from org.apache.lucene.util import Version
from org.apache.lucene.analysis.miscellaneous import PerFieldAnalyzerWrapper
from java.util import HashMap
from lxml import etree
from search import Searcher
from index import Indexer, CustomAnalyzer
INDEX_DIR = 'index'
# DATA_DIR = 'data/dblp.xml'
DATA_DIR = 'data/dblp_small.xml'
if __name__ == "__main__":
# user inputs
topN = 10
lucene.initVM()
# index documents
config = {'lowercase': True, 'stemming': True, 'stopwords': True}
title_analyzer = CustomAnalyzer(config)
per_field = HashMap()
per_field.put("title", title_analyzer)
analyzer = PerFieldAnalyzerWrapper(
StandardAnalyzer(Version.LUCENE_CURRENT), per_field)
Indexer(DATA_DIR, INDEX_DIR, context, analyzer)
searcher = Searcher(INDEX_DIR, analyzer)
# # q = raw_input("Query: ")
# # searcher.search(q, N=topN)
searcher.run(topN)
from search import Searcher
from connectionist import Connectionist
from vertex import Vertex
n_vertices = 10 # number of elements/nodes
g = Generator(n_vertices)
searcher = Searcher()
connector = Connectionist()
n = 20 # number of runs
for i in range(n):
g.generate()
belief_network = g.get_belief_network()
neural_network = g.get_neural_network()
coherence, (true, false) = searcher.run(belief_network)
print 'coherence search:', coherence
print 'accepted propositions:', sorted(true, key=lambda v: v.n)
print 'rejected propositions:', sorted(false, key=lambda v: v.n)
print '-----------------------------------------------'
activations, harmony = connector.run(neural_network)
print 'harmony', harmony
true = []
false = []
for i, a in enumerate(activations):
if a == 1:
true.append(Vertex(i))
else:
false.append(Vertex(i))
print 'accepted propositions:', sorted(true, key=lambda v: v.n)
from java.util import HashMap
from search import Searcher
from index import CustomAnalyzer
from utils import check_config
CONFIG_DIR = 'config.json'
INDEX_DIR = 'index'
DATA_DIR = 'data/dblp.xml'
# run search on command line
# see ui_search.py to use the search via web UI
if __name__ == "__main__":
with open(CONFIG_DIR) as f:
config = json.load(f)
config = check_config(config)
lucene.initVM() # start JVM for Lucene
# index documents
# use different analyzer for title field
title_analyzer = CustomAnalyzer(config['titleAnalyzer'])
per_field = HashMap()
per_field.put("title", title_analyzer)
analyzer = PerFieldAnalyzerWrapper(
StandardAnalyzer(Version.LUCENE_CURRENT), per_field)
searcher = Searcher(INDEX_DIR, analyzer)
# q = raw_input("Query: ")
# searcher.search(q, N=config['topN'])
searcher.run(config['topN'])
