test_factor.rb in statsample-0.6.5

- old
+ new
@@ -1,38 +1,46 @@
 $:.unshift(File.dirname(__FILE__)+'/../lib/')
 require 'statsample'
 require 'test/unit'
 class StatsampleFactorTestCase < Test::Unit::TestCase
     def test_pca
-      require 'gsl'
-      a=[2.5, 0.5, 2.2, 1.9, 3.1, 2.3, 2.0, 1.0, 1.5, 1.1].to_scale
-      b=[2.4,0.7,2.9,2.2,3.0,2.7,1.6,1.1,1.6,0.9].to_scale
-      a.recode! {|c| c-a.mean}
-      b.recode! {|c| c-b.mean}
-      ds={'a'=>a,'b'=>b}.to_dataset
-      cov_matrix=Statsample::Bivariate.covariance_matrix(ds)
-      pca=Statsample::Factor::PCA.new(cov_matrix)
-      expected_eigenvalues=[1.284, 0.0490]
-      expected_eigenvalues.each_with_index{|ev,i|
-        assert_in_delta(ev,pca.eigenvalues[i],0.001)
-      }
-      expected_fm_1=GSL::Matrix[[0.677], [0.735]]
-      expected_fm_2=GSL::Matrix[[0.677,0.735], [0.735, -0.677]]
-      _test_matrix(expected_fm_1,pca.feature_vector(1))
-      _test_matrix(expected_fm_2,pca.feature_vector(2))
+      if HAS_GSL
+        require 'gsl'
+        a=[2.5, 0.5, 2.2, 1.9, 3.1, 2.3, 2.0, 1.0, 1.5, 1.1].to_scale
+        b=[2.4,0.7,2.9,2.2,3.0,2.7,1.6,1.1,1.6,0.9].to_scale
+        a.recode! {|c| c-a.mean}
+        b.recode! {|c| c-b.mean}
+        ds={'a'=>a,'b'=>b}.to_dataset
+        cov_matrix=Statsample::Bivariate.covariance_matrix(ds)
+        pca=Statsample::Factor::PCA.new(cov_matrix)
+        expected_eigenvalues=[1.284, 0.0490]
+        expected_eigenvalues.each_with_index{|ev,i|
+          assert_in_delta(ev,pca.eigenvalues[i],0.001)
+        }
+        expected_fm_1=GSL::Matrix[[0.677], [0.735]]
+        expected_fm_2=GSL::Matrix[[0.677,0.735], [0.735, -0.677]]
+        _test_matrix(expected_fm_1,pca.feature_vector(1))
+        _test_matrix(expected_fm_2,pca.feature_vector(2))
+      else
+        puts "PCA not tested. Requires GSL"
+      end
     end
     def test_rotation_varimax
-      a = Matrix[ [ 0.4320,  0.8129,  0.3872]  ,
-       [0.7950, -0.5416,  0.2565]  ,
-       [0.5944,  0.7234, -0.3441],
-       [0.8945, -0.3921, -0.1863] ]
-       expected= Matrix[[-0.0204423,     0.938674,    -0.340334],
-       [0.983662, 0.0730206, 0.134997],
-       [0.0826106, 0.435975, -0.893379],
-       [0.939901, -0.0965213, -0.309596]].to_gsl
-       varimax=Statsample::Factor::Varimax.new(a)
-       varimax.iterate
-       _test_matrix(expected,varimax.rotated)
+      if HAS_GSL
+        a = Matrix[ [ 0.4320,  0.8129,  0.3872]  ,
+         [0.7950, -0.5416,  0.2565]  ,
+         [0.5944,  0.7234, -0.3441],
+         [0.8945, -0.3921, -0.1863] ]
+         expected= Matrix[[-0.0204423,     0.938674,    -0.340334],
+         [0.983662, 0.0730206, 0.134997],
+         [0.0826106, 0.435975, -0.893379],
+         [0.939901, -0.0965213, -0.309596]].to_gsl
+         varimax=Statsample::Factor::Varimax.new(a)
+         varimax.iterate
+         _test_matrix(expected,varimax.rotated)
+       else
+         puts "Rotation not tested. Requires GSL"
+       end
     end
     def _test_matrix(a,b)
       a.size1.times {|i|
         a.size2.times {|j|
           assert_in_delta(a[i,j], b[i,j],0.001)