FIX: pytest.raises does not support str argument

Using the second argument to pytest.raises as a string is deprecated
since pytest versiono 4.0 and has been removed since pytest 5.1:
https://docs.pytest.org/en/latest/changelog.html#pytest-5-1-0-2019-08-15

mdp/test/test_Convolution2DNode.py

@@ -18,13 +18,13 @@ def testConvolution2DNodeFunctionality():
     filters = numx.empty((3,1,1))
     filters[:,0,0] = [1.,2.,3.]
     x = numx_rand.random((10,3,4))
-    
+
     for mode in ['valid', 'same', 'full']:
         for boundary in ['fill', 'wrap', 'symm']:
             node = mdp.nodes.Convolution2DNode(filters, approach='linear', mode=mode,
                                                boundary=boundary, output_2d=False)
             y = node.execute(x)
-            
+
             assert_equal(y.shape, (x.shape[0], 3, x.shape[1], x.shape[2]))
             for n_flt in range(3):
                 assert_array_equal(x*(n_flt+1.), y[:,n_flt,:,:])
@@ -33,21 +33,21 @@ def testConvolution2DNodeFunctionality():
 def testConvolution2DNode_2D3Dinput():
     filters = numx.empty((3,1,1))
     filters[:,0,0] = [1.,2.,3.]
-    
+
     # 1) input 2D/3D
-    x = numx_rand.random((10,12))        
+    x = numx_rand.random((10,12))
     node = mdp.nodes.Convolution2DNode(filters, approach='linear',
                                        input_shape=(3,4), output_2d=False)
     y = node.execute(x)
     assert_equal(y.shape, (x.shape[0], 3, 3, 4))
-    
-    x = numx.random.random((10,3,4)) 
+
+    x = numx.random.random((10,3,4))
     node = mdp.nodes.Convolution2DNode(filters, output_2d=False)
     y = node.execute(x)
     assert_equal(y.shape, (x.shape[0], 3, 3, 4))
-        
+
     # 2) output 2D/3D
-    x = numx.random.random((10,12))        
+    x = numx.random.random((10,12))
     node = mdp.nodes.Convolution2DNode(filters, approach='linear',
                                        input_shape=(3,4), output_2d=True)
     y = node.execute(x)
@@ -60,7 +60,7 @@ def testConvolution2DNode_fft():
     filters = numx.empty((3,1,1))
     filters[:,0,0] = [1.,2.,3.]
     x = numx.random.random((10,3,4))
-    
+
     for mode in ['valid', 'same', 'full']:
         node = mdp.nodes.Convolution2DNode(filters, approach='fft', mode=mode,
                                            output_2d=False)
@@ -80,21 +80,21 @@ def testConvolution2DNode_fft():
                                                boundary='fill', output_2d=False)
         y_fft = node_fft.execute(x)
         y_lin = node_lin.execute(x)
-        
+
         assert_array_almost_equal(y_fft, y_lin, 6)
 
 @requires_signal
 def testConvolution2DNode_in_Flow():
     filters = numx.empty((3,1,1))
     filters[:,0,0] = [1.,2.,3.]
-    
+
     # with 3D input
-    x = numx.random.random((10,3,4))   
+    x = numx.random.random((10,3,4))
     node = mdp.nodes.Convolution2DNode(filters, output_2d=True)
     flow = mdp.Flow([node, mdp.nodes.PCANode(output_dim=3)])
     flow.train(x)
     flow.execute(x)
-    
+
     # with 2D input
     x = numx.random.random((10,12))
     node = mdp.nodes.Convolution2DNode(filters, input_shape=(3,4), output_2d=True)
@@ -109,15 +109,15 @@ def testConvolution2DNode_arguments():
     # filters must be 3D
     filters = numx.random.random((5,4))
     pytest.raises(mdp.NodeException,
-                  "mdp.nodes.Convolution2DNode(filters)")
+                  mdp.nodes.Convolution2DNode, filters)
     filters = numx.random.random((5,4,2,2))
     pytest.raises(mdp.NodeException,
-                  "mdp.nodes.Convolution2DNode(filters)")
+                  mdp.nodes.Convolution2DNode, filters)
     # filters must be array
     filters = [[[2.]]]
     pytest.raises(mdp.NodeException,
-                  "mdp.nodes.Convolution2DNode(filters)")
- 
+                  mdp.nodes.Convolution2DNode, filters)
+
     filters = numx.random.random((1,1,1))
     with pytest.raises(mdp.NodeException):
         mdp.nodes.Convolution2DNode(filters, approach='bug')

mdp/test/test_FANode.py

@@ -75,5 +75,5 @@ def test_FANode_singular_cov():
     fanode = mdp.nodes.FANode(output_dim=3)
     fanode.train(x)
     # the matrix x is singular
-    pytest.raises(mdp.NodeException, "fanode.stop_training()")
+    pytest.raises(mdp.NodeException, fanode.stop_training)
 

mdp/test/test_PCANode.py

@@ -232,5 +232,4 @@ def test_PCANode_no_eigenvalues_left():
     mat = numx.zeros((100,4), dtype='d')
     pca = mdp.nodes.PCANode(svd=True, reduce=True)
     pca.train(mat)
-    pytest.raises(mdp.NodeException, 'pca.stop_training()')
-
+    pytest.raises(mdp.NodeException, pca.stop_training)

mdp/test/test_metaclass_and_extensions.py

@@ -39,7 +39,8 @@ def _train(self, x, foo=None):
     assert get_signature(cnode._train) == 'self, x, foo'
     cnode.train(X, foo=42)
     assert cnode.foo == 42
-    pytest.raises(AttributeError, 'cnode.foo2')
+    with pytest.raises(AttributeError):
+        _ = cnode.foo2
 
 
 def test_signatures_more_arguments():
@@ -59,7 +60,8 @@ def _train(self, x, foo=None):
     cnode.train._undecorated_(cnode, X, foo=42)
     cnode.train(X, foo=42)
     assert cnode.foo == 42
-    pytest.raises(AttributeError, 'cnode.foo2')
+    with pytest.raises(AttributeError):
+        _ = cnode.foo2
 
 
 def test_signatures_less_arguments():
@@ -82,7 +84,8 @@ def _train(self, x):
     cnode.train._undecorated_(cnode, X)
     cnode.train(X)
     assert cnode.moo == 3
-    pytest.raises(AttributeError, 'cnode.foo')
+    with pytest.raises(AttributeError):
+        _ = cnode.foo
 
 
 def test_simple_extension():

mdp/test/test_nodes_generic.py

@@ -262,16 +262,16 @@ def _test(node):
             # raises an appropriate error
             # case 1: both in the constructor
             pytest.raises(InconsistentDimException,
-                          'klass(input_dim=inp.shape[1], output_dim=output_dim, *args)')
+                          klass, *args, input_dim=inp.shape[1], output_dim=output_dim)
             # case 2: first input_dim, then output_dim
             node = klass(input_dim=inp.shape[1], *args)
-            pytest.raises(InconsistentDimException,
-                          'node.output_dim = output_dim')
+            with pytest.raises(InconsistentDimException):
+                node.output_dim = output_dim
             # case 3: first output_dim, then input_dim
             node = klass(output_dim=output_dim, *args)
             node.output_dim = output_dim
-            pytest.raises(InconsistentDimException,
-                          'node.input_dim = inp.shape[1]')
+            with pytest.raises(InconsistentDimException):
+                node.input_dim = inp.shape[1]
 
         # check that output_dim is set to whatever the output dim is
         node = klass(*args)