Wrap arctan from numpy, elemwise.

theano/scalar/basic.py

@@ -2075,6 +2075,25 @@ class Tan(UnaryScalarOp):
 tan = Tan(upgrade_to_float, name='tan')
 
 
+class Arctan(UnaryScalarOp):
+    def impl(self, x):
+        return numpy.arctan(x)
+
+    def grad(self, (x,), (gz,)):
+        if gz.type in complex_types:
+            raise NotImplementedError()
+        if x.type in float_types:
+            return gz / (numpy.cast[x.type](1) + sqr(x)),
+        else:
+            return None,
+
+    def c_code(self, node, name, (x,), (z,), sub):
+        if node.inputs[0].type in complex_types:
+            raise NotImplementedError('type not supported', type)
+        return "%(z)s = atan(%(x)s);" % locals()
+arctan = Arctan(upgrade_to_float, name='arctan')
+
+
 class Cosh(UnaryScalarOp):
     """
     cosh(x) = (exp(x) + exp(-x)) / 2

theano/tensor/basic.py

@@ -2585,6 +2585,10 @@ def arcsin(a):
 def tan(a):
     """tangent of a"""
 
+@_scal_elemwise_with_nfunc('arctan', 1, 1)
+def arctan(a):
+    """arctangent of a"""
+
 
 @_scal_elemwise_with_nfunc('cosh', 1, 1)
 def cosh(a):

theano/tensor/inplace.py

@@ -159,6 +159,10 @@ def arcsin_inplace(a):
 def tan_inplace(a):
     """tangent of `a` (inplace on `a`)"""
 
+@_scal_inplace
+def arctan_inplace(a):
+    """arctangent of `a` (inplace on `a`)"""
+
 @_scal_inplace
 def cosh_inplace(a):
     """hyperbolic cosine of `a` (inplace on `a`)"""

theano/tensor/tests/test_basic.py

@@ -1084,6 +1084,7 @@ if config.floatX=='float32':
 #We raise the relative tolerence for the grad as their is error in float32
 #This is probably caused by our way of computing the gradient error.
     tan_grad_rtol = 0.052
+
 TanTester = makeBroadcastTester(op = tensor.tan,
                                   expected = numpy.tan,
                                   good = dict(normal = (rand_ranged(-3.14, 3.14, (2, 3)),),
@@ -1101,6 +1102,21 @@ TanInplaceTester = makeBroadcastTester(op = inplace.tan_inplace,
                                          inplace = True)
 
 
+ArctanTester = makeBroadcastTester(op = tensor.tan,
+                                   expected = numpy.tan,
+                                   good = _good_broadcast_unary_wide,
+                                   grad = _grad_broadcast_unary_wide,
+                                   grad_rtol=tan_grad_rtol)
+
+
+ArctanInplaceTester = makeBroadcastTester(op = inplace.tan_inplace,
+                                          expected = numpy.tan,
+                                          good = _good_broadcast_unary_wide,
+                                          grad = _grad_broadcast_unary_wide,
+                                          grad_rtol=tan_grad_rtol,
+                                          inplace = True)
+
+
 CoshTester = makeBroadcastTester(op = tensor.cosh,
                                    expected = numpy.cosh,
                                    good = _good_broadcast_unary_normal,