DOC: merge wiki edits. Add percentile to statistics routines (ML sugg…

…estion).

doc/source/reference/index.rst

@@ -7,6 +7,7 @@ NumPy Reference
 :Release: |version|
 :Date: |today|
 
+
 .. module:: numpy
 
 This reference manual details functions, modules, and objects

doc/source/reference/routines.statistics.rst

@@ -4,8 +4,8 @@ Statistics
 .. currentmodule:: numpy
 
 
-Extremal values
----------------
+Order statistics
+----------------
 
 .. autosummary::
    :toctree: generated/
@@ -15,6 +15,7 @@ Extremal values
    nanmin
    nanmax
    ptp
+   percentile
 
 Averages and variances
 ----------------------

numpy/add_newdocs.py

@@ -1822,10 +1822,21 @@ def luf(lamdaexpr, *args, **kwargs):
 
     """)
 
-add_newdoc('numpy.core.multiarray','newbuffer',
-    """newbuffer(size)
+add_newdoc('numpy.core.multiarray', 'newbuffer',
+    """
+    newbuffer(size)
+
+    Return a new uninitialized buffer object.
 
-    Return a new uninitialized buffer object of size bytes
+    Parameters
+    ----------
+    size : int
+        Size in bytes of returned buffer object.
+
+    Returns
+    -------
+    newbuffer : buffer object
+        Returned, uninitialized buffer object of `size` bytes.
 
     """)
 
@@ -3717,8 +3728,9 @@ def luf(lamdaexpr, *args, **kwargs):
     """
     copyto(dst, src, casting='same_kind', where=None, preservena=False)
 
-    Copies values from `src` into `dst`, broadcasting as necessary.
-    Raises a TypeError if the casting rule is violated, and if
+    Copies values from one array to another, broadcasting as necessary.
+
+    Raises a TypeError if the `casting` rule is violated, and if
     `where` is provided, it selects which elements to copy.
 
     .. versionadded:: 1.7.0

numpy/core/numeric.py

@@ -696,9 +696,10 @@ def correlate(a, v, mode='valid', old_behavior=False):
         Refer to the `convolve` docstring.  Note that the default
         is `valid`, unlike `convolve`, which uses `full`.
     old_behavior : bool
-        If True, uses the old behavior from Numeric, (correlate(a,v) == correlate(v,
-        a), and the conjugate is not taken for complex arrays). If False, uses
-        the conventional signal processing definition (see note).
+        If True, uses the old behavior from Numeric,
+        (correlate(a,v) == correlate(v,a), and the conjugate is not taken
+        for complex arrays). If False, uses the conventional signal
+        processing definition.
 
     See Also
     --------
@@ -2344,7 +2345,14 @@ def setbufsize(size):
     return old
 
 def getbufsize():
-    """Return the size of the buffer used in ufuncs.
+    """
+    Return the size of the buffer used in ufuncs.
+
+    Returns
+    -------
+    getbufsize : int
+        Size of ufunc buffer in bytes.
+
     """
     return umath.geterrobj()[0]
 

numpy/core/shape_base.py

@@ -12,7 +12,7 @@ def atleast_1d(*arys):
 
     Parameters
     ----------
-    array1, array2, ... : array_like
+    arys1, arys2, ... : array_like
         One or more input arrays.
 
     Returns
@@ -61,7 +61,7 @@ def atleast_2d(*arys):
 
     Parameters
     ----------
-    array1, array2, ... : array_like
+    arys1, arys2, ... : array_like
         One or more array-like sequences.  Non-array inputs are converted
         to arrays.  Arrays that already have two or more dimensions are
         preserved.
@@ -113,7 +113,7 @@ def atleast_3d(*arys):
 
     Parameters
     ----------
-    array1, array2, ... : array_like
+    arys1, arys2, ... : array_like
         One or more array-like sequences.  Non-array inputs are converted to
         arrays.  Arrays that already have three or more dimensions are
         preserved.

numpy/lib/function_base.py

@@ -1316,9 +1316,10 @@ def place(arr, mask, vals):
     """
     Change elements of an array based on conditional and input values.
 
-    Similar to ``np.copyto(arr, vals, where=mask)``, the difference is that `place`
-    uses the first N elements of `vals`, where N is the number of True values
-    in `mask`, while `copyto` uses the elements where `mask` is True.
+    Similar to ``np.copyto(arr, vals, where=mask)``, the difference is that
+    `place` uses the first N elements of `vals`, where N is the number of
+    True values in `mask`, while `copyto` uses the elements where `mask`
+    is True.
 
     Note that `extract` does the exact opposite of `place`.
 

numpy/lib/npyio.py

@@ -470,8 +470,7 @@ def savez(file, *args, **kwds):
     --------
     save : Save a single array to a binary file in NumPy format.
     savetxt : Save an array to a file as plain text.
-    numpy.savez_compressed : Save several arrays into a compressed .npz file
-    format
+    savez_compressed : Save several arrays into a compressed .npz file format
 
     Notes
     -----

numpy/random/mtrand/mtrand.pyx

@@ -2178,13 +2178,13 @@ cdef class RandomState:
 
         References
         ----------
-        ..[1] NIST/SEMATECH e-Handbook of Statistical Methods, "Cauchy
+        .. [1] NIST/SEMATECH e-Handbook of Statistical Methods, "Cauchy
               Distribution",
               http://www.itl.nist.gov/div898/handbook/eda/section3/eda3663.htm
-        ..[2] Weisstein, Eric W. "Cauchy Distribution." From MathWorld--A
+        .. [2] Weisstein, Eric W. "Cauchy Distribution." From MathWorld--A
               Wolfram Web Resource.
               http://mathworld.wolfram.com/CauchyDistribution.html
-        ..[3] Wikipedia, "Cauchy distribution"
+        .. [3] Wikipedia, "Cauchy distribution"
               http://en.wikipedia.org/wiki/Cauchy_distribution
 
         Examples
@@ -2516,10 +2516,10 @@ cdef class RandomState:
 
         See Also
         --------
-        scipy.stats.distributions.weibull : probability density function,
-            distribution or cumulative density function, etc.
-
-        gumbel, scipy.stats.distributions.genextreme
+        scipy.stats.distributions.weibull_max
+        scipy.stats.distributions.weibull_min
+        scipy.stats.distributions.genextreme
+        gumbel
 
         Notes
         -----
@@ -3159,9 +3159,9 @@ cdef class RandomState:
 
         References
         ----------
-        ..[1] Brighton Webs Ltd., Rayleigh Distribution,
+        .. [1] Brighton Webs Ltd., Rayleigh Distribution,
               http://www.brighton-webs.co.uk/distributions/rayleigh.asp
-        ..[2] Wikipedia, "Rayleigh distribution"
+        .. [2] Wikipedia, "Rayleigh distribution"
               http://en.wikipedia.org/wiki/Rayleigh_distribution
 
         Examples
@@ -3247,12 +3247,12 @@ cdef class RandomState:
 
         References
         ----------
-        ..[1] Brighton Webs Ltd., Wald Distribution,
+        .. [1] Brighton Webs Ltd., Wald Distribution,
               http://www.brighton-webs.co.uk/distributions/wald.asp
-        ..[2] Chhikara, Raj S., and Folks, J. Leroy, "The Inverse Gaussian
+        .. [2] Chhikara, Raj S., and Folks, J. Leroy, "The Inverse Gaussian
               Distribution: Theory : Methodology, and Applications", CRC Press,
               1988.
-        ..[3] Wikipedia, "Wald distribution"
+        .. [3] Wikipedia, "Wald distribution"
               http://en.wikipedia.org/wiki/Wald_distribution
 
         Examples
@@ -3331,7 +3331,7 @@ cdef class RandomState:
 
         References
         ----------
-        ..[1] Wikipedia, "Triangular distribution"
+        .. [1] Wikipedia, "Triangular distribution"
               http://en.wikipedia.org/wiki/Triangular_distribution
 
         Examples

numpy/testing/nosetester.py

@@ -119,11 +119,12 @@ class NoseTester(object):
 
     Notes
     -----
-    The default for `raise_warnings` is ``(DeprecationWarning, RuntimeWarning)``
-    for the master branch of NumPy, and ``()`` for maintenance branches and
-    released versions.  The purpose of this switching behavior is to catch as
-    many warnings as possible during development, but not give problems for
-    packaging of released versions.
+    The default for `raise_warnings` is
+    ``(DeprecationWarning, RuntimeWarning)`` for the master branch of NumPy,
+    and ``()`` for maintenance branches and released versions.  The purpose
+    of this switching behavior is to catch as many warnings as possible
+    during development, but not give problems for packaging of released
+    versions.
 
     """
     # Stuff to exclude from tests. These are from numpy.distutils