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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
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