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Experiments suite without expsuite.
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1 | +#!/usr/bin/env python | |
2 | +""" | |
3 | + recommender suite - recommender experiments suite | |
4 | +""" | |
5 | +__author__ = "Tassia Camoes Araujo <tassia@gmail.com>" | |
6 | +__copyright__ = "Copyright (C) 2011 Tassia Camoes Araujo" | |
7 | +__license__ = """ | |
8 | + This program is free software: you can redistribute it and/or modify | |
9 | + it under the terms of the GNU General Public License as published by | |
10 | + the Free Software Foundation, either version 3 of the License, or | |
11 | + (at your option) any later version. | |
12 | + | |
13 | + This program is distributed in the hope that it will be useful, | |
14 | + but WITHOUT ANY WARRANTY; without even the implied warranty of | |
15 | + MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the | |
16 | + GNU General Public License for more details. | |
17 | + | |
18 | + You should have received a copy of the GNU General Public License | |
19 | + along with this program. If not, see <http://www.gnu.org/licenses/>. | |
20 | +""" | |
21 | + | |
22 | +import sys | |
23 | +sys.path.insert(0,'../') | |
24 | +from config import Config | |
25 | +from data import PopconXapianIndex, PopconSubmission, AppAptXapianIndex | |
26 | +from recommender import Recommender | |
27 | +from user import LocalSystem, User | |
28 | +from evaluation import * | |
29 | +import logging | |
30 | +import random | |
31 | +import Gnuplot | |
32 | + | |
33 | +def run_iteration(label,cfg,sample_proportion,n): | |
34 | + rec = Recommender(cfg) | |
35 | + repo_size = rec.items_repository.get_doccount() | |
36 | + user = PopconSystem("/root/popularity-contest-tassia") | |
37 | + print "profile",user.pkg_profile | |
38 | + user.maximal_pkg_profile() | |
39 | + sample_size = int(len(user.pkg_profile)*sample_proportion) | |
40 | + for n in range(iteration): | |
41 | + item_score = dict.fromkeys(user.pkg_profile,1) | |
42 | + # Prepare partition | |
43 | + sample = {} | |
44 | + for i in range(sample_size): | |
45 | + key = random.choice(item_score.keys()) | |
46 | + sample[key] = item_score.pop(key) | |
47 | + # Get full recommendation | |
48 | + user = User(item_score) | |
49 | + recommendation = rec.get_recommendation(user,repo_size) | |
50 | + # Write recall log | |
51 | + log_file = "results/strategies/"+label["values"] | |
52 | + output = open(log_file,'w') | |
53 | + output.write("# %s\n" % label["description"]) | |
54 | + output.write("# %s\n" % label["values"]) | |
55 | + notfound = [] | |
56 | + ranks = [] | |
57 | + for pkg in sample.keys(): | |
58 | + if pkg in recommendation.ranking: | |
59 | + ranks.append(recommendation.ranking.index(pkg)) | |
60 | + else: | |
61 | + notfound.append(pkg) | |
62 | + for r in sorted(ranks): | |
63 | + output.write(str(r)+"\n") | |
64 | + if notfound: | |
65 | + output.write("Out of recommendation:\n") | |
66 | + for pkg in notfound: | |
67 | + output.write(pkg+"\n") | |
68 | + output.close() | |
69 | + # Plot metrics summary | |
70 | + accuracy = [] | |
71 | + precision = [] | |
72 | + recall = [] | |
73 | + f1 = [] | |
74 | + g = Gnuplot.Gnuplot() | |
75 | + g('set style data lines') | |
76 | + g.xlabel('Recommendation size') | |
77 | + for size in range(1,len(recommendation.ranking)+1,100): | |
78 | + predicted = RecommendationResult(dict.fromkeys(recommendation.ranking[:size],1)) | |
79 | + real = RecommendationResult(sample) | |
80 | + evaluation = Evaluation(predicted,real,repo_size) | |
81 | + accuracy.append([size,evaluation.run(Accuracy())]) | |
82 | + precision.append([size,evaluation.run(Precision())]) | |
83 | + recall.append([size,evaluation.run(Recall())]) | |
84 | + f1.append([size,evaluation.run(F1())]) | |
85 | + | |
86 | + g.plot(Gnuplot.Data(accuracy,title="Accuracy"), | |
87 | + Gnuplot.Data(precision,title="Precision"), | |
88 | + Gnuplot.Data(recall,title="Recall"), | |
89 | + Gnuplot.Data(f1,title="F1")) | |
90 | + g.hardcopy(log_file+"-plot.ps", enhanced=1, color=1) | |
91 | + | |
92 | + | |
93 | +if __name__ == '__main__': | |
94 | + iteration = 10 | |
95 | + samples_proportion = [0.5, 0.6, 0.7, 0.8, 0.9] | |
96 | + weights = ['bm25', 'trad'] | |
97 | + cb_strategies = ['cb','cbt','cbd'] | |
98 | + #cb_strategies = [] | |
99 | + profile_size = range(10,100,10) | |
100 | + items_repository = ["data/AppAxi","/var/lib/apt-xapian-index/index"] | |
101 | + users_repository = ["data/popcon_index_full","data/popcon_index-50000", | |
102 | + "data/popcon_index_10000","data/popcon_index_1000"] | |
103 | + users_repository = [] | |
104 | + neighbors = range(10,1010,100) | |
105 | + | |
106 | + cfg = Config() | |
107 | + cfg.index_mode = "old" | |
108 | + label = {} | |
109 | + | |
110 | + for w in weights: | |
111 | + cfg.weight = w | |
112 | + for items_repo in items_repository: | |
113 | + cfg.axi = items_repo | |
114 | + if "App" in cfg.axi: | |
115 | + axi_str = "axiapp" | |
116 | + else: | |
117 | + axi_str = "axifull" | |
118 | + for sample_proportion in samples_proportion: | |
119 | + if "content" in sys.argv or len(sys.argv)<2: | |
120 | + for size in profile_size: | |
121 | + cfg.profile_size = size | |
122 | + for strategy in cb_strategies: | |
123 | + cfg.strategy = strategy | |
124 | + for n in range(iteration): | |
125 | + label["description"] = "weight-axi-profile-strategy-sample-n" | |
126 | + label["values"] = ("%s-%s-%d-%s-%.2f-%d" % | |
127 | + (cfg.weight,axi_str,cfg.profile_size, | |
128 | + cfg.strategy,sample_proportion,n)) | |
129 | + run_iteration(label,cfg,sample_proportion,n) | |
130 | + if "colaborative" in sys.argv or len(sys.argv)<2: | |
131 | + cfg.strategy = "col" | |
132 | + for users_repo in users_repository: | |
133 | + cfg.popcon_index = users_repo | |
134 | + for k in neighbors: | |
135 | + cfg.k_neighbors = k | |
136 | + for n in range(iteration): | |
137 | + k_str = "k"+str(cfg.k_neighbors) | |
138 | + if "full" in cfg.popcon_index: | |
139 | + popcon_str = "popfull" | |
140 | + if "50000" in cfg.popcon_index: | |
141 | + popcon_str = "pop50000" | |
142 | + if "10000" in cfg.popcon_index: | |
143 | + popcon_str = "pop10000" | |
144 | + if "1000" in cfg.popcon_index: | |
145 | + popcon_str = "pop1000" | |
146 | + label["description"] = "weight-axi-popcon-profile-strategy-k-sample-n" | |
147 | + label["values"] = ("%s-%s-%s-%d-%s-%s-%.2f-%d" % | |
148 | + (cfg.weight,axi_str,popcon_str,cfg.profile_size, | |
149 | + cfg.strategy,k_str,sample_proportion,n)) | |
150 | + run_iteration(label,cfg,sample_proportion,n) | ... | ... |