pep8

theano/sparse/basic.py

@@ -1750,7 +1750,7 @@ class AddSD(gof.op.Op):
 
     def c_code(self, node, name, (_data, _indices, _indptr, y), (z, ), sub):
         inplace = int(self.inplace)
-        format = {'csc': 0, 'csr':1}[self.format]
+        format = {'csc': 0, 'csr': 1}[self.format]
         code = """
                 Py_XDECREF(%(z)s);
                 if (!%(inplace)s){
@@ -1759,7 +1759,7 @@ class AddSD(gof.op.Op):
                   %(z)s = %(y)s;
                   Py_XINCREF(%(z)s);
                 }
-                
+
                 npy_intp N =  PyArray_DIMS(%(_indptr)s)[0]-1;
                 const npy_int32 * __restrict__ indptr = (npy_int32 *)%(_indptr)s->data;
                 const npy_int32 * __restrict__ indices = (npy_int32*)%(_indices)s->data;
@@ -1795,9 +1795,9 @@ class AddSD(gof.op.Op):
         assert _is_dense(y)
 
         if self.format == 'csr':
-            x = scipy.sparse.csr_matrix((data, indices, indptr), shape = y.shape)
+            x = scipy.sparse.csr_matrix((data, indices, indptr), shape=y.shape)
         elif self.format == 'csc':
-            x = scipy.sparse.csc_matrix((data, indices, indptr), shape = y.shape)
+            x = scipy.sparse.csc_matrix((data, indices, indptr), shape=y.shape)
 
         # The asarray is needed as in some case, this return a
         # numpy.matrixlib.defmatrix.matrix object and not an ndarray.

theano/sparse/tests/test_basic.py

@@ -506,8 +506,8 @@ class T_AddMul(unittest.TestCase):
             elif op is mul:
                 self.assertTrue(_is_sparse_variable(apb))
                 self.assertTrue(numpy.all(val.todense() == (b.multiply(a))))
-                self.assertTrue(numpy.all(val.todense() == numpy.array([[1, 0],
-[9, 0], [0, 36]])))
+                self.assertTrue(numpy.all(val.todense() == numpy.array(
+                    [[1, 0], [9, 0], [0, 36]])))
 
     def _testDS(self, op, array1=numpy.array([[1., 0], [3, 0], [0, 6]]),
                 array2=numpy.asarray([[0, 2.], [0, 4], [5, 0]])):