Merge pull request numpy#17250 from albertvillanova/fix-docstring

DOC: Fix docstring cross-referencing

Author: charris

numpy/core/fromnumeric.py

@@ -460,7 +460,7 @@ def repeat(a, repeats, axis=None):
     --------
     tile : Tile an array.
     unique : Find the unique elements of an array.
-    
+
     Examples
     --------
     >>> np.repeat(3, 4)
@@ -2007,8 +2007,8 @@ 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
-    ufuncs-output-type
+    extract: Equivalent method when working on 1-D arrays
+    :ref:`ufuncs-output-type`
 
     Examples
     --------
@@ -2082,7 +2082,7 @@ def clip(a, a_min, a_max, out=None, **kwargs):
 
     See Also
     --------
-    ufuncs-output-type
+    :ref:`ufuncs-output-type`
 
     Examples
     --------
@@ -2278,7 +2278,7 @@ 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 `ufuncs-output-type` for more details.
+        See :ref:`ufuncs-output-type` for more details.
 
     keepdims : bool, optional
         If this is set to True, the axes which are reduced are left
@@ -2363,7 +2363,7 @@ 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 `ufuncs-output-type` for more
+        will consist of 0.0's and 1.0's). See :ref:`ufuncs-output-type` for more
         details.
 
     keepdims : bool, optional
@@ -2442,7 +2442,7 @@ 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 `ufuncs-output-type` for
+        but the type will be cast if necessary. See :ref:`ufuncs-output-type` for
         more details.
 
     Returns
@@ -2613,7 +2613,7 @@ 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 `ufuncs-output-type` for more details.
+        See :ref:`ufuncs-output-type` for more details.
 
     keepdims : bool, optional
         If this is set to True, the axes which are reduced are left
@@ -2738,7 +2738,7 @@ 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 `ufuncs-output-type` for more details.
+        See :ref:`ufuncs-output-type` for more details.
 
     keepdims : bool, optional
         If this is set to True, the axes which are reduced are left
@@ -2948,7 +2948,7 @@ def prod(a, axis=None, dtype=None, out=None, keepdims=np._NoValue,
     See Also
     --------
     ndarray.prod : equivalent method
-    ufuncs-output-type
+    :ref:`ufuncs-output-type`
 
     Notes
     -----
@@ -3044,7 +3044,7 @@ def cumprod(a, axis=None, dtype=None, out=None):
 
     See Also
     --------
-    ufuncs-output-type
+    :ref:`ufuncs-output-type`
 
     Notes
     -----
@@ -3190,7 +3190,7 @@ 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 `ufuncs-output-type` for more
+        values will be cast if necessary. See :ref:`ufuncs-output-type` for more
         details.
 
     Returns
@@ -3305,7 +3305,7 @@ 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 `ufuncs-output-type` for more details.
+        See :ref:`ufuncs-output-type` for more details.
 
     keepdims : bool, optional
         If this is set to True, the axes which are reduced are left
@@ -3440,12 +3440,12 @@ def std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=np._NoValue):
     See Also
     --------
     var, mean, nanmean, nanstd, nanvar
-    ufuncs-output-type
+    :ref:`ufuncs-output-type`
 
     Notes
     -----
     The standard deviation is the square root of the average of the squared
-    deviations from the mean, i.e., ``std = sqrt(mean(x))``, where 
+    deviations from the mean, i.e., ``std = sqrt(mean(x))``, where
     ``x = abs(a - a.mean())**2``.
 
     The average squared deviation is typically calculated as ``x.sum() / N``,
@@ -3566,7 +3566,7 @@ def var(a, axis=None, dtype=None, out=None, ddof=0, keepdims=np._NoValue):
     See Also
     --------
     std, mean, nanmean, nanstd, nanvar
-    ufuncs-output-type
+    :ref:`ufuncs-output-type`
 
     Notes
     -----

numpy/core/records.py

@@ -374,7 +374,7 @@ class recarray(ndarray):
 
     See Also
     --------
-    rec.fromrecords : Construct a record array from data.
+    core.records.fromrecords : Construct a record array from data.
     record : fundamental data-type for `recarray`.
     format_parser : determine a data-type from formats, names, titles.
 
@@ -630,7 +630,7 @@ def fromarrays(arrayList, dtype=None, shape=None, formats=None,
     >>> x1[1]=34
     >>> r.a
     array([1, 2, 3, 4])
-    
+
     >>> x1 = np.array([1, 2, 3, 4])
     >>> x2 = np.array(['a', 'dd', 'xyz', '12'])
     >>> x3 = np.array([1.1, 2, 3,4])
@@ -911,7 +911,7 @@ def fromfile(fd, dtype=None, shape=None, offset=0, formats=None,
         shape = (shape,)
 
     if hasattr(fd, 'readinto'):
-        # GH issue 2504. fd supports io.RawIOBase or io.BufferedIOBase interface. 
+        # GH issue 2504. fd supports io.RawIOBase or io.BufferedIOBase interface.
         # Example of fd: gzip, BytesIO, BufferedReader
         # file already opened
         ctx = contextlib_nullcontext(fd)
@@ -958,7 +958,7 @@ def array(obj, dtype=None, shape=None, offset=0, strides=None, formats=None,
     """
     Construct a record array from a wide-variety of objects.
 
-    A general-purpose record array constructor that dispatches to the 
+    A general-purpose record array constructor that dispatches to the
     appropriate `recarray` creation function based on the inputs (see Notes).
 
     Parameters
@@ -996,7 +996,7 @@ def array(obj, dtype=None, shape=None, offset=0, strides=None, formats=None,
     `obj` is a string, then call the `fromstring` constructor. If `obj` is a
     list or a tuple, then if the first object is an `~numpy.ndarray`, call
     `fromarrays`, otherwise call `fromrecords`. If `obj` is a
-    `~numpy.recarray`, then make a copy of the data in the recarray 
+    `~numpy.recarray`, then make a copy of the data in the recarray
     (if ``copy=True``) and use the new formats, names, and titles. If `obj`
     is a file, then call `fromfile`. Finally, if obj is an `ndarray`, then
     return ``obj.view(recarray)``, making a copy of the data if ``copy=True``.

numpy/distutils/ccompiler_opt.py

@@ -2186,7 +2186,7 @@ def try_dispatch(self, sources, src_dir=None, **kwargs):
 
         See Also
         --------
-        parse_targets() :
+        parse_targets :
             Parsing the configuration statements of dispatch-able sources.
         """
         to_compile = {}

numpy/doc/constants.py

@@ -135,10 +135,6 @@ def add_newdoc(module, name, doc):
     """
     A convenient alias for None, useful for indexing arrays.
 
-    See Also
-    --------
-    `numpy.doc.indexing`
-
     Examples
     --------
     >>> newaxis is None

numpy/lib/function_base.py

@@ -4229,10 +4229,9 @@ def meshgrid(*xi, copy=True, sparse=False, indexing='xy'):
 
     See Also
     --------
-    index_tricks.mgrid : Construct a multi-dimensional "meshgrid"
-                     using indexing notation.
-    index_tricks.ogrid : Construct an open multi-dimensional "meshgrid"
-                     using indexing notation.
+    mgrid : Construct a multi-dimensional "meshgrid" using indexing notation.
+    ogrid : Construct an open multi-dimensional "meshgrid" using indexing 
+            notation.
 
     Examples
     --------

numpy/lib/nanfunctions.py

@@ -244,7 +244,7 @@ def nanmin(a, axis=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
-        `ufuncs-output-type` for more details.
+        :ref:`ufuncs-output-type` for more details.
 
         .. versionadded:: 1.8.0
     keepdims : bool, optional
@@ -359,7 +359,7 @@ def nanmax(a, axis=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
-        `ufuncs-output-type` for more details.
+        :ref:`ufuncs-output-type` for more details.
 
         .. versionadded:: 1.8.0
     keepdims : bool, optional
@@ -584,7 +584,7 @@ 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
-        `ufuncs-output-type` for more details. The casting of NaN to integer
+        :ref:`ufuncs-output-type` for more details. The casting of NaN to integer
         can yield unexpected results.
 
         .. versionadded:: 1.8.0
@@ -681,7 +681,7 @@ def nanprod(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
-        `ufuncs-output-type` for more details. The casting of NaN to integer
+        :ref:`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
@@ -749,7 +749,7 @@ 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 `ufuncs-output-type` for
+        but the type will be cast if necessary. See :ref:`ufuncs-output-type` for
         more details.
 
     Returns
@@ -888,7 +888,7 @@ def nanmean(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
-        `ufuncs-output-type` for more details.
+        :ref:`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,
@@ -1256,7 +1256,7 @@ def nanquantile(a, q, axis=None, out=None, overwrite_input=False,
     Compute the qth quantile of the data along the specified axis,
     while ignoring nan values.
     Returns the qth quantile(s) of the array elements.
-    
+
     .. versionadded:: 1.15.0
 
     Parameters
@@ -1472,7 +1472,7 @@ def nanvar(a, axis=None, dtype=None, out=None, ddof=0, keepdims=np._NoValue):
     mean : Average
     var : Variance while not ignoring NaNs
     nanstd, nanmean
-    ufuncs-output-type
+    :ref:`ufuncs-output-type`
 
     Notes
     -----
@@ -1624,7 +1624,7 @@ def nanstd(a, axis=None, dtype=None, out=None, ddof=0, keepdims=np._NoValue):
     --------
     var, mean, std
     nanvar, nanmean
-    ufuncs-output-type
+    :ref:`ufuncs-output-type`
 
     Notes
     -----

numpy/lib/scimath.py

@@ -14,6 +14,22 @@
 Similarly, `sqrt`, other base logarithms, `power` and trig functions are
 correctly handled.  See their respective docstrings for specific examples.
 
+Functions
+---------
+
+.. autosummary::
+   :toctree: generated/
+
+   sqrt
+   log
+   log2
+   logn
+   log10
+   power
+   arccos
+   arcsin
+   arctanh
+
 """
 import numpy.core.numeric as nx
 import numpy.core.numerictypes as nt