summaryrefslogtreecommitdiff
path: root/test/dataset.rb
blob: 055a029912bc2f3677599639f40b0ce3291fa209 (plain)
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
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
require_relative "setup.rb"

class DatasetTest < MiniTest::Test

  # basics

  def test_create_empty
    d = Dataset.new
    assert_equal Dataset, d.class
    refute_nil d.id
    assert_kind_of BSON::ObjectId, d.id
  end

  def test_all
    d1 = Dataset.new 
    d1.save
    datasets = Dataset.all 
    assert datasets.first.is_a?(Dataset), "#{datasets.first} is not a Dataset."
    d1.delete
  end

  # real datasets

  def test_upload_hamster
    d = Dataset.from_csv_file "#{DATA_DIR}/hamster_carcinogenicity.csv"
    assert_equal Dataset, d.class
    assert_equal 1, d.features.size
    assert_equal 85, d.compounds.size
    csv = CSV.read("#{DATA_DIR}/hamster_carcinogenicity.csv")
    csv.shift
    csv.each do |row|
      c = Compound.from_smiles row.shift
      assert_equal row, d.values(c,d.features.first)
    end
    d.delete 
  end

  def test_upload_kazius
    f = File.join DATA_DIR, "kazius.csv"
    d = OpenTox::Dataset.from_csv_file f 
    csv = CSV.read f
    assert_equal csv.size-1, d.compounds.size
    assert_equal csv.first.size-1, d.features.size
    assert_empty d.warnings
    #  493 COC1=C(C=C(C(=C1)Cl)OC)Cl,1
    c = d.compounds[491]
    assert_equal c.smiles, "COc1cc(Cl)c(cc1Cl)OC"
    assert_equal ["1"], d.values(c,d.features.first)
    d.delete
  end

  def test_upload_multicell
    duplicates = [
      "InChI=1S/C6HCl5O/c7-1-2(8)4(10)6(12)5(11)3(1)9/h12H",
      "InChI=1S/C12H8Cl6O/c13-8-9(14)11(16)5-3-1-2(6-7(3)19-6)4(5)10(8,15)12(11,17)18/h2-7H,1H2",
      "InChI=1S/C2HCl3/c3-1-2(4)5/h1H",
      "InChI=1S/C4H5Cl/c1-3-4(2)5/h3H,1-2H2",
      "InChI=1S/C4H7Cl/c1-4(2)3-5/h1,3H2,2H3",
      "InChI=1S/C8H14O4/c1-5-4-8(11-6(2)9)12-7(3)10-5/h5,7-8H,4H2,1-3H3",
      "InChI=1S/C19H30O5/c1-3-5-7-20-8-9-21-10-11-22-14-17-13-19-18(23-15-24-19)12-16(17)6-4-2/h12-13H,3-11,14-15H2,1-2H3",
    ].collect{|inchi| Compound.from_inchi(inchi).smiles}
    errors = ['O=P(H)(OC)OC', 'C=CCNN.HCl' ]
    f = File.join DATA_DIR, "multi_cell_call.csv"
    d = OpenTox::Dataset.from_csv_file f 
    csv = CSV.read f
    assert_equal true, d.features.first.nominal?
    assert_equal 1056, d.compounds.size
    assert_equal csv.first.size-1, d.features.size
    errors.each do |smi|
      refute_empty d.warnings.grep %r{#{Regexp.escape(smi)}}
    end
    duplicates.each do |smi|
      refute_empty d.warnings.grep %r{#{Regexp.escape(smi)}}
    end
    d.delete
  end

  def test_upload_isscan
    f = File.join DATA_DIR, "ISSCAN-multi.csv"
    d = OpenTox::Dataset.from_csv_file f 
    csv = CSV.read f
    assert_equal csv.size-1, d.compounds.size
    assert_equal csv.first.size-1, d.features.size
    d.delete
  end

  def test_upload_epafhm
    f = File.join DATA_DIR, "EPAFHM_log10.csv"
    d = OpenTox::Dataset.from_csv_file f
    assert_equal Dataset, d.class
    csv = CSV.read f
    assert_equal csv.size-1, d.compounds.size
    assert_equal csv.first.size-1, d.features.size
    assert_match "EPAFHM_log10.csv",  d.source
    assert_equal "EPAFHM_log10",  d.name
    feature = d.features.first
    assert_kind_of NumericFeature, feature
    assert_equal -Math.log10(0.0113), d.values(d.compounds.first,feature).first
    assert_equal -Math.log10(0.00323), d.values(d.compounds[4],feature).first
    d2 = Dataset.find d.id
    assert_equal -Math.log10(0.0113), d2.values(d2.compounds[0],feature).first
    assert_equal -Math.log10(0.00323), d2.values(d2.compounds[4],feature).first
    d.delete
  end

  # batch predictions

  def test_create_without_features_smiles_and_inchi
    ["smiles", "inchi"].each do |type|
      d = Dataset.from_csv_file File.join(DATA_DIR,"batch_prediction_#{type}_small.csv"), true
      assert_equal Dataset, d.class
      refute_nil d.id
      dataset = Dataset.find d.id
      assert_equal 3, d.compounds.size
      d.delete
    end
  end

  # dataset operations

  def test_folds
    dataset = Dataset.from_csv_file File.join(DATA_DIR,"loael.csv")
    dataset.folds(10).each do |fold|
      fold.each do |d|
        assert_operator d.compounds.size, :>=, d.compounds.uniq.size
      end
      assert_operator fold[0].compounds.size, :>=, fold[1].compounds.size
      assert_equal dataset.substances.size, fold.first.substances.size + fold.last.substances.size
      assert_empty (fold.first.substances & fold.last.substances)
    end
  end

  # serialisation

  def test_to_csv
    d = Dataset.from_csv_file "#{DATA_DIR}/multicolumn.csv"
    refute_nil d.warnings
    assert d.warnings.grep(/Duplicate compound/)  
    assert d.warnings.grep(/3, 5/)  
    assert_equal 6, d.features.size
    assert_equal 5, d.compounds.uniq.size
    assert_equal 5, d.compounds.collect{|c| c.inchi}.uniq.size
    csv = CSV.parse(d.to_csv)
    original_csv = CSV.read("#{DATA_DIR}/multicolumn.csv")
    csv.shift
    original_csv.shift
    original = {}
    original_csv.each do |row|
      c = Compound.from_smiles row.shift.strip
      original[c.inchi] = row.collect{|v| v.strip}
    end
    serialized = {}
    csv.each do |row|
      c = Compound.from_smiles row.shift
      serialized[c.inchi] = row
    end
    #puts serialized.to_yaml
    original.each do |inchi,row|
      row.each_with_index do |v,i|
        if v.numeric?
          assert_equal v.to_f, serialized[inchi][i].to_f
        else
          assert_equal v.to_s, serialized[inchi][i].to_s
        end
      end

    end
    d.delete 
  end

  # special cases/details

  def test_dataset_accessors
    d = Dataset.from_csv_file "#{DATA_DIR}/multicolumn.csv"
    # create empty dataset
    new_dataset = Dataset.find d.id
    # get metadata
    assert_match "multicolumn.csv",  new_dataset.source
    assert_equal "multicolumn",  new_dataset.name
    # get features
    assert_equal 6, new_dataset.features.size
    assert_equal 5, new_dataset.compounds.uniq.size
    c = new_dataset.compounds.last
    f = new_dataset.features.first
    assert_equal ["1"], new_dataset.values(c,f)
    f = new_dataset.features.last.id.to_s
    assert_equal [1.0], new_dataset.values(c,f)
    f = new_dataset.features[2]
    assert_equal ["false"], new_dataset.values(c,f)
    d.delete
  end

  def test_create_from_file_with_wrong_smiles_compound_entries
    d = Dataset.from_csv_file File.join(DATA_DIR,"wrong_dataset.csv")
    refute_nil d.warnings
    assert_match /2|3|4|5|6|7|8/, d.warnings.join
    d.delete
  end

  def test_from_csv_classification
    ["int", "float", "string"].each do |mode|
      d = Dataset.from_csv_file "#{DATA_DIR}/hamster_carcinogenicity.mini.bool_#{mode}.csv"
      csv = CSV.read("#{DATA_DIR}/hamster_carcinogenicity.mini.bool_#{mode}.csv")
      csv.shift
      csv.each do |row|
        c = Compound.from_smiles row.shift
        assert_equal row, d.values(c,d.features.first)
      end
      d.delete 
    end
  end

  def test_from_csv2
    File.open("#{DATA_DIR}/temp_test.csv", "w+") { |file| file.write("SMILES,Hamster\nCC=O,true\n ,true\nO=C(N),true") }
    dataset = Dataset.from_csv_file "#{DATA_DIR}/temp_test.csv"
    assert_equal "Cannot parse SMILES compound '' at line 3 of /home/ist/lazar/test/data/temp_test.csv, all entries are ignored.",  dataset.warnings.join
    File.delete "#{DATA_DIR}/temp_test.csv"
    dataset.features.each{|f| feature = Feature.find f.id; feature.delete}
    dataset.delete
  end

  def test_same_feature
    datasets = []
    features = []
    2.times do |i|
      d = Dataset.from_csv_file "#{DATA_DIR}/hamster_carcinogenicity.mini.csv"
      features << d.features.first
      assert features[0].id==features[-1].id,"re-upload should find old feature, but created new one"
      datasets << d
    end
    datasets.each{|d| d.delete}
  end

  def test_simultanous_upload
    threads = []
    3.times do |t|
      threads << Thread.new(t) do |up|
        d = OpenTox::Dataset.from_csv_file "#{DATA_DIR}/hamster_carcinogenicity.csv"
        assert_equal OpenTox::Dataset, d.class
        assert_equal 1, d.features.size
        assert_equal 85, d.compounds.size
        csv = CSV.read("#{DATA_DIR}/hamster_carcinogenicity.csv")
        csv.shift
        csv.each do |row|
          c = Compound.from_smiles(row.shift)
          assert_equal row, d.values(c,d.features.first)
        end
        d.delete 
      end
    end
    threads.each {|aThread| aThread.join}
  end

  def test_upload_feature_dataset
    skip
    t = Time.now
    f = File.join DATA_DIR, "rat_feature_dataset.csv"
    d = Dataset.from_csv_file f
    assert_equal 458, d.features.size
    d.save
    #p "Upload: #{Time.now-t}"
    d2 = Dataset.find d.id
    t = Time.now
    assert_equal d.features.size, d2.features.size
    csv = CSV.read f
    csv.shift # remove header
    assert_empty d2.warnings
    assert_equal csv.size, d2.compounds.size 
    assert_equal csv.first.size-1, d2.features.size
    d2.compounds.each_with_index do |compound,i|
      row = csv[i]
      row.shift # remove compound
      assert_equal row, d2.data_entries[i]
    end
    #p "Dowload: #{Time.now-t}"
    d2.delete
    assert_nil Dataset.find d.id
  end

end