Merge pull request #1847 from Hengjean/ptp

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

@@ -5000,3 +5000,24 @@ def stacklists(arg):
         return stack(*map(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.
+
+    :param a : Input tensor.
+
+    :param axis : Axis along which to find the peaks. By default,
+                flatten the array.
+
+    :return : A new array holding the result.
+    """
+
+    a = as_tensor_variable(a)
+
+    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)
+        stacklists, DimShuffle, hessian, ptp)
 
 from theano.tests import unittest_tools as utt
 
@@ -6777,6 +6777,74 @@ 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):
+        """
+        Should return 0 for all scalar
+        """
+        x = scalar('x')
+        p = ptp(x)
+        f = theano.function([x], p)
+        self.assertTrue(f(rand() * 20000 - 10000) == 0)
+
+    def test_vector(self):
+
+        x = vector('x')
+        p = ptp(x, 0)
+        f = theano.function([x], p)
+
+        y = rand_ranged(-1000, 1000, [100])
+        result = f(y)
+        numpyResult = numpy.ptp(y, 0)
+
+        self.assertTrue(numpy.array_equal(result, numpyResult))
+
+    def test_matrix_first_axis(self):
+
+        x = matrix('x')
+        p = ptp(x, 1)
+        f = theano.function([x], p)
+
+        y = rand_ranged(-1000, 1000, [100, 100])
+        result = f(y)
+        numpyResult = numpy.ptp(y, 1)
+
+        self.assertTrue(numpy.array_equal(result, numpyResult))
+
+    def test_matrix_second_axis(self):
+        x = matrix('x')
+        p = ptp(x, 0)
+        f = theano.function([x], p)
+
+        y = rand_ranged(-1000, 1000, [100, 100])
+        result = f(y)
+        numpyResult = numpy.ptp(y, 0)
+
+        self.assertTrue(numpy.array_equal(result, numpyResult))
+
+    def test_matrix_neg_axis(self):
+        x = matrix('x')
+        p = ptp(x, -1)
+        f = theano.function([x], p)
+
+        y = rand_ranged(-1000, 1000, [100, 100])
+        result = f(y)
+        numpyResult = numpy.ptp(y, -1)
+
+        self.assertTrue(numpy.array_equal(result, numpyResult))
+
+    def test_matrix_no_axis(self):
+        x = matrix('x')
+        p = ptp(x)
+        f = theano.function([x], p)
+
+        y = rand_ranged(-1000, 1000, [100, 100])
+        result = f(y)
+        numpyResult = numpy.ptp(y)
+
+        self.assertTrue(numpy.array_equal(result, numpyResult))
+
 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."""