Example #1
0
         if reduce(operator.or_, 
                   [x in chunk.lower() for x in useless_lines]): continue
         if len(chunk) < 2: continue
         outfile.write('%010d|%s\n' % (chunkid, chunk))
         chunkmap[fakename].append(chunkid)
         chunkid += 1
 outfile.close()
 print "Saving chunkmap"
 pickle.dump(chunkmap, open(outmapname, "wb"), pickle.HIGHEST_PROTOCOL)
 print "These files couldn't be processed:"
 print '\n'.join(skipped)
 print "Opening (or creating) cache in", sys.argv[2]
 the_cache=StringDBDict(os.path.join(sys.argv[2], DEFAULT_CACHE_NAME),
                        file_mode='c')
 PubMed.download_many([str(x) for x in known_articles if str(x) not in 
                       the_cache.keys()], download_callback,
                      parser=Medline.RecordParser())
 mti_filename=sys.argv[1]+'.mti'
 print "Finished processing the cache. Using the cache to build", \
        mti_filename
 mti_file=open(mti_filename, "w")
 chunkmap={}
 hexfinder=re.compile(r'\\x[a-f0-9][a-f0-9]', re.IGNORECASE)
 for article in known_articles:
     try:
         article_record=the_cache[str(article)]
     except KeyError:
         print "Article doesn't exist in cache. Skipping."
         continue
     if article_record.abstract=='':
         print "Article", article, "has no abstract. Skipping."
Example #2
0
class Tree(object):
    """Describes a tree of MeSH terms. The contents should be tree_node,
    generated by the build_mesh_tree_file script. The tree contains a 
    term name (string)->tree_node mapping."""
    def __init__(self, filename="*&$#$%#", file_mode="r", cachesize=1048576):
        # If the filename isn't specified, use the default one (None has a
        # special meaning, so we can't use it - it means create a temp file)
        if filename == "*&$#$%#":
            filename = _DEFAULT_TREE_DATA
        logging.info("Initializing tree with data from %r", filename)
        self._tree = StringDBDict(persistent_file=filename,
                                  file_mode=file_mode,
                                  cachesize=cachesize)
        self._invlookup = None  # Init the inverse name lookup database lazily
        self._origname = filename
        self.terms = self._tree.keys()
        self.terms.sort()
        # This one is for speedy retrieval and indexing
        self._term_list_as_dict = None
        self._search_dict = None
        self.num_terms = len(self.terms)
        return

    def original_filename(self):
        """Returns the original filename of the tree."""
        return self._origname

    def __repr__(self):
        return "<MeSH Semantic tree from %s with %d terms>" % \
                (self._origname, self.num_terms)

    @staticmethod
    def common_root(pos1, pos2):
        """Determines the common dotted root of a pair of tree positions."""
        pos1_split = pos1.split(".")
        pos2_split = pos2.split(".")
        common_terms = []
        for x in zip(pos1_split, pos2_split):
            if x[0] != x[1]: break
            common_terms.append(x[0])
        return '.'.join(common_terms)

    def semantic_distance(self, term1, term2):
        """Distance between two nodes, assuming there is a single root node
        for the tree linking all subtrees. Qualifiers and descriptors are
        automatically excluded"""
        node1 = self._tree[term1]
        node2 = self._tree[term2]
        if node1.is_qualifier() or node2.is_qualifier():
            return -1
        if node1.is_descriptor() or node2.is_descriptor():
            return -1
        distance = 999999999999
        for pos1 in node1.position:
            pos1 = '#.%s' % pos1
            for pos2 in node2.position:
                # The extra item in pos 1 and pos 2 emulates the common root
                # node
                pos2 = '#.%s' % pos2
                root = self.common_root(pos1, pos2)
                rootdots = root.count(".")
                dist_1 = pos1.count(".") - rootdots
                dist_2 = pos2.count(".") - rootdots
                dist = dist_1 + dist_2
                if dist < 0.0:
                    raise ValueError(
                        "Problem: %s<->%s have a negative "
                        "distance", pos1, pos2)
                if dist < distance: distance = dist
        return distance

    def distance(self, term1, term2):
        """Distance between two nodes, assuming no single root node
        for the tree linking all subtrees."""
        # Check for same-treeness
        possible_trees1 = self._tree[term1].get_trees()
        possible_trees2 = self._tree[term2].get_trees()
        combination_thereof = [x in possible_trees2 for x in possible_trees1]
        if True not in combination_thereof:
            return -1
        sd = self.semantic_distance(term1, term2)
        return sd

    def deepest_of_list(self, list_of_terms):
        return max(
            (self._tree[x].deepest_depth(), x) for x in list_of_terms)[1]

    def _init_inverse_lookup(self):
        """Sets up the internal data store to perform reverse lookups."""
        logging.debug("First request of a reverse lookup. Building the " \
                      "inverse lookup dictionary.")
        self._invlookup = {}
        for k, items in self._tree.iteritems():
            for item in items.position:
                self._invlookup[item] = k
        logging.log(ULTRADEBUG, "Done building inverse lookup dictionary.")
        return

    def reverse_lookup(self, term):
        """Perform a reverse lookup, after setting up the reverse lookup
        dictionary if necessary."""
        if self._invlookup is None:
            self._init_inverse_lookup()
        try:
            return self._invlookup[term]
        except KeyError:
            raise PositionNotInTree("%s is not a position in this tree." %
                                    term)

    def __getitem__(self, key):
        try:
            return self._tree[key.lower()]
        except KeyError:
            raise TermNotInTree("The term %s is not in the tree %r." %
                                (key, self))

    def eliminate_checktags(self, list_of_terms):
        """Returns a list of terms with the checktags omitted."""
        return [x for x in list_of_terms if x not in checktags]

    def eliminate_descriptors(self, list_of_terms):
        return [x for x in list_of_terms if not self._tree[x].is_descriptor(x)]

    def eliminate_qualifiers(self, list_of_terms):
        return [x for x in list_of_terms if not self[x].is_qualifier()]

    def only_checktags(self, list_of_terms):
        return [x for x in list_of_terms if x in checktags]

    def only_qualifiers(self, list_of_terms):
        return [x for x in list_of_terms if self._tree[x].is_qualifier()]

    def only_descriptors(self, list_of_terms):
        return [x for x in list_of_terms if self._tree[x].is_descriptor()]

    def index(self, term):
        """Returns the index of a term in the sorted term list"""
        if self._term_list_as_dict is None:
            # Precompute all indexes
            logging.debug("Building MeSH tree index.")
            currindex = 0
            self._term_list_as_dict = {}
            for each_term in self.terms:
                self._term_list_as_dict[each_term] = currindex
                for each_synonym in self[each_term].synonyms:
                    self._term_list_as_dict[each_synonym] = currindex
                currindex += 1
        try:
            return self._term_list_as_dict[term]
        except KeyError:
            raise TermNotInTree("Term %s is not a member of tree %r" %
                                (term, self))

    def term_vector(self, list_of_terms):
        """Returns a VocabularyVector representing the list of terms as seen 
        by this tree."""
        new_vector = VocabularyVector(self.num_terms)
        for term in list_of_terms:
            try:
                new_vector[self.index(term)] = 1
            except TermNotInTree:
                logging.warn(
                    'Weird: term %r could not be found in %r. It '
                    'should be there.', term, self)
        return new_vector

    def _init_search_dict(self):
        """Sets up the internal data store to perform searches."""
        logging.debug("First request of a search. Building the " \
                      "search dictionary.")
        self._search_dict = {}
        for k, items in self._tree.iteritems():
            for synonym in items.synonyms:
                if synonym in self._search_dict:
                    self._search_dict[synonym].append(k)
                else:
                    self._search_dict[synonym] = [k]
            if k in self._search_dict:
                self._search_dict[k].append(k)
            else:
                self._search_dict[k] = [k]

    def search(self, term):
        """Searches the tree for a term, looking at synonyms as well as keys"""
        if self._search_dict is None:
            self._init_search_dict()
        try:
            result = self._search_dict[term]
        except KeyError:
            return TreeSearchResults([])
        if len(result) == 1:
            return TreeSearchResults(self[result[0]])
        return TreeSearchResults([self[x] for x in result])
Example #3
0
File: tree.py Project: YZWD/MEDRank
class Tree(object):
    """Describes a tree of MeSH terms. The contents should be tree_node,
    generated by the build_mesh_tree_file script. The tree contains a 
    term name (string)->tree_node mapping."""
    def __init__(self, filename="*&$#$%#", file_mode="r", cachesize=1048576):
        # If the filename isn't specified, use the default one (None has a
        # special meaning, so we can't use it - it means create a temp file)
        if filename=="*&$#$%#":
            filename=_DEFAULT_TREE_DATA
        logging.info("Initializing tree with data from %r", filename)
        self._tree=StringDBDict(persistent_file=filename, file_mode=file_mode,
                                cachesize=cachesize)
        self._invlookup=None # Init the inverse name lookup database lazily
        self._origname=filename
        self.terms=self._tree.keys()
        self.terms.sort()
        # This one is for speedy retrieval and indexing
        self._term_list_as_dict=None
        self._search_dict=None
        self.num_terms=len(self.terms)
        return
    def original_filename(self):
        """Returns the original filename of the tree."""
        return self._origname
    def __repr__(self): 
        return "<MeSH Semantic tree from %s with %d terms>" % \
                (self._origname, self.num_terms)
    
    @staticmethod
    def common_root(pos1, pos2):
        """Determines the common dotted root of a pair of tree positions."""
        pos1_split=pos1.split(".")
        pos2_split=pos2.split(".")
        common_terms=[]
        for x in zip(pos1_split, pos2_split):
            if x[0]!=x[1]: break
            common_terms.append(x[0])
        return '.'.join(common_terms)
    
    def semantic_distance(self, term1, term2):
        """Distance between two nodes, assuming there is a single root node
        for the tree linking all subtrees. Qualifiers and descriptors are
        automatically excluded"""
        node1=self._tree[term1]
        node2=self._tree[term2]
        if node1.is_qualifier() or node2.is_qualifier():
            return -1
        if node1.is_descriptor() or node2.is_descriptor():
            return -1
        distance=999999999999
        for pos1 in node1.position:
            pos1='#.%s' % pos1
            for pos2 in node2.position:
                # The extra item in pos 1 and pos 2 emulates the common root 
                # node
                pos2='#.%s' % pos2
                root=self.common_root(pos1, pos2)
                rootdots=root.count(".")
                dist_1=pos1.count(".")-rootdots
                dist_2=pos2.count(".")-rootdots
                dist=dist_1+dist_2
                if dist < 0.0:
                    raise ValueError("Problem: %s<->%s have a negative "
                                     "distance", pos1, pos2)
                if dist < distance: distance=dist
        return distance
    def distance(self, term1, term2):
        """Distance between two nodes, assuming no single root node
        for the tree linking all subtrees."""
        # Check for same-treeness
        possible_trees1=self._tree[term1].get_trees()
        possible_trees2=self._tree[term2].get_trees()
        combination_thereof=[x in possible_trees2 for x in possible_trees1]
        if True not in combination_thereof:
            return -1
        sd=self.semantic_distance(term1, term2)
        return sd
    def deepest_of_list(self, list_of_terms):
        return max((self._tree[x].deepest_depth(), x)
                   for x in list_of_terms)[1]
    def _init_inverse_lookup(self):
        """Sets up the internal data store to perform reverse lookups."""
        logging.debug("First request of a reverse lookup. Building the " \
                      "inverse lookup dictionary.")
        self._invlookup={}
        for k, items in self._tree.iteritems():
            for item in items.position:
                self._invlookup[item]=k
        logging.log(ULTRADEBUG, "Done building inverse lookup dictionary.")
        return

    def reverse_lookup(self, term):
        """Perform a reverse lookup, after setting up the reverse lookup
        dictionary if necessary."""
        if self._invlookup is None:
            self._init_inverse_lookup()
        try:
            return self._invlookup[term]
        except KeyError:
            raise PositionNotInTree("%s is not a position in this tree." %
                                    term)

    def __getitem__(self, key):
        try:
            return self._tree[key.lower()]
        except KeyError:
            raise TermNotInTree("The term %s is not in the tree %r." % 
                                (key, self))

    def eliminate_checktags(self, list_of_terms):
        """Returns a list of terms with the checktags omitted."""
        return [x for x in list_of_terms if x not in checktags]

    def eliminate_descriptors(self, list_of_terms):
        return [x for x in list_of_terms 
                if not self._tree[x].is_descriptor(x)]
    def eliminate_qualifiers(self, list_of_terms):
        return [x for x in list_of_terms
                if not self[x].is_qualifier()]
    def only_checktags(self, list_of_terms):
        return [x for x in list_of_terms if x in checktags]
    def only_qualifiers(self, list_of_terms):
        return [x for x in list_of_terms if self._tree[x].is_qualifier()]
    def only_descriptors(self, list_of_terms):
        return [x for x in list_of_terms if self._tree[x].is_descriptor()]
    def index(self, term):
        """Returns the index of a term in the sorted term list"""
        if self._term_list_as_dict is None:
            # Precompute all indexes
            logging.debug("Building MeSH tree index.")
            currindex=0
            self._term_list_as_dict={}
            for each_term in self.terms:
                self._term_list_as_dict[each_term]=currindex
                for each_synonym in self[each_term].synonyms:
                    self._term_list_as_dict[each_synonym]=currindex
                currindex+=1
        try:
            return self._term_list_as_dict[term]
        except KeyError:
            raise TermNotInTree("Term %s is not a member of tree %r" % 
                                (term, self))
    def term_vector(self, list_of_terms):
        """Returns a VocabularyVector representing the list of terms as seen 
        by this tree."""
        new_vector=VocabularyVector(self.num_terms)
        for term in list_of_terms:
            try:
                new_vector[self.index(term)]=1
            except TermNotInTree:
                logging.warn('Weird: term %r could not be found in %r. It '
                             'should be there.',
                             term, self)
        return new_vector
    def _init_search_dict(self):
        """Sets up the internal data store to perform searches."""
        logging.debug("First request of a search. Building the " \
                      "search dictionary.")
        self._search_dict={}
        for k, items in self._tree.iteritems():
            for synonym in items.synonyms:
                if synonym in self._search_dict:
                    self._search_dict[synonym].append(k)
                else:
                    self._search_dict[synonym]=[k]
            if k in self._search_dict:
                self._search_dict[k].append(k)
            else:
                self._search_dict[k]=[k]
    def search(self, term):
        """Searches the tree for a term, looking at synonyms as well as keys"""
        if self._search_dict is None:
            self._init_search_dict()
        try:
            result=self._search_dict[term]
        except KeyError:
            return TreeSearchResults([])
        if len(result)==1:
            return TreeSearchResults(self[result[0]])
        return TreeSearchResults([self[x] for x in result])