diff options
38 files changed, 52 insertions, 51 deletions
diff --git a/benchmarks/benchmarks/bench_function_base.py b/benchmarks/benchmarks/bench_function_base.py index f730bf6ba..2170c4fc4 100644 --- a/benchmarks/benchmarks/bench_function_base.py +++ b/benchmarks/benchmarks/bench_function_base.py @@ -269,7 +269,7 @@ class SortWorst(Benchmark): def time_sort_worst(self): np.sort(self.worst) - # Retain old benchmark name for backward compatability + # Retain old benchmark name for backward compatibility time_sort_worst.benchmark_name = "bench_function_base.Sort.time_sort_worst" diff --git a/doc/DISTUTILS.rst.txt b/doc/DISTUTILS.rst.txt index 42aa9561d..a4909d66d 100644 --- a/doc/DISTUTILS.rst.txt +++ b/doc/DISTUTILS.rst.txt @@ -302,7 +302,7 @@ Template files NumPy Distutils preprocesses C source files (extension: :file:`.c.src`) written in a custom templating language to generate C code. The :c:data:`@` symbol is -used to wrap macro-style variables to empower a string substitution mechansim +used to wrap macro-style variables to empower a string substitution mechanism that might describe (for instance) a set of data types. As a more detailed scenario, a loop in the NumPy C source code may diff --git a/doc/Makefile b/doc/Makefile index 776f9b778..842d2ad13 100644 --- a/doc/Makefile +++ b/doc/Makefile @@ -5,7 +5,7 @@ # issues with the amendments to PYTHONPATH and install paths (see DIST_VARS). # Use explicit "version_info" indexing since make cannot handle colon characters, and -# evaluate it now to allow easier debugging when printing the varaible +# evaluate it now to allow easier debugging when printing the variable PYVER:=$(shell python3 -c 'from sys import version_info as v; print("{0}.{1}".format(v[0], v[1]))') PYTHON = python$(PYVER) diff --git a/doc/source/reference/c-api.array.rst b/doc/source/reference/c-api.array.rst index de412a5d2..d01d28f0e 100644 --- a/doc/source/reference/c-api.array.rst +++ b/doc/source/reference/c-api.array.rst @@ -219,7 +219,7 @@ From scratch If *data* is ``NULL``, then new unitinialized memory will be allocated and *flags* can be non-zero to indicate a Fortran-style contiguous array. Use - :c:func:`PyArray_FILLWBYTE` to initialze the memory. + :c:func:`PyArray_FILLWBYTE` to initialize the memory. If *data* is not ``NULL``, then it is assumed to point to the memory to be used for the array and the *flags* argument is used as the diff --git a/doc/source/reference/c-api.coremath.rst b/doc/source/reference/c-api.coremath.rst index bb457eb0d..7e00322f9 100644 --- a/doc/source/reference/c-api.coremath.rst +++ b/doc/source/reference/c-api.coremath.rst @@ -185,7 +185,7 @@ Those can be useful for precise floating point comparison. * NPY_FPE_INVALID Note that :c:func:`npy_get_floatstatus_barrier` is preferable as it prevents - agressive compiler optimizations reordering the call relative to + aggressive compiler optimizations reordering the call relative to the code setting the status, which could lead to incorrect results. .. versionadded:: 1.9.0 @@ -193,7 +193,7 @@ Those can be useful for precise floating point comparison. .. c:function:: int npy_get_floatstatus_barrier(char*) Get floating point status. A pointer to a local variable is passed in to - prevent aggresive compiler optimizations from reodering this function call + prevent aggressive compiler optimizations from reodering this function call relative to the code setting the status, which could lead to incorrect results. @@ -211,7 +211,7 @@ Those can be useful for precise floating point comparison. Clears the floating point status. Returns the previous status mask. Note that :c:func:`npy_clear_floatstatus_barrier` is preferable as it - prevents agressive compiler optimizations reordering the call relative to + prevents aggressive compiler optimizations reordering the call relative to the code setting the status, which could lead to incorrect results. .. versionadded:: 1.9.0 @@ -219,7 +219,7 @@ Those can be useful for precise floating point comparison. .. c:function:: int npy_clear_floatstatus_barrier(char*) Clears the floating point status. A pointer to a local variable is passed in to - prevent aggresive compiler optimizations from reodering this function call. + prevent aggressive compiler optimizations from reodering this function call. Returns the previous status mask. .. versionadded:: 1.15.0 diff --git a/doc/source/reference/random/index.rst b/doc/source/reference/random/index.rst index 0b8145735..3159f0e1c 100644 --- a/doc/source/reference/random/index.rst +++ b/doc/source/reference/random/index.rst @@ -5,7 +5,7 @@ numpy.random ============ -Numpy's random number routines produce psuedo random numbers using +Numpy's random number routines produce pseudo random numbers using combinations of a `BitGenerator` to create sequences and a `Generator` to use those sequences to sample from different statistical distributions: @@ -41,7 +41,7 @@ which will be faster than the legacy methods in `RandomState` `Generator` can be used as a direct replacement for `~RandomState`, although the random values are generated by `~xoshiro256.Xoshiro256`. The -`Generator` holds an instance of a BitGenerator. It is accessable as +`Generator` holds an instance of a BitGenerator. It is accessible as ``gen.bit_generator``. .. code-block:: python @@ -127,7 +127,7 @@ What's New or Different :ref:`Cython <randomgen_cython>`. * `~.Generator.integers` is now the canonical way to generate integer random numbers from a discrete uniform distribution. The ``rand`` and - ``randn`` methods are only availabe through the legacy `~.RandomState`. + ``randn`` methods are only available through the legacy `~.RandomState`. The ``endpoint`` keyword can be used to specify open or closed intervals. This replaces both ``randint`` and the deprecated ``random_integers``. * `~.Generator.random` is now the canonical way to generate floating-point diff --git a/doc/source/reference/random/new-or-different.rst b/doc/source/reference/random/new-or-different.rst index 969a9372d..a6de9c8dc 100644 --- a/doc/source/reference/random/new-or-different.rst +++ b/doc/source/reference/random/new-or-different.rst @@ -54,7 +54,7 @@ And in more detail: `~.Generator.standard_gamma`. * `~.Generator.integers` is now the canonical way to generate integer random numbers from a discrete uniform distribution. The ``rand`` and - ``randn`` methods are only availabe through the legacy `~.RandomState`. + ``randn`` methods are only available through the legacy `~.RandomState`. This replaces both ``randint`` and the deprecated ``random_integers``. * The Box-Muller used to produce NumPy's normals is no longer available. * All bit generators can produce doubles, uint64s and diff --git a/numpy/core/_dtype_ctypes.py b/numpy/core/_dtype_ctypes.py index 0852b1ef2..708241289 100644 --- a/numpy/core/_dtype_ctypes.py +++ b/numpy/core/_dtype_ctypes.py @@ -1,7 +1,7 @@ """ Conversion from ctypes to dtype. -In an ideal world, we could acheive this through the PEP3118 buffer protocol, +In an ideal world, we could achieve this through the PEP3118 buffer protocol, something like:: def dtype_from_ctypes_type(t): diff --git a/numpy/core/einsumfunc.py b/numpy/core/einsumfunc.py index 83b7d8287..3412c3fd5 100644 --- a/numpy/core/einsumfunc.py +++ b/numpy/core/einsumfunc.py @@ -287,7 +287,7 @@ def _update_other_results(results, best): Returns ------- mod_results : list - The list of modifed results, updated with outcome of ``best`` contraction. + The list of modified results, updated with outcome of ``best`` contraction. """ best_con = best[1] diff --git a/numpy/core/numerictypes.py b/numpy/core/numerictypes.py index 3ec8235db..ab1ff65a4 100644 --- a/numpy/core/numerictypes.py +++ b/numpy/core/numerictypes.py @@ -275,7 +275,7 @@ def obj2sctype(rep, default=None): <class 'list'> """ - # prevent abtract classes being upcast + # prevent abstract classes being upcast if isinstance(rep, type) and issubclass(rep, generic): return rep # extract dtype from arrays diff --git a/numpy/core/shape_base.py b/numpy/core/shape_base.py index 45115adb6..ccec25a7a 100644 --- a/numpy/core/shape_base.py +++ b/numpy/core/shape_base.py @@ -555,10 +555,10 @@ def _concatenate_shapes(shapes, axis): ret[(slice(None),) * axis + sl_c] == c ``` - Thses are called slice prefixes since they are used in the recursive + These are called slice prefixes since they are used in the recursive blocking algorithm to compute the left-most slices during the recursion. Therefore, they must be prepended to rest of the slice - that was computed deeper in the recusion. + that was computed deeper in the recursion. These are returned as tuples to ensure that they can quickly be added to existing slice tuple without creating a new tuple everytime. @@ -841,9 +841,9 @@ def block(arrays): return _block_concatenate(arrays, list_ndim, result_ndim) -# Theses helper functions are mostly used for testing. +# These helper functions are mostly used for testing. # They allow us to write tests that directly call `_block_slicing` -# or `_block_concatenate` without blocking large arrays to forse the wisdom +# or `_block_concatenate` without blocking large arrays to force the wisdom # to trigger the desired path. def _block_setup(arrays): """ diff --git a/numpy/core/src/multiarray/arraytypes.c.src b/numpy/core/src/multiarray/arraytypes.c.src index 5f7bcb8f7..3b986ed04 100644 --- a/numpy/core/src/multiarray/arraytypes.c.src +++ b/numpy/core/src/multiarray/arraytypes.c.src @@ -2260,7 +2260,7 @@ VOID_copyswapn (char *dst, npy_intp dstride, char *src, npy_intp sstride, char *dstptr, *srcptr; /* * In certain cases subarray copy can be optimized. This is when - * swapping is unecessary and the subarrays data type can certainly + * swapping is unnecessary and the subarrays data type can certainly * be simply copied (no object, fields, subarray, and not a user dtype). */ npy_bool can_optimize_subarray = (!swap && @@ -2347,7 +2347,7 @@ VOID_copyswap (char *dst, char *src, int swap, PyArrayObject *arr) int subitemsize; /* * In certain cases subarray copy can be optimized. This is when - * swapping is unecessary and the subarrays data type can certainly + * swapping is unnecessary and the subarrays data type can certainly * be simply copied (no object, fields, subarray, and not a user dtype). */ npy_bool can_optimize_subarray = (!swap && diff --git a/numpy/core/src/multiarray/ctors.c b/numpy/core/src/multiarray/ctors.c index 4b524c365..9dc904c08 100644 --- a/numpy/core/src/multiarray/ctors.c +++ b/numpy/core/src/multiarray/ctors.c @@ -3170,7 +3170,7 @@ PyArray_Zeros(int nd, npy_intp *dims, PyArray_Descr *type, int is_f_order) * Empty * * accepts NULL type - * steals referenct to type + * steals a reference to type */ NPY_NO_EXPORT PyObject * PyArray_Empty(int nd, npy_intp *dims, PyArray_Descr *type, int is_f_order) diff --git a/numpy/core/src/multiarray/methods.c b/numpy/core/src/multiarray/methods.c index 9254a7a70..b843c7983 100644 --- a/numpy/core/src/multiarray/methods.c +++ b/numpy/core/src/multiarray/methods.c @@ -1687,7 +1687,7 @@ array_reduce(PyArrayObject *self, PyObject *NPY_UNUSED(args)) Notice because Python does not describe a mechanism to write raw data to the pickle, this performs a copy to a string first - This issue is now adressed in protocol 5, where a buffer is serialized + This issue is now addressed in protocol 5, where a buffer is serialized instead of a string, */ diff --git a/numpy/core/src/npymath/npy_math_complex.c.src b/numpy/core/src/npymath/npy_math_complex.c.src index 7aa07f16d..dad381232 100644 --- a/numpy/core/src/npymath/npy_math_complex.c.src +++ b/numpy/core/src/npymath/npy_math_complex.c.src @@ -1246,7 +1246,7 @@ _clog_for_large_values@c@(@type@ x, @type@ y, * Divide x and y by E, and then add 1 to the logarithm. This depends * on E being larger than sqrt(2). * Dividing by E causes an insignificant loss of accuracy; however - * this method is still poor since it is uneccessarily slow. + * this method is still poor since it is unnecessarily slow. */ if (ax > @TMAX@ / 2) { *rr = npy_log@c@(npy_hypot@c@(x / NPY_E@c@, y / NPY_E@c@)) + 1; diff --git a/numpy/core/src/npysort/selection.c.src b/numpy/core/src/npysort/selection.c.src index 1e0934558..be645450f 100644 --- a/numpy/core/src/npysort/selection.c.src +++ b/numpy/core/src/npysort/selection.c.src @@ -40,7 +40,7 @@ static NPY_INLINE void store_pivot(npy_intp pivot, npy_intp kth, } /* - * If pivot is the requested kth store it, overwritting other pivots if + * If pivot is the requested kth store it, overwriting other pivots if * required. This must be done so iterative partition can work without * manually shifting lower data offset by kth each time */ diff --git a/numpy/core/src/umath/ufunc_type_resolution.c b/numpy/core/src/umath/ufunc_type_resolution.c index b2400a2a1..96591ba80 100644 --- a/numpy/core/src/umath/ufunc_type_resolution.c +++ b/numpy/core/src/umath/ufunc_type_resolution.c @@ -1737,7 +1737,7 @@ set_ufunc_loop_data_types(PyUFuncObject *self, PyArrayObject **op, } /* * For outputs, copy the dtype from op[0] if the type_num - * matches, similarly to preserve metdata. + * matches, similarly to preserve metadata. */ else if (i >= nin && op[0] != NULL && PyArray_DESCR(op[0])->type_num == type_nums[i]) { diff --git a/numpy/core/tests/test_dtype.py b/numpy/core/tests/test_dtype.py index c554e9832..f4736d694 100644 --- a/numpy/core/tests/test_dtype.py +++ b/numpy/core/tests/test_dtype.py @@ -603,7 +603,7 @@ class TestStructuredDtypeSparseFields(object): 'offsets':[4]}, (2, 3))]) @pytest.mark.xfail(reason="inaccessible data is changed see gh-12686.") - @pytest.mark.valgrind_error(reason="reads from unitialized buffers.") + @pytest.mark.valgrind_error(reason="reads from uninitialized buffers.") def test_sparse_field_assignment(self): arr = np.zeros(3, self.dtype) sparse_arr = arr.view(self.sparse_dtype) diff --git a/numpy/core/tests/test_half.py b/numpy/core/tests/test_half.py index 770712501..1e1e6d7d9 100644 --- a/numpy/core/tests/test_half.py +++ b/numpy/core/tests/test_half.py @@ -104,7 +104,7 @@ class TestHalf(object): # logic will be necessary, an arbitrarily small offset should cause # normal up/down rounding always. - # Calculate the expecte pattern: + # Calculate the expected pattern: cmp_patterns = f16s_patterns[1:-1].copy() if shift == "down" and offset != "up": diff --git a/numpy/core/tests/test_nditer.py b/numpy/core/tests/test_nditer.py index 26fd9c346..9499bedec 100644 --- a/numpy/core/tests/test_nditer.py +++ b/numpy/core/tests/test_nditer.py @@ -2292,7 +2292,7 @@ class TestIterNested(object): assert_equal(vals, [[0, 1, 2], [3, 4, 5]]) vals = None - # writebackifcopy - using conext manager + # writebackifcopy - using context manager a = arange(6, dtype='f4').reshape(2, 3) i, j = np.nested_iters(a, [[0], [1]], op_flags=['readwrite', 'updateifcopy'], diff --git a/numpy/core/tests/test_scalar_methods.py b/numpy/core/tests/test_scalar_methods.py index 0e4ac5f39..93434dd1b 100644 --- a/numpy/core/tests/test_scalar_methods.py +++ b/numpy/core/tests/test_scalar_methods.py @@ -64,7 +64,7 @@ class TestAsIntegerRatio(object): R(*np.double(2.1).as_integer_ratio())) assert_equal(R(-4728779608739021, 2251799813685248), R(*np.double(-2.1).as_integer_ratio())) - # longdouble is platform depedent + # longdouble is platform dependent @pytest.mark.parametrize("ftype, frac_vals, exp_vals", [ # dtype test cases generated using hypothesis diff --git a/numpy/core/tests/test_scalarprint.py b/numpy/core/tests/test_scalarprint.py index cde1355aa..86b0ca199 100644 --- a/numpy/core/tests/test_scalarprint.py +++ b/numpy/core/tests/test_scalarprint.py @@ -51,7 +51,7 @@ class TestRealScalars(object): def test_py2_float_print(self): # gh-10753 - # In python2, the python float type implements an obsolte method + # In python2, the python float type implements an obsolete method # tp_print, which overrides tp_repr and tp_str when using "print" to # output to a "real file" (ie, not a StringIO). Make sure we don't # inherit it. diff --git a/numpy/distutils/fcompiler/__init__.py b/numpy/distutils/fcompiler/__init__.py index 98c2840ab..3723470f3 100644 --- a/numpy/distutils/fcompiler/__init__.py +++ b/numpy/distutils/fcompiler/__init__.py @@ -484,11 +484,11 @@ class FCompiler(CCompiler): # XXX Assuming that free format is default for f90 compiler. fix = self.command_vars.compiler_fix # NOTE: this and similar examples are probably just - # exluding --coverage flag when F90 = gfortran --coverage + # excluding --coverage flag when F90 = gfortran --coverage # instead of putting that flag somewhere more appropriate # this and similar examples where a Fortran compiler # environment variable has been customized by CI or a user - # should perhaps eventually be more throughly tested and more + # should perhaps eventually be more thoroughly tested and more # robustly handled if fix: fix = _shell_utils.NativeParser.split(fix) diff --git a/numpy/doc/basics.py b/numpy/doc/basics.py index 61f5bf4ef..7946c6432 100644 --- a/numpy/doc/basics.py +++ b/numpy/doc/basics.py @@ -276,7 +276,7 @@ but gives 1874919424 (incorrect) for a 32-bit integer. The behaviour of NumPy and Python integer types differs significantly for integer overflows and may confuse users expecting NumPy integers to behave similar to Python's ``int``. Unlike NumPy, the size of Python's ``int`` is -flexible. This means Python integers may expand to accomodate any integer and +flexible. This means Python integers may expand to accommodate any integer and will not overflow. NumPy provides `numpy.iinfo` and `numpy.finfo` to verify the diff --git a/numpy/doc/indexing.py b/numpy/doc/indexing.py index b752582c2..676015668 100644 --- a/numpy/doc/indexing.py +++ b/numpy/doc/indexing.py @@ -1,4 +1,5 @@ -"""============== +""" +============== Array indexing ============== @@ -107,7 +108,7 @@ arrays and thus greatly improve performance. It is possible to use special features to effectively increase the number of dimensions in an array through indexing so the resulting -array aquires the shape needed for use in an expression or with a +array acquires the shape needed for use in an expression or with a specific function. Index arrays diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py index 2a6d39abc..fabb87adc 100644 --- a/numpy/lib/function_base.py +++ b/numpy/lib/function_base.py @@ -1,7 +1,7 @@ from __future__ import division, absolute_import, print_function try: - # Accessing collections abstact classes from collections + # Accessing collections abstract classes from collections # has been deprecated since Python 3.3 import collections.abc as collections_abc except ImportError: @@ -4341,7 +4341,7 @@ def delete(arr, obj, axis=None): else: slobj[axis] = slice(None, start) new[tuple(slobj)] = arr[tuple(slobj)] - # copy end chunck + # copy end chunk if stop == N: pass else: diff --git a/numpy/lib/recfunctions.py b/numpy/lib/recfunctions.py index 08a9cf09c..fabb509ab 100644 --- a/numpy/lib/recfunctions.py +++ b/numpy/lib/recfunctions.py @@ -146,7 +146,7 @@ def get_names(adtype): def get_names_flat(adtype): """ Returns the field names of the input datatype as a tuple. Nested structure - are flattend beforehand. + are flattened beforehand. Parameters ---------- diff --git a/numpy/lib/tests/test_histograms.py b/numpy/lib/tests/test_histograms.py index afaa526af..4895a722c 100644 --- a/numpy/lib/tests/test_histograms.py +++ b/numpy/lib/tests/test_histograms.py @@ -798,7 +798,7 @@ class TestHistogramdd(object): hist, edges = histogramdd((y, x), bins=(y_edges, x_edges)) assert_equal(hist, relative_areas) - # resulting histogram should be uniform, since counts and areas are propotional + # resulting histogram should be uniform, since counts and areas are proportional hist, edges = histogramdd((y, x), bins=(y_edges, x_edges), density=True) assert_equal(hist, 1 / (8*8)) diff --git a/numpy/random/generator.pyx b/numpy/random/generator.pyx index fd93d5efe..cb3df2626 100644 --- a/numpy/random/generator.pyx +++ b/numpy/random/generator.pyx @@ -440,7 +440,7 @@ cdef class Generator: 'when required.') # Implementation detail: the old API used a masked method to generate - # bounded uniform integers. Lemire's method is preferrable since it is + # bounded uniform integers. Lemire's method is preferable since it is # faster. randomgen allows a choice, we will always use the faster one. cdef bint _masked = True diff --git a/numpy/random/mtrand.pyx b/numpy/random/mtrand.pyx index 50c8a0b2f..48ff6b0a6 100644 --- a/numpy/random/mtrand.pyx +++ b/numpy/random/mtrand.pyx @@ -621,7 +621,7 @@ cdef class RandomState: 'ValueError', DeprecationWarning) # Implementation detail: the use a masked method to generate - # bounded uniform integers. Lemire's method is preferrable since it is + # bounded uniform integers. Lemire's method is preferable since it is # faster. randomgen allows a choice, we will always use the slower but # backward compatible one. cdef bint _masked = True diff --git a/numpy/random/src/philox/philox-benchmark.c b/numpy/random/src/philox/philox-benchmark.c index 0cab04cf5..df5814d5f 100644 --- a/numpy/random/src/philox/philox-benchmark.c +++ b/numpy/random/src/philox/philox-benchmark.c @@ -5,7 +5,7 @@ * * gcc philox-benchmark.c -O3 -o philox-benchmark * - * Requres the Random123 directory containing header files to be located in the + * Requires the Random123 directory containing header files to be located in the * same directory (not included). */ #include "Random123/philox.h" diff --git a/numpy/random/src/philox/philox-test-data-gen.c b/numpy/random/src/philox/philox-test-data-gen.c index 442e18b55..a5fcaa690 100644 --- a/numpy/random/src/philox/philox-test-data-gen.c +++ b/numpy/random/src/philox/philox-test-data-gen.c @@ -7,7 +7,7 @@ * gcc philox-test-data-gen.c -o philox-test-data-gen * ./philox-test-data-gen * - * Requres the Random123 directory containing header files to be located in the + * Requires the Random123 directory containing header files to be located in the * same directory (not included). * */ diff --git a/numpy/random/src/threefry/threefry-benchmark.c b/numpy/random/src/threefry/threefry-benchmark.c index 6d6239cd3..5e2cfe844 100644 --- a/numpy/random/src/threefry/threefry-benchmark.c +++ b/numpy/random/src/threefry/threefry-benchmark.c @@ -5,7 +5,7 @@ * * gcc threefry-benchmark.c -O3 -o threefry-benchmark * - * Requres the Random123 directory containing header files to be located in the + * Requires the Random123 directory containing header files to be located in the * same directory (not included). */ #include "Random123/threefry.h" diff --git a/numpy/random/src/threefry/threefry-test-data-gen.c b/numpy/random/src/threefry/threefry-test-data-gen.c index 328eb2575..8514a227e 100644 --- a/numpy/random/src/threefry/threefry-test-data-gen.c +++ b/numpy/random/src/threefry/threefry-test-data-gen.c @@ -8,7 +8,7 @@ * threefry-test-data-gen * ./threefry-test-data-gen * - * Requres the Random123 directory containing header files to be located in the + * Requires the Random123 directory containing header files to be located in the * same directory (not included). * */ diff --git a/numpy/random/src/xoshiro256/xoshiro256-test-data-gen.c b/numpy/random/src/xoshiro256/xoshiro256-test-data-gen.c index 94eeb7346..b5351bf7a 100644 --- a/numpy/random/src/xoshiro256/xoshiro256-test-data-gen.c +++ b/numpy/random/src/xoshiro256/xoshiro256-test-data-gen.c @@ -9,7 +9,7 @@ * ../splitmix64/splitmix64.c -o xoshiro256-test-data-gen * ./xoshiro256-test-data-gen * - * Requres the Random123 directory containing header files to be located in the + * Requires the Random123 directory containing header files to be located in the * same directory (not included). * */ diff --git a/numpy/random/src/xoshiro512/xoshiro512-test-data-gen.c b/numpy/random/src/xoshiro512/xoshiro512-test-data-gen.c index 83e164a51..698923bda 100644 --- a/numpy/random/src/xoshiro512/xoshiro512-test-data-gen.c +++ b/numpy/random/src/xoshiro512/xoshiro512-test-data-gen.c @@ -9,7 +9,7 @@ * ../splitmix64/splitmix64.c -o xoshiro512-test-data-gen * ./xoshiro512-test-data-gen * - * Requres the Random123 directory containing header files to be located in the + * Requires the Random123 directory containing header files to be located in the * same directory (not included). * */ diff --git a/numpy/random/tests/test_randomstate.py b/numpy/random/tests/test_randomstate.py index 5e2b93f52..d8a07e8b2 100644 --- a/numpy/random/tests/test_randomstate.py +++ b/numpy/random/tests/test_randomstate.py @@ -1903,7 +1903,7 @@ class TestSingleEltArrayInput(object): assert_equal(out.shape, self.tgtShape) -# Ensure returned array dtype is corect for platform +# Ensure returned array dtype is correct for platform def test_integer_dtype(int_func): random.seed(123456789) fname, args, md5 = int_func diff --git a/numpy/testing/_private/utils.py b/numpy/testing/_private/utils.py index 53181bc49..ead5d264d 100644 --- a/numpy/testing/_private/utils.py +++ b/numpy/testing/_private/utils.py @@ -708,7 +708,7 @@ def assert_array_compare(comparison, x, y, err_msg='', verbose=True, x = array(x, copy=False, subok=True) y = array(y, copy=False, subok=True) - # original array for output formating + # original array for output formatting ox, oy = x, y def isnumber(x): @@ -733,7 +733,7 @@ def assert_array_compare(comparison, x, y, err_msg='', verbose=True, # (2) __eq__ on some ndarray subclasses returns Python booleans # instead of element-wise comparisons, so we cast to bool_() and # use isinstance(..., bool) checks - # (3) subclasses with bare-bones __array_function__ implemenations may + # (3) subclasses with bare-bones __array_function__ implementations may # not implement np.all(), so favor using the .all() method # We are not committed to supporting such subclasses, but it's nice to # support them if possible. |