From ec87f7e079f3a7ef8ea6a0fa57f3b40e81ecaed0 Mon Sep 17 00:00:00 2001
From: Christoph Helma <helma@in-silico.ch>
Date: Wed, 5 Oct 2016 14:43:18 +0200
Subject: classification and regression tests

---
 test/classification.rb |  8 ++++----
 test/regression.rb     | 25 +++++++++++++++++++------
 2 files changed, 23 insertions(+), 10 deletions(-)

diff --git a/test/classification.rb b/test/classification.rb
index 9104022..6638a79 100644
--- a/test/classification.rb
+++ b/test/classification.rb
@@ -4,7 +4,7 @@ class LazarClassificationTest < MiniTest::Test
 
   def test_lazar_classification
     training_dataset = Dataset.from_csv_file File.join(DATA_DIR,"hamster_carcinogenicity.csv")
-    model = Model::LazarClassification.create training_dataset.features.first, training_dataset
+    model = Model::Lazar.create training_dataset: training_dataset
 
     [ {
       :compound => OpenTox::Compound.from_inchi("InChI=1S/C6H6/c1-2-4-6-5-3-1/h1-6H"),
@@ -40,9 +40,9 @@ class LazarClassificationTest < MiniTest::Test
 
   def test_lazar_kazius
     t = Time.now
-    dataset = Dataset.from_csv_file File.join(DATA_DIR,"kazius.csv")
+    training_dataset = Dataset.from_csv_file File.join(DATA_DIR,"kazius.csv")
     t = Time.now
-    model = Model::LazarClassification.create(dataset.features.first,dataset)
+    model = Model::Lazar.create training_dataset: training_dataset
     t = Time.now
     2.times do
       compound = Compound.from_smiles("Clc1ccccc1NN")
@@ -50,6 +50,6 @@ class LazarClassificationTest < MiniTest::Test
       assert_equal "1", prediction[:value]
       #assert_in_delta 0.019858401199860445, prediction[:confidence], 0.001
     end
-    dataset.delete
+    training_dataset.delete
   end
 end
diff --git a/test/regression.rb b/test/regression.rb
index dff0518..4c21450 100644
--- a/test/regression.rb
+++ b/test/regression.rb
@@ -4,7 +4,15 @@ class LazarRegressionTest < MiniTest::Test
 
   def test_weighted_average
     training_dataset = Dataset.from_csv_file "#{DATA_DIR}/EPAFHM.medi_log10.csv"
-    model = Model::LazarRegression.create training_dataset.features.first, training_dataset, {:neighbor_algorithm_parameters => {:min_sim => 0}, :prediction_algorithm => "OpenTox::Algorithm::Regression.local_weighted_average"}
+    algorithms = {
+      :similarity => {
+        :min => 0
+      },
+      :prediction => {
+        :method => "Algorithm::Regression.weighted_average",
+      },
+    }
+    model = Model::Lazar.create training_dataset: training_dataset, algorithms: algorithms
     compound = Compound.from_smiles "CC(C)(C)CN"
     prediction = model.predict compound
     assert_equal -0.86, prediction[:value].round(2)
@@ -13,17 +21,22 @@ class LazarRegressionTest < MiniTest::Test
 
   def test_mpd_fingerprints
     training_dataset = Dataset.from_csv_file "#{DATA_DIR}/EPAFHM.medi_log10.csv"
-    model = Model::LazarRegression.create training_dataset.features.first, training_dataset
-    model.neighbor_algorithm_parameters[:type] = "MP2D"
+    algorithms = {
+      :descriptors => {
+        :method => "fingerprint",
+        :type => "MP2D"
+      }
+    }
+    model = Model::Lazar.create training_dataset: training_dataset, algorithms: algorithms
     compound = Compound.from_smiles "CCCSCCSCC"
     prediction = model.predict compound
-    assert_equal 1.37, prediction[:value].round(2)
     assert_equal 3, prediction[:neighbors].size
+    assert_equal 1.37, prediction[:value].round(2)
   end
 
   def test_local_fingerprint_regression
     training_dataset = Dataset.from_csv_file "#{DATA_DIR}/EPAFHM.medi_log10.csv"
-    model = Model::LazarRegression.create(training_dataset.features.first, training_dataset, :prediction_algorithm => "OpenTox::Algorithm::Regression.local_fingerprint_regression")
+    model = Model::Lazar.create training_dataset: training_dataset
     compound = Compound.from_smiles "NC(=O)OCCC"
     prediction = model.predict compound
     refute_nil prediction[:value]
@@ -34,7 +47,7 @@ class LazarRegressionTest < MiniTest::Test
   def test_local_physchem_regression
     skip # TODO: fix
     training_dataset = Dataset.from_csv_file "#{DATA_DIR}/EPAFHM.medi_log10.csv"
-    model = Model::LazarRegression.create(training_dataset.features.first, training_dataset, :prediction_algorithm => "OpenTox::Algorithm::Regression.local_physchem_regression")
+    model = Model::Lazar.create(training_dataset.features.first, training_dataset, :prediction_algorithm => "OpenTox::Algorithm::Regression.local_physchem_regression")
     compound = Compound.from_smiles "NC(=O)OCCC"
     prediction = model.predict compound
     refute_nil prediction[:value]
-- 
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