first set of checkins from the doc editor

1 files changed, 31 insertions, 12 deletions

diff --git a/numpy/core/numeric.py b/numpy/core/numeric.py
index 3ca2d988f..be10d5005 100644
--- a/numpy/core/numeric.py
+++ b/numpy/core/numeric.py
@@ -105,29 +105,43 @@ def zeros_like(a):
 
 def empty_like(a):
     """
-    Create a new array with the same shape and type as another.
+    Return a new array with the same shape and type as a given array.
 
     Parameters
     ----------
-    a : ndarray
-        Returned array will have same shape and type as `a`.
+    a : array_like
+        The shape and data-type of `a` define the parameters of the
+        returned array.
+
+    Returns
+    -------
+    out : ndarray
+        Array of random data with the same shape and type as `a`.
 
     See Also
     --------
-    zeros_like, ones_like, zeros, ones, empty
+    ones_like : Return an array of ones with shape and type of input.
+    zeros_like : Return an array of zeros with shape and type of input.
+    empty : Return a new uninitialized array.
+    ones : Return a new array setting values to one.
+    zeros : Return a new array setting values to zero.
 
     Notes
     -----
     This function does *not* initialize the returned array; to do that use
-    `zeros_like` or `ones_like` instead.
+    `zeros_like` or `ones_like` instead. It may be marginally faster than the
+    functions that do set the array values.
 
     Examples
     --------
-    >>> a = np.array([[1,2,3],[4,5,6]])
+    >>> a = ([1,2,3], [4,5,6])                         # a is array-like
     >>> np.empty_like(a)
+    array([[-1073741821, -1073741821,           3],    #random
+           [          0,           0, -1073741821]])
+    >>> a = np.array([[1., 2., 3.],[4.,5.,6.]])
     >>> np.empty_like(a)
-    array([[-1073741821, -1067702173,       65538],    #random data
-           [      25670,    23454291,       71800]])
+    array([[ -2.00000715e+000,   1.48219694e-323,  -2.00000572e+000], #random
+           [  4.38791518e-305,  -2.00000715e+000,   4.17269252e-309]])
 
     """
     if isinstance(a, ndarray):
@@ -1661,11 +1675,11 @@ def base_repr (number, base=2, padding=0):
     ----------
     number : scalar
         The value to convert. Only positive values are handled.
-    base : int
+    base : int, optional
         Convert `number` to the `base` number system. The valid range is 2-36,
         the default value is 2.
     padding : int, optional
-        Number of zeros padded on the left.
+        Number of zeros padded on the left. Default is 0 (no padding).
 
     Returns
     -------
@@ -1679,13 +1693,18 @@ def base_repr (number, base=2, padding=0):
 
     Examples
     --------
-    >>> np.base_repr(3, 5)
-    '3'
+    >>> np.base_repr(5)
+    '101'
     >>> np.base_repr(6, 5)
     '11'
     >>> np.base_repr(7, base=5, padding=3)
     '00012'
 
+    >>> np.base_repr(10, base=16)
+    'A'
+    >>> np.base_repr(32, base=16)
+    '20'
+
     """
     if number < 0:
         raise ValueError("negative numbers not handled in base_repr")