diff options
Diffstat (limited to 'numpy/lib/recfunctions.py')
| -rw-r--r-- | numpy/lib/recfunctions.py | 30 |
1 files changed, 17 insertions, 13 deletions
diff --git a/numpy/lib/recfunctions.py b/numpy/lib/recfunctions.py index a11d5f2c7..ee4fbcd74 100644 --- a/numpy/lib/recfunctions.py +++ b/numpy/lib/recfunctions.py @@ -513,7 +513,7 @@ def drop_fields(base, drop_names, usemask=True, asrecarray=False): Nested fields are supported. - ..versionchanged: 1.18.0 + .. versionchanged:: 1.18.0 `drop_fields` returns an array with 0 fields if all fields are dropped, rather than returning ``None`` as it did previously. @@ -784,7 +784,8 @@ def repack_fields(a, align=False, recurse=False): This method removes any overlaps and reorders the fields in memory so they have increasing byte offsets, and adds or removes padding bytes depending - on the `align` option, which behaves like the `align` option to `np.dtype`. + on the `align` option, which behaves like the `align` option to + `numpy.dtype`. If `align=False`, this method produces a "packed" memory layout in which each field starts at the byte the previous field ended, and any padding @@ -819,7 +820,8 @@ def repack_fields(a, align=False, recurse=False): ... >>> dt = np.dtype('u1, <i8, <f8', align=True) >>> dt - dtype({'names':['f0','f1','f2'], 'formats':['u1','<i8','<f8'], 'offsets':[0,8,16], 'itemsize':24}, align=True) + dtype({'names': ['f0', 'f1', 'f2'], 'formats': ['u1', '<i8', '<f8'], \ +'offsets': [0, 8, 16], 'itemsize': 24}, align=True) >>> print_offsets(dt) offsets: [0, 8, 16] itemsize: 24 @@ -899,7 +901,7 @@ def _structured_to_unstructured_dispatcher(arr, dtype=None, copy=None, @array_function_dispatch(_structured_to_unstructured_dispatcher) def structured_to_unstructured(arr, dtype=None, copy=False, casting='unsafe'): """ - Converts and n-D structured array into an (n+1)-D unstructured array. + Converts an n-D structured array into an (n+1)-D unstructured array. The new array will have a new last dimension equal in size to the number of field-elements of the input array. If not supplied, the output @@ -916,11 +918,12 @@ def structured_to_unstructured(arr, dtype=None, copy=False, casting='unsafe'): dtype : dtype, optional The dtype of the output unstructured array. copy : bool, optional - See copy argument to `ndarray.astype`. If true, always return a copy. - If false, and `dtype` requirements are satisfied, a view is returned. + See copy argument to `numpy.ndarray.astype`. If true, always return a + copy. If false, and `dtype` requirements are satisfied, a view is + returned. casting : {'no', 'equiv', 'safe', 'same_kind', 'unsafe'}, optional - See casting argument of `ndarray.astype`. Controls what kind of data - casting may occur. + See casting argument of `numpy.ndarray.astype`. Controls what kind of + data casting may occur. Returns ------- @@ -996,7 +999,7 @@ def _unstructured_to_structured_dispatcher(arr, dtype=None, names=None, def unstructured_to_structured(arr, dtype=None, names=None, align=False, copy=False, casting='unsafe'): """ - Converts and n-D unstructured array into an (n-1)-D structured array. + Converts an n-D unstructured array into an (n-1)-D structured array. The last dimension of the input array is converted into a structure, with number of field-elements equal to the size of the last dimension of the @@ -1019,11 +1022,12 @@ def unstructured_to_structured(arr, dtype=None, names=None, align=False, align : boolean, optional Whether to create an aligned memory layout. copy : bool, optional - See copy argument to `ndarray.astype`. If true, always return a copy. - If false, and `dtype` requirements are satisfied, a view is returned. + See copy argument to `numpy.ndarray.astype`. If true, always return a + copy. If false, and `dtype` requirements are satisfied, a view is + returned. casting : {'no', 'equiv', 'safe', 'same_kind', 'unsafe'}, optional - See casting argument of `ndarray.astype`. Controls what kind of data - casting may occur. + See casting argument of `numpy.ndarray.astype`. Controls what kind of + data casting may occur. Returns ------- |