def main():
args = docopt(__doc__)
c = get_config()
session = open_db()
zodb_root = open_zodb(read_only=True)
ids = session.query(Speech.id).all()
all_words = set()
for (id,) in progress.bar(ids, label="Progress: ", every=100):
all_words = all_words.union(zodb_root.features['words'][id].keys())
print "Word set size: ", len(all_words)
#print "Subtracting stopwords..."
#nltk.download('stopwords')
#langs = ['english', 'spanish']
#all_stopwords = reduce(lambda x, y: x | y, [set(nltk.corpus.stopwords.words(lng)) for lng in langs])
#all_stopwords = set(map(unidecode, all_stopwords))
#all_words = all_words - all_stopwords
#print "Resulting word set size: ", len(all_words)
print "Saving..."
zodb_root = open_zodb()
zodb_root.all_words = all_words
transaction.commit()
print "Done"
def main():
args = docopt(__doc__)
feature_name = args['<feature_name>']
assert feature_name == 'words'
assert args['<experimentset_name>'] in EXPERIMENT_SETS, '<experimentset_name> must be one of %s' % str(EXPERIMENT_SETS.keys())
c = get_config()
experiment_set = EXPERIMENT_SETS[args['<experimentset_name>']](feature_name=feature_name)
print "Computing foreground group sums using %d cores..." % c.num_cores
pool = Pool(c.num_cores, init_worker)
fg_groups = experiment_set.list_foreground_groups()
cache = {}
try:
for group_name, sum_vector in progress.bar(pool.imap_unordered(ComputeForegroundGroupSumCallable(experiment_set), fg_groups), label="Progress ", expected_size=len(fg_groups)):
cache[group_name] = sum_vector
except KeyboardInterrupt:
print "Terminating pool.."
pool.terminate()
pool.join()
print "Computing background sums..."
bg_groups = experiment_set.list_background_groups()
for g in bg_groups:
sum_vector = experiment_set.compute_background_group_sum(g, cache)
cache[g] = sum_vector
print "Saving sums to ZODB..."
zodb_root = open_zodb(read_only=False)
if getattr(zodb_root, 'group_sums', None) is None:
zodb_root.group_sums = BTrees.OOBTree.OOBTree()
transaction.commit()
if feature_name not in zodb_root.group_sums:
zodb_root.group_sums[feature_name] = BTrees.OOBTree.OOBTree()
transaction.commit()
for k, v in cache.iteritems():
zodb_root.group_sums[feature_name][k] = v
transaction.commit()
print "Creating output db tables..."
create_db(c.resultsdb_url)
session_out = open_db(c.resultsdb_url)
print "Computing overrepresentation using %d cores..." % c.num_cores
exps = experiment_set.list_experiments()
cls = experiment_set.result_table_class()
try:
for fg, bg, results in progress.bar(pool.imap_unordered(ComputeOverrepresentedWordsCallable(experiment_set), exps), label="Progress ", expected_size=len(exps)):
for w, odds, pval in results:
c = cls(foreground_group_name=fg, background_group_name=bg, word=w, odds=odds, pval=pval)
session_out.add(c)
except KeyboardInterrupt:
print "Terminating pool.."
pool.terminate()
pool.join()
print "Committing..."
session_out.commit()
print "Done"
def compute_foreground_group_sum(self, group_name):
session = open_db(self.config.db_url)
zodb = open_zodb(self.config, read_only=True)
result = Counter()
wordset = zodb.all_words
for (id,) in session.query(Speech.id).filter(Speech.speaker_uri == group_name):
v = zodb.features[self.feature_name][id]
for w in v:
if w in wordset:
result[w] += v[w]
return result
def compute_foreground_group_sum(self, group_name):
session = open_db(self.config.db_url)
zodb = open_zodb(self.config, read_only=True)
result = Counter()
wordset = zodb.all_words
y, m = map(int, group_name.split('-'))
dmin = datetime.date(y,m,1)
dmax = dmin + relativedelta(months=1)
for (id,) in session.query(Speech.id).filter(Speech.date >= dmin).filter(Speech.date < dmax):
v = zodb.features[self.feature_name][id]
for w in v:
if w in wordset:
result[w] += v[w]
return result
def extract_features(self, foreground_group_name, background_group_name):
"""Extract overrepresented words for a given foreground/background group. Runs on worker nodes.
Uses zodb.group_sums[self.feature_name] data precomputed in previous steps."""
z = open_zodb(self.config, read_only=True)
fg_counts = z.group_sums[self.feature_name][foreground_group_name]
bg_counts = z.group_sums[self.feature_name][background_group_name]
total_fg_count = sum(fg_counts.values())
total_bg_count = sum(bg_counts.values())
result = []
cutoff = 0.01/max(1, len(fg_counts))
for w in fg_counts:
contingency = [[fg_counts[w], bg_counts[w] - fg_counts[w]],
[total_fg_count - fg_counts[w], total_bg_count - total_fg_count - bg_counts[w] + fg_counts[w]]]
odds, pval = fisher_exact(contingency, alternative='greater')
if pval < cutoff:
result.append((w, odds, pval))
return result
def main():
args = docopt(__doc__)
extractor_name = args['<feature_name>']
extractor = getattr(talkofactawords.extract, extractor_name, None)
if extractor is None:
print "Unknown extractor name"
sys.exit(1)
c = get_config()
s = open_db()
print "Preparing ZODB"
zodb_root = open_zodb(read_only=False)
if getattr(zodb_root, 'features', None) is None:
zodb_root.features = BTrees.OOBTree.OOBTree()
transaction.commit()
if extractor_name not in zodb_root.features:
zodb_root.features[extractor_name] = BTrees.OOBTree.OOBTree()
transaction.commit()
runner = TaskRunner(extractor)
print "Querying database..."
speeches = s.query(Speech).all()
total_speeches = len(speeches)
print "Computing using %d cores..." % c.num_cores
pool = Pool(c.num_cores, init_worker)
try:
for i, (id, result) in enumerate(progress.bar(pool.imap_unordered(runner, speeches), label='Progress ', expected_size=total_speeches, every=100), 1):
zodb_root.features[extractor_name][id] = result
if i % 1000 == 0:
transaction.commit()
transaction.commit()
except KeyboardInterrupt:
print "Terminating pool.."
pool.terminate()
pool.join()
print "Done"
