require 'rubygems'
require 'opentox-ruby'
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([-1.3421074161875, -0.127000127000191, 1.46910754318769],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.eigenvector_matrix, ev
#      assert_equal pca.restore, rd
#    end
#
#    td = GSL::Matrix.alloc([-1.3421074161875, 0.0721061461855949, -0.127000127000191, -0.127000127000191, 1.46910754318769, 0.0548939808145955],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.eigenvector_matrix, ev
#      assert_equal pca.restore, d
#    end
#
#  end

end