def _set_doc_parts(doc, parts):
"""
Update a document so that it has annotations from all
the given subdocuments.
Note that no attention is paid to annotation ids, spans,
etc. It's up to you to ensure that everything is kosher.
"""
doc.units = concat_l(x.units for x in parts)
doc.relations = concat_l(x.relations for x in parts)
doc.schemas = concat_l(x.schemas for x in parts)
def _set_doc_parts(doc, parts):
"""
Update a document so that it has annotations from all
the given subdocuments.
Note that no attention is paid to annotation ids, spans,
etc. It's up to you to ensure that everything is kosher.
"""
doc.units = concat_l(x.units for x in parts)
doc.relations = concat_l(x.relations for x in parts)
doc.schemas = concat_l(x.schemas for x in parts)
def overlapping_structs(inputs, k):
"""
Return items for structural annotations that have overlaps
"""
return concat_l(overlapping(inputs, k,
lambda x, t=ty: x.type == t)
for ty in stac.STRUCTURE_TYPES)
def overlapping_structs(inputs, k):
"""
Return items for structural annotations that have overlaps
"""
return concat_l(overlapping(inputs, k,
lambda x, t=ty: x.type == t)
for ty in stac.STRUCTURE_TYPES)
def reflow(text, width=40):
"""
Wrap some text, at the same time ensuring that all original
linebreaks are still in place
"""
def wrap(line):
"""
Wrap a single line of text. If empty, return a blank line
rather that no lines at all
"""
return textwrap.wrap(line, width) or ['']
return concat_l(wrap(t) for t in text.split("\n"))
def reflow(text, width=40):
"""
Wrap some text, at the same time ensuring that all original
linebreaks are still in place
"""
def wrap(line):
"""
Wrap a single line of text. If empty, return a blank line
rather that no lines at all
"""
return textwrap.wrap(line, width) or ['']
return concat_l(wrap(t) for t in text.split("\n"))
def _maybe_lozenge(gra, node):
"""Return (if applicable) lozenge nodes/edges starting from the given node
If the given node looks like the start of a lozenge, return all of
the nodes participating in the lozenge. If not, return None
Parameters
----------
gra: educe.stac.graph.Graph
node: string
hypergraph node name
Returns
-------
nodes: set(string)
nodes in lozenge (if whole tuple not None)
edges:
edges in lozenge (if whole tuple not None)
"""
top = [node]
top_out = _outgoing(gra, node)
if len(top_out) < 2:
return None
mid = [gra.rel_links(e)[1] for e in top_out]
if len(mid) != len(set(mid)):
# must all point to different nodes
return None
mid_outs = [_outgoing(gra, m) for m in mid]
# for each mid point: find the set of bottoms it points
# to (we're happy if non-empty intersection)
bots = [frozenset(gra.rel_links(e)[1]
for e in es)
for es in mid_outs]
bot = bots[0]
for cand in bots[1:]:
bot &= cand
if len(bot) < 1:
# no intersection
return None
loz_nodes = frozenset(top + mid) | bot
loz_edges = frozenset(top_out + concat_l(mid_outs))
return loz_nodes, loz_edges
def _maybe_lozenge(gra, node):
"""Return (if applicable) lozenge nodes/edges starting from the given node
If the given node looks like the start of a lozenge, return all of
the nodes participating in the lozenge. If not, return None
Parameters
----------
gra: educe.stac.graph.Graph
node: string
hypergraph node name
Returns
-------
nodes: set(string)
nodes in lozenge (if whole tuple not None)
edges:
edges in lozenge (if whole tuple not None)
"""
top = [node]
top_out = _outgoing(gra, node)
if len(top_out) < 2:
return None
mid = [gra.rel_links(e)[1] for e in top_out]
if len(mid) != len(set(mid)):
# must all point to different nodes
return None
mid_outs = [_outgoing(gra, m) for m in mid]
# for each mid point: find the set of bottoms it points
# to (we're happy if non-empty intersection)
bots = [frozenset(gra.rel_links(e)[1] for e in es) for es in mid_outs]
bot = bots[0]
for cand in bots[1:]:
bot &= cand
if len(bot) < 1:
# no intersection
return None
loz_nodes = frozenset(top + mid) | bot
loz_edges = frozenset(top_out + concat_l(mid_outs))
return loz_nodes, loz_edges
def nplike_trees(current, edu):
"any trees within an EDU that look like nps (smallest match)"
trees = enclosed_trees(edu.text_span(), current.parses.trees)
return concat_l(t.topdown_smallest(is_nplike) for t in trees)
def nplike_trees(current, edu):
"any trees within an EDU that look like nps (smallest match)"
trees = enclosed_trees(edu.text_span(),
current.parses.trees)
return concat_l(t.topdown_smallest(is_nplike)
for t in trees)
