some pep8

theano/tensor/tests/test_opt.py

@@ -1495,11 +1495,11 @@ def test_log1p():
     f = function([x], T.log(1 + (x)), mode=m)
     assert [node.op for node in f.maker.fgraph.toposort()] == [T.log1p]
     f = function([x], T.log(1 + (-x)), mode=m)
-    assert [node.op for node in f.maker.fgraph.toposort()] == [T.neg,
-         inplace.log1p_inplace]
+    assert [node.op for node in f.maker.fgraph.toposort()] == [
+        T.neg, inplace.log1p_inplace]
     f = function([x], -T.log(1 + (-x)), mode=m)
-    assert [node.op for node in f.maker.fgraph.toposort()] == [T.neg,
-         inplace.log1p_inplace, inplace.neg_inplace]
+    assert [node.op for node in f.maker.fgraph.toposort()] == [
+        T.neg, inplace.log1p_inplace, inplace.neg_inplace]
 
     # check trickier cases (and use different dtype)
     y = fmatrix()
@@ -1507,12 +1507,12 @@ def test_log1p():
     print f.maker.fgraph.toposort()
     # the first three ops are Shape_i, Shape_i, and Dimshuffle
     theano.printing.debugprint(f)
-    assert [node.op for node in f.maker.fgraph.toposort()][3:] \
-            == [T.log1p, tensor.alloc]
+    assert [node.op for node in f.maker.fgraph.toposort()][3:] == [
+        T.log1p, tensor.alloc]
     f = function([x, y], T.log(0 + (x) + tensor.fill(y, 1.0)), mode=m)
     theano.printing.debugprint(f)
-    assert [node.op for node in f.maker.fgraph.toposort()][3:] \
-            == [T.log1p, tensor.alloc]
+    assert [node.op for node in f.maker.fgraph.toposort()][3:] == [
+        T.log1p, tensor.alloc]
     f = function([x, y], T.log(2 + (x) - tensor.fill(y, 1.0)), mode=m)
     theano.printing.debugprint(f)
     assert [node.op for node in f.maker.fgraph.toposort()][3:] \
@@ -2333,7 +2333,8 @@ class Test_alloc_zero(unittest.TestCase):
     def setUp(self):
         mode = theano.compile.mode.get_default_mode()
         self.mode = mode.including("local_incsubtensor_of_allocs",
-             "local_setsubtensor_of_allocs", "local_0_dot_x")
+                                   "local_setsubtensor_of_allocs",
+                                   "local_0_dot_x")
 
     def test_setsubtensor_allocs0(self):
         x = tensor.matrix()
@@ -2427,7 +2428,7 @@ class Test_alloc_zero(unittest.TestCase):
                     f(_e1[1], _e2[1])
                     f(_e1[2], _e2[2])
                     assert numpy.all([not isinstance(x.op, tensor.Dot) for x in
-                                      f.maker.fgraph.toposort() ])
+                                      f.maker.fgraph.toposort()])
 
                     #test that we don't remove shape errors
                     self.assertRaises((ValueError, AssertionError), f,
@@ -2809,8 +2810,8 @@ class test_assert(utt.InferShapeTester):
 
         x = T.scalar()
         y = T.scalar()
-        f = theano.function([x, y], theano.tensor.opt.assert_(x, y,
-             1), mode=mode)
+        f = theano.function([x, y], theano.tensor.opt.assert_(x, y, 1),
+                            mode=mode)
         assert f(1, 1) == 1
         assert f(5, 1) == 5
         topo = f.maker.fgraph.toposort()
@@ -2827,8 +2828,8 @@ class test_assert(utt.InferShapeTester):
 
         x = T.scalar()
         y = T.scalar()
-        f = theano.function([x, y], theano.tensor.opt.assert_(x, y,
-             0), mode=mode)
+        f = theano.function([x, y], theano.tensor.opt.assert_(x, y, 0),
+                            mode=mode)
         self.assertRaises(AssertionError, f, 1, 0)
         topo = f.maker.fgraph.toposort()
         assert len(topo) == 2
@@ -3177,8 +3178,9 @@ def test_constant_get_stabilized():
 class T_local_switch_sink(unittest.TestCase):
     def setUp(self):
         # condition values
-        self.condm = numpy.asarray([[0.1, 0, 1, -1], [0., 0., 0.,
-             0.], [1, 1, 1, 1]])
+        self.condm = numpy.asarray([[0.1, 0, 1, -1],
+                                    [0., 0., 0., 0.],
+                                    [1, 1, 1, 1]])
         self.condv = numpy.asarray([0.1, 0, 1, -1])
         self.conds = [0.1, 0, 1, -1]
 
@@ -3256,14 +3258,14 @@ class T_local_erf(unittest.TestCase):
 
         f = theano.function([x], 1 + T.erf(x), mode=self.mode)
         print f.maker.fgraph.toposort()
-        assert [n.op for n in f.maker.fgraph.toposort()] == [T.mul, T.
-            erfc], f.maker.fgraph.toposort()
+        assert [n.op for n in f.maker.fgraph.toposort()] == [
+            T.mul, T.erfc], f.maker.fgraph.toposort()
         f(val)
 
         f = theano.function([x], T.erf(x) + 1, mode=self.mode)
         print f.maker.fgraph.toposort()
-        assert [n.op for n in f.maker.fgraph.toposort()] == [T.mul, T.
-            erfc], f.maker.fgraph.toposort()
+        assert [n.op for n in f.maker.fgraph.toposort()] == [
+            T.mul, T.erfc], f.maker.fgraph.toposort()
         f(val)
 
         f = theano.function([x], T.erf(x) + 2, mode=self.mode)
@@ -3305,7 +3307,7 @@ class T_local_erf(unittest.TestCase):
         assert topo[0].op == T.erf, f.maker.fgraph.toposort()
         assert isinstance(topo[1].op, T.Elemwise), f.maker.fgraph.toposort()
         assert isinstance(topo[1].op.scalar_op, scal.Add)\
-            or isinstance(topo[1].op.scalar_op,scal.Sub), f.maker.fgraph.toposort()
+            or isinstance(topo[1].op.scalar_op, scal.Sub), f.maker.fgraph.toposort()
         print f(val)
 
     def test_local_erf_minus_one(self):
@@ -3345,7 +3347,8 @@ class T_local_erfc(unittest.TestCase):
             'canonicalize').including('fast_run').excluding('gpu')
         self.mode = self.mode_fusion.excluding('fusion')
         self.mode._optimizer.position_cutoff = 1.50001
-        if theano.config.cxx == '' and not theano.scalar.basic_scipy.imported_scipy_special:
+        if (theano.config.cxx == '' and
+            not theano.scalar.basic_scipy.imported_scipy_special):
             raise SkipTest("erfc need a c++ compiler or scipy")
 
     def test_local_one_minus_erfc(self):