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-rw-r--r--doc/source/reference/c-api/array.rst (renamed from doc/source/reference/c-api.array.rst)59
-rw-r--r--doc/source/reference/c-api/config.rst (renamed from doc/source/reference/c-api.config.rst)0
-rw-r--r--doc/source/reference/c-api/coremath.rst (renamed from doc/source/reference/c-api.coremath.rst)0
-rw-r--r--doc/source/reference/c-api/deprecations.rst (renamed from doc/source/reference/c-api.deprecations.rst)0
-rw-r--r--doc/source/reference/c-api/dtype.rst (renamed from doc/source/reference/c-api.dtype.rst)0
-rw-r--r--doc/source/reference/c-api/generalized-ufuncs.rst (renamed from doc/source/reference/c-api.generalized-ufuncs.rst)0
-rw-r--r--doc/source/reference/c-api/index.rst (renamed from doc/source/reference/c-api.rst)18
-rw-r--r--doc/source/reference/c-api/iterator.rst (renamed from doc/source/reference/c-api.iterator.rst)0
-rw-r--r--doc/source/reference/c-api/types-and-structures.rst (renamed from doc/source/reference/c-api.types-and-structures.rst)0
-rw-r--r--doc/source/reference/c-api/ufunc.rst (renamed from doc/source/reference/c-api.ufunc.rst)0
-rw-r--r--doc/source/reference/index.rst2
-rw-r--r--numpy/core/setup_common.py2
-rw-r--r--numpy/core/src/multiarray/multiarraymodule.c33
-rw-r--r--numpy/core/src/umath/cpuid.c6
-rw-r--r--numpy/lib/recfunctions.py84
-rw-r--r--numpy/lib/tests/test_recfunctions.py4
16 files changed, 95 insertions, 113 deletions
diff --git a/doc/source/reference/c-api.array.rst b/doc/source/reference/c-api/array.rst
index 3d6246baa..1d9d31b83 100644
--- a/doc/source/reference/c-api.array.rst
+++ b/doc/source/reference/c-api/array.rst
@@ -1578,7 +1578,7 @@ Flag checking
^^^^^^^^^^^^^
For all of these macros *arr* must be an instance of a (subclass of)
-:c:data:`PyArray_Type`, but no checking is done.
+:c:data:`PyArray_Type`.
.. c:function:: PyArray_CHKFLAGS(arr, flags)
@@ -2052,6 +2052,17 @@ Calculation
effect that is obtained by passing in *axis* = :const:`None` in Python
(treating the array as a 1-d array).
+
+.. note::
+
+ The out argument specifies where to place the result. If out is
+ NULL, then the output array is created, otherwise the output is
+ placed in out which must be the correct size and type. A new
+ reference to the output array is always returned even when out
+ is not NULL. The caller of the routine has the responsibility
+ to ``Py_DECREF`` out if not NULL or a memory-leak will occur.
+
+
.. c:function:: PyObject* PyArray_ArgMax( \
PyArrayObject* self, int axis, PyArrayObject* out)
@@ -2064,18 +2075,6 @@ Calculation
Equivalent to :meth:`ndarray.argmin<numpy.ndarray.argmin>` (*self*, *axis*). Return the index of
the smallest element of *self* along *axis*.
-
-
-
-.. note::
-
- The out argument specifies where to place the result. If out is
- NULL, then the output array is created, otherwise the output is
- placed in out which must be the correct size and type. A new
- reference to the output array is always returned even when out
- is not NULL. The caller of the routine has the responsibility
- to ``DECREF`` out if not NULL or a memory-leak will occur.
-
.. c:function:: PyObject* PyArray_Max( \
PyArrayObject* self, int axis, PyArrayObject* out)
@@ -2655,22 +2654,24 @@ cost of a slight overhead.
The mode should be one of:
- * NPY_NEIGHBORHOOD_ITER_ZERO_PADDING: zero padding. Outside bounds values
- will be 0.
- * NPY_NEIGHBORHOOD_ITER_ONE_PADDING: one padding, Outside bounds values
- will be 1.
- * NPY_NEIGHBORHOOD_ITER_CONSTANT_PADDING: constant padding. Outside bounds
- values will be the same as the first item in fill_value.
- * NPY_NEIGHBORHOOD_ITER_MIRROR_PADDING: mirror padding. Outside bounds
- values will be as if the array items were mirrored. For example, for the
- array [1, 2, 3, 4], x[-2] will be 2, x[-2] will be 1, x[4] will be 4,
- x[5] will be 1, etc...
- * NPY_NEIGHBORHOOD_ITER_CIRCULAR_PADDING: circular padding. Outside bounds
- values will be as if the array was repeated. For example, for the
- array [1, 2, 3, 4], x[-2] will be 3, x[-2] will be 4, x[4] will be 1,
- x[5] will be 2, etc...
-
- If the mode is constant filling (NPY_NEIGHBORHOOD_ITER_CONSTANT_PADDING),
+ .. c:macro:: NPY_NEIGHBORHOOD_ITER_ZERO_PADDING
+ Zero padding. Outside bounds values will be 0.
+ .. c:macro:: NPY_NEIGHBORHOOD_ITER_ONE_PADDING
+ One padding, Outside bounds values will be 1.
+ .. c:macro:: NPY_NEIGHBORHOOD_ITER_CONSTANT_PADDING
+ Constant padding. Outside bounds values will be the
+ same as the first item in fill_value.
+ .. c:macro:: NPY_NEIGHBORHOOD_ITER_MIRROR_PADDING
+ Mirror padding. Outside bounds values will be as if the
+ array items were mirrored. For example, for the array [1, 2, 3, 4],
+ x[-2] will be 2, x[-2] will be 1, x[4] will be 4, x[5] will be 1,
+ etc...
+ .. c:macro:: NPY_NEIGHBORHOOD_ITER_CIRCULAR_PADDING
+ Circular padding. Outside bounds values will be as if the array
+ was repeated. For example, for the array [1, 2, 3, 4], x[-2] will
+ be 3, x[-2] will be 4, x[4] will be 1, x[5] will be 2, etc...
+
+ If the mode is constant filling (`NPY_NEIGHBORHOOD_ITER_CONSTANT_PADDING`),
fill_value should point to an array object which holds the filling value
(the first item will be the filling value if the array contains more than
one item). For other cases, fill_value may be NULL.
diff --git a/doc/source/reference/c-api.config.rst b/doc/source/reference/c-api/config.rst
index 05e6fe44d..05e6fe44d 100644
--- a/doc/source/reference/c-api.config.rst
+++ b/doc/source/reference/c-api/config.rst
diff --git a/doc/source/reference/c-api.coremath.rst b/doc/source/reference/c-api/coremath.rst
index 7e00322f9..7e00322f9 100644
--- a/doc/source/reference/c-api.coremath.rst
+++ b/doc/source/reference/c-api/coremath.rst
diff --git a/doc/source/reference/c-api.deprecations.rst b/doc/source/reference/c-api/deprecations.rst
index a382017a2..a382017a2 100644
--- a/doc/source/reference/c-api.deprecations.rst
+++ b/doc/source/reference/c-api/deprecations.rst
diff --git a/doc/source/reference/c-api.dtype.rst b/doc/source/reference/c-api/dtype.rst
index 72e908861..72e908861 100644
--- a/doc/source/reference/c-api.dtype.rst
+++ b/doc/source/reference/c-api/dtype.rst
diff --git a/doc/source/reference/c-api.generalized-ufuncs.rst b/doc/source/reference/c-api/generalized-ufuncs.rst
index b59f077ad..b59f077ad 100644
--- a/doc/source/reference/c-api.generalized-ufuncs.rst
+++ b/doc/source/reference/c-api/generalized-ufuncs.rst
diff --git a/doc/source/reference/c-api.rst b/doc/source/reference/c-api/index.rst
index b8cbe97b2..56fe8e473 100644
--- a/doc/source/reference/c-api.rst
+++ b/doc/source/reference/c-api/index.rst
@@ -40,12 +40,12 @@ code.
.. toctree::
:maxdepth: 2
- c-api.types-and-structures
- c-api.config
- c-api.dtype
- c-api.array
- c-api.iterator
- c-api.ufunc
- c-api.generalized-ufuncs
- c-api.coremath
- c-api.deprecations
+ types-and-structures
+ config
+ dtype
+ array
+ iterator
+ ufunc
+ generalized-ufuncs
+ coremath
+ deprecations
diff --git a/doc/source/reference/c-api.iterator.rst b/doc/source/reference/c-api/iterator.rst
index b77d029cc..b77d029cc 100644
--- a/doc/source/reference/c-api.iterator.rst
+++ b/doc/source/reference/c-api/iterator.rst
diff --git a/doc/source/reference/c-api.types-and-structures.rst b/doc/source/reference/c-api/types-and-structures.rst
index 336dff211..336dff211 100644
--- a/doc/source/reference/c-api.types-and-structures.rst
+++ b/doc/source/reference/c-api/types-and-structures.rst
diff --git a/doc/source/reference/c-api.ufunc.rst b/doc/source/reference/c-api/ufunc.rst
index 92a679510..92a679510 100644
--- a/doc/source/reference/c-api.ufunc.rst
+++ b/doc/source/reference/c-api/ufunc.rst
diff --git a/doc/source/reference/index.rst b/doc/source/reference/index.rst
index 6accb8535..6742d605a 100644
--- a/doc/source/reference/index.rst
+++ b/doc/source/reference/index.rst
@@ -24,7 +24,7 @@ For learning how to use NumPy, see also :ref:`user`.
routines
distutils
distutils_guide
- c-api
+ c-api/index
internals
swig
diff --git a/numpy/core/setup_common.py b/numpy/core/setup_common.py
index bf6abcf02..307fab334 100644
--- a/numpy/core/setup_common.py
+++ b/numpy/core/setup_common.py
@@ -138,6 +138,8 @@ OPTIONAL_INTRINSICS = [("__builtin_isnan", '5.'),
# broken on OSX 10.11, make sure its not optimized away
("volatile int r = __builtin_cpu_supports", '"sse"',
"stdio.h", "__BUILTIN_CPU_SUPPORTS"),
+ ("volatile int r = __builtin_cpu_supports", '"avx512f"',
+ "stdio.h", "__BUILTIN_CPU_SUPPORTS_AVX512F"),
# MMX only needed for icc, but some clangs don't have it
("_m_from_int64", '0', "emmintrin.h"),
("_mm_load_ps", '(float*)0', "xmmintrin.h"), # SSE
diff --git a/numpy/core/src/multiarray/multiarraymodule.c b/numpy/core/src/multiarray/multiarraymodule.c
index e5df6bf1b..bef978c94 100644
--- a/numpy/core/src/multiarray/multiarraymodule.c
+++ b/numpy/core/src/multiarray/multiarraymodule.c
@@ -288,20 +288,10 @@ PyArray_AsCArray(PyObject **op, void *ptr, npy_intp *dims, int nd,
NPY_NO_EXPORT int
PyArray_As1D(PyObject **op, char **ptr, int *d1, int typecode)
{
- npy_intp newd1;
- PyArray_Descr *descr;
- static const char msg[] = "PyArray_As1D: use PyArray_AsCArray.";
-
/* 2008-07-14, 1.5 */
- if (DEPRECATE(msg) < 0) {
- return -1;
- }
- descr = PyArray_DescrFromType(typecode);
- if (PyArray_AsCArray(op, (void *)ptr, &newd1, 1, descr) == -1) {
- return -1;
- }
- *d1 = (int) newd1;
- return 0;
+ PyErr_SetString(PyExc_NotImplementedError,
+ "PyArray_As1D: use PyArray_AsCArray.");
+ return -1;
}
/*NUMPY_API
@@ -310,21 +300,10 @@ PyArray_As1D(PyObject **op, char **ptr, int *d1, int typecode)
NPY_NO_EXPORT int
PyArray_As2D(PyObject **op, char ***ptr, int *d1, int *d2, int typecode)
{
- npy_intp newdims[2];
- PyArray_Descr *descr;
- static const char msg[] = "PyArray_As1D: use PyArray_AsCArray.";
-
/* 2008-07-14, 1.5 */
- if (DEPRECATE(msg) < 0) {
- return -1;
- }
- descr = PyArray_DescrFromType(typecode);
- if (PyArray_AsCArray(op, (void *)ptr, newdims, 2, descr) == -1) {
- return -1;
- }
- *d1 = (int ) newdims[0];
- *d2 = (int ) newdims[1];
- return 0;
+ PyErr_SetString(PyExc_NotImplementedError,
+ "PyArray_As2D: use PyArray_AsCArray.");
+ return -1;
}
/* End Deprecated */
diff --git a/numpy/core/src/umath/cpuid.c b/numpy/core/src/umath/cpuid.c
index 51c540457..8673f1736 100644
--- a/numpy/core/src/umath/cpuid.c
+++ b/numpy/core/src/umath/cpuid.c
@@ -57,10 +57,10 @@ npy_cpu_supports(const char * feature)
{
#ifdef HAVE___BUILTIN_CPU_SUPPORTS
if (strcmp(feature, "avx512f") == 0) {
-#if defined(__GNUC__) && (__GNUC__ < 5)
- return 0;
-#else
+#ifdef HAVE___BUILTIN_CPU_SUPPORTS_AVX512F
return __builtin_cpu_supports("avx512f") && os_avx512_support();
+#else
+ return 0;
#endif
}
else if (strcmp(feature, "avx2") == 0) {
diff --git a/numpy/lib/recfunctions.py b/numpy/lib/recfunctions.py
index fabb509ab..6e257bb3f 100644
--- a/numpy/lib/recfunctions.py
+++ b/numpy/lib/recfunctions.py
@@ -26,10 +26,13 @@ _check_fill_value = np.ma.core._check_fill_value
__all__ = [
- 'append_fields', 'drop_fields', 'find_duplicates',
- 'get_fieldstructure', 'join_by', 'merge_arrays',
- 'rec_append_fields', 'rec_drop_fields', 'rec_join',
- 'recursive_fill_fields', 'rename_fields', 'stack_arrays',
+ 'append_fields', 'apply_along_fields', 'assign_fields_by_name',
+ 'drop_fields', 'find_duplicates', 'flatten_descr',
+ 'get_fieldstructure', 'get_names', 'get_names_flat',
+ 'join_by', 'merge_arrays', 'rec_append_fields',
+ 'rec_drop_fields', 'rec_join', 'recursive_fill_fields',
+ 'rename_fields', 'repack_fields', 'require_fields',
+ 'stack_arrays', 'structured_to_unstructured', 'unstructured_to_structured',
]
@@ -76,7 +79,7 @@ def recursive_fill_fields(input, output):
return output
-def get_fieldspec(dtype):
+def _get_fieldspec(dtype):
"""
Produce a list of name/dtype pairs corresponding to the dtype fields
@@ -91,7 +94,7 @@ def get_fieldspec(dtype):
>>> dt = np.dtype([(('a', 'A'), np.int64), ('b', np.double, 3)])
>>> dt.descr
[(('a', 'A'), '<i8'), ('b', '<f8', (3,))]
- >>> get_fieldspec(dt)
+ >>> _get_fieldspec(dt)
[(('a', 'A'), dtype('int64')), ('b', dtype(('<f8', (3,))))]
"""
@@ -204,12 +207,7 @@ def flatten_descr(ndtype):
return tuple(descr)
-def _zip_dtype_dispatcher(seqarrays, flatten=None):
- return seqarrays
-
-
-@array_function_dispatch(_zip_dtype_dispatcher)
-def zip_dtype(seqarrays, flatten=False):
+def _zip_dtype(seqarrays, flatten=False):
newdtype = []
if flatten:
for a in seqarrays:
@@ -219,14 +217,13 @@ def zip_dtype(seqarrays, flatten=False):
current = a.dtype
if current.names and len(current.names) <= 1:
# special case - dtypes of 0 or 1 field are flattened
- newdtype.extend(get_fieldspec(current))
+ newdtype.extend(_get_fieldspec(current))
else:
newdtype.append(('', current))
return np.dtype(newdtype)
-@array_function_dispatch(_zip_dtype_dispatcher)
-def zip_descr(seqarrays, flatten=False):
+def _zip_descr(seqarrays, flatten=False):
"""
Combine the dtype description of a series of arrays.
@@ -237,7 +234,7 @@ def zip_descr(seqarrays, flatten=False):
flatten : {boolean}, optional
Whether to collapse nested descriptions.
"""
- return zip_dtype(seqarrays, flatten=flatten).descr
+ return _zip_dtype(seqarrays, flatten=flatten).descr
def get_fieldstructure(adtype, lastname=None, parents=None,):
@@ -318,12 +315,7 @@ def _izip_fields(iterable):
yield element
-def _izip_records_dispatcher(seqarrays, fill_value=None, flatten=None):
- return seqarrays
-
-
-@array_function_dispatch(_izip_records_dispatcher)
-def izip_records(seqarrays, fill_value=None, flatten=True):
+def _izip_records(seqarrays, fill_value=None, flatten=True):
"""
Returns an iterator of concatenated items from a sequence of arrays.
@@ -445,7 +437,7 @@ def merge_arrays(seqarrays, fill_value=-1, flatten=False,
# Make sure we have named fields
if not seqdtype.names:
seqdtype = np.dtype([('', seqdtype)])
- if not flatten or zip_dtype((seqarrays,), flatten=True) == seqdtype:
+ if not flatten or _zip_dtype((seqarrays,), flatten=True) == seqdtype:
# Minimal processing needed: just make sure everythng's a-ok
seqarrays = seqarrays.ravel()
# Find what type of array we must return
@@ -468,7 +460,7 @@ def merge_arrays(seqarrays, fill_value=-1, flatten=False,
sizes = tuple(a.size for a in seqarrays)
maxlength = max(sizes)
# Get the dtype of the output (flattening if needed)
- newdtype = zip_dtype(seqarrays, flatten=flatten)
+ newdtype = _zip_dtype(seqarrays, flatten=flatten)
# Initialize the sequences for data and mask
seqdata = []
seqmask = []
@@ -496,9 +488,9 @@ def merge_arrays(seqarrays, fill_value=-1, flatten=False,
seqdata.append(itertools.chain(data, [fval] * nbmissing))
seqmask.append(itertools.chain(mask, [fmsk] * nbmissing))
# Create an iterator for the data
- data = tuple(izip_records(seqdata, flatten=flatten))
+ data = tuple(_izip_records(seqdata, flatten=flatten))
output = ma.array(np.fromiter(data, dtype=newdtype, count=maxlength),
- mask=list(izip_records(seqmask, flatten=flatten)))
+ mask=list(_izip_records(seqmask, flatten=flatten)))
if asrecarray:
output = output.view(MaskedRecords)
else:
@@ -516,7 +508,7 @@ def merge_arrays(seqarrays, fill_value=-1, flatten=False,
else:
fval = None
seqdata.append(itertools.chain(data, [fval] * nbmissing))
- output = np.fromiter(tuple(izip_records(seqdata, flatten=flatten)),
+ output = np.fromiter(tuple(_izip_records(seqdata, flatten=flatten)),
dtype=newdtype, count=maxlength)
if asrecarray:
output = output.view(recarray)
@@ -743,7 +735,7 @@ def append_fields(base, names, data, dtypes=None,
#
output = ma.masked_all(
max(len(base), len(data)),
- dtype=get_fieldspec(base.dtype) + get_fieldspec(data.dtype))
+ dtype=_get_fieldspec(base.dtype) + _get_fieldspec(data.dtype))
output = recursive_fill_fields(base, output)
output = recursive_fill_fields(data, output)
#
@@ -834,17 +826,18 @@ def repack_fields(a, align=False, recurse=False):
Examples
--------
+ >>> from numpy.lib import recfunctions as rfn
>>> def print_offsets(d):
... print("offsets:", [d.fields[name][1] for name in d.names])
... print("itemsize:", d.itemsize)
...
- >>> dt = np.dtype('u1,<i4,<f4', align=True)
+ >>> 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)
>>> print_offsets(dt)
offsets: [0, 8, 16]
itemsize: 24
- >>> packed_dt = repack_fields(dt)
+ >>> packed_dt = rfn.repack_fields(dt)
>>> packed_dt
dtype([('f0', 'u1'), ('f1', '<i8'), ('f2', '<f8')])
>>> print_offsets(packed_dt)
@@ -932,12 +925,13 @@ def structured_to_unstructured(arr, dtype=None, copy=False, casting='unsafe'):
Examples
--------
+ >>> from numpy.lib import recfunctions as rfn
>>> a = np.zeros(4, dtype=[('a', 'i4'), ('b', 'f4,u2'), ('c', 'f4', 2)])
>>> a
array([(0, (0., 0), [0., 0.]), (0, (0., 0), [0., 0.]),
(0, (0., 0), [0., 0.]), (0, (0., 0), [0., 0.])],
dtype=[('a', '<i4'), ('b', [('f0', '<f4'), ('f1', '<u2')]), ('c', '<f4', (2,))])
- >>> structured_to_unstructured(arr)
+ >>> rfn.structured_to_unstructured(a)
array([[0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0.],
@@ -945,7 +939,7 @@ def structured_to_unstructured(arr, dtype=None, copy=False, casting='unsafe'):
>>> b = np.array([(1, 2, 5), (4, 5, 7), (7, 8 ,11), (10, 11, 12)],
... dtype=[('x', 'i4'), ('y', 'f4'), ('z', 'f8')])
- >>> np.mean(structured_to_unstructured(b[['x', 'z']]), axis=-1)
+ >>> np.mean(rfn.structured_to_unstructured(b[['x', 'z']]), axis=-1)
array([ 3. , 5.5, 9. , 11. ])
"""
@@ -982,6 +976,7 @@ def structured_to_unstructured(arr, dtype=None, copy=False, casting='unsafe'):
# finally is it safe to view the packed fields as the unstructured type
return arr.view((out_dtype, (sum(counts),)))
+
def _unstructured_to_structured_dispatcher(arr, dtype=None, names=None,
align=None, copy=None, casting=None):
return (arr,)
@@ -1027,6 +1022,7 @@ def unstructured_to_structured(arr, dtype=None, names=None, align=False,
Examples
--------
+ >>> from numpy.lib import recfunctions as rfn
>>> dt = np.dtype([('a', 'i4'), ('b', 'f4,u2'), ('c', 'f4', 2)])
>>> a = np.arange(20).reshape((4,5))
>>> a
@@ -1034,7 +1030,7 @@ def unstructured_to_structured(arr, dtype=None, names=None, align=False,
[ 5, 6, 7, 8, 9],
[10, 11, 12, 13, 14],
[15, 16, 17, 18, 19]])
- >>> unstructured_to_structured(a, dt)
+ >>> rfn.unstructured_to_structured(a, dt)
array([( 0, ( 1., 2), [ 3., 4.]), ( 5, ( 6., 7), [ 8., 9.]),
(10, (11., 12), [13., 14.]), (15, (16., 17), [18., 19.])],
dtype=[('a', '<i4'), ('b', [('f0', '<f4'), ('f1', '<u2')]), ('c', '<f4', (2,))])
@@ -1111,11 +1107,12 @@ def apply_along_fields(func, arr):
Examples
--------
+ >>> from numpy.lib import recfunctions as rfn
>>> b = np.array([(1, 2, 5), (4, 5, 7), (7, 8 ,11), (10, 11, 12)],
... dtype=[('x', 'i4'), ('y', 'f4'), ('z', 'f8')])
- >>> apply_along_fields(np.mean, b)
+ >>> rfn.apply_along_fields(np.mean, b)
array([ 2.66666667, 5.33333333, 8.66666667, 11. ])
- >>> apply_along_fields(np.mean, b[['x', 'z']])
+ >>> rfn.apply_along_fields(np.mean, b[['x', 'z']])
array([ 3. , 5.5, 9. , 11. ])
"""
@@ -1200,14 +1197,15 @@ def require_fields(array, required_dtype):
Examples
--------
+ >>> from numpy.lib import recfunctions as rfn
>>> a = np.ones(4, dtype=[('a', 'i4'), ('b', 'f8'), ('c', 'u1')])
- >>> require_fields(a, [('b', 'f4'), ('c', 'u1')])
+ >>> rfn.require_fields(a, [('b', 'f4'), ('c', 'u1')])
array([(1., 1), (1., 1), (1., 1), (1., 1)],
dtype=[('b', '<f4'), ('c', 'u1')])
- >>> require_fields(a, [('b', 'f4'), ('newf', 'u1')])
+ >>> rfn.require_fields(a, [('b', 'f4'), ('newf', 'u1')])
array([(1., 0), (1., 0), (1., 0), (1., 0)],
dtype=[('b', '<f4'), ('newf', 'u1')])
-
+
"""
out = np.empty(array.shape, dtype=required_dtype)
assign_fields_by_name(out, array)
@@ -1270,10 +1268,10 @@ def stack_arrays(arrays, defaults=None, usemask=True, asrecarray=False,
fldnames = [d.names for d in ndtype]
#
dtype_l = ndtype[0]
- newdescr = get_fieldspec(dtype_l)
+ newdescr = _get_fieldspec(dtype_l)
names = [n for n, d in newdescr]
for dtype_n in ndtype[1:]:
- for fname, fdtype in get_fieldspec(dtype_n):
+ for fname, fdtype in _get_fieldspec(dtype_n):
if fname not in names:
newdescr.append((fname, fdtype))
names.append(fname)
@@ -1496,15 +1494,15 @@ def join_by(key, r1, r2, jointype='inner', r1postfix='1', r2postfix='2',
#
# Build the new description of the output array .......
# Start with the key fields
- ndtype = get_fieldspec(r1k.dtype)
+ ndtype = _get_fieldspec(r1k.dtype)
# Add the fields from r1
- for fname, fdtype in get_fieldspec(r1.dtype):
+ for fname, fdtype in _get_fieldspec(r1.dtype):
if fname not in key:
ndtype.append((fname, fdtype))
# Add the fields from r2
- for fname, fdtype in get_fieldspec(r2.dtype):
+ for fname, fdtype in _get_fieldspec(r2.dtype):
# Have we seen the current name already ?
# we need to rebuild this list every time
names = list(name for name, dtype in ndtype)
diff --git a/numpy/lib/tests/test_recfunctions.py b/numpy/lib/tests/test_recfunctions.py
index f713fb64d..0126ccaf8 100644
--- a/numpy/lib/tests/test_recfunctions.py
+++ b/numpy/lib/tests/test_recfunctions.py
@@ -12,9 +12,11 @@ from numpy.lib.recfunctions import (
find_duplicates, merge_arrays, append_fields, stack_arrays, join_by,
repack_fields, unstructured_to_structured, structured_to_unstructured,
apply_along_fields, require_fields, assign_fields_by_name)
+get_fieldspec = np.lib.recfunctions._get_fieldspec
get_names = np.lib.recfunctions.get_names
get_names_flat = np.lib.recfunctions.get_names_flat
-zip_descr = np.lib.recfunctions.zip_descr
+zip_descr = np.lib.recfunctions._zip_descr
+zip_dtype = np.lib.recfunctions._zip_dtype
class TestRecFunctions(object):
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