def __init__(self, signature):
self.signature = signature
self.score = 0.0 # aggregate score as per user-weights
self.counts = util.MatchCounts() # aggregate match counts
self.example_category = None # exemplar category for the parse
self.rejected = 0 # no. of parses rejected by the formula
self.selected = 0 # no. of parses allowed by the formula
def counts_for(self, span_subset=None, counts=None):
if counts is None:
counts = util.MatchCounts()
for index, count in enumerate(self.span_counts):
if span_subset is None or span_subset.is_allowed(index):
counts.merge(count)
return counts
def __init__(self, request):
self.request = request
self.error_message = None
self.span_signatures = util.parse_to_span_signatures(request.query)
# All counts are after the parse selector has come into play.
self.counts_across_spans = util.MatchCounts()
self.counts_across_selected_spans = util.MatchCounts()
self.counts_by_span = [
util.MatchCounts() for _ in self.span_signatures
]
# Top selected parses shown.
self.top_parses = []
# Statistics of selected parses that aren't not shown.
self.top_parses_not_shown = {"num": 0, "counts": util.MatchCounts()}
# Statistics of unselected parses.
self.unselected_parses = {"num": 0, "counts": util.MatchCounts()}
def __init__(self):
# Exemplar category QID, frame, and parse with this signature.
self.example_qid = None
self.example_category = None
self.example_parse = None
# Aggregate stats across all (category, parse) pairs with this signature.
# If a category has >=2 parses with this signature, then only the highest
# scoring parse is considered.
# Total score across all parses.
self.score = 0.0
# Total fact-matching statistics.
self.fact_matches = util.MatchCounts()
# Non-deduped total number of member items.
self.members = 0
# Total number of categories.
self.num = 0
def handle_signature(self, signature, categories, form):
score_type = form.getvalue("main_form_sort_metric")
fact_weights = self.fact_match_weights(form)
signature_type = form.getvalue("main_form_signature_type")
# Sort all parses with this signature.
output = []
for (qid, category, parse) in categories:
score = self.parse_score(category, parse, score_type, fact_weights)
output.append((qid, category, parse, score))
output.sort(key=lambda x: -x[3])
# Get fact-matching statistics. Consider only the top parse for a category
# if it has >1 parses with the same signature.
category_count = defaultdict(int)
match_counts = util.MatchCounts()
span_match_counts = defaultdict(util.MatchCounts)
num_members = 0
for qid, category, parse, score in output:
category_count[qid] += 1
if category_count[qid] > 1:
continue
num_members += len(category.members)
util.fact_matches_for_parse(parse, match_counts)
for span in parse.spans:
span_signature = util.span_signature(span, signature_type)
util.fact_matches_for_span(span, span_match_counts[span_signature])
# Write a summary.
self._tag("div",
"<b>%s</b>: in %d (category, parse) pairs across %d categories" % \
(signature, len(categories), len(category_count)))
self._tag("b", "#Items across categories: ")
self._text("%d (incl. possible duplicates)" % num_members)
self._br()
self._tag("b", "Span-level fact-matching statistics")
self.write_main_table_header(
["Span Signature"],
[t.name for t in FactMatchType])
for span_signature, span_matches in span_match_counts.iteritems():
self._begin("tr")
self._cell(span_signature)
self._separator(header=False)
self.write_fact_match_counts(span_matches)
self._end("tr")
self._begin("tr")
self._cell("All")
self._separator(header=False)
self.write_fact_match_counts(match_counts)
self._end("tr")
self._end("table")
# Give an option to generate a recordio file.
if signature_type == "full":
self._br()
self._begin("table class='main_table'")
self._begin("tr")
self._begin("td")
self._begin("form", id="recordio_form", method="POST", action="", \
target="_blank")
self._begin_end("input", type="hidden", name="main_form_functionality", \
value="recordio")
self._begin_end("input", type="hidden", name="recordio_signature", \
id="recordio_signature", value=signature)
self._tag("b", "Generate recordio for this signature")
self._br()
self._br()
self._text("Filename: ")
filename = "local/data/e/wikicat/" + signature.replace("$", "_") + ".rec"
self._begin_end("input", type="text", size=100, \
name="recordio_filename", value=filename)
self._br()
self._text("Category QIDs ('ALL' for all): ")
self._begin_end("input", type="text", size=100, value="ALL", \
name="recordio_categories")
self._br()
self._text("Generate facts for these types:")
self._begin_end("input", type="text", size=100, \
value="NEW,ADDITIONAL,SUBSUMED_BY_EXISTING", \
name="recordio_match_types")
self._br()
self._text("Generate the following facts:")
self._br()
count = 0
for token in signature.split():
if token[0] == '$' and token[1:].find("$") >= 0:
name = "recordio_span%d" % count
self._text(" " + token + " ")
self._begin_end("input", type="checkbox", name=name, id=name, \
checked="on")
self._br()
count += 1
self._begin_end("input", type="hidden", name="recordio_num_spans", \
id="recordio_total_spans", value=count)
self._begin_end("input", type="submit")
self._end(["form", "td", "tr", "table"])
# Write the individual parses in a tabular form.
self._br()
self._tag("b", "Categories with parses matching '" + signature + "'")
seen = set()
max_rows = 200
self.write_main_table_header(
["Category", "Prelim parse score", "#Members", "Fact-matching score"],
[t.name for t in FactMatchType])
row_count = 0
for qid, category, parse, score in output:
if row_count >= max_rows:
break
if qid in seen:
continue
row_count += 1
seen.add(qid)
self._begin("tr")
self._begin("td")
self._form_anchor(qid + ": " + category.name, qid)
if category_count[qid] > 1:
more = category_count[qid] - 1
self._text(" (%d more parse%s)" % (more, "" if more == 1 else "s"))
self._end("td")
self._cell(parse.score, numeric=True)
self._cell(len(category.members), numeric=True)
self._cell("%.4f" % self.parse_fact_score(parse, fact_weights), True)
self._separator(header=False)
counts = util.fact_matches_for_parse(parse)
self.write_fact_match_counts(counts)
self._end("tr")
self._end("table")
