diff options
| -rw-r--r-- | doc/neps/nep-0012-missing-data.rst | 2 | ||||
| -rw-r--r-- | doc/neps/nep-0021-advanced-indexing.rst | 2 | ||||
| -rw-r--r-- | doc/neps/nep-0028-website-redesign.rst | 2 | ||||
| -rw-r--r-- | doc/neps/nep-0041-improved-dtype-support.rst | 2 | ||||
| -rw-r--r-- | doc/release/upcoming_changes/14995.compatibility.rst | 2 | ||||
| -rw-r--r-- | doc/source/reference/arrays.indexing.rst | 2 | ||||
| -rw-r--r-- | doc/source/reference/c-api/array.rst | 2 | ||||
| -rw-r--r-- | doc/source/reference/random/performance.rst | 4 | ||||
| -rw-r--r-- | doc/source/reference/ufuncs.rst | 2 | ||||
| -rw-r--r-- | doc/source/user/c-info.how-to-extend.rst | 2 | ||||
| -rw-r--r-- | doc/source/user/c-info.python-as-glue.rst | 4 | ||||
| -rw-r--r-- | numpy/core/defchararray.py | 2 | ||||
| -rw-r--r-- | numpy/core/setup.py | 2 | ||||
| -rw-r--r-- | numpy/core/src/common/mem_overlap.c | 2 | ||||
| -rw-r--r-- | numpy/core/src/multiarray/arraytypes.c.src | 2 | ||||
| -rw-r--r-- | numpy/core/src/multiarray/dragon4.c | 2 | ||||
| -rw-r--r-- | numpy/core/src/multiarray/mapping.c | 2 | ||||
| -rw-r--r-- | numpy/lib/financial.py | 2 | ||||
| -rw-r--r-- | tools/refguide_check.py | 2 |
19 files changed, 21 insertions, 21 deletions
diff --git a/doc/neps/nep-0012-missing-data.rst b/doc/neps/nep-0012-missing-data.rst index f59cf394f..f7026b4be 100644 --- a/doc/neps/nep-0012-missing-data.rst +++ b/doc/neps/nep-0012-missing-data.rst @@ -926,7 +926,7 @@ to access the array elements. This python indexing still goes through the Python API, so the NA handling and error checking in numpy still can work like normal and fail if the inputs have NAs which cannot fit in the output array. In this case it fails when trying to convert the NA into an integer -to set in in the output. +to set in the output. The next version of the code introduces more efficient indexing. This operates based on Python's buffer protocol. This causes Cython to call diff --git a/doc/neps/nep-0021-advanced-indexing.rst b/doc/neps/nep-0021-advanced-indexing.rst index 8e525b0cb..0d20d680f 100644 --- a/doc/neps/nep-0021-advanced-indexing.rst +++ b/doc/neps/nep-0021-advanced-indexing.rst @@ -48,7 +48,7 @@ NumPy arrays currently support a flexible range of indexing operations: For clarity, we will refer to these existing rules as "legacy indexing". This is only a high-level summary; for more details, see NumPy's documentation -and and `Examples` below. +and `Examples` below. Outer indexing ~~~~~~~~~~~~~~ diff --git a/doc/neps/nep-0028-website-redesign.rst b/doc/neps/nep-0028-website-redesign.rst index 022a1fdbb..68f25ad4d 100644 --- a/doc/neps/nep-0028-website-redesign.rst +++ b/doc/neps/nep-0028-website-redesign.rst @@ -153,7 +153,7 @@ significant drain on the time of maintainers. 2. *Github Pages.* Github Pages also has a 100GB bandwidth limit, and is unclear if additional bandwidth can be purchased. It is also unclear where sites are deployed, and should be assumed sites aren't deployed globally. Github Pages has an easy to - use CI & DNS, similar to to Netlify. HTTPS is supported. + use CI & DNS, similar to Netlify. HTTPS is supported. 3. *Cloudflare.* An excellent option, additional CI is likely needed for the same ease of deployment. diff --git a/doc/neps/nep-0041-improved-dtype-support.rst b/doc/neps/nep-0041-improved-dtype-support.rst index 294f52746..56ff5eac6 100644 --- a/doc/neps/nep-0041-improved-dtype-support.rst +++ b/doc/neps/nep-0041-improved-dtype-support.rst @@ -392,7 +392,7 @@ numerical dtypes since there is no "universal" output type:: In fact ``np.result_type(meters, seconds)`` must error without context of the operation being done. This example highlights how the specific ufunc loop -(loop with known, specific DTypes as inputs), has to be able to to make +(loop with known, specific DTypes as inputs), has to be able to make certain decisions before the actual calculation can start. diff --git a/doc/release/upcoming_changes/14995.compatibility.rst b/doc/release/upcoming_changes/14995.compatibility.rst index b3b8b5933..140e66486 100644 --- a/doc/release/upcoming_changes/14995.compatibility.rst +++ b/doc/release/upcoming_changes/14995.compatibility.rst @@ -6,5 +6,5 @@ meaning an object implementing ``obj.__array__()``, buffer interface and which are also sequences (i.e. Pandas objects) will now always retain there shape correctly when converted to an array. If such an object has a shape of ``(0, 1)`` previously, it could -be converted into an array of of shape ``(0,)`` (losing all dimensions +be converted into an array of shape ``(0,)`` (losing all dimensions after the first 0). diff --git a/doc/source/reference/arrays.indexing.rst b/doc/source/reference/arrays.indexing.rst index a425b6e8b..56b99f272 100644 --- a/doc/source/reference/arrays.indexing.rst +++ b/doc/source/reference/arrays.indexing.rst @@ -117,7 +117,7 @@ concepts to remember include: array([5, 6, 7, 8, 9]) - If the number of objects in the selection tuple is less than - *N* , then ``:`` is assumed for any subsequent dimensions. + *N*, then ``:`` is assumed for any subsequent dimensions. .. admonition:: Example diff --git a/doc/source/reference/c-api/array.rst b/doc/source/reference/c-api/array.rst index 83289010b..56fc59da3 100644 --- a/doc/source/reference/c-api/array.rst +++ b/doc/source/reference/c-api/array.rst @@ -1886,7 +1886,7 @@ Item selection and manipulation Equivalent to :meth:`ndarray.sort<numpy.ndarray.sort>` (*self*, *axis*, *kind*). Return an array with the items of *self* sorted along *axis*. The array - is sorted using the algorithm denoted by *kind* , which is an integer/enum pointing + is sorted using the algorithm denoted by *kind*, which is an integer/enum pointing to the type of sorting algorithms used. .. c:function:: PyObject* PyArray_ArgSort(PyArrayObject* self, int axis) diff --git a/doc/source/reference/random/performance.rst b/doc/source/reference/random/performance.rst index d70dd064a..74dad4cc3 100644 --- a/doc/source/reference/random/performance.rst +++ b/doc/source/reference/random/performance.rst @@ -81,7 +81,7 @@ performance was computed using a geometric mean. .. note:: - All timings were taken using Linux on a i5-3570 processor. + All timings were taken using Linux on an i5-3570 processor. Performance on different Operating Systems ****************************************** @@ -150,4 +150,4 @@ Exponentials 100 33.7 26.3 109.8 Linux timings used Ubuntu 18.04 and GCC 7.4. Windows timings were made on Windows 10 using Microsoft C/C++ Optimizing Compiler Version 19 (Visual - Studio 2015). All timings were produced on a i5-3570 processor. + Studio 2015). All timings were produced on an i5-3570 processor. diff --git a/doc/source/reference/ufuncs.rst b/doc/source/reference/ufuncs.rst index aad285122..6d58d1a6d 100644 --- a/doc/source/reference/ufuncs.rst +++ b/doc/source/reference/ufuncs.rst @@ -380,7 +380,7 @@ advanced usage and will not typically be used. result as a dimension with size one, so that the result will broadcast correctly against the inputs. This option can only be used for generalized ufuncs that operate on inputs that all have the same number of core - dimensions and with outputs that have no core dimensions , i.e., with + dimensions and with outputs that have no core dimensions, i.e., with signatures like ``(i),(i)->()`` or ``(m,m)->()``. If used, the location of the dimensions in the output can be controlled with ``axes`` and ``axis``. diff --git a/doc/source/user/c-info.how-to-extend.rst b/doc/source/user/c-info.how-to-extend.rst index 7aeed57cf..d75242092 100644 --- a/doc/source/user/c-info.how-to-extend.rst +++ b/doc/source/user/c-info.how-to-extend.rst @@ -163,7 +163,7 @@ ignored. The *args* argument contains all of the arguments passed in to the function as a tuple. You can do anything you want at this point, but usually the easiest way to manage the input arguments is to call :c:func:`PyArg_ParseTuple` (args, format_string, -addresses_to_C_variables...) or :c:func:`PyArg_UnpackTuple` (tuple, "name" , +addresses_to_C_variables...) or :c:func:`PyArg_UnpackTuple` (tuple, "name", min, max, ...). A good description of how to use the first function is contained in the Python C-API reference manual under section 5.5 (Parsing arguments and building values). You should pay particular diff --git a/doc/source/user/c-info.python-as-glue.rst b/doc/source/user/c-info.python-as-glue.rst index 201bd8417..9fe5f8f6e 100644 --- a/doc/source/user/c-info.python-as-glue.rst +++ b/doc/source/user/c-info.python-as-glue.rst @@ -671,7 +671,7 @@ simply have a shared library available to you). Items to remember are: - A shared library must be compiled in a special way ( *e.g.* using the ``-shared`` flag with gcc). -- On some platforms (*e.g.* Windows) , a shared library requires a +- On some platforms (*e.g.* Windows), a shared library requires a .def file that specifies the functions to be exported. For example a mylib.def file might contain:: @@ -802,7 +802,7 @@ Calling the function The function is accessed as an attribute of or an item from the loaded shared-library. Thus, if ``./mylib.so`` has a function named -``cool_function1`` , I could access this function either as: +``cool_function1``, I could access this function either as: .. code-block:: python diff --git a/numpy/core/defchararray.py b/numpy/core/defchararray.py index cd01c0e77..1d447b86a 100644 --- a/numpy/core/defchararray.py +++ b/numpy/core/defchararray.py @@ -1779,7 +1779,7 @@ def isdecimal(a): Calls `unicode.isdecimal` element-wise. Decimal characters include digit characters, and all characters - that that can be used to form decimal-radix numbers, + that can be used to form decimal-radix numbers, e.g. ``U+0660, ARABIC-INDIC DIGIT ZERO``. Parameters diff --git a/numpy/core/setup.py b/numpy/core/setup.py index 76f3f5abe..fcc422545 100644 --- a/numpy/core/setup.py +++ b/numpy/core/setup.py @@ -520,7 +520,7 @@ def configuration(parent_package='',top_path=None): def generate_numpyconfig_h(ext, build_dir): """Depends on config.h: generate_config_h has to be called before !""" # put common include directory in build_dir on search path - # allows using code generation in headers headers + # allows using code generation in headers config.add_include_dirs(join(build_dir, "src", "common")) config.add_include_dirs(join(build_dir, "src", "npymath")) diff --git a/numpy/core/src/common/mem_overlap.c b/numpy/core/src/common/mem_overlap.c index 21db1893b..9da33bfc1 100644 --- a/numpy/core/src/common/mem_overlap.c +++ b/numpy/core/src/common/mem_overlap.c @@ -127,7 +127,7 @@ ends up considering all values x3=0...5 separately. The upper bound for work done is prod(shape_a)*prod(shape_b), which scales - faster than than work done by binary ufuncs, after broadcasting, + faster than work done by binary ufuncs, after broadcasting, prod(shape_a). The bound may be loose, but it is possible to construct hard instances where ufunc is faster (adapted from [2,3]):: diff --git a/numpy/core/src/multiarray/arraytypes.c.src b/numpy/core/src/multiarray/arraytypes.c.src index 024dcab8c..38d5f21eb 100644 --- a/numpy/core/src/multiarray/arraytypes.c.src +++ b/numpy/core/src/multiarray/arraytypes.c.src @@ -3846,7 +3846,7 @@ static void */ /* - * Compute correlation of data with with small kernels + * Compute correlation of data with small kernels * Calling a BLAS dot product for the inner loop of the correlation is overkill * for small kernels. It is faster to compute it directly. * Intended to be used by _pyarray_correlate so no input verifications is done diff --git a/numpy/core/src/multiarray/dragon4.c b/numpy/core/src/multiarray/dragon4.c index 282cdad28..553d0effb 100644 --- a/numpy/core/src/multiarray/dragon4.c +++ b/numpy/core/src/multiarray/dragon4.c @@ -1566,7 +1566,7 @@ Dragon4(BigInt *bigints, const npy_int32 exponent, * * scientific - boolean controlling whether scientific notation is used * digit_mode - whether to use unique or fixed fractional output - * cutoff_mode - whether 'precision' refers to to all digits, or digits past + * cutoff_mode - whether 'precision' refers to all digits, or digits past * the decimal point. * precision - When negative, prints as many digits as needed for a unique * number. When positive specifies the maximum number of diff --git a/numpy/core/src/multiarray/mapping.c b/numpy/core/src/multiarray/mapping.c index 7047304eb..43dbde2f1 100644 --- a/numpy/core/src/multiarray/mapping.c +++ b/numpy/core/src/multiarray/mapping.c @@ -2689,7 +2689,7 @@ PyArray_MapIterNew(npy_index_info *indices , int index_num, int index_type, if (mit->numiter == 0) { /* * For MapIterArray, it is possible that there is no fancy index. - * to support this case, add a a dummy iterator. + * to support this case, add a dummy iterator. * Since it is 0-d its transpose, etc. does not matter. */ diff --git a/numpy/lib/financial.py b/numpy/lib/financial.py index b055bb1ec..709a79dc0 100644 --- a/numpy/lib/financial.py +++ b/numpy/lib/financial.py @@ -466,7 +466,7 @@ def _rbl(rate, per, pmt, pv, when): This function is here to simply have a different name for the 'fv' function to not interfere with the 'fv' keyword argument within the 'ipmt' function. It is the 'remaining balance on loan' which might be useful as - it's own function, but is easily calculated with the 'fv' function. + its own function, but is easily calculated with the 'fv' function. """ return fv(rate, (per - 1), pmt, pv, when) diff --git a/tools/refguide_check.py b/tools/refguide_check.py index 31d2997d3..b3891c5cb 100644 --- a/tools/refguide_check.py +++ b/tools/refguide_check.py @@ -1037,7 +1037,7 @@ def iter_included_files(base_path, verbose=0, suffixes=('.rst',)): Yields ------ path - Path of the directory and it's sub directories + Path of the directory and its sub directories """ if os.path.exists(base_path) and os.path.isfile(base_path): yield base_path |