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
143
144
145
146
147
148
149
150
151
152
153
|
require 'rubygems'
require 'opentox-ruby'
require 'test/unit'
require "./validate-owl.rb"
class Float
def round_to(x)
(self * 10**x).round.to_f / 10**x
end
end
class LazarTest < Test::Unit::TestCase
def setup
@predictions = []
@models = []
end
def teardown
@predictions.each {|p| p.delete(@@subjectid)}
@models.each {|m| m.delete(@@subjectid)}
end
=begin
=end
def test_create_regression_model
model_uri = OpenTox::Algorithm::Lazar.new.run({:dataset_uri => @@regression_training_dataset.uri, :subjectid => @@subjectid}).to_s
puts model_uri
validate_owl model_uri,@@subjectid
lazar = OpenTox::Model::Lazar.find model_uri, @@subjectid
@models << lazar
assert_equal 185, lazar.features.size
compound = OpenTox::Compound.from_smiles("c1ccccc1NN")
prediction_uri = lazar.run(:compound_uri => compound.uri, :subjectid => @@subjectid).to_s
prediction = OpenTox::LazarPrediction.find(prediction_uri, @@subjectid)
@predictions << prediction
assert_equal prediction.value(compound).round_to(3),0.2849.round_to(3)
assert_equal prediction.confidence(compound).round_to(3), 0.3223.round_to(3)
#assert_equal prediction.value(compound).round_to(4), 0.2847.round_to(4)
#assert_equal prediction.confidence(compound).round_to(4), 0.3223.round_to(4)
assert_equal prediction.neighbors(compound).size, 73
end
def test_classification_model
# create model
model_uri = OpenTox::Algorithm::Lazar.new.run({:dataset_uri => @@classification_training_dataset.uri, :subjectid => @@subjectid}).to_s
validate_owl model_uri,@@subjectid
lazar = OpenTox::Model::Lazar.find model_uri, @@subjectid
@models << lazar
assert_equal lazar.features.size, 52
# single prediction
compound = OpenTox::Compound.from_smiles("c1ccccc1NN")
prediction_uri = lazar.run(:compound_uri => compound.uri, :subjectid => @@subjectid)
prediction = OpenTox::LazarPrediction.find(prediction_uri, @@subjectid)
@predictions << prediction
#puts prediction_uri
assert_equal prediction.value(compound), false
assert_equal prediction.confidence(compound).round_to(4), 0.3067.round_to(4)
assert_equal prediction.neighbors(compound).size, 14
# dataset activity
compound = OpenTox::Compound.from_smiles("CNN")
prediction_uri = lazar.run(:compound_uri => compound.uri, :subjectid => @@subjectid)
prediction = OpenTox::LazarPrediction.find prediction_uri, @@subjectid
@predictions << prediction
assert !prediction.measured_activities(compound).empty?
assert_equal prediction.measured_activities(compound).first, true
assert prediction.value(compound).nil?
# dataset prediction
test_dataset = OpenTox::Dataset.create_from_csv_file("data/multicolumn.csv", @@subjectid)
prediction = OpenTox::LazarPrediction.find lazar.run(:dataset_uri => test_dataset.uri, :subjectid => @@subjectid), @@subjectid
@predictions << prediction
assert_equal prediction.compounds.size, 4
compound = OpenTox::Compound.from_smiles "CC(=Nc1ccc2c(c1)Cc1ccccc21)O"
assert_equal prediction.value(compound), nil
assert_equal prediction.measured_activities(compound).first, true
end
def test_classification_svm_model
# create model
model_uri = OpenTox::Algorithm::Lazar.new.run({:dataset_uri => @@classification_training_dataset.uri, :subjectid => @@subjectid, :prediction_algorithm => "local_svm_classification"}).to_s
lazar = OpenTox::Model::Lazar.find model_uri, @@subjectid
@models << lazar
assert_equal lazar.features.size, 52
# single prediction
compound = OpenTox::Compound.from_smiles("c1ccccc1NN")
prediction_uri = lazar.run(:compound_uri => compound.uri, :subjectid => @@subjectid)
prediction = OpenTox::LazarPrediction.find(prediction_uri, @@subjectid)
@predictions << prediction
assert_equal prediction.value(compound), false
assert_equal prediction.confidence(compound).round_to(4), 0.4131.round_to(4)
assert_equal prediction.neighbors(compound).size, 14
# dataset prediction
test_dataset = OpenTox::Dataset.create_from_csv_file("data/multicolumn.csv", @@subjectid)
prediction = OpenTox::LazarPrediction.find lazar.run(:dataset_uri => test_dataset.uri, :subjectid => @@subjectid), @@subjectid
@predictions << prediction
assert_equal prediction.compounds.size, 4
compound = OpenTox::Compound.from_smiles "CC(=Nc1ccc2c(c1)Cc1ccccc21)O"
assert_equal prediction.value(compound), nil
assert_equal prediction.measured_activities(compound).first, true
end
=begin
def test_ambit_classification_model
# create model
dataset_uri = "http://apps.ideaconsult.net:8080/ambit2/dataset/9"
feature_uri ="http://apps.ideaconsult.net:8080/ambit2/feature/21573"
#model_uri = OpenTox::Algorithm::Lazar.new.run({:dataset_uri => dataset_uri, :prediction_feature => feature_uri}).to_s
#lazar = OpenTox::Model::Lazar.find model_uri
model_uri = OpenTox::Algorithm::Lazar.new.run({:dataset_uri => dataset_uri, :prediction_feature => feature_uri, :subjectid => @@subjectid}).to_s
validate_owl model_uri,@@subjectid
lazar = OpenTox::Model::Lazar.find model_uri, @@subjectid
assert_equal lazar.features.size, 6609
#puts "Model: #{lazar.uri}"
#puts lazar.features.size
# single prediction
compound = OpenTox::Compound.from_smiles("c1ccccc1NN")
#prediction_uri = lazar.run(:compound_uri => compound.uri)
#prediction = OpenTox::LazarPrediction.find(prediction_uri)
prediction_uri = lazar.run(:compound_uri => compound.uri, :subjectid => @@subjectid)
prediction = OpenTox::LazarPrediction.find(prediction_uri, @@subjectid)
#puts "Prediction: #{prediction.uri}"
#puts prediction.value(compound)
assert_equal prediction.value(compound), true
#puts @prediction.confidence(compound).round_to(4)
#assert_equal @prediction.confidence(compound).round_to(4), 0.3005.round_to(4)
#assert_equal @prediction.neighbors(compound).size, 15
#@prediction.delete(@@subjectid)
# dataset activity
#compound = OpenTox::Compound.from_smiles("CNN")
#prediction_uri = @lazar.run(:compound_uri => compound.uri, :subjectid => @@subjectid)
#@prediction = OpenTox::LazarPrediction.find prediction_uri, @@subjectid
#assert !@prediction.measured_activities(compound).empty?
#assert_equal @prediction.measured_activities(compound).first, true
#assert @prediction.value(compound).nil?
#@prediction.delete(@@subjectid)
# dataset prediction
#@lazar.delete(@@subjectid)
end
=end
end
|
