formatted to pep8 and added doc

doc/library/tensor/basic.txt

@@ -966,6 +966,18 @@ Reductions
      * an *int* - computed along this axis
      * a *list of ints* - computed along these axes
 
+.. function:: ptp(x, axis = None)
+    
+    Range of values (maximum - minimum) along an axis.
+    The name of the function comes from the acronym for peak to peak.
+
+    :Parameter: *x* Input tensor.
+
+    :Parameter: *axis Axis along which to find the peaks. By default,
+                flatten the array.
+
+    :Returns: A new array holding the result.
+ 
 
 Indexing
 ========

theano/tensor/basic.py

@@ -5001,26 +5001,23 @@ def stacklists(arg):
     else:
         return arg
 
+
 def ptp(a, axis=None):
     """
     Range of values (maximum - minimum) along an axis.
 
-    The name of the function comes from the acronym for peak to peak.	
+    The name of the function comes from the acronym for peak to peak.
 
     :param a : Input tensor.
 
-    :param axis : Axis along which to find the peaks. By default, flatten the array.
+    :param axis : Axis along which to find the peaks. By default,
+                flatten the array.
 
-    :return : A new array holding the result, unless out was specified, in which case a reference to out is returned.
+    :return : A new array holding the result.
     """
-    
+
     a = as_tensor_variable(a)
-    
-    out = max (a, axis)-min(a, axis)
-   
-    return out
-    
-    
-    
-    
 
+    out = max(a, axis) - min(a, axis)
+
+    return out

theano/tensor/tests/test_basic.py

@@ -45,7 +45,7 @@ from theano.tensor import (_shared, wvector, bvector, autocast_float_as,
         dtensor3, SpecifyShape, Mean,
         itensor3, Tile, switch, Diagonal, Diag,
         nonzero, flatnonzero, nonzero_values,
-        stacklists, DimShuffle, hessian,ptp)
+        stacklists, DimShuffle, hessian, ptp)
 
 from theano.tests import unittest_tools as utt
 
@@ -6777,6 +6777,7 @@ def test_norm():
     f = theano.function([x], n)
     assert numpy.allclose(f([1, 1]), numpy.sqrt(2))
 
+
 class test_ptp(unittest.TestCase):
     def test_scalar(self):
         """
@@ -6785,54 +6786,55 @@ class test_ptp(unittest.TestCase):
         x = scalar('x')
         p = ptp(x)
         f = theano.function([x], p)
-        self.assertTrue(f(rand()*20000-10000)==0)
-        
+        self.assertTrue(f(rand() * 20000 - 10000) == 0)
+
     def test_vector(self):
-        
+
         x = vector('x')
-        p = ptp(x,0)
+        p = ptp(x, 0)
         f = theano.function([x], p)
-        
+
         y = rand_ranged(-1000, 1000, {100})
         result = f(y)
-        maxLessMin=[numpy.amax(y)-numpy.amin(y)]
-        
-        self.assertTrue(result==maxLessMin)
-    
+        maxLessMin = [numpy.amax(y) - numpy.amin(y)]
+
+        self.assertTrue(result == maxLessMin)
+
     def test_matrix_first_axis(self):
-        
+
         x = matrix('x')
-        p = ptp(x,1)
+        p = ptp(x, 1)
         f = theano.function([x], p)
-        
-        y = rand_ranged(-1000, 1000, [100,100])
+
+        y = rand_ranged(-1000, 1000, [100, 100])
         result = f(y)
-        maxLessMin=[numpy.amax(i)-numpy.amin(i) for i in y]
-        
-        self.assertTrue(numpy.array_equal(result,maxLessMin))
-        
+        maxLessMin = [numpy.amax(i) - numpy.amin(i) for i in y]
+
+        self.assertTrue(numpy.array_equal(result, maxLessMin))
+
     def test_matrix_second_axis(self):
         x = matrix('x')
-        p = ptp(x,0)
+        p = ptp(x, 0)
         f = theano.function([x], p)
-        
-        y = rand_ranged(-1000, 1000, [100,100])
+
+        y = rand_ranged(-1000, 1000, [100, 100])
         result = f(y)
-        y = numpy.swapaxes(y, 0,1)
-        maxLessMin=[numpy.amax(i)-numpy.amin(i) for i in y]
-        
-        self.assertTrue(numpy.array_equal(result,maxLessMin))
-        
+        y = numpy.swapaxes(y, 0, 1)
+        maxLessMin = [numpy.amax(i) - numpy.amin(i) for i in y]
+
+        self.assertTrue(numpy.array_equal(result, maxLessMin))
+
     def test_matrix_neg_axis(self):
         x = matrix('x')
-        p = ptp(x,-1)
+        p = ptp(x, -1)
         f = theano.function([x], p)
-        
-        y = rand_ranged(-1000, 1000, [100,100])
+
+        y = rand_ranged(-1000, 1000, [100, 100])
         result = f(y)
-        maxLessMin=[numpy.amax(i)-numpy.amin(i) for i in y]
-        
-	
+        maxLessMin = [numpy.amax(i) - numpy.amin(i) for i in y]
+
+        self.assertTrue(numpy.array_equal(result, maxLessMin))
+
 if __name__ == '__main__':
 
     t = TestInferShape('setUp')

theano/tensor/var.py

@@ -552,6 +552,11 @@ class _tensor_py_operators:
     def cumprod(self, axis=None):
         return theano.tensor.extra_ops.cumprod(self, axis)
 
+    def ptp(self, axis=None):
+        """see 'theano.tensor.ptp'"""
+
+        return theano.tensor.ptp(self, axis)
+
 
 class TensorVariable(_tensor_py_operators, Variable):
     """Subclass to add the tensor operators to the basic `Variable` class."""