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author | Andreas Maunz <andreas@maunz.de> | 2011-11-09 13:50:18 +0100 |
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committer | Andreas Maunz <andreas@maunz.de> | 2011-11-09 13:50:18 +0100 |
commit | 4f5f15ae60a0d98c419e67f86a7dc161721ded14 (patch) | |
tree | 0ca7b109a384ab9f7d32f33de061949422ae278f /transform.rb | |
parent | 8cfb409e1e3431441f1094c53a1950f680320b6a (diff) |
Added tests for LogAutoScaler
Diffstat (limited to 'transform.rb')
-rw-r--r-- | transform.rb | 142 |
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 |