summaryrefslogtreecommitdiff
path: root/numpy
diff options
context:
space:
mode:
Diffstat (limited to 'numpy')
-rw-r--r--numpy/core/_add_newdocs.py26
-rw-r--r--numpy/core/_internal.py2
-rw-r--r--numpy/core/arrayprint.py2
-rw-r--r--numpy/core/code_generators/ufunc_docstrings.py4
-rw-r--r--numpy/core/defchararray.py10
-rw-r--r--numpy/core/fromnumeric.py50
-rw-r--r--numpy/core/numeric.py2
-rw-r--r--numpy/core/shape_base.py2
-rw-r--r--numpy/lib/function_base.py2
-rw-r--r--numpy/lib/nanfunctions.py30
-rw-r--r--numpy/ma/core.py30
-rw-r--r--numpy/ma/extras.py2
-rw-r--r--numpy/matrixlib/defmatrix.py2
13 files changed, 82 insertions, 82 deletions
diff --git a/numpy/core/_add_newdocs.py b/numpy/core/_add_newdocs.py
index dbe3d226f..b60edd1df 100644
--- a/numpy/core/_add_newdocs.py
+++ b/numpy/core/_add_newdocs.py
@@ -1326,9 +1326,9 @@ add_newdoc('numpy.core.multiarray', 'arange',
See Also
--------
- linspace : Evenly spaced numbers with careful handling of endpoints.
- ogrid: Arrays of evenly spaced numbers in N-dimensions.
- mgrid: Grid-shaped arrays of evenly spaced numbers in N-dimensions.
+ numpy.linspace : Evenly spaced numbers with careful handling of endpoints.
+ numpy.ogrid: Arrays of evenly spaced numbers in N-dimensions.
+ numpy.mgrid: Grid-shaped arrays of evenly spaced numbers in N-dimensions.
Examples
--------
@@ -3706,10 +3706,10 @@ add_newdoc('numpy.core.multiarray', 'ndarray', ('sort',
See Also
--------
numpy.sort : Return a sorted copy of an array.
- argsort : Indirect sort.
- lexsort : Indirect stable sort on multiple keys.
- searchsorted : Find elements in sorted array.
- partition: Partial sort.
+ numpy.argsort : Indirect sort.
+ numpy.lexsort : Indirect stable sort on multiple keys.
+ numpy.searchsorted : Find elements in sorted array.
+ numpy.partition: Partial sort.
Notes
-----
@@ -4497,7 +4497,7 @@ add_newdoc('numpy.core', 'ufunc',
Alternate array object(s) in which to put the result; if provided, it
must have a shape that the inputs broadcast to. A tuple of arrays
(possible only as a keyword argument) must have length equal to the
- number of outputs; use `None` for uninitialized outputs to be
+ number of outputs; use None for uninitialized outputs to be
allocated by the ufunc.
where : array_like, optional
This condition is broadcast over the input. At locations where the
@@ -4691,7 +4691,7 @@ add_newdoc('numpy.core', 'ufunc', ('signature',
-----
Generalized ufuncs are used internally in many linalg functions, and in
the testing suite; the examples below are taken from these.
- For ufuncs that operate on scalars, the signature is `None`, which is
+ For ufuncs that operate on scalars, the signature is None, which is
equivalent to '()' for every argument.
Examples
@@ -4742,7 +4742,7 @@ add_newdoc('numpy.core', 'ufunc', ('reduce',
.. versionadded:: 1.7.0
- If this is `None`, a reduction is performed over all the axes.
+ If this is None, a reduction is performed over all the axes.
If this is a tuple of ints, a reduction is performed on multiple
axes, instead of a single axis or all the axes as before.
@@ -4755,7 +4755,7 @@ add_newdoc('numpy.core', 'ufunc', ('reduce',
to the data-type of the output array if this is provided, or
the data-type of the input array if no output array is provided.
out : ndarray, None, or tuple of ndarray and None, optional
- A location into which the result is stored. If not provided or `None`,
+ A location into which the result is stored. If not provided or None,
a freshly-allocated array is returned. For consistency with
``ufunc.__call__``, if given as a keyword, this may be wrapped in a
1-element tuple.
@@ -4872,7 +4872,7 @@ add_newdoc('numpy.core', 'ufunc', ('accumulate',
to the data-type of the output array if such is provided, or the
the data-type of the input array if no output array is provided.
out : ndarray, None, or tuple of ndarray and None, optional
- A location into which the result is stored. If not provided or `None`,
+ A location into which the result is stored. If not provided or None,
a freshly-allocated array is returned. For consistency with
``ufunc.__call__``, if given as a keyword, this may be wrapped in a
1-element tuple.
@@ -4954,7 +4954,7 @@ add_newdoc('numpy.core', 'ufunc', ('reduceat',
to the data type of the output array if this is provided, or
the data type of the input array if no output array is provided.
out : ndarray, None, or tuple of ndarray and None, optional
- A location into which the result is stored. If not provided or `None`,
+ A location into which the result is stored. If not provided or None,
a freshly-allocated array is returned. For consistency with
``ufunc.__call__``, if given as a keyword, this may be wrapped in a
1-element tuple.
diff --git a/numpy/core/_internal.py b/numpy/core/_internal.py
index 5fd643505..05e401e0b 100644
--- a/numpy/core/_internal.py
+++ b/numpy/core/_internal.py
@@ -313,7 +313,7 @@ class _ctypes(object):
crashing. User Beware! The value of this attribute is exactly the same
as ``self._array_interface_['data'][0]``.
- Note that unlike `data_as`, a reference will not be kept to the array:
+ Note that unlike ``data_as``, a reference will not be kept to the array:
code like ``ctypes.c_void_p((a + b).ctypes.data)`` will result in a
pointer to a deallocated array, and should be spelt
``(a + b).ctypes.data_as(ctypes.c_void_p)``
diff --git a/numpy/core/arrayprint.py b/numpy/core/arrayprint.py
index 8a7626d9d..401018015 100644
--- a/numpy/core/arrayprint.py
+++ b/numpy/core/arrayprint.py
@@ -111,7 +111,7 @@ def set_printoptions(precision=None, threshold=None, edgeitems=None,
----------
precision : int or None, optional
Number of digits of precision for floating point output (default 8).
- May be `None` if `floatmode` is not `fixed`, to print as many digits as
+ May be None if `floatmode` is not `fixed`, to print as many digits as
necessary to uniquely specify the value.
threshold : int, optional
Total number of array elements which trigger summarization
diff --git a/numpy/core/code_generators/ufunc_docstrings.py b/numpy/core/code_generators/ufunc_docstrings.py
index 1ac477b54..4dec73505 100644
--- a/numpy/core/code_generators/ufunc_docstrings.py
+++ b/numpy/core/code_generators/ufunc_docstrings.py
@@ -22,7 +22,7 @@ subst = {
'PARAMS': textwrap.dedent("""
out : ndarray, None, or tuple of ndarray and None, optional
A location into which the result is stored. If provided, it must have
- a shape that the inputs broadcast to. If not provided or `None`,
+ a shape that the inputs broadcast to. If not provided or None,
a freshly-allocated array is returned. A tuple (possible only as a
keyword argument) must have length equal to the number of outputs.
where : array_like, optional
@@ -2596,7 +2596,7 @@ add_newdoc('numpy.core.umath', 'matmul',
out : ndarray, optional
A location into which the result is stored. If provided, it must have
a shape that matches the signature `(n,k),(k,m)->(n,m)`. If not
- provided or `None`, a freshly-allocated array is returned.
+ provided or None, a freshly-allocated array is returned.
**kwargs
For other keyword-only arguments, see the
:ref:`ufunc docs <ufuncs.kwargs>`.
diff --git a/numpy/core/defchararray.py b/numpy/core/defchararray.py
index a941c5b81..2d89d6fe0 100644
--- a/numpy/core/defchararray.py
+++ b/numpy/core/defchararray.py
@@ -82,7 +82,7 @@ def _clean_args(*args):
Many of the Python string operations that have optional arguments
do not use 'None' to indicate a default value. In these cases,
- we need to remove all `None` arguments, and those following them.
+ we need to remove all None arguments, and those following them.
"""
newargs = []
for chk in args:
@@ -1333,7 +1333,7 @@ def rsplit(a, sep=None, maxsplit=None):
a : array_like of str or unicode
sep : str or unicode, optional
- If `sep` is not specified or `None`, any whitespace string
+ If `sep` is not specified or None, any whitespace string
is a separator.
maxsplit : int, optional
If `maxsplit` is given, at most `maxsplit` splits are done,
@@ -1417,7 +1417,7 @@ def split(a, sep=None, maxsplit=None):
a : array_like of str or unicode
sep : str or unicode, optional
- If `sep` is not specified or `None`, any whitespace string is a
+ If `sep` is not specified or None, any whitespace string is a
separator.
maxsplit : int, optional
@@ -2659,7 +2659,7 @@ def array(obj, itemsize=None, copy=True, unicode=None, order=None):
unicode : bool, optional
When true, the resulting `chararray` can contain Unicode
characters, when false only 8-bit characters. If unicode is
- `None` and `obj` is one of the following:
+ None and `obj` is one of the following:
- a `chararray`,
- an ndarray of type `str` or `unicode`
@@ -2799,7 +2799,7 @@ def asarray(obj, itemsize=None, unicode=None, order=None):
unicode : bool, optional
When true, the resulting `chararray` can contain Unicode
characters, when false only 8-bit characters. If unicode is
- `None` and `obj` is one of the following:
+ None and `obj` is one of the following:
- a `chararray`,
- an ndarray of type `str` or 'unicode`
diff --git a/numpy/core/fromnumeric.py b/numpy/core/fromnumeric.py
index 6c0b9cde9..5f7716455 100644
--- a/numpy/core/fromnumeric.py
+++ b/numpy/core/fromnumeric.py
@@ -1409,7 +1409,7 @@ def squeeze(a, axis=None):
Raises
------
ValueError
- If `axis` is not `None`, and an axis being squeezed is not of length 1
+ If `axis` is not None, and an axis being squeezed is not of length 1
See Also
--------
@@ -1945,7 +1945,7 @@ def compress(condition, a, axis=None, out=None):
take, choose, diag, diagonal, select
ndarray.compress : Equivalent method in ndarray
np.extract: Equivalent method when working on 1-D arrays
- numpy.doc.ufuncs : Section "Output arguments"
+ ufuncs-output-type
Examples
--------
@@ -1995,14 +1995,14 @@ def clip(a, a_min, a_max, out=None, **kwargs):
----------
a : array_like
Array containing elements to clip.
- a_min : scalar or array_like or `None`
- Minimum value. If `None`, clipping is not performed on lower
+ a_min : scalar or array_like or None
+ Minimum value. If None, clipping is not performed on lower
interval edge. Not more than one of `a_min` and `a_max` may be
- `None`.
- a_max : scalar or array_like or `None`
- Maximum value. If `None`, clipping is not performed on upper
+ None.
+ a_max : scalar or array_like or None
+ Maximum value. If None, clipping is not performed on upper
interval edge. Not more than one of `a_min` and `a_max` may be
- `None`. If `a_min` or `a_max` are array_like, then the three
+ None. If `a_min` or `a_max` are array_like, then the three
arrays will be broadcasted to match their shapes.
out : ndarray, optional
The results will be placed in this array. It may be the input
@@ -2023,7 +2023,7 @@ def clip(a, a_min, a_max, out=None, **kwargs):
See Also
--------
- numpy.doc.ufuncs : Section "Output arguments"
+ ufuncs-output-type
Examples
--------
@@ -2206,7 +2206,7 @@ def any(a, axis=None, out=None, keepdims=np._NoValue):
Input array or object that can be converted to an array.
axis : None or int or tuple of ints, optional
Axis or axes along which a logical OR reduction is performed.
- The default (`axis` = `None`) is to perform a logical OR over all
+ The default (``axis=None``) is to perform a logical OR over all
the dimensions of the input array. `axis` may be negative, in
which case it counts from the last to the first axis.
@@ -2219,7 +2219,7 @@ def any(a, axis=None, out=None, keepdims=np._NoValue):
the same shape as the expected output and its type is preserved
(e.g., if it is of type float, then it will remain so, returning
1.0 for True and 0.0 for False, regardless of the type of `a`).
- See `doc.ufuncs` (Section "Output arguments") for details.
+ See `ufuncs-output-type` for more details.
keepdims : bool, optional
If this is set to True, the axes which are reduced are left
@@ -2292,7 +2292,7 @@ def all(a, axis=None, out=None, keepdims=np._NoValue):
Input array or object that can be converted to an array.
axis : None or int or tuple of ints, optional
Axis or axes along which a logical AND reduction is performed.
- The default (`axis` = `None`) is to perform a logical AND over all
+ The default (``axis=None``) is to perform a logical AND over all
the dimensions of the input array. `axis` may be negative, in
which case it counts from the last to the first axis.
@@ -2304,8 +2304,8 @@ def all(a, axis=None, out=None, keepdims=np._NoValue):
Alternate output array in which to place the result.
It must have the same shape as the expected output and its
type is preserved (e.g., if ``dtype(out)`` is float, the result
- will consist of 0.0's and 1.0's). See `doc.ufuncs` (Section
- "Output arguments") for more details.
+ will consist of 0.0's and 1.0's). See `ufuncs-output-type` for more
+ details.
keepdims : bool, optional
If this is set to True, the axes which are reduced are left
@@ -2383,8 +2383,8 @@ def cumsum(a, axis=None, dtype=None, out=None):
out : ndarray, optional
Alternative output array in which to place the result. It must
have the same shape and buffer length as the expected output
- but the type will be cast if necessary. See `doc.ufuncs`
- (Section "Output arguments") for more details.
+ but the type will be cast if necessary. See `ufuncs-output-type` for
+ more details.
Returns
-------
@@ -2529,7 +2529,7 @@ def amax(a, axis=None, out=None, keepdims=np._NoValue, initial=np._NoValue,
out : ndarray, optional
Alternative output array in which to place the result. Must
be of the same shape and buffer length as the expected output.
- See `doc.ufuncs` (Section "Output arguments") for more details.
+ See `ufuncs-output-type` for more details.
keepdims : bool, optional
If this is set to True, the axes which are reduced are left
@@ -2654,7 +2654,7 @@ def amin(a, axis=None, out=None, keepdims=np._NoValue, initial=np._NoValue,
out : ndarray, optional
Alternative output array in which to place the result. Must
be of the same shape and buffer length as the expected output.
- See `doc.ufuncs` (Section "Output arguments") for more details.
+ See `ufuncs-output-type` for more details.
keepdims : bool, optional
If this is set to True, the axes which are reduced are left
@@ -2861,7 +2861,7 @@ def prod(a, axis=None, dtype=None, out=None, keepdims=np._NoValue,
See Also
--------
ndarray.prod : equivalent method
- numpy.doc.ufuncs : Section "Output arguments"
+ ufuncs-output-type
Notes
-----
@@ -2957,7 +2957,7 @@ def cumprod(a, axis=None, dtype=None, out=None):
See Also
--------
- numpy.doc.ufuncs : Section "Output arguments"
+ ufuncs-output-type
Notes
-----
@@ -3103,8 +3103,8 @@ def around(a, decimals=0, out=None):
out : ndarray, optional
Alternative output array in which to place the result. It must have
the same shape as the expected output, but the type of the output
- values will be cast if necessary. See `doc.ufuncs` (Section
- "Output arguments") for details.
+ values will be cast if necessary. See `ufuncs-output-type` for more
+ details.
Returns
-------
@@ -3218,7 +3218,7 @@ def mean(a, axis=None, dtype=None, out=None, keepdims=np._NoValue):
Alternate output array in which to place the result. The default
is ``None``; if provided, it must have the same shape as the
expected output, but the type will be cast if necessary.
- See `doc.ufuncs` for details.
+ See `ufuncs-output-type` for more details.
keepdims : bool, optional
If this is set to True, the axes which are reduced are left
@@ -3353,7 +3353,7 @@ def std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=np._NoValue):
See Also
--------
var, mean, nanmean, nanstd, nanvar
- numpy.doc.ufuncs : Section "Output arguments"
+ ufuncs-output-type
Notes
-----
@@ -3478,7 +3478,7 @@ def var(a, axis=None, dtype=None, out=None, ddof=0, keepdims=np._NoValue):
See Also
--------
std, mean, nanmean, nanstd, nanvar
- numpy.doc.ufuncs : Section "Output arguments"
+ ufuncs-output-type
Notes
-----
diff --git a/numpy/core/numeric.py b/numpy/core/numeric.py
index 750f69db8..2c148712f 100644
--- a/numpy/core/numeric.py
+++ b/numpy/core/numeric.py
@@ -292,7 +292,7 @@ def full(shape, fill_value, dtype=None, order='C'):
fill_value : scalar
Fill value.
dtype : data-type, optional
- The desired data-type for the array The default, `None`, means
+ The desired data-type for the array The default, None, means
`np.array(fill_value).dtype`.
order : {'C', 'F'}, optional
Whether to store multidimensional data in C- or Fortran-contiguous
diff --git a/numpy/core/shape_base.py b/numpy/core/shape_base.py
index d7e769e62..369d956fb 100644
--- a/numpy/core/shape_base.py
+++ b/numpy/core/shape_base.py
@@ -472,7 +472,7 @@ def _block_check_depths_match(arrays, parent_index=[]):
first_index : list of int
The full index of an element from the bottom of the nesting in
`arrays`. If any element at the bottom is an empty list, this will
- refer to it, and the last index along the empty axis will be `None`.
+ refer to it, and the last index along the empty axis will be None.
max_arr_ndim : int
The maximum of the ndims of the arrays nested in `arrays`.
final_size: int
diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py
index c39c2eea1..3ad630a7d 100644
--- a/numpy/lib/function_base.py
+++ b/numpy/lib/function_base.py
@@ -1893,7 +1893,7 @@ class vectorize(object):
typecode characters or a list of data type specifiers. There should
be one data type specifier for each output.
doc : str, optional
- The docstring for the function. If `None`, the docstring will be the
+ The docstring for the function. If None, the docstring will be the
``pyfunc.__doc__``.
excluded : set, optional
Set of strings or integers representing the positional or keyword
diff --git a/numpy/lib/nanfunctions.py b/numpy/lib/nanfunctions.py
index 6cffab6ac..18ccab3b8 100644
--- a/numpy/lib/nanfunctions.py
+++ b/numpy/lib/nanfunctions.py
@@ -244,8 +244,8 @@ def nanmin(a, axis=None, out=None, keepdims=np._NoValue):
out : ndarray, optional
Alternate output array in which to place the result. The default
is ``None``; if provided, it must have the same shape as the
- expected output, but the type will be cast if necessary. See
- `doc.ufuncs` for details.
+ expected output, but the type will be cast if necessary. See
+ `ufuncs-output-type` for more details.
.. versionadded:: 1.8.0
keepdims : bool, optional
@@ -359,8 +359,8 @@ def nanmax(a, axis=None, out=None, keepdims=np._NoValue):
out : ndarray, optional
Alternate output array in which to place the result. The default
is ``None``; if provided, it must have the same shape as the
- expected output, but the type will be cast if necessary. See
- `doc.ufuncs` for details.
+ expected output, but the type will be cast if necessary. See
+ `ufuncs-output-type` for more details.
.. versionadded:: 1.8.0
keepdims : bool, optional
@@ -585,8 +585,8 @@ def nansum(a, axis=None, dtype=None, out=None, keepdims=np._NoValue):
Alternate output array in which to place the result. The default
is ``None``. If provided, it must have the same shape as the
expected output, but the type will be cast if necessary. See
- `doc.ufuncs` for details. The casting of NaN to integer can yield
- unexpected results.
+ `ufuncs-output-type` for more details. The casting of NaN to integer
+ can yield unexpected results.
.. versionadded:: 1.8.0
keepdims : bool, optional
@@ -681,9 +681,9 @@ def nanprod(a, axis=None, dtype=None, out=None, keepdims=np._NoValue):
out : ndarray, optional
Alternate output array in which to place the result. The default
is ``None``. If provided, it must have the same shape as the
- expected output, but the type will be cast if necessary. See
- `doc.ufuncs` for details. The casting of NaN to integer can yield
- unexpected results.
+ expected output, but the type will be cast if necessary. See
+ `ufuncs-output-type` for more details. The casting of NaN to integer
+ can yield unexpected results.
keepdims : bool, optional
If True, the axes which are reduced are left in the result as
dimensions with size one. With this option, the result will
@@ -750,8 +750,8 @@ def nancumsum(a, axis=None, dtype=None, out=None):
out : ndarray, optional
Alternative output array in which to place the result. It must
have the same shape and buffer length as the expected output
- but the type will be cast if necessary. See `doc.ufuncs`
- (Section "Output arguments") for more details.
+ but the type will be cast if necessary. See `ufuncs-output-type` for
+ more details.
Returns
-------
@@ -888,8 +888,8 @@ def nanmean(a, axis=None, dtype=None, out=None, keepdims=np._NoValue):
out : ndarray, optional
Alternate output array in which to place the result. The default
is ``None``; if provided, it must have the same shape as the
- expected output, but the type will be cast if necessary. See
- `doc.ufuncs` for details.
+ expected output, but the type will be cast if necessary. See
+ `ufuncs-output-type` for more details.
keepdims : bool, optional
If this is set to True, the axes which are reduced are left
in the result as dimensions with size one. With this option,
@@ -1473,7 +1473,7 @@ def nanvar(a, axis=None, dtype=None, out=None, ddof=0, keepdims=np._NoValue):
mean : Average
var : Variance while not ignoring NaNs
nanstd, nanmean
- numpy.doc.ufuncs : Section "Output arguments"
+ ufuncs-output-type
Notes
-----
@@ -1625,7 +1625,7 @@ def nanstd(a, axis=None, dtype=None, out=None, ddof=0, keepdims=np._NoValue):
--------
var, mean, std
nanvar, nanmean
- numpy.doc.ufuncs : Section "Output arguments"
+ ufuncs-output-type
Notes
-----
diff --git a/numpy/ma/core.py b/numpy/ma/core.py
index bb3788c9a..bb0d8d412 100644
--- a/numpy/ma/core.py
+++ b/numpy/ma/core.py
@@ -4394,7 +4394,7 @@ class MaskedArray(ndarray):
----------
axis : None or int or tuple of ints, optional
Axis or axes along which the count is performed.
- The default (`axis` = `None`) performs the count over all
+ The default, None, performs the count over all
the dimensions of the input array. `axis` may be negative, in
which case it counts from the last to the first axis.
@@ -4774,7 +4774,7 @@ class MaskedArray(ndarray):
See Also
--------
- ndarray.all : corresponding function for ndarrays
+ numpy.ndarray.all : corresponding function for ndarrays
numpy.all : equivalent function
Examples
@@ -4812,7 +4812,7 @@ class MaskedArray(ndarray):
See Also
--------
- ndarray.any : corresponding function for ndarrays
+ numpy.ndarray.any : corresponding function for ndarrays
numpy.any : equivalent function
"""
@@ -4866,7 +4866,7 @@ class MaskedArray(ndarray):
flatnonzero :
Return indices that are non-zero in the flattened version of the input
array.
- ndarray.nonzero :
+ numpy.ndarray.nonzero :
Equivalent ndarray method.
count_nonzero :
Counts the number of non-zero elements in the input array.
@@ -4994,7 +4994,7 @@ class MaskedArray(ndarray):
See Also
--------
- ndarray.sum : corresponding function for ndarrays
+ numpy.ndarray.sum : corresponding function for ndarrays
numpy.sum : equivalent function
Examples
@@ -5065,7 +5065,7 @@ class MaskedArray(ndarray):
See Also
--------
- ndarray.cumsum : corresponding function for ndarrays
+ numpy.ndarray.cumsum : corresponding function for ndarrays
numpy.cumsum : equivalent function
Examples
@@ -5102,7 +5102,7 @@ class MaskedArray(ndarray):
See Also
--------
- ndarray.prod : corresponding function for ndarrays
+ numpy.ndarray.prod : corresponding function for ndarrays
numpy.prod : equivalent function
"""
kwargs = {} if keepdims is np._NoValue else {'keepdims': keepdims}
@@ -5148,7 +5148,7 @@ class MaskedArray(ndarray):
See Also
--------
- ndarray.cumprod : corresponding function for ndarrays
+ numpy.ndarray.cumprod : corresponding function for ndarrays
numpy.cumprod : equivalent function
"""
result = self.filled(1).cumprod(axis=axis, dtype=dtype, out=out)
@@ -5171,7 +5171,7 @@ class MaskedArray(ndarray):
See Also
--------
- ndarray.mean : corresponding function for ndarrays
+ numpy.ndarray.mean : corresponding function for ndarrays
numpy.mean : Equivalent function
numpy.ma.average: Weighted average.
@@ -5260,7 +5260,7 @@ class MaskedArray(ndarray):
See Also
--------
- ndarray.var : corresponding function for ndarrays
+ numpy.ndarray.var : corresponding function for ndarrays
numpy.var : Equivalent function
"""
kwargs = {} if keepdims is np._NoValue else {'keepdims': keepdims}
@@ -5323,7 +5323,7 @@ class MaskedArray(ndarray):
See Also
--------
- ndarray.std : corresponding function for ndarrays
+ numpy.ndarray.std : corresponding function for ndarrays
numpy.std : Equivalent function
"""
kwargs = {} if keepdims is np._NoValue else {'keepdims': keepdims}
@@ -5344,7 +5344,7 @@ class MaskedArray(ndarray):
See Also
--------
- ndarray.around : corresponding function for ndarrays
+ numpy.ndarray.around : corresponding function for ndarrays
numpy.around : equivalent function
"""
result = self._data.round(decimals=decimals, out=out).view(type(self))
@@ -5406,7 +5406,7 @@ class MaskedArray(ndarray):
--------
MaskedArray.sort : Describes sorting algorithms used.
lexsort : Indirect stable sort with multiple keys.
- ndarray.sort : Inplace sort.
+ numpy.ndarray.sort : Inplace sort.
Notes
-----
@@ -5558,7 +5558,7 @@ class MaskedArray(ndarray):
See Also
--------
- ndarray.sort : Method to sort an array in-place.
+ numpy.ndarray.sort : Method to sort an array in-place.
argsort : Indirect sort.
lexsort : Indirect stable sort on multiple keys.
searchsorted : Find elements in a sorted array.
@@ -5978,7 +5978,7 @@ class MaskedArray(ndarray):
See Also
--------
- ndarray.tobytes
+ numpy.ndarray.tobytes
tolist, tofile
Notes
diff --git a/numpy/ma/extras.py b/numpy/ma/extras.py
index de1aa3af8..4a83ac781 100644
--- a/numpy/ma/extras.py
+++ b/numpy/ma/extras.py
@@ -542,7 +542,7 @@ def average(a, axis=None, weights=None, returned=False):
Data to be averaged.
Masked entries are not taken into account in the computation.
axis : int, optional
- Axis along which to average `a`. If `None`, averaging is done over
+ Axis along which to average `a`. If None, averaging is done over
the flattened array.
weights : array_like, optional
The importance that each element has in the computation of the average.
diff --git a/numpy/matrixlib/defmatrix.py b/numpy/matrixlib/defmatrix.py
index 3c7e8ffc2..cabd41367 100644
--- a/numpy/matrixlib/defmatrix.py
+++ b/numpy/matrixlib/defmatrix.py
@@ -1046,7 +1046,7 @@ def bmat(obj, ldict=None, gdict=None):
referenced by name.
ldict : dict, optional
A dictionary that replaces local operands in current frame.
- Ignored if `obj` is not a string or `gdict` is `None`.
+ Ignored if `obj` is not a string or `gdict` is None.
gdict : dict, optional
A dictionary that replaces global operands in current frame.
Ignored if `obj` is not a string.
View Lorry Controller Status