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Commit c20a2199d79b5108f5aab76e981c9ba87c940f01

Authored by Tássia Camões Araújo
1 parent 100c5082
Exists in master and in 1 other branch add_vagrant

Fixed bug with sample randomless.

Showing 1 changed file with 10 additions and 12 deletions   Show diff stats
src/experiments/runner.py
  Diff comments   View file @c20a219
... ... @@ -74,12 +74,13 @@ class ContentBasedSuite(expsuite.PyExperimentSuite):
74 74  
75 75 def iterate(self, params, rep, n):
76 76 if params['name'].startswith("content"):
77   - # Get full recommendation
78 77 item_score = dict.fromkeys(self.user.pkg_profile,1)
  78 + # Prepare partition
79 79 sample = {}
80 80 for i in range(self.sample_size):
81   - item, score = item_score.popitem()
82   - sample[item] = score
  81 + key = random.choice(item_score.keys())
  82 + sample[key] = item_score.pop(key)
  83 + # Get full recommendation
83 84 user = User(item_score)
84 85 recommendation = self.rec.get_recommendation(user,self.repo_size)
85 86 # Write recall log
... ... @@ -106,13 +107,13 @@ class ContentBasedSuite(expsuite.PyExperimentSuite):
106 107 output.write(pkg+"\n")
107 108 output.close()
108 109 # Plot metrics summary
109   - g = Gnuplot.Gnuplot()
110   - g('set style data lines')
111   - g.xlabel('Recommendation size')
112 110 accuracy = []
113 111 precision = []
114 112 recall = []
115 113 f1 = []
  114 + g = Gnuplot.Gnuplot()
  115 + g('set style data lines')
  116 + g.xlabel('Recommendation size')
116 117 for size in range(1,len(recommendation.ranking)+1,100):
117 118 predicted = RecommendationResult(dict.fromkeys(recommendation.ranking[:size],1))
118 119 real = RecommendationResult(sample)
... ... @@ -121,17 +122,14 @@ class ContentBasedSuite(expsuite.PyExperimentSuite):
121 122 precision.append([size,evaluation.run(Precision())])
122 123 recall.append([size,evaluation.run(Recall())])
123 124 f1.append([size,evaluation.run(F1())])
124   - #print "accuracy", len(accuracy)
125   - #print "precision", len(precision)
126   - #print "recall", len(recall)
127   - #print "f1", len(f1)
128 125 g.plot(Gnuplot.Data(accuracy,title="Accuracy"),
129 126 Gnuplot.Data(precision,title="Precision"),
130 127 Gnuplot.Data(recall,title="Recall"),
131 128 Gnuplot.Data(f1,title="F1"))
132 129 g.hardcopy(recall_file+"-plot.ps", enhanced=1, color=1)
133   - result = {}
134   - result = {'weight': params['weight'],
  130 + # Iteration log
  131 + result = {'iteration': n,
  132 + 'weight': params['weight'],
135 133 'strategy': params['strategy'],
136 134 'accuracy': accuracy[20],
137 135 'precision': precision[20],
... ...