Added tests for LogAutoScaler

1 files changed, 97 insertions, 45 deletions

diff --git a/transform.rb b/transform.rb
index dee511c..049909c 100644
--- a/transform.rb
+++ b/transform.rb
@@ -5,53 +5,105 @@ require 'test/unit'
 
 class TransformTest < Test::Unit::TestCase
 
-#def test_mlr
-#  2.times {
-#    n_prop = [ [1,1], [2,2], [3,3] ] # erste WH
-#    acts = [ 3,2,3 ]   # should yield a constant y=2.8
-#    sims = [ 4,2,4 ]   # move constant closer to 3.0
-#    q_prop = [0.5,0.5] # extrapolation
-#    params={:n_prop => n_prop, :q_prop => q_prop, :sims => sims, :acts => acts}
-#
-#    prediction = OpenTox::Algorithm::Neighbors.mlr(params)
-#    assert_in_delta prediction, 2.8, 1.0E-10 # small deviations, don't know why
-#
-#    q_prop = [1.5,1.5] # interpolation
-#    prediction = OpenTox::Algorithm::Neighbors.mlr(params)
-#    assert_in_delta prediction, 2.8, 1.0E-10 # small deviations, don't know why
-#  }
-#end
-
-def test_pca
-
-  d = GSL::Matrix.alloc([1,1.1,2,1.9,3,3.3], 3, 2)
-  td = GSL::Matrix.alloc([-1.64373917483226, -0.155542754209564, 1.79928192904182],3,1)
-  ev = GSL::Matrix.alloc([0.707106781186548, 0.707106781186548], 2, 1)
-  rd = GSL::Matrix.alloc([1.05098674493306, 1.043223563717, 1.91019734898661, 2.0, 3.03881590608033, 3.256776436283], 3, 2)
-
-  # Lossy
-  2.times do # repeat to ensure idempotency
-    pca = OpenTox::Algorithm::Transform::PCA.new(d, 0.05)
-    assert_equal pca.data_matrix, d
-    assert_equal pca.data_transformed_matrix, td
-    assert_equal pca.transform(d), td
-    assert_equal pca.eigenvector_matrix, ev
-    assert_equal pca.restore, rd
+  #def test_mlr
+  #  2.times {
+  #    n_prop = [ [1,1], [2,2], [3,3] ] # erste WH
+  #    acts = [ 3,2,3 ]   # should yield a constant y=2.8
+  #    sims = [ 4,2,4 ]   # move constant closer to 3.0
+  #    q_prop = [0.5,0.5] # extrapolation
+  #    params={:n_prop => n_prop, :q_prop => q_prop, :sims => sims, :acts => acts}
+  #
+  #    prediction = OpenTox::Algorithm::Neighbors.mlr(params)
+  #    assert_in_delta prediction, 2.8, 1.0E-10 # small deviations, don't know why
+  #
+  #    q_prop = [1.5,1.5] # interpolation
+  #    prediction = OpenTox::Algorithm::Neighbors.mlr(params)
+  #    assert_in_delta prediction, 2.8, 1.0E-10 # small deviations, don't know why
+  #  }
+  #end
+  
+  def test_pca
+  
+    d = GSL::Matrix.alloc([1,1.1,2,1.9,3,3.3], 3, 2)
+    td = GSL::Matrix.alloc([-1.64373917483226, -0.155542754209564, 1.79928192904182],3,1)
+    ev = GSL::Matrix.alloc([0.707106781186548, 0.707106781186548], 2, 1)
+    rd = GSL::Matrix.alloc([1.05098674493306, 1.043223563717, 1.91019734898661, 2.0, 3.03881590608033, 3.256776436283], 3, 2)
+  
+    # Lossy
+    2.times do # repeat to ensure idempotency
+      pca = OpenTox::Transform::PCA.new(d, 0.05)
+      assert_equal pca.data_matrix, d
+      assert_equal pca.data_transformed_matrix, td
+      assert_equal pca.transform(d), td
+      assert_equal pca.eigenvector_matrix, ev
+      assert_equal pca.restore, rd
+    end
+  
+    td = GSL::Matrix.alloc([-1.64373917483226, 0.0883116327366195, -0.155542754209564, -0.155542754209564, 1.79928192904182, 0.0672311214729441],3,2)
+    ev = GSL::Matrix.alloc([0.707106781186548, -0.707106781186548, 0.707106781186548, 0.707106781186548], 2, 2)
+  
+    # Lossless
+    2.times do
+      pca = OpenTox::Transform::PCA.new(d, 0.0)
+      assert_equal pca.data_matrix, d
+      assert_equal pca.data_transformed_matrix, td
+      assert_equal pca.transform(d), td
+      assert_equal pca.eigenvector_matrix, ev
+      assert_equal pca.restore, d
+    end
+  
   end
+  
+  def test_logas
+  
+    d1 = [ 1,2,3 ]
+    d2 = [ -1,0,1 ]
+    d3 = [ -2,3,8 ]
+    d4 = [ -20,30,80 ]
 
-  td = GSL::Matrix.alloc([-1.64373917483226, 0.0883116327366195, -0.155542754209564, -0.155542754209564, 1.79928192904182, 0.0672311214729441],3,2)
-  ev = GSL::Matrix.alloc([0.707106781186548, -0.707106781186548, 0.707106781186548, 0.707106781186548], 2, 2)
-
-  # Lossless
-  2.times do
-    pca = OpenTox::Algorithm::Transform::PCA.new(d, 0.0)
-    assert_equal pca.data_matrix, d
-    assert_equal pca.data_transformed_matrix, td
-    assert_equal pca.transform(d), td
-    assert_equal pca.eigenvector_matrix, ev
-    assert_equal pca.restore, d
-  end
 
-end
+    2.times {
+
+      logas = OpenTox::Transform::LogAutoScale.new(d1)
+      d1la = logas.vs
+      d1la.each_with_index { |v,i| 
+        assert_in_delta v, [ -1.31668596949013, 0.211405021140643, 1.10528094834949 ][i], 1.0E-10
+      }
+      assert_equal logas.transform(d1), d1la
+      logas.restore(d1la).each_with_index { |v,i|
+        assert_in_delta v, d1[i], 1.0E-10
+      }
+  
+      logas = OpenTox::Transform::LogAutoScale.new(d2)
+      d2la = logas.vs
+      assert_equal d2la, d1la
+      assert_equal logas.transform(d2), d2la
+      logas.restore(d2la).each_with_index { |v,i|
+        assert_in_delta v, d2[i], 1.0E-10
+      }
+  
+      logas = OpenTox::Transform::LogAutoScale.new(d3)
+      d3la = logas.vs
+      d3la.each_with_index { |v,i|
+        assert_in_delta v, [ -1.37180016053906, 0.388203523926062, 0.983596636612997 ][i], 1.0E-10
+      }
+      assert_equal logas.transform(d3), d3la
+      logas.restore(d3la).each_with_index { |v,i|
+        assert_in_delta v, d3[i], 1.0E-10
+      }
+   
+      logas = OpenTox::Transform::LogAutoScale.new(d4)
+      d4la = logas.vs
+      d4la.each_with_index { |v,i|
+        assert_in_delta v, [ -1.40084731572532, 0.532435269814955, 0.868412045910369 ][i], 1.0E-10
+      }
+      assert_equal logas.transform(d4), d4la
+      logas.restore(d4la).each_with_index { |v,i|
+        assert_in_delta v, d4[i], 1.0E-10
+      }
+
+    }
+ 
+  end
 
 end