Python KeyTerms.keyterm_in_node方法代码示例

# 需要导入模块: from regparser.layer.key_terms import KeyTerms [as 别名]
# 或者: from regparser.layer.key_terms.KeyTerms import keyterm_in_node [as 别名]
def collapsed_markers_matches(node_text, tagged_text):
    """Find collapsed markers, i.e. tree node paragraphs that begin within a
    single XML node, within this text. Remove citations and other false
    positives. This is pretty hacky right now -- it focuses on the plain
    text but takes cues from the tagged text. @todo: streamline logic"""
    # In addition to the regex above, keyterms are an acceptable prefix. We
    # therefore convert keyterms to satisfy the above regex
    node_for_keyterms = Node(node_text, node_type=Node.INTERP,
                             label=[get_first_interp_marker(node_text)])
    node_for_keyterms.tagged_text = tagged_text
    keyterm = KeyTerms.keyterm_in_node(node_for_keyterms)
    if keyterm:
        node_text = node_text.replace(keyterm, '.'*len(keyterm))

    collapsed_markers = []
    for marker in _first_markers:
        possible = ((m, m.start(), m.end())
                    for m in marker.finditer(node_text) if m.start() > 0)
        possible = remove_citation_overlaps(node_text, possible)
        # If certain characters follow, kill it
        for following in ("e.", ")", "”", '"', "'"):
            possible = [(m, s, end) for m, s, end in possible
                        if not node_text[end:].startswith(following)]
        possible = [m for m, _, _ in possible]
        # As all "1." collapsed markers must be emphasized, run a quick
        # check to weed out some false positives
        if '<E T="03">1' not in tagged_text:
            possible = filter(lambda m: m.group(1) != '1', possible)
        collapsed_markers.extend(possible)
    return collapsed_markers

# 需要导入模块: from regparser.layer.key_terms import KeyTerms [as 别名]
# 或者: from regparser.layer.key_terms.KeyTerms import keyterm_in_node [as 别名]
def collapsed_markers_matches(node_text, tagged_text):
    """Find collapsed markers, i.e. tree node paragraphs that begin within a
    single XML node, within this text. Remove citations and other false
    positives. This is pretty hacky right now -- it focuses on the plain
    text but takes cues from the tagged text. @todo: streamline logic"""
    # In addition to the regex above, keyterms are an acceptable prefix. We
    # therefore convert keyterms to satisfy the above regex
    node_for_keyterms = Node(
        node_text, node_type=Node.INTERP, tagged_text=tagged_text,
        label=[get_first_interp_marker(node_text)]
    )
    keyterm = KeyTerms.keyterm_in_node(node_for_keyterms)
    if keyterm:
        node_text = node_text.replace(keyterm, '.' * len(keyterm))

    collapsed_markers = []
    for marker in _first_markers:
        possible = [(m, m.start(), m.end())
                    for m in marker.finditer(node_text)]
        possible = remove_citation_overlaps(node_text, possible)
        possible = [triplet[0] for triplet in possible]
        collapsed_markers.extend(
            match for match in possible
            if not false_collapsed_marker(match, node_text, tagged_text)
        )
    return collapsed_markers

# 需要导入模块: from regparser.layer.key_terms import KeyTerms [as 别名]
# 或者: from regparser.layer.key_terms.KeyTerms import keyterm_in_node [as 别名]
    def test_emphasis_later(self):
        """ Don't pick up something that is emphasized later in a paragraph as
        a key-term. """
        node = Node(
            '(a) This has a list: apples et seq.',
            label=['101', '22', 'a'],
            tagged_text='(a) This has a list: apples <E T="03">et seq.</E>')

        assert KeyTerms.keyterm_in_node(node) is None

# 需要导入模块: from regparser.layer.key_terms import KeyTerms [as 别名]
# 或者: from regparser.layer.key_terms.KeyTerms import keyterm_in_node [as 别名]
    def test_emphasis_close_to_front(self):
        """ An emphasized word is close to the front, but is not a key term.
        """

        node = Node(
            '(a) T et seq. has a list: apples',
            label=['101', '22', 'a'],
            tagged_text='(a) T <E T="03">et seq.</E> has a list: apples')

        assert KeyTerms.keyterm_in_node(node) is None

# 需要导入模块: from regparser.layer.key_terms import KeyTerms [as 别名]
# 或者: from regparser.layer.key_terms.KeyTerms import keyterm_in_node [as 别名]
 def replace_markerless(self, stack, node, depth):
     """Assign a unique index to all of the MARKERLESS paragraphs"""
     if node.label[-1] == mtypes.MARKERLESS:
         keyterm = KeyTerms.keyterm_in_node(node, ignore_definitions=False)
         if keyterm:
             p_num = hash_for_paragraph(keyterm)
         else:
             # len(n.label[-1]) < 6 filters out keyterm nodes
             p_num = sum(n.is_markerless() and len(n.label[-1]) < 6
                         for n in stack.peek_level(depth)) + 1
         node.label[-1] = 'p{}'.format(p_num)

# 需要导入模块: from regparser.layer.key_terms import KeyTerms [as 别名]
# 或者: from regparser.layer.key_terms.KeyTerms import keyterm_in_node [as 别名]
    def paragraph_with_marker(self, text, tagged_text):
        """The paragraph has a marker, like (a) or a. etc."""
        # To aid in determining collapsed paragraphs, replace any
        # keyterms present
        node_for_keyterms = Node(text, node_type=Node.APPENDIX)
        node_for_keyterms.tagged_text = tagged_text
        node_for_keyterms.label = [initial_marker(text)[0]]
        keyterm = KeyTerms.keyterm_in_node(node_for_keyterms)
        if keyterm:
            mtext = text.replace(keyterm, '.'*len(keyterm))
        else:
            mtext = text

        for mtext in split_paragraph_text(mtext):
            if keyterm:     # still need the original text
                mtext = mtext.replace('.'*len(keyterm), keyterm)
            node = Node(mtext, node_type=Node.APPENDIX,
                        label=[initial_marker(mtext)[0]])
            self.nodes.append(node)