use numpy testing to get more accurate error messages

bob/math/test_gsvd.py

@@ -9,9 +9,9 @@ Tests GSVD
  Basically these tests test the GSVD relation.
  Given 2 matrices A and B  GSVD(A,B) = [U,V,X,C,S] where,
 
-  A= (X * C.T * U^T)^T and 
+  A= (X * C.T * U^T)^T and
   B= (X * S.T * V^T)^T and
-  
+
   C**2 + S**2 = 1
 
 """
@@ -34,22 +34,22 @@ def gsvd_relations(A,B):
   A_check = numpy.dot(numpy.dot(X,C.T),U.T).T
   nose.tools.eq_( (abs(A-A_check) < 1e-10).all(), True )
 
-  # Cheking the relation B= (X * S.T * V^T)^T 
+  # Cheking the relation B= (X * S.T * V^T)^T
   B_check = numpy.dot(numpy.dot(X,S.T),V.T).T
   nose.tools.eq_( (abs(B-B_check) < 1e-10).all(), True )
 
 
 def svd_relations(A):
 
-  [U, S, V] = bob.math.svd(A)  
+  [U, S, V] = bob.math.svd(A)
   A_check = numpy.dot(numpy.dot(V,S), U)
   nose.tools.eq_( (abs(A-A_check) < 1e-10).all(), True )
 
 
 def test_first_case():
-  
+
   #Testing the first scenario of gsvd:
-  #M-K-L >= 0 (check http://www.netlib.org/lapack/explore-html/d1/d7e/group__double_g_esing_ga4a187519e5c71da3b3f67c85e9baf0f2.html#ga4a187519e5c71da3b3f67c85e9baf0f2)  
+  #M-K-L >= 0 (check http://www.netlib.org/lapack/explore-html/d1/d7e/group__double_g_esing_ga4a187519e5c71da3b3f67c85e9baf0f2.html#ga4a187519e5c71da3b3f67c85e9baf0f2)
 
   A = numpy.random.rand(10,10)
   B = numpy.random.rand(790,10)
@@ -58,9 +58,9 @@ def test_first_case():
 
 
 def test_second_case():
-  
+
   #Testing the second scenario of gsvd:
-  #M-K-L < 0 (check http://www.netlib.org/lapack/explore-html/d1/d7e/group__double_g_esing_ga4a187519e5c71da3b3f67c85e9baf0f2.html#ga4a187519e5c71da3b3f67c85e9baf0f2)  
+  #M-K-L < 0 (check http://www.netlib.org/lapack/explore-html/d1/d7e/group__double_g_esing_ga4a187519e5c71da3b3f67c85e9baf0f2.html#ga4a187519e5c71da3b3f67c85e9baf0f2)
 
 
   A = numpy.random.rand(4,5)
@@ -98,23 +98,23 @@ def test_svd_relation():
 def test_svd_signal():
 
   ##Testing SVD signal
-  ##This test was imported from bob.learn.linear  
+  ##This test was imported from bob.learn.linear
 
   A = numpy.array([[3,-3,100], [4,-4,50], [3.5,-3.5,-50], [3.8,-3.7,-100]], dtype='float64')
 
   U_ref = numpy.array([[  2.20825004e-03,  -1.80819459e-03,  -9.99995927e-01],
                        [ -7.09549949e-01,  7.04649416e-01,  -2.84101853e-03],
                        [ 7.04651683e-01,  7.09553332e-01,  2.73037723e-04]])
-  
+
   [U,S,V] = bob.math.svd(A)
-  nose.tools.eq_((abs(U-U_ref) < 1e-7).all(), True)
+  numpy.testing.assert_allclose(U, U_ref, rtol=1e-5, atol=1e-6)
   svd_relations(A)
-  
 
-  
+
+
 def test_svd_signal_book_example():
 
-  ## Reference copied from here http://prod.sandia.gov/techlib/access-control.cgi/2007/076422.pdf  
+  ## Reference copied from here http://prod.sandia.gov/techlib/access-control.cgi/2007/076422.pdf
 
   A = numpy.array([[2.5, 63.5, 40.1, 78, 61.1],
                    [0.9, 58.0, 25.1, 78, 94.1],
@@ -130,6 +130,6 @@ def test_svd_signal_book_example():
   [U,S,V] = bob.math.svd(A)
   assert U[0,0] > 0
   svd_relations(A)
-  
-  
+
+