diff options
Diffstat (limited to 'numpy/core/src')
23 files changed, 39 insertions, 39 deletions
diff --git a/numpy/core/src/_simd/_simd_inc.h.src b/numpy/core/src/_simd/_simd_inc.h.src index 9858fc0dc..fbdf982c2 100644 --- a/numpy/core/src/_simd/_simd_inc.h.src +++ b/numpy/core/src/_simd/_simd_inc.h.src @@ -113,7 +113,7 @@ typedef struct int is_scalar:1; // returns '1' if the type represent a vector int is_vector:1; - // returns the len of multi-vector if the type reprsent x2 or x3 vector + // returns the len of multi-vector if the type represent x2 or x3 vector // otherwise returns 0, e.g. returns 2 if data type is simd_data_vu8x2 int is_vectorx; // returns the equivalent scalar data type e.g. simd_data_vu8 -> simd_data_u8 diff --git a/numpy/core/src/common/npy_cpu_dispatch.h b/numpy/core/src/common/npy_cpu_dispatch.h index 8c2b40c27..e814cd425 100644 --- a/numpy/core/src/common/npy_cpu_dispatch.h +++ b/numpy/core/src/common/npy_cpu_dispatch.h @@ -196,7 +196,7 @@ * Example: * Assume we have a dispatch-able source exporting the following function: * - * @targets baseline avx2 avx512_skx // configration statements + * @targets baseline avx2 avx512_skx // configuration statements * * void NPY_CPU_DISPATCH_CURFX(dispatch_me)(const int *src, int *dst) * { diff --git a/numpy/core/src/common/npy_cpu_features.c.src b/numpy/core/src/common/npy_cpu_features.c.src index 1e0f4a571..a2383c45f 100644 --- a/numpy/core/src/common/npy_cpu_features.c.src +++ b/numpy/core/src/common/npy_cpu_features.c.src @@ -230,7 +230,7 @@ npy__cpu_try_disable_env(void) notsupp_cur[flen] = ' '; notsupp_cur += flen + 1; goto next; } - // Finaly we can disable it + // Finally we can disable it npy__cpu_have[feature_id] = 0; next: feature = strtok(NULL, delim); diff --git a/numpy/core/src/common/npy_cpuinfo_parser.h b/numpy/core/src/common/npy_cpuinfo_parser.h index 9e85e3a2f..364873a23 100644 --- a/numpy/core/src/common/npy_cpuinfo_parser.h +++ b/numpy/core/src/common/npy_cpuinfo_parser.h @@ -123,7 +123,7 @@ read_file(const char* pathname, char* buffer, size_t buffsize) } /* - * Extract the content of a the first occurence of a given field in + * Extract the content of a the first occurrence of a given field in * the content of /proc/cpuinfo and return it as a heap-allocated * string that must be freed by the caller. * @@ -138,7 +138,7 @@ extract_cpuinfo_field(const char* buffer, int buflen, const char* field) int len; const char *p, *q; - /* Look for first field occurence, and ensures it starts the line. */ + /* Look for first field occurrence, and ensures it starts the line. */ p = buffer; for (;;) { p = memmem(p, bufend-p, field, fieldlen); diff --git a/numpy/core/src/common/simd/emulate_maskop.h b/numpy/core/src/common/simd/emulate_maskop.h index 7e7446bc5..41e397c2d 100644 --- a/numpy/core/src/common/simd/emulate_maskop.h +++ b/numpy/core/src/common/simd/emulate_maskop.h @@ -1,5 +1,5 @@ /** - * This header is used internaly by all current supported SIMD extention, + * This header is used internally by all current supported SIMD extensions, * execpt for AVX512. */ #ifndef NPY_SIMD diff --git a/numpy/core/src/common/simd/intdiv.h b/numpy/core/src/common/simd/intdiv.h index f6ea9abf2..5d2ab2906 100644 --- a/numpy/core/src/common/simd/intdiv.h +++ b/numpy/core/src/common/simd/intdiv.h @@ -39,7 +39,7 @@ * for (; len >= vstep; src += vstep, dst += vstep, len -= vstep) { * npyv_s32 a = npyv_load_s32(*src); // load s32 vector from memory * a = npyv_divc_s32(a, divisor); // divide all elements by x - * npyv_store_s32(dst, a); // store s32 vector into memroy + * npyv_store_s32(dst, a); // store s32 vector into memory * } * ** NOTES: diff --git a/numpy/core/src/common/simd/neon/math.h b/numpy/core/src/common/simd/neon/math.h index ced82d1de..19ea6f22f 100644 --- a/numpy/core/src/common/simd/neon/math.h +++ b/numpy/core/src/common/simd/neon/math.h @@ -31,7 +31,7 @@ NPY_FINLINE npyv_f32 npyv_square_f32(npyv_f32 a) const npyv_f32 zero = vdupq_n_f32(0.0f); const npyv_u32 pinf = vdupq_n_u32(0x7f800000); npyv_u32 is_zero = vceqq_f32(a, zero), is_inf = vceqq_u32(vreinterpretq_u32_f32(a), pinf); - // guard agianst floating-point division-by-zero error + // guard against floating-point division-by-zero error npyv_f32 guard_byz = vbslq_f32(is_zero, vreinterpretq_f32_u32(pinf), a); // estimate to (1/√a) npyv_f32 rsqrte = vrsqrteq_f32(guard_byz); diff --git a/numpy/core/src/common/simd/vsx/operators.h b/numpy/core/src/common/simd/vsx/operators.h index 23c5d0dbe..d34057ff3 100644 --- a/numpy/core/src/common/simd/vsx/operators.h +++ b/numpy/core/src/common/simd/vsx/operators.h @@ -103,7 +103,7 @@ NPYV_IMPL_VSX_BIN_B64(or) NPYV_IMPL_VSX_BIN_B64(xor) // NOT -// note: we implement npyv_not_b*(boolen types) for internal use*/ +// note: we implement npyv_not_b*(boolean types) for internal use*/ #define NPYV_IMPL_VSX_NOT_INT(VEC_LEN) \ NPY_FINLINE npyv_u##VEC_LEN npyv_not_u##VEC_LEN(npyv_u##VEC_LEN a) \ { return vec_nor(a, a); } \ diff --git a/numpy/core/src/multiarray/abstractdtypes.c b/numpy/core/src/multiarray/abstractdtypes.c index 99573f089..cc1d7fad8 100644 --- a/numpy/core/src/multiarray/abstractdtypes.c +++ b/numpy/core/src/multiarray/abstractdtypes.c @@ -157,7 +157,7 @@ int_common_dtype(PyArray_DTypeMeta *NPY_UNUSED(cls), PyArray_DTypeMeta *other) } else if (PyTypeNum_ISNUMBER(other->type_num) || other->type_num == NPY_TIMEDELTA) { - /* All other numeric types (ant timdelta) are preserved: */ + /* All other numeric types (ant timedelta) are preserved: */ Py_INCREF(other); return other; } diff --git a/numpy/core/src/multiarray/array_coercion.c b/numpy/core/src/multiarray/array_coercion.c index 90b50097a..847bdafc3 100644 --- a/numpy/core/src/multiarray/array_coercion.c +++ b/numpy/core/src/multiarray/array_coercion.c @@ -136,7 +136,7 @@ _prime_global_pytype_to_type_dict(void) * * This assumes that the DType class is guaranteed to hold on the * python type (this assumption is guaranteed). - * This functionality supercedes ``_typenum_fromtypeobj``. + * This functionality supersedes ``_typenum_fromtypeobj``. * * @param DType DType to map the python type to * @param pytype Python type to map from @@ -1400,7 +1400,7 @@ PyArray_DiscoverDTypeAndShape( * These should be largely deprecated, and represent only the DType class * for most `dtype` parameters. * - * TODO: This function should eventually recieve a deprecation warning and + * TODO: This function should eventually receive a deprecation warning and * be removed. * * @param descr diff --git a/numpy/core/src/multiarray/arrayobject.c b/numpy/core/src/multiarray/arrayobject.c index d653bfc22..9b9df08f2 100644 --- a/numpy/core/src/multiarray/arrayobject.c +++ b/numpy/core/src/multiarray/arrayobject.c @@ -858,7 +858,7 @@ _uni_release(char *ptr, int nc) relfunc(aptr, N1); \ return -1; \ } \ - val = compfunc(aptr, bptr, N1, N2); \ + val = compfunc(aptr, bptr, N1, N2); \ *dptr = (val CMP 0); \ PyArray_ITER_NEXT(iself); \ PyArray_ITER_NEXT(iother); \ @@ -870,7 +870,7 @@ _uni_release(char *ptr, int nc) #define _reg_loop(CMP) { \ while(size--) { \ - val = compfunc((void *)iself->dataptr, \ + val = compfunc((void *)iself->dataptr, \ (void *)iother->dataptr, \ N1, N2); \ *dptr = (val CMP 0); \ diff --git a/numpy/core/src/multiarray/convert_datatype.c b/numpy/core/src/multiarray/convert_datatype.c index b6755e91d..12dd99504 100644 --- a/numpy/core/src/multiarray/convert_datatype.c +++ b/numpy/core/src/multiarray/convert_datatype.c @@ -1649,7 +1649,7 @@ PyArray_ResultType( } Py_INCREF(all_DTypes[i_all]); /* - * Leave the decriptor empty, if we need it, we will have to go + * Leave the descriptor empty, if we need it, we will have to go * to more extreme lengths unfortunately. */ all_descriptors[i_all] = NULL; @@ -2243,7 +2243,7 @@ PyArray_AddCastingImplementation(PyBoundArrayMethodObject *meth) * Add a new casting implementation using a PyArrayMethod_Spec. * * @param spec - * @param private If private, allow slots not publically exposed. + * @param private If private, allow slots not publicly exposed. * @return 0 on success -1 on failure */ NPY_NO_EXPORT int diff --git a/numpy/core/src/multiarray/datetime.c b/numpy/core/src/multiarray/datetime.c index 093090b4c..11a941e72 100644 --- a/numpy/core/src/multiarray/datetime.c +++ b/numpy/core/src/multiarray/datetime.c @@ -427,7 +427,7 @@ PyArray_DatetimeStructToDatetime( } /*NUMPY_API - * Create a timdelta value from a filled timedelta struct and resolution unit. + * Create a timedelta value from a filled timedelta struct and resolution unit. * * TO BE REMOVED - NOT USED INTERNALLY. */ diff --git a/numpy/core/src/multiarray/dtypemeta.c b/numpy/core/src/multiarray/dtypemeta.c index 059ec201e..cbde91b76 100644 --- a/numpy/core/src/multiarray/dtypemeta.c +++ b/numpy/core/src/multiarray/dtypemeta.c @@ -101,7 +101,7 @@ static PyObject * legacy_dtype_default_new(PyArray_DTypeMeta *self, PyObject *args, PyObject *kwargs) { - /* TODO: This should allow endianess and possibly metadata */ + /* TODO: This should allow endianness and possibly metadata */ if (NPY_DT_is_parametric(self)) { /* reject parametric ones since we would need to get unit, etc. info */ PyErr_Format(PyExc_TypeError, diff --git a/numpy/core/src/multiarray/einsum_sumprod.c.src b/numpy/core/src/multiarray/einsum_sumprod.c.src index 333b8e188..29ceabd71 100644 --- a/numpy/core/src/multiarray/einsum_sumprod.c.src +++ b/numpy/core/src/multiarray/einsum_sumprod.c.src @@ -80,7 +80,7 @@ static NPY_GCC_OPT_3 @temptype@ @name@_sum_of_arr(@type@ *data, npy_intp count) /* Use aligned instructions if possible */ const int is_aligned = EINSUM_IS_ALIGNED(data); const int vstep = npyv_nlanes_@sfx@; - npyv_@sfx@ vaccum = npyv_zero_@sfx@(); + npyv_@sfx@ v_accum = npyv_zero_@sfx@(); const npy_intp vstepx4 = vstep * 4; /**begin repeat1 @@ -98,15 +98,15 @@ static NPY_GCC_OPT_3 @temptype@ @name@_sum_of_arr(@type@ *data, npy_intp count) npyv_@sfx@ a01 = npyv_add_@sfx@(a0, a1); npyv_@sfx@ a23 = npyv_add_@sfx@(a2, a3); npyv_@sfx@ a0123 = npyv_add_@sfx@(a01, a23); - vaccum = npyv_add_@sfx@(a0123, vaccum); + v_accum = npyv_add_@sfx@(a0123, v_accum); } } /**end repeat1**/ for (; count > 0; count -= vstep, data += vstep) { npyv_@sfx@ a = npyv_load_tillz_@sfx@(data, count); - vaccum = npyv_add_@sfx@(a, vaccum); + v_accum = npyv_add_@sfx@(a, v_accum); } - accum = npyv_sum_@sfx@(vaccum); + accum = npyv_sum_@sfx@(v_accum); npyv_cleanup(); #else #ifndef NPY_DISABLE_OPTIMIZATION @@ -485,7 +485,7 @@ static NPY_GCC_OPT_3 void /* Use aligned instructions if possible */ const int is_aligned = EINSUM_IS_ALIGNED(data0) && EINSUM_IS_ALIGNED(data1); const int vstep = npyv_nlanes_@sfx@; - npyv_@sfx@ vaccum = npyv_zero_@sfx@(); + npyv_@sfx@ v_accum = npyv_zero_@sfx@(); /**begin repeat2 * #cond = if(is_aligned), else# @@ -501,19 +501,19 @@ static NPY_GCC_OPT_3 void npyv_@sfx@ a@i@ = npyv_@ld@_@sfx@(data0 + vstep * @i@); npyv_@sfx@ b@i@ = npyv_@ld@_@sfx@(data1 + vstep * @i@); /**end repeat3**/ - npyv_@sfx@ ab3 = npyv_muladd_@sfx@(a3, b3, vaccum); + npyv_@sfx@ ab3 = npyv_muladd_@sfx@(a3, b3, v_accum); npyv_@sfx@ ab2 = npyv_muladd_@sfx@(a2, b2, ab3); npyv_@sfx@ ab1 = npyv_muladd_@sfx@(a1, b1, ab2); - vaccum = npyv_muladd_@sfx@(a0, b0, ab1); + v_accum = npyv_muladd_@sfx@(a0, b0, ab1); } } /**end repeat2**/ for (; count > 0; count -= vstep, data0 += vstep, data1 += vstep) { npyv_@sfx@ a = npyv_load_tillz_@sfx@(data0, count); npyv_@sfx@ b = npyv_load_tillz_@sfx@(data1, count); - vaccum = npyv_muladd_@sfx@(a, b, vaccum); + v_accum = npyv_muladd_@sfx@(a, b, v_accum); } - accum = npyv_sum_@sfx@(vaccum); + accum = npyv_sum_@sfx@(v_accum); npyv_cleanup(); #else #ifndef NPY_DISABLE_OPTIMIZATION diff --git a/numpy/core/src/multiarray/lowlevel_strided_loops.c.src b/numpy/core/src/multiarray/lowlevel_strided_loops.c.src index b32664cc9..e313d2447 100644 --- a/numpy/core/src/multiarray/lowlevel_strided_loops.c.src +++ b/numpy/core/src/multiarray/lowlevel_strided_loops.c.src @@ -1849,7 +1849,7 @@ mapiter_@name@(PyArrayMapIterObject *mit) return -1; } #else - /* The operand order is reveresed here */ + /* The operand order is reversed here */ char *args[2] = {subspace_ptrs[1], subspace_ptrs[0]}; npy_intp strides[2] = {subspace_strides[1], subspace_strides[0]}; if (NPY_UNLIKELY(cast_info.func(&cast_info.context, diff --git a/numpy/core/src/multiarray/nditer_api.c b/numpy/core/src/multiarray/nditer_api.c index 811eece7d..0f0a79ddf 100644 --- a/numpy/core/src/multiarray/nditer_api.c +++ b/numpy/core/src/multiarray/nditer_api.c @@ -2130,7 +2130,7 @@ npyiter_copy_to_buffers(NpyIter *iter, char **prev_dataptrs) /* * Try to do make the outersize as big as possible. This allows * it to shrink when processing the last bit of the outer reduce loop, - * then grow again at the beginnning of the next outer reduce loop. + * then grow again at the beginning of the next outer reduce loop. */ NBF_REDUCE_OUTERSIZE(bufferdata) = (NAD_SHAPE(reduce_outeraxisdata)- NAD_INDEX(reduce_outeraxisdata)); @@ -2804,9 +2804,9 @@ npyiter_checkreducesize(NpyIter *iter, npy_intp count, if (coord != 0) { /* * In this case, it is only safe to reuse the buffer if the amount - * of data copied is not more then the current axes, as is the + * of data copied is not more than the current axes, as is the * case when reuse_reduce_loops was active already. - * It should be in principle OK when the idim loop returns immidiatly. + * It should be in principle OK when the idim loop returns immediately. */ NIT_ITFLAGS(iter) &= ~NPY_ITFLAG_REUSE_REDUCE_LOOPS; } diff --git a/numpy/core/src/multiarray/nditer_constr.c b/numpy/core/src/multiarray/nditer_constr.c index 57dbb3a94..bf32e1f6b 100644 --- a/numpy/core/src/multiarray/nditer_constr.c +++ b/numpy/core/src/multiarray/nditer_constr.c @@ -1405,7 +1405,7 @@ check_mask_for_writemasked_reduction(NpyIter *iter, int iop) /* * Check whether a reduction is OK based on the flags and the operand being * readwrite. This path is deprecated, since usually only specific axes - * should be reduced. If axes are specified explicitely, the flag is + * should be reduced. If axes are specified explicitly, the flag is * unnecessary. */ static int diff --git a/numpy/core/src/multiarray/nditer_templ.c.src b/numpy/core/src/multiarray/nditer_templ.c.src index 05ce6ae75..3f91a482b 100644 --- a/numpy/core/src/multiarray/nditer_templ.c.src +++ b/numpy/core/src/multiarray/nditer_templ.c.src @@ -132,7 +132,7 @@ npyiter_iternext_itflags@tag_itflags@_dims@tag_ndim@_iters@tag_nop@( /* Reset the 1st and 2nd indices to 0 */ NAD_INDEX(axisdata0) = 0; NAD_INDEX(axisdata1) = 0; - /* Reset the 1st and 2nd pointers to the value of the 3nd */ + /* Reset the 1st and 2nd pointers to the value of the 3rd */ for (istrides = 0; istrides < nstrides; ++istrides) { NAD_PTRS(axisdata0)[istrides] = NAD_PTRS(axisdata2)[istrides]; NAD_PTRS(axisdata1)[istrides] = NAD_PTRS(axisdata2)[istrides]; diff --git a/numpy/core/src/umath/_scaled_float_dtype.c b/numpy/core/src/umath/_scaled_float_dtype.c index 866f636a0..eeef33a3d 100644 --- a/numpy/core/src/umath/_scaled_float_dtype.c +++ b/numpy/core/src/umath/_scaled_float_dtype.c @@ -733,9 +733,9 @@ NPY_NO_EXPORT PyObject * get_sfloat_dtype(PyObject *NPY_UNUSED(mod), PyObject *NPY_UNUSED(args)) { /* Allow calling the function multiple times. */ - static npy_bool initalized = NPY_FALSE; + static npy_bool initialized = NPY_FALSE; - if (initalized) { + if (initialized) { Py_INCREF(&PyArray_SFloatDType); return (PyObject *)&PyArray_SFloatDType; } @@ -764,6 +764,6 @@ get_sfloat_dtype(PyObject *NPY_UNUSED(mod), PyObject *NPY_UNUSED(args)) return NULL; } - initalized = NPY_TRUE; + initialized = NPY_TRUE; return (PyObject *)&PyArray_SFloatDType; } diff --git a/numpy/core/src/umath/_umath_tests.c.src b/numpy/core/src/umath/_umath_tests.c.src index 0cd673831..ed4c617a4 100644 --- a/numpy/core/src/umath/_umath_tests.c.src +++ b/numpy/core/src/umath/_umath_tests.c.src @@ -586,7 +586,7 @@ fail: return NULL; } -// Testing the utilites of the CPU dispatcher +// Testing the utilities of the CPU dispatcher #ifndef NPY_DISABLE_OPTIMIZATION #include "_umath_tests.dispatch.h" #endif diff --git a/numpy/core/src/umath/_umath_tests.dispatch.c b/numpy/core/src/umath/_umath_tests.dispatch.c index 66058550e..9d8df4c86 100644 --- a/numpy/core/src/umath/_umath_tests.dispatch.c +++ b/numpy/core/src/umath/_umath_tests.dispatch.c @@ -1,5 +1,5 @@ /** - * Testing the utilites of the CPU dispatcher + * Testing the utilities of the CPU dispatcher * * @targets $werror baseline * SSE2 SSE41 AVX2 diff --git a/numpy/core/src/umath/loops_utils.h.src b/numpy/core/src/umath/loops_utils.h.src index 1a2a5a32b..762e9ee59 100644 --- a/numpy/core/src/umath/loops_utils.h.src +++ b/numpy/core/src/umath/loops_utils.h.src @@ -6,7 +6,7 @@ /** * Old versions of MSVC causes ambiguous link errors when we deal with large SIMD kernels - * which lead to break the build, probably releated to the following bug: + * which lead to break the build, probably related to the following bug: * https://developercommunity.visualstudio.com/content/problem/415095/internal-compiler-error-with-perfectly-forwarded-r.html */ #if defined(_MSC_VER) && _MSC_VER < 1916 |