Merge pull request #20784 from DimitriPapadopoulos/codespell

MAINT, DOC: fix new typos detected by codespell

6 files changed, 7 insertions, 7 deletions

diff --git a/numpy/core/_add_newdocs.py b/numpy/core/_add_newdocs.py
index 219383e1e..a800143a8 100644
--- a/numpy/core/_add_newdocs.py
+++ b/numpy/core/_add_newdocs.py
@@ -833,7 +833,7 @@ add_newdoc('numpy.core.multiarray', 'array',
         the returned array will be forced to be a base-class array (default).
     ndmin : int, optional
         Specifies the minimum number of dimensions that the resulting
-        array should have.  Ones will be pre-pended to the shape as
+        array should have.  Ones will be prepended to the shape as
         needed to meet this requirement.
     ${ARRAY_FUNCTION_LIKE}
 
@@ -4097,7 +4097,7 @@ add_newdoc('numpy.core.multiarray', 'ndarray', ('partition',
 
     See Also
     --------
-    numpy.partition : Return a parititioned copy of an array.
+    numpy.partition : Return a partitioned copy of an array.
     argpartition : Indirect partition.
     sort : Full sort.
 
diff --git a/numpy/core/include/numpy/experimental_dtype_api.h b/numpy/core/include/numpy/experimental_dtype_api.h
index 83639f186..88565cd52 100644
--- a/numpy/core/include/numpy/experimental_dtype_api.h
+++ b/numpy/core/include/numpy/experimental_dtype_api.h
@@ -141,7 +141,7 @@ typedef struct {
  * NOTE: Expected changes:
  *       * invert logic of floating point error flag
  *       * probably split runtime and general flags into two
- *       * should possibly not use an enum for typdef for more stable ABI?
+ *       * should possibly not use an enum for typedef for more stable ABI?
  */
 typedef enum {
     /* Flag for whether the GIL is required */
diff --git a/numpy/core/src/common/simd/vsx/vsx.h b/numpy/core/src/common/simd/vsx/vsx.h
index 66b76208f..b4d8172a2 100644
--- a/numpy/core/src/common/simd/vsx/vsx.h
+++ b/numpy/core/src/common/simd/vsx/vsx.h
@@ -61,7 +61,7 @@ typedef struct { npyv_f64 val[3]; } npyv_f64x3;
 #define npyv_nlanes_f32 4
 #define npyv_nlanes_f64 2
 
-// using __bool with typdef cause ambiguous errors
+// using __bool with typedef cause ambiguous errors
 #define npyv_b8  __vector __bool char
 #define npyv_b16 __vector __bool short
 #define npyv_b32 __vector __bool int
diff --git a/numpy/core/src/umath/reduction.c b/numpy/core/src/umath/reduction.c
index 8cb44d433..8c4df6e02 100644
--- a/numpy/core/src/umath/reduction.c
+++ b/numpy/core/src/umath/reduction.c
@@ -337,7 +337,7 @@ PyUFunc_ReduceWrapper(PyArrayMethod_Context *context,
 
     /*
      * Note that we need to ensure that the iterator is reset before getting
-     * the fixed strides.  (The buffer information is unitialized before.)
+     * the fixed strides.  (The buffer information is uninitialized before.)
      */
     npy_intp fixed_strides[3];
     NpyIter_GetInnerFixedStrideArray(iter, fixed_strides);
diff --git a/numpy/core/src/umath/ufunc_object.c b/numpy/core/src/umath/ufunc_object.c
index 2674c85d9..7b0db9e04 100644
--- a/numpy/core/src/umath/ufunc_object.c
+++ b/numpy/core/src/umath/ufunc_object.c
@@ -2704,7 +2704,7 @@ PyUFunc_GenericFunction(PyUFuncObject *NPY_UNUSED(ufunc),
  * @param out_descrs New references to the resolved descriptors (on success).
  * @param method The ufunc method, "reduce", "reduceat", or "accumulate".
 
- * @returns ufuncimpl The `ArrayMethod` implemention to use. Or NULL if an
+ * @returns ufuncimpl The `ArrayMethod` implementation to use. Or NULL if an
  *          error occurred.
  */
 static PyArrayMethodObject *
diff --git a/numpy/core/tests/test_api.py b/numpy/core/tests/test_api.py
index d3c7211cd..22a06619c 100644
--- a/numpy/core/tests/test_api.py
+++ b/numpy/core/tests/test_api.py
@@ -144,7 +144,7 @@ def test_array_array():
 
 @pytest.mark.parametrize("array", [True, False])
 def test_array_impossible_casts(array):
-    # All builtin types can forst cast as least theoretically
+    # All builtin types can be forcibly cast, at least theoretically,
     # but user dtypes cannot necessarily.
     rt = rational(1, 2)
     if array: