def encode_test():
graph = wordnet_graph()
language = singleresolution(100000)
node = ('levy', 'v')
codes = encode(graph, node, language)
print 'encoded results'
print_nodes(graph, codes)
'''
language is a list of words (or wordnet nodes).
wordnet nodes consists of word, (word, pos), and synsets.
'''
from math import *
from graphparse import wordnet_graph
from util import *
g = wordnet_graph()
def multiresolution(n_layer = 10, dim = 1000, factor = 1.6):
word_size = int(ceil(dim * pow(factor, n_layer-1)))
assert(word_size <= g.number_of_nodes())
top_nodes = top_k(word_size, g)
# Each dimension consists of a set of words contained in a certain
# bandwidth. We call those sets 'languages'.
langs = []
for i in range(n_layer):
start = int(floor(dim * pow(factor, i-1))) if i > 0 else 0
end = int(floor(dim * pow(factor, i)))
langs.append(top_nodes[start:end])
return langs
