Added .argmin(), .argmax(), .clip(), .conj(), .repeat(), .trace(),

theano/tensor/basic.py

@@ -1758,6 +1758,10 @@ class _tensor_py_operators:
         """See `theano.tensor.var`"""
         return var(self, axis, keepdims=keepdims)
 
+    def std(self, axis=None, keepdims=False):
+        """See `theano.tensor.std`"""
+        return std(self, axis, keepdims=keepdims)
+
     def min(self, axis=None, keepdims=False):
         """See `theano.tensor.min`"""
         return min(self, axis, keepdims=keepdims)
@@ -1766,6 +1770,35 @@ class _tensor_py_operators:
         """See `theano.tensor.max`"""
         return max(self, axis, keepdims=keepdims)
 
+    def argmin(self, axis=None, keepdims=False):
+        """See `theano.tensor.argmin`"""
+        return argmin(self, axis, keepdims=keepdims)
+
+    def argmax(self, axis=None, keepdims=False):
+        """See `theano.tensor.argmax`"""
+        return argmax(self, axis, keepdims=keepdims)
+
+    def clip(self, a_min, a_max):
+        "Clip (limit) the values in an array."
+        return clip(self, a_min, a_max)
+
+    def conj(self):
+        """See `theano.tensor.conj`"""
+        return conj(self)
+
+    def repeat(self, repeats, axis=None):
+        """See `theano.tensor.repeat`"""
+        from theano.tensor.extra_ops import repeat
+        return repeat(self, repeats, axis)
+
+    def round(self, mode="half_away_from_zero"):
+        """See `theano.tensor.round`"""
+        return round(self, mode)
+
+    def trace(self):
+        from theano.sandbox.linalg import trace
+        return trace(self)
+
     # TO TRUMP NUMPY OPERATORS
     __array_priority__ = 1000
 
@@ -2971,12 +3004,12 @@ def psi(a):
 @_scal_elemwise_with_nfunc('real', 1, -1)
 def real(z):
     """Return real component of complex-valued tensor `z`"""
-
+_tensor_py_operators.real = property(real)
 
 @_scal_elemwise_with_nfunc('imag', 1, -1)
 def imag(z):
     """Return imaginary component of complex-valued tensor `z`"""
-
+_tensor_py_operators.imag = property(imag)
 
 @_scal_elemwise_with_nfunc('angle', 1, -1)
 def angle(z):

theano/tensor/tests/test_basic.py

@@ -7006,6 +7006,23 @@ class TestTensorInstanceMethods(unittest.TestCase):
         self.vars = matrices('X', 'Y')
         self.vals = [rand(2,2),rand(2,2)]
 
+    def test_argmin(self):
+        X, _ = self.vars
+        x, _ = self.vals
+        self.assertTrue(numpy.all(X.argmin().eval({X: x}) == x.argmin()))
+
+    def test_argmax(self):
+        X, _ = self.vars
+        x, _ = self.vals
+        self.assertTrue(numpy.all(X.argmax().eval({X: x}) == x.argmax()))
+
+    def test_dot(self):
+        X, Y = self.vars
+        x, y = self.vals
+        Z = X.clip(0.5 - Y, 0.5 + Y)
+        z = x.clip(0.5 - y, 0.5 + y)
+        self.assertTrue(numpy.all(Z.eval({X: x, Y: y}) == z))
+
     def test_dot(self):
         X, Y = self.vars
         x, y = self.vals
@@ -7013,7 +7030,43 @@ class TestTensorInstanceMethods(unittest.TestCase):
         Z = X.dot(Y)
         z = x.dot(y)
         self.assertTrue(numpy.all(x.dot(z) == X.dot(Z).eval({X: x, Z: z})))
-        
+
+    def test_real_imag(self):
+        X, Y = self.vars
+        x, y = self.vals
+        Z = X + Y * 1j
+        z = x + y * 1j
+        self.assertTrue(numpy.all(Z.real.eval({Z: z}) == x))
+        self.assertTrue(numpy.all(Z.imag.eval({Z: z}) == y))
+
+    def test_conj(self):
+        X, Y = self.vars
+        x, y = self.vals
+        Z = X + Y * 1j
+        z = x + y * 1j
+        self.assertTrue(numpy.all(Z.conj().eval({Z: z}) == z.conj()))
+
+    def test_round(self):
+        X, _ = self.vars
+        x, _ = self.vals
+        self.assertTrue(numpy.all(X.round().eval({X: x}) == x.round()))
+
+    def test_std(self):
+        X, _ = self.vars
+        x, _ = self.vals
+        self.assertTrue(numpy.all(X.std().eval({X: x}) == x.std()))
+
+    def test_repeat(self):
+        X, _ = self.vars
+        x, _ = self.vals
+        self.assertTrue(numpy.all(X.repeat(2).eval({X: x}) == x.repeat(2)))
+
+    def test_trace(self):
+        X, _ = self.vars
+        x, _ = self.vals
+        self.assertTrue(numpy.all(X.trace().eval({X: x}) == x.trace()))
+
+
 if __name__ == '__main__':
 
     t = TestInferShape('setUp')