Update import and indent.

theano/sandbox/linalg/ops.py

 import numpy
 
-from theano.gof import Variable, Op, utils, Type, Constant,  Value, Apply
+from theano.gof import Op, Apply
 
 from theano.tensor import as_tensor_variable, dot, DimShuffle
 from theano import tensor
@@ -174,7 +174,7 @@ def is_positive(v):
     print 'is_positive', v
     if v.owner and v.owner.op == tensor.pow:
         print 'try for pow', v, v.owner.inputs
-        try: 
+        try:
             exponent = tensor.get_constant_value(v.owner.inputs[1])
         except TypeError:
             return False
@@ -530,5 +530,3 @@ class A_Xinv_b(Op):
         gX = -matrix_dot(iX.T, a, gz, b.T, iX.T)
         gb = matrix_dot(ix.T, a.T, gz)
         return [ga, gX, gb]
-
-

theano/sandbox/linalg/tests/test_linalg.py

@@ -5,7 +5,18 @@ import theano.scipy # To know if scipy is available.
 from theano import tensor, function
 from theano.tensor.basic import _allclose
 
-from theano.sandbox.linalg.ops import *
+# The one in comment are not tested...
+from theano.sandbox.linalg.ops import (cholesky,
+                                       matrix_inverse,
+                                       #solve,
+                                       #diag,
+                                       #extract_diag,
+                                       #alloc_diag,
+                                       det,
+                                       #PSD_hint,
+                                       #trace,
+                                       #spectral_radius_bound
+                                       )
 
 from nose.plugins.skip import SkipTest
 
@@ -21,7 +32,7 @@ if 0:
         pd = numpy.dot(r,r.T)
 
         x = tensor.matrix()
-        chol = Cholesky()(x)
+        chol = cholesky(x)
         f = function([x], tensor.dot(chol, chol.T)) # an optimization could remove this
 
         ch_f = function([x], chol)