From 7ff0e703482f99e1ac40faf464377c5c33585bd1 Mon Sep 17 00:00:00 2001
From: Victor Zimmermann <zimmermann@cl.uni-heidelberg.de>
Date: Wed, 7 Mar 2018 14:34:03 +0100
Subject: [PATCH] Replace try-except blocks with if statements
---
code/absinth_nx.py | 32 +++++++++++++++++++-------------
1 file changed, 19 insertions(+), 13 deletions(-)
diff --git a/code/absinth_nx.py b/code/absinth_nx.py
index 14726b1..ce072f4 100644
--- a/code/absinth_nx.py
+++ b/code/absinth_nx.py
@@ -5,11 +5,12 @@ import spacy # for nlp
import networkx as nx # for visualisation
import matplotlib.pyplot as plt # for visualisation
from copy import deepcopy
+from nltk.corpus import stopwords
import numpy as np # for calculations
nlp = spacy.load('en') # standard english nlp
-def frequencies(corpus_path, target, stop_words=['utc', 'new', 'other'], allowed_tags=['NN','NNS','JJ','JJS','JJR','NNP'], min_context_size = 4, max_nodes=100000, max_edges=10000000):
+def frequencies(corpus_path, target, stop_words=[], allowed_tags=['NN','NNS','JJ','JJS','JJR','NNP','VBZ','VBG'], min_context_size = 4, max_nodes=100000, max_edges=10000000):
node_freq = dict()
edge_freq = dict()
@@ -111,7 +112,7 @@ def build_graph(node_freq, edge_freq, min_node_freq=10, min_edge_freq=5, max_wei
return G
-def root_hubs(graph, edge_freq, min_neighbors=4, theshold=0.8):
+def root_hubs(graph, edge_freq, min_neighbors=5, theshold=0.8):
G = deepcopy(graph)
V = sorted(G.nodes, key=lambda key: G.degree[key], reverse=True) # -1 to sort descending (...3 -> 2 -> 1...)
@@ -178,16 +179,19 @@ def disambiguate(mst, hubs, contexts):
for h in H:
- try:
+ if nx.has_path(T,v,h):
+
path = nx.shortest_path(T,v,h,'weight')
total_weight = 0
for i in range(1, len(path)):
+
total_weight += T[path[i-1]][path[i]]['weight']
scores.append(1/(1+total_weight))
- except:
+ else:
+
scores.append(0)
T.nodes[v]['s'] = np.array([s if s == max(scores) else 0 for s in scores])
@@ -199,14 +203,12 @@ def disambiguate(mst, hubs, contexts):
idx = contexts.index(c) + 1
- try:
- if max(vector) == 0:
- pass
- else:
- cluster = np.argmax(vector)
- result.append((cluster, idx))
- except:
+ if len(vector) == 0: #if no senses are found -> all in one
result.append((0, idx))
+ elif max(vector) == 0: #if no sense matches -> singletons
+ pass
+ else:
+ result.append((np.argmax(vector), idx))
return result
@@ -224,6 +226,8 @@ if __name__ == '__main__':
corpus_path = '/proj/absinth/wikipedia.txt.dump.20140615-en.SZTAKI/'
results_path = '/home/students/zimmermann/Courses/ws17/fsem/absinth/results/'
+ stop = set(stopwords.words('english') + ['utc', 'new', 'other'])
+
results = dict()
with open(data_path+'results.txt', 'r') as results_file:
@@ -260,14 +264,16 @@ if __name__ == '__main__':
f.write('subTopicID\tresultID\n')
print('[A] Counting Tokens...')
- node_freq, edge_freq = frequencies(corpus_path, target)
+ node_freq, edge_freq = frequencies(corpus_path, target, stop)
print('\n[A] Building Graph.\n')
G = build_graph(node_freq, edge_freq)
print('[A] Collecting Root Hubs...')
H = root_hubs(G, edge_freq)
- print('Root Hubs:', H, '\n')
+ for h in H:
+ mfn = sorted(G.adj[h], key=lambda key: edge_freq[h,key] if h < key else edge_freq[key, h], reverse=True)[:6]
+ print('{}: {}\n'.format(h, mfn))
print('[A] Building Minimum Spanning Tree.\n')
T = components(G, H, target)
--
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