self, model, clusters, reasons): """ :param model: :type model: :class:`macsypy.model.Model` object :param clusters: list of clusters. These Clusters should be created with :class:`macsypy.cluster.Cluster` of :class:`macsypy.hit.ValidHit` objects :type clusters: list of :class:`macsypy.cluster.Cluster` objects :param reason: the reason why these clusters have been rejected :type reason: list of string """ if isinstance(clusters, Cluster): self.clusters = [clusters] else: self.clusters = clusters self._replicon_name = self.clusters[0].replicon_name self._reasons = reasons if isinstance(reasons, list) else [reasons] super().__init__(model, self._replicon_name)
[docs] def __str__(self): """ :return: a string representation of this RejectedCluster """ s = '' for c in self.clusters: s += str(c) s += '\n' s += "These clusters have been rejected because:\n" for r in self.reasons: s += f"\t- {r}\n" return s
@property def hits(self): """ :return: The list of all hits that compose this system :rtype: [:class:`macsypy.hit.ValidHits` , ... ] """ hits = self._sort_hits([h for cluster in self.clusters for h in cluster.hits]) return hits @property def reasons(self): return self._reasons
[docs]class AbstractUnordered(AbstractSetOfHits): """ Technical abstract class to factorize code share between LikelySystem and UnlikelySystem """ _id = itertools.count(1)
[docs] def __init__(self, model, mandatory_hits, accessory_hits, neutral_hits, forbidden_hits): self._mandatory_hits = mandatory_hits self._accessory_hits = accessory_hits self._neutral_hits = neutral_hits self._forbidden_hits = forbidden_hits self._replicon_name = self.allowed_hits[0].replicon_name self.id = f"{self.replicon_name}_{model.name}_{next(self._id)}" super().__init__(model, self._replicon_name)
@property def hits(self): """ :return: The list of all hits sorted by their position :rtype: list of :class:`macsypy.hit.ValidHit` objects """ return self._sort_hits(self._mandatory_hits + self._accessory_hits + self._neutral_hits + self.forbidden_hits) @property def mandatory_hits(self): """ :return: The list of mandatory hits :rtype: list of :class:`macsypy.hit.ValidHit` objects """ return self._mandatory_hits[:] @property def accessory_hits(self): """ :return: The list of accesory hits :rtype: list of :class:`macsypy.hit.ValidHit` objects """ return self._accessory_hits[:] @property def neutral_hits(self): """ :return: The list of neutral hits :rtype: list of :class:`macsypy.hit.ValidHit` objects """ return self._neutral_hits[:] @property def forbidden_hits(self): """ :return: The list of forbidden hits :rtype: list of :class:`macsypy.hit.ValidHit` objects """ return self._forbidden_hits[:] @property def allowed_hits(self): """ :return: The list of allowed (mandatory, accessory, neutral) hits :rtype: list of :class:`macsypy.hit.ValidHit` objects """ return self._mandatory_hits + self._accessory_hits + self._neutral_hits
[docs]class LikelySystem(AbstractUnordered): """" Handle components that fill the quorum requirements defined in model. with no idea about genetic organization (gene cluster) so we cannot take in account forbidden genes .. note: do not forget that this class inherits from MetaSetOfHits so the getter to mandatory, accessory, neutral, forbidden is dynamically injected by the meta class base on _supported_status """ _supported_status = (GeneStatus.MANDATORY, GeneStatus.ACCESSORY, GeneStatus.NEUTRAL, GeneStatus.FORBIDDEN)
[docs] def __str__(self): """ :return: a string representation of this LikelySystem """ return ', '.join([f"({h.id}, {h.gene.name}, {h.position})" for h in self.hits])
[docs]class UnlikelySystem(AbstractUnordered): """ Handle components that not fill the quorum requirements defined in model. """ _supported_status = (GeneStatus.MANDATORY, GeneStatus.ACCESSORY, GeneStatus.NEUTRAL, GeneStatus.FORBIDDEN)
[docs] def __init__(self, model, mandatory_hits, accessory_hits, neutral_hits, forbidden_hits, reasons): """ :param model: The model which has ben used to build this system :type model: :class:`macsypy.model.Model` object :param allowed_hits: The list of hits that form this potential system this hits status must be MANDATORY, ACCESSORY or NEUTRAL :type allowed_hits: list of :class:`macsypy.hit.ValidHit` objects :param forbidden_hits: The list of hits that are forbidden :type forbidden_hits: list of :class:`macsypy.hit.ValidHit` objects :param reasons: the reasons why this set of hits has been rejected :type reasons: List of str """ super().__init__(model, mandatory_hits, accessory_hits, neutral_hits, forbidden_hits) self._reasons = reasons if isinstance(reasons, list) else [reasons]
[docs] def __str__(self): """ :return: a string representation of this UnlikelySystem """ s = ', '.join([f"({h.id}, {h.gene.name}, {h.position})" for h in self.hits]) s += ': These hits does not probably constitute a system because:\n' s += '\n'.join(self.reasons) return s
@property def reasons(self): """ :return: The reasons why it probably not a system :rtype: list of string """ return self._reasons