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
|
require_relative "setup.rb"
class LazarPhyschemDescriptorTest < MiniTest::Test
def test_lazar_pc_descriptors
# check available descriptors
desc = OpenTox::Algorithm::Descriptor.physchem_descriptors.keys
assert_equal 111,desc.size,"wrong num physchem descriptors"
sum = 0
{"Openbabel"=>16,"Cdk"=>50,"Joelib"=>45}.each do |k,v|
assert_equal v,desc.select{|x| x=~/^#{k}\./}.size,"wrong num #{k} descriptors"
sum += v
end
assert_equal 111,sum
# select descriptors for test
desc.keep_if{|x| x=~/^Openbabel\./}
unless defined?($short_tests)
# the actual descriptor calculation is rather fast, computing 3D structures takes time
desc += ["Cdk.XLogP", "Cdk.WienerNumbers", "Joelib.LogP", "Joelib.count.HeteroCycles"]
end
puts "descriptors for modeling: #{desc}"
dataset = OpenTox::Dataset.new
dataset.upload File.join(DATA_DIR,"EPAFHM.medi.csv")
assert_equal dataset.uri.uri?, true
puts dataset.uri
model_uri = OpenTox::Model::Lazar.create :dataset_uri => dataset.uri, :feature_generation_uri => File.join($algorithm[:uri],"descriptor","physchem"), :descriptors => desc
puts model_uri
model = OpenTox::Model::Lazar.new model_uri
assert_equal model_uri.uri?, true
puts model.predicted_variable
compound_uri = "#{$compound[:uri]}/InChI=1S/C13H8Cl2O2/c14-12-5-4-11(7-13(12)15)17-10-3-1-2-9(6-10)8-16/h1-8H"
prediction_uri = model.predict :compound_uri => compound_uri
prediction = OpenTox::Dataset.new prediction_uri
assert_equal prediction.uri.uri?, true
puts prediction.uri
assert prediction.features.collect{|f| f.uri}.include?(model.predicted_variable),"prediction feature #{model.predicted_variable} not included prediction dataset #{prediction.features.collect{|f| f.uri}}"
assert prediction.compounds.collect{|c| c.uri}.include?(compound_uri),"compound #{compound_uri} not included in prediction dataset #{prediction.compounds.collect{|c| c.uri}}"
assert_equal 1,prediction.compound_indices(compound_uri).size,"compound should only be once in the dataset"
predicted_value = prediction.data_entry_value(prediction.compound_indices(compound_uri).first,model.predicted_variable)
puts predicted_value
assert predicted_value > 0.005,"predicted values should be above 0.005, is #{predicted_value}"
assert predicted_value < 0.1,"predicted values should be below 0.1, is #{predicted_value}"
end
end
|
