DOC: merge wiki edits for module core.

4 files changed, 19 insertions, 9 deletions

diff --git a/numpy/core/fromnumeric.py b/numpy/core/fromnumeric.py
index b255e89af..c142cd1ed 100644
--- a/numpy/core/fromnumeric.py
+++ b/numpy/core/fromnumeric.py
@@ -2371,7 +2371,7 @@ def std(a, axis=None, dtype=None, out=None, ddof=0):
     The standard deviation is the square root of the average of the squared
     deviations from the mean, i.e., ``std = sqrt(mean(abs(x - x.mean())**2))``.
 
-    The mean is normally calculated as ``x.sum() / N``, where
+    The average squared deviation is normally calculated as ``x.sum() / N``, where
     ``N = len(x)``.  If, however, `ddof` is specified, the divisor ``N - ddof``
     is used instead. In standard statistical practice, ``ddof=1`` provides an
     unbiased estimator of the variance of the infinite population. ``ddof=0``
diff --git a/numpy/core/memmap.py b/numpy/core/memmap.py
index 83de1cf0a..71f5de93c 100644
--- a/numpy/core/memmap.py
+++ b/numpy/core/memmap.py
@@ -61,6 +61,16 @@ class memmap(ndarray):
         Fortran (column-major).  This only has an effect if the shape is
         greater than 1-D.  The default order is 'C'.
 
+    Attributes
+    ----------
+    filename : str
+        Path to the mapped file.
+    offset : int
+        Offset position in the file.
+    mode : str
+        File mode.
+
+
     Methods
     -------
     close
diff --git a/numpy/core/numeric.py b/numpy/core/numeric.py
index fba6512b2..eb028874a 100644
--- a/numpy/core/numeric.py
+++ b/numpy/core/numeric.py
@@ -35,10 +35,10 @@ if sys.version_info[0] < 3:
 
 class ComplexWarning(RuntimeWarning):
     """
-    Warning that is raised when casting complex numbers to real.
+    The warning raised when casting a complex dtype to a real dtype.
 
-    Casting a complex number to real discards its imaginary part, and
-    this behavior may not be what is intended in all cases.
+    As implemented, casting a complex number to a real discards its imaginary
+    part, but this behavior may not be what the user actually wants.
 
     """
     pass
@@ -743,15 +743,15 @@ def convolve(a,v,mode='full'):
 
     See Also
     --------
-    scipy.signal.fftconv : Convolve two arrays using the Fast Fourier
-                           Transform.
+    scipy.signal.fftconvolve : Convolve two arrays using the Fast Fourier
+                               Transform.
     scipy.linalg.toeplitz : Used to construct the convolution operator.
 
     Notes
     -----
     The discrete convolution operation is defined as
 
-    .. math:: (f * g)[n] = \\sum_{m = -\\infty}^{\\infty} f[m] f[n - m]
+    .. math:: (f * g)[n] = \\sum_{m = -\\infty}^{\\infty} f[m] g[n - m]
 
     It can be shown that a convolution :math:`x(t) * y(t)` in time/space
     is equivalent to the multiplication :math:`X(f) Y(f)` in the Fourier
diff --git a/numpy/core/records.py b/numpy/core/records.py
index 2afb89f81..dc1dfad68 100644
--- a/numpy/core/records.py
+++ b/numpy/core/records.py
@@ -285,7 +285,7 @@ class recarray(ndarray):
     """
     Construct an ndarray that allows field access using attributes.
 
-    Arrays may have a data-types containing fields, analagous
+    Arrays may have a data-types containing fields, analogous
     to columns in a spread sheet.  An example is ``[(x, int), (y, float)]``,
     where each entry in the array is a pair of ``(int, float)``.  Normally,
     these attributes are accessed using dictionary lookups such as ``arr['x']``
@@ -346,7 +346,7 @@ class recarray(ndarray):
     Notes
     -----
     This constructor can be compared to ``empty``: it creates a new record
-    array but does not fill it with data.  To create a reccord array from data,
+    array but does not fill it with data.  To create a record array from data,
     use one of the following methods:
 
     1. Create a standard ndarray and convert it to a record array,