pep8

theano/tensor/tests/test_complex.py

@@ -5,30 +5,31 @@ from theano.tests import unittest_tools as utt
 
 from numpy.testing import dec
 
+
 class TestRealImag(unittest.TestCase):
 
     def test0(self):
-        x= zvector()
+        x = zvector()
         rng = numpy.random.RandomState(23)
-        xval = numpy.asarray(list(numpy.complex(rng.randn(), rng.randn()) for i in xrange(10)))
-        assert numpy.all( xval.real == theano.function([x], real(x))(xval))
-        assert numpy.all( xval.imag == theano.function([x], imag(x))(xval))
+        xval = numpy.asarray(list(numpy.complex(rng.randn(), rng.randn())
+                                  for i in xrange(10)))
+        assert numpy.all(xval.real == theano.function([x], real(x))(xval))
+        assert numpy.all(xval.imag == theano.function([x], imag(x))(xval))
 
     def test_on_real_input(self):
-        x= dvector()
+        x = dvector()
         rng = numpy.random.RandomState(23)
         xval = rng.randn(10)
-        numpy.all( 0 == theano.function([x], imag(x))(xval))
-        numpy.all( xval == theano.function([x], real(x))(xval))
-
+        numpy.all(0 == theano.function([x], imag(x))(xval))
+        numpy.all(xval == theano.function([x], real(x))(xval))
 
-        x= imatrix()
-        xval = numpy.asarray(rng.randn(3,3)*100, dtype='int32')
-        numpy.all( 0 == theano.function([x], imag(x))(xval))
-        numpy.all( xval == theano.function([x], real(x))(xval))
+        x = imatrix()
+        xval = numpy.asarray(rng.randn(3, 3) * 100, dtype='int32')
+        numpy.all(0 == theano.function([x], imag(x))(xval))
+        numpy.all(xval == theano.function([x], real(x))(xval))
 
     def test_cast(self):
-        x= zvector()
+        x = zvector()
         self.assertRaises(TypeError, cast, x, 'int32')
 
     def test_complex(self):
@@ -36,27 +37,27 @@ class TestRealImag(unittest.TestCase):
         m = fmatrix()
         c = complex(m[0], m[1])
         assert c.type == cvector
-        r,i = [real(c), imag(c)]
+        r, i = [real(c), imag(c)]
         assert r.type == fvector
         assert i.type == fvector
-        f = theano.function([m], [r,i] )
+        f = theano.function([m], [r, i])
 
-        mval = numpy.asarray(rng.randn(2,5), dtype='float32')
+        mval = numpy.asarray(rng.randn(2, 5), dtype='float32')
         rval, ival = f(mval)
-        assert numpy.all(rval == mval[0]), (rval,mval[0])
+        assert numpy.all(rval == mval[0]), (rval, mval[0])
         assert numpy.all(ival == mval[1]), (ival, mval[1])
 
-    @dec.knownfailureif(True,"Complex grads not enabled, see #178")
+    @dec.knownfailureif(True, "Complex grads not enabled, see #178")
     def test_complex_grads(self):
         def f(m):
             c = complex(m[0], m[1])
             return .5 * real(c) + .9 * imag(c)
 
         rng = numpy.random.RandomState(9333)
-        mval = numpy.asarray(rng.randn(2,5))
+        mval = numpy.asarray(rng.randn(2, 5))
         utt.verify_grad(f, [mval])
 
-    @dec.knownfailureif(True,"Complex grads not enabled, see #178")
+    @dec.knownfailureif(True, "Complex grads not enabled, see #178")
     def test_mul_mixed0(self):
 
         def f(a):
@@ -64,7 +65,7 @@ class TestRealImag(unittest.TestCase):
             return abs((ac)**2).sum()
 
         rng = numpy.random.RandomState(9333)
-        aval = numpy.asarray(rng.randn(2,5))
+        aval = numpy.asarray(rng.randn(2, 5))
         try:
             utt.verify_grad(f, [aval])
         except utt.verify_grad.E_grad, e:
@@ -72,7 +73,7 @@ class TestRealImag(unittest.TestCase):
             print e.analytic_grad
             raise
 
-    @dec.knownfailureif(True,"Complex grads not enabled, see #178")
+    @dec.knownfailureif(True, "Complex grads not enabled, see #178")
     def test_mul_mixed1(self):
 
         def f(a):
@@ -80,22 +81,23 @@ class TestRealImag(unittest.TestCase):
             return abs(ac).sum()
 
         rng = numpy.random.RandomState(9333)
-        aval = numpy.asarray(rng.randn(2,5))
+        aval = numpy.asarray(rng.randn(2, 5))
         try:
             utt.verify_grad(f, [aval])
         except utt.verify_grad.E_grad, e:
             print e.num_grad.gf
             print e.analytic_grad
             raise
-    @dec.knownfailureif(True,"Complex grads not enabled, see #178")
+
+    @dec.knownfailureif(True, "Complex grads not enabled, see #178")
     def test_mul_mixed(self):
 
-        def f(a,b):
+        def f(a, b):
             ac = complex(a[0], a[1])
             return abs((ac*b)**2).sum()
 
         rng = numpy.random.RandomState(9333)
-        aval = numpy.asarray(rng.randn(2,5))
+        aval = numpy.asarray(rng.randn(2, 5))
         bval = rng.randn(5)
         try:
             utt.verify_grad(f, [aval, bval])
@@ -104,22 +106,22 @@ class TestRealImag(unittest.TestCase):
             print e.analytic_grad
             raise
 
-    @dec.knownfailureif(True,"Complex grads not enabled, see #178")
+    @dec.knownfailureif(True, "Complex grads not enabled, see #178")
     def test_polar_grads(self):
         def f(m):
             c = complex_from_polar(abs(m[0]), m[1])
             return .5 * real(c) + .9 * imag(c)
 
         rng = numpy.random.RandomState(9333)
-        mval = numpy.asarray(rng.randn(2,5))
+        mval = numpy.asarray(rng.randn(2, 5))
         utt.verify_grad(f, [mval])
 
-    @dec.knownfailureif(True,"Complex grads not enabled, see #178")
+    @dec.knownfailureif(True, "Complex grads not enabled, see #178")
     def test_abs_grad(self):
         def f(m):
             c = complex(m[0], m[1])
             return .5 * abs(c)
 
         rng = numpy.random.RandomState(9333)
-        mval = numpy.asarray(rng.randn(2,5))
+        mval = numpy.asarray(rng.randn(2, 5))
         utt.verify_grad(f, [mval])