1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
|
require_relative "setup.rb"
class ExperimentTest < MiniTest::Test
def test_regression_experiment
datasets = [
"EPAFHM.medi.csv",
#"EPAFHM.csv",
#"FDA_v3b_Maximum_Recommended_Daily_Dose_mmol.csv",
"LOAEL_mmol_corrected_smiles.csv"
]
experiment = Experiment.create(
:name => "Default regression for datasets #{datasets}.",
:dataset_ids => datasets.collect{|d| Dataset.from_csv_file(File.join(DATA_DIR, d)).id},
:model_settings => [
{
:algorithm => "OpenTox::Model::LazarRegression",
}
]
)
#experiment.run
puts experiment.report.to_yaml
assert_equal datasets.size, experiment.results.size
experiment.results.each do |dataset_id, result|
assert_equal 1, result.size
result.each do |r|
assert_kind_of BSON::ObjectId, r[:model_id]
assert_kind_of BSON::ObjectId, r[:repeated_crossvalidation_id]
end
end
end
def test_classification_experiment
datasets = [ "hamster_carcinogenicity.csv" ]
experiment = Experiment.create(
:name => "Fminer vs fingerprint classification for datasets #{datasets}.",
:dataset_ids => datasets.collect{|d| Dataset.from_csv_file(File.join(DATA_DIR, d)).id},
:model_settings => [
{
:algorithm => "OpenTox::Model::LazarClassification",
},{
:algorithm => "OpenTox::Model::LazarClassification",
:neighbor_algorithm_parameter => {:min_sim => 0.3}
},
#{
#:algorithm => "OpenTox::Model::LazarFminerClassification",
#}
]
)
#experiment.run
=begin
experiment = Experiment.find "55f944a22b72ed7de2000000"
=end
puts experiment.report.to_yaml
experiment.results.each do |dataset_id, result|
assert_equal 2, result.size
result.each do |r|
assert_kind_of BSON::ObjectId, r[:model_id]
assert_kind_of BSON::ObjectId, r[:repeated_crossvalidation_id]
end
end
end
def test_regression_fingerprints
=begin
datasets = [
"EPAFHM.medi.csv",
#"LOAEL_mmol_corrected_smiles.csv"
]
min_sims = [0.3,0.7]
#min_sims = [0.7]
#types = ["FP2","FP3","FP4","MACCS","mpd"]
types = ["mpd","FP3"]
experiment = Experiment.create(
:name => "Fingerprint regression with different types for datasets #{datasets}.",
:dataset_ids => datasets.collect{|d| Dataset.from_csv_file(File.join(DATA_DIR, d)).id},
)
types.each do |type|
min_sims.each do |min_sim|
experiment.model_settings << {
:model_algorithm => "OpenTox::Model::LazarRegression",
:prediction_algorithm => "OpenTox::Algorithm::Regression.weighted_average",
:neighbor_algorithm => "fingerprint_neighbors",
:neighbor_algorithm_parameters => {
:type => type,
:min_sim => min_sim,
}
}
end
end
experiment.run
=end
#=begin
experiment = Experiment.find '56029cb92b72ed673d000000'
#=end
p experiment.id
experiment.results.each do |dataset,result|
result.each do |r|
params = Model::Lazar.find(r["model_id"])[:neighbor_algorithm_parameters]
RepeatedCrossValidation.find(r["repeated_crossvalidation_id"]).crossvalidations.each do |cv|
cv.validation_ids.each do |vid|
model_params = Model::Lazar.find(Validation.find(vid).model_id)[:neighbor_algorithm_parameters]
assert_equal params[:type], model_params[:type]
assert_equal params[:min_sim], model_params[:min_sim]
refute_equal params[:training_dataset_id], model_params[:training_dataset_id]
end
end
end
end
puts experiment.report.to_yaml
p experiment.summary
end
def test_mpd_fingerprints
=begin
datasets = [
"EPAFHM.medi.csv",
]
types = ["FP2","mpd"]
experiment = Experiment.create(
:name => "FP2 vs mpd fingerprint regression for datasets #{datasets}.",
:dataset_ids => datasets.collect{|d| Dataset.from_csv_file(File.join(DATA_DIR, d)).id},
)
types.each do |type|
experiment.model_settings << {
:algorithm => "OpenTox::Model::LazarRegression",
:neighbor_algorithm => "fingerprint_neighbors",
:neighbor_algorithm_parameter => {
:type => type,
:min_sim => 0.7,
}
}
end
experiment.run
p experiment.id
=end
experiment = Experiment.find '55ffd0c02b72ed123c000000'
p experiment
puts experiment.report.to_yaml
end
end
|
