def cmd_oracle(args, t, active_events):
import cuttsum.judgements
print t.clear
all_matches = cuttsum.judgements.get_merged_dataframe()
for event in active_events:
print event
matches = all_matches[all_matches["query id"] == event.query_id]
matching_doc_ids = set(matches["document id"].tolist())
print matches[0:10]
if event.query_id.startswith("TS13"):
corpus = cuttsum.corpora.EnglishAndUnknown2013()
elif event.query_id.startswith("TS14"):
corpus = cuttsum.corpora.SerifOnly2014()
else:
raise Exception("Bad query id: {}".format(event.query_id))
from cuttsum.trecdata import SCChunkResource
chunks_res = SCChunkResource()
for hour, path, si in chunks_res.streamitem_iter(event, corpus):
print si.stream_id, hour
if si.stream_id in matching_doc_ids:
print si.stream_id, si.stream_time, hour
for match in matches[matches["document id"] ==
si.stream_id].iterrows():
print match[["nugget text", "update text"]]
#if si.body.clean_visible is not None:
with t.cbreak():
t.inkey()
def cmd_oracle(args, t, active_events):
import cuttsum.judgements
print t.clear
all_matches = cuttsum.judgements.get_merged_dataframe()
for event in active_events:
print event
matches = all_matches[all_matches["query id"] == event.query_id]
matching_doc_ids = set(matches["document id"].tolist())
print matches[0:10]
if event.query_id.startswith("TS13"):
corpus = cuttsum.corpora.EnglishAndUnknown2013()
elif event.query_id.startswith("TS14"):
corpus = cuttsum.corpora.SerifOnly2014()
else:
raise Exception("Bad query id: {}".format(event.query_id))
from cuttsum.trecdata import SCChunkResource
chunks_res = SCChunkResource()
for hour, path, si in chunks_res.streamitem_iter(event, corpus):
print si.stream_id, hour
if si.stream_id in matching_doc_ids:
print si.stream_id, si.stream_time, hour
for match in matches[matches["document id"] == si.stream_id].iterrows():
print match[["nugget text", "update text"]]
#if si.body.clean_visible is not None:
with t.cbreak():
t.inkey()
def cmd_readstream(args, t, active_events):
import textwrap
from goose import Goose, Configuration
config = Configuration()
config.enable_image_fetching = False
g = Goose(config)
raw_stream = True
for arg in args:
if arg == "articles":
raw_stream = False
for event in active_events:
print event
if event.query_id.startswith("TS13"):
corpus = cuttsum.corpora.EnglishAndUnknown2013()
elif event.query_id.startswith("TS14"):
corpus = cuttsum.corpora.SerifOnly2014()
else:
raise Exception("Bad query id: {}".format(event.query_id))
if raw_stream is True:
from cuttsum.trecdata import SCChunkResource
si_iter = SCChunkResource().streamitem_iter(event, corpus)
else:
from cuttsum.pipeline import ArticlesResource
si_iter = ArticlesResource().streamitem_iter(event, corpus)
for hour, path, si in si_iter:
if si.body.clean_visible is not None:
print si.stream_id
try:
text_height = t.height - 4
#n_chars = t.
article = g.extract(raw_html=si.body.clean_html)
lines = textwrap.wrap(article.cleaned_text)
idx = 0
while 1:
print t.clear
print "hour:", hour
print "title:", article.title
print "article:"
print "\n".join(lines[idx:idx + text_height])
#print article.cleaned_text
with t.cbreak():
char = t.inkey()
if char == "i" and idx > 0:
idx -= 1 #idx - 1 if idx > 0 else 0
elif char == "k" and idx + text_height < len(
lines):
idx += 1
elif char == "l":
break
except Exception, e:
print e
continue
def get_job_units(self, event, corpus, **kwargs):
extractor = kwargs.get("extractor", "gold")
overwrite = kwargs.get("overwrite", False)
data_dir = os.path.join(self.dir_, extractor, event.fs_name())
if not os.path.exists(data_dir):
os.makedirs(data_dir)
chunks_resource = SCChunkResource()
if extractor == "gold":
import cuttsum.judgements
all_matches = cuttsum.judgements.get_matches()
matches = all_matches[all_matches["query id"] == event.query_id]
hours = set([datetime.utcfromtimestamp(int(update_id.split("-")[0])).replace(
minute=0, second=0)
for update_id in matches["update id"].tolist()])
hours = sorted(list(hours))
units = []
for h, hour in enumerate(hours):
output_path = self.get_chunk_path(event, extractor, hour)
if overwrite is True or ouput_path is None or not os.path.exists(output_path):
units.append(h)
return units
elif extractor == "goose":
hours = event.list_event_hours()
units = []
for h, hour in enumerate(hours):
output_path = self.get_chunk_path(event, extractor, hour, corpus)
if overwrite is True or output_path is None or not os.path.exists(output_path):
units.append(h)
return units
else:
raise Exception("extractor: {} not implemented!".format(extractor))
def do_job_unit(self, event, corpus, unit, **kwargs):
extractor = kwargs.get("extractor", "gold")
data_dir = os.path.join(self.dir_, extractor, event.fs_name())
chunks_resource = SCChunkResource()
if not os.path.exists(data_dir):
try:
os.makedirs(data_dir)
except OSError as exc:
if exc.errno == errno.EEXIST and os.path.isdir(data_dir):
pass
if extractor == "gold":
import cuttsum.judgements
all_matches = cuttsum.judgements.get_matches()
matches = all_matches[all_matches["query id"] == event.query_id]
stream_ids = set(
matches["update id"].apply(
lambda x: "-".join(x.split("-")[:-1])).tolist())
hours = set([datetime.utcfromtimestamp(
int(update_id.split("-")[0])).replace(
minute=0, second=0)
for update_id in matches["update id"].tolist()])
hours = sorted(list(hours))
hour = hours[unit]
output_path = self.get_chunk_path(event, extractor, hour, corpus)
gold_si = []
for path in chunks_resource.get_chunks_for_hour(hour, corpus, event):
with sc.Chunk(path=path, mode="rb",
message=corpus.sc_msg()) as chunk:
for si in chunk:
if si.stream_id in stream_ids:
gold_si.append(si)
gold_si.sort(key=lambda x: x.stream_id)
for si in gold_si:
print si.stream_id
if os.path.exists(output_path):
os.remove(path)
with sc.Chunk(path=output_path, mode="wb",
message=corpus.sc_msg()) as chunk:
for si in gold_si:
chunk.add(si)
elif extractor == "goose":
import nltk
from nltk.tokenize import WordPunctTokenizer
sent_tok = nltk.data.load('tokenizers/punkt/english.pickle')
word_tok = WordPunctTokenizer()
from goose import Goose, Configuration
config = Configuration()
config.enable_image_fetching = False
g = Goose(config)
hour = event.list_event_hours()[unit]
output_path_tmp = self.get_chunk_template(event, extractor, hour, corpus)
good_si = []
for path in chunks_resource.get_chunks_for_hour(hour, corpus, event):
try:
with sc.Chunk(path=path, mode="rb",
message=corpus.sc_msg()) as chunk:
for si in chunk:
if si.body.clean_visible is None:
continue
article_text = self._get_goose_text(g, si)
if article_text is None:
continue
if not self._contains_query(event, article_text):
continue
art_pretty = sent_tok.tokenize(article_text)
art_sents = [word_tok.tokenize(sent)
for sent in art_pretty]
df = si2df(si)
I = self._map_goose2streamitem(
art_sents, df["words"].tolist())
if "serif" in si.body.sentences:
si_sentences = si.body.sentences["serif"]
elif "lingpipe" in si.body.sentences:
si_sentences = si.body.sentences["lingpipe"]
else:
raise Exception("Bad sentence annotator.")
ann = sc.Annotator()
ann.annotator_id = "goose"
si.body.sentences["goose"] = [sc.Sentence()
for _ in si_sentences]
for i_goose, i_si in enumerate(I):
#print art_pretty[i_goose]
#print df.loc[i_si, "sent text"]
#print
tokens = [sc.Token(token=token.encode("utf-8"))
for token in art_sents[i_goose]]
si.body.sentences["goose"][i_si].tokens.extend(
tokens)
good_si.append(si)
except TypeError:
continue
#if len(good_si) == 0:
# print "Nothing in hour:", hour
# return
output_path = output_path_tmp.format(len(good_si))
odir = os.path.dirname(output_path)
if not os.path.exists(odir):
os.makedirs(odir)
if os.path.exists(output_path):
os.remove(path)
good_si.sort(key=lambda x: x.stream_id)
for si in good_si:
print si.stream_id
if os.path.exists(output_path):
os.remove(output_path)
print "Writing to", output_path
with sc.Chunk(path=output_path, mode="wb",
message=corpus.sc_msg()) as chunk:
for si in good_si:
chunk.add(si)
else:
raise Exception("extractor: {} not implemented!".format(extractor))
pd.set_option("display.width", 200)
import locale
locale.setlocale(locale.LC_ALL, "en_US.UTF8")
def format_int(x):
return locale.format("%d", x, grouping=True)
def epoch(dt):
return int((dt - datetime(1970, 1, 1)).total_seconds())
chunk_res = SCChunkResource()
articles_res = ArticlesResource()
ded_articles_res = DedupedArticlesResource()
data = []
event2ids = defaultdict(set)
fltr_event2ids = defaultdict(set)
for event in cuttsum.events.get_events():
corpus = cuttsum.corpora.get_raw_corpus(event)
hours = event.list_event_hours()
hour2ded = defaultdict(int)
hour2ded_fltr = defaultdict(int)
ded_df = ded_articles_res.get_stats_df(event, corpus, "goose", 0.8)
pd.set_option('display.width', 200)
import locale
locale.setlocale(locale.LC_ALL, 'en_US.UTF8')
def format_int(x):
return locale.format("%d", x, grouping=True)
def epoch(dt):
return int((dt - datetime(1970, 1, 1)).total_seconds())
chunk_res = SCChunkResource()
articles_res = ArticlesResource()
ded_articles_res = DedupedArticlesResource()
data = []
event2ids = defaultdict(set)
fltr_event2ids = defaultdict(set)
for event in cuttsum.events.get_events():
corpus = cuttsum.corpora.get_raw_corpus(event)
hours = event.list_event_hours()
hour2ded = defaultdict(int)
hour2ded_fltr = defaultdict(int)
ded_df = ded_articles_res.get_stats_df(event, corpus, "goose", .8)
