8000 ENH: Added countbits (popcount) · ganesh-k13/numpy@cc760a9 · GitHub
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ENH: Added countbits (popcount)
ENH, DOC: Added countbits (popcount) ENH: Popcount implementation ENH: Add popcount to umath ENH: Added countbits (popcount) to umath `__all__` ENH: Refined popcount logic DOC: Added `bit_count` Co-authored-by: Eric Wieser <wieser.eric@gmail.com> MAINT: Renamed `countbits` to `bit_count` MAINT: Fixed 4 1s magic number DOC: Added `popcount` to docstring ENH: Added bit_count annotations ENH: Added GNU/CLANG popcount DOC: Added `popcount` language example ENH, BUG: Moved `bitcount` to npy_math.h as `popcount` | Fixed final right shift ENH: Enable `popcount` for signed TST: Tests for `bit_count` BUG, DOC: (BUG) Added missing typecast causing an unwanted upcast (DOC) Added more details on `popcount` implementation MAINT, BUG: (MAINT) Refined `popcount` TC to use typecode (BUG) Fixed ufunc.ntypes to include signed ints ENH: Added windows builtin support ENH: Added `popcount` implementation for big python ints natively [1/2] `popcount` object loop changes ENH: Object loop for `bit_count` [2/2] `popcount` object loop changes TST: Refined `bit_count` tests and added object type ENH: Added `bit_count` to `np.int*` DOC: Added `np.bit_count` (numpy#19355) MAINT: Various linting and minor fixes: 1. Fixed passing all args to _internals umath bitcount. Note: We use kwargs here that might hinder performance 2. Fixed linting errors. 3. Improved verbosity of logs 4. Made a generic TO_BITS_LEN macro to accomdate more length based functions in future BENCH: Added bit_count (popcount) MAINT: Style nits | Added signed case DOC, MAINT: Improved example ENH: Added annotations for bit_count TST: Added annotations tests for bit_count MAINT: Fixed linting errors MAINT: Moved Magic constants to npy_math_internal MAINT: Remove python implementation | Added 3.10 check to tests DOC: Added abs value usage to doc MAINT: Resolved merge conflicts
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‎benchmarks/benchmarks/bench_ufunc.py

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88

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ufuncs = ['abs', 'absolute', 'add', 'arccos', 'arccosh', 'arcsin', 'arcsinh',
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'arctan', 'arctan2', 'arctanh', 'bitwise_and', 'bitwise_not',
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'arctan', 'arctan2', 'arctanh', 'bit_count', 'bitwise_and', 'bitwise_not',
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'bitwise_or', 'bitwise_xor', 'cbrt', 'ceil', 'conj', 'conjugate',
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'copysign', 'cos', 'cosh', 'deg2rad', 'degrees', 'divide', 'divmod',
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'equal', 'exp', 'exp2', 'expm1', 'fabs', 'float_power', 'floor',

‎doc/release/upcoming_changes/19355.new_feature.rst

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`np.bit_count` to compute the number of 1-bits in an integer
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------------------------------------------------------------
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This new function counts the number of 1-bits in a number.
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These work on all the numpy integer types, as well as the
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builtin arbitrary-precision `Decimal` and `long` types.
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.. code-block:: python
< 1E79 /code>
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>>> a = np.array([2**i - 1 for i in range(16)])
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>>> np.bit_count(a)
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array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15])

‎doc/so F438 urce/reference/routines.math.rst

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@@ -182,3 +182,5 @@ Miscellaneous
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real_if_close
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interp
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bit_count

‎numpy/__init__.pyi

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@@ -2491,6 +2491,17 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]):
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def __dlpack__(self: NDArray[number[Any]], *, stream: None = ...) -> _PyCapsule: ...
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def __dlpack_device__(self) -> tuple[int, L[0]]: ...
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def bit_count(
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self,
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out: None | NDArray[Any] = ...,
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*,
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where: _ArrayLikeBool_co = ...,
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casting: _CastingKind = ...,
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order: _OrderKACF = ...,
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dtype: DTypeLike = ...,
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subok: bool = ...,
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) -> NDArray[Any]: ...
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# Keep `dtype` at the bottom to avoid name conflicts with `np.dtype`
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@property
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def dtype(self) -> _DType_co: ...
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self: _ScalarType, *shape: SupportsIndex, order: _OrderACF = ...
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) -> ndarray[Any, _dtype[_ScalarType]]: ...
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def bit_count(
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self,
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out: None | NDArray[Any] = ...,
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*,
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where: _ArrayLikeBool_co = ...,
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casting: _CastingKind = ...,
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order: _OrderKACF = ...,
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dtype: DTypeLike = ...,
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subok: bool = ...,
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) -> Any: ...
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def squeeze(
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self: _ScalarType, axis: None | L[0] | tuple[()] = ...
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) -> _ScalarType: ...
@@ -3154,6 +3176,7 @@ arcsinh: _UFunc_Nin1_Nout1[L['arcsinh'], L[8], None]
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arctan2: _UFunc_Nin2_Nout1[L['arctan2'], L[5], None]
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arctan: _UFunc_Nin1_Nout1[L['arctan'], L[8], None]
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arctanh: _UFunc_Nin1_Nout1[L['arctanh'], L[8], None]
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bit_count: _UFunc_Nin1_Nout1[L['bit_count'], L[11], None]
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bitwise_and: _UFunc_Nin2_Nout1[L['bitwise_and'], L[12], L[-1]]
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bitwise_not: _UFunc_Nin1_Nout1[L['invert'], L[12], None]
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bitwise_or: _UFunc_Nin2_Nout1[L['bitwise_or'], L[12], L[0]]

‎numpy/core/_methods.py

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umr_minimum = um.minimum.reduce
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umr_sum = um.add.reduce
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umr_prod = um.multiply.reduce
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umr_bit_count = um.bit_count
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umr_any = um.logical_or.reduce
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umr_all = um.logical_and.reduce
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def _dumps(self, protocol=2):
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return pickle.dumps(self, protocol=protocol)
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def _bit_count(a, out=None, *, where=True, casting='same_kind',
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order='K', dtype=None, subok=True):
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return umr_bit_count(a, out, where=where, casting=casting,
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order=order, dtype=dtype, subok=subok)

‎numpy/core/code_generators/generate_umath.py

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TD(ints),
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TD('O', f='npy_ObjectLCM'),
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),
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'bit_count':
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Ufunc(1, 1, None,
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docstrings.get('numpy.core.umath.bit_count'),
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None,
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TD(ints),
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TD('O', f='npy_ObjectPopCount'),
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),
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'matmul' :
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Ufunc(2, 1, None,
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docstrings.get('numpy.core.umath.matmul'),

‎numpy/core/code_generators/ufunc_docstrings.py

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array([ 0, 20, 20, 60, 20, 20])
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""")
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add_newdoc('numpy.core.umath', 'bit_count',
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"""
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Computes the number of 1-bits in the absolute value of ``x``.
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Analogous to the builtin `int.bit_count` or ``popcount`` in C++.
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Parameters
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----------
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x : array_like, unsigned int
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Input array.
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$PARAMS
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Returns
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-------
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y : ndarray
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The corresponding number of 1-bits in the input.
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$OUT_SCALAR_1
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References
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----------
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.. [1] https://stackoverflow.com/a/109025/5671364
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.. [2] Wikipedia, "Hamming weight",
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https://en.wikipedia.org/wiki/Hamming_weight
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Examples
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--------
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>>> np.bit_count(1023)
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10
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>>> a = np.array([2**i - 1 for i in range(16)])
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>>> np.bit_count(a)
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array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15])
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""")

‎numpy/core/src/multiarray/methods.c

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NPY_FORWARD_NDARRAY_METHOD("_ptp");
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}
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static PyObject *
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array_bit_count(PyArrayObject *self, PyObject *args, PyObject *kwds)
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{
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NPY_FORWARD_NDARRAY_METHOD("_bit_count");
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}
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static PyObject *
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array_swapaxes(PyArrayObject *self, PyObject *args)
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{"__dlpack__",
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(PyCFunction)array_dlpack,
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METH_FASTCALL | METH_KEYWORDS, NULL},
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{"__dlpack_device__",
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(PyCFunction)array_dlpack_device,
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METH_NOARGS, NULL},
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{"bit_count",
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(PyCFunction)array_bit_count,
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METH_VARARGS | METH_KEYWORDS, NULL},
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{NULL, NULL, 0, NULL} /* sentinel */
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};

‎numpy/core/src/multiarray/scalartypes.c.src

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* std, var, sum, cumsum, prod, cumprod, compress, sort, argsort,
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* round, argmax, argmin, max, min, ptp, any, all, astype, resize,
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* reshape, choose, tostring, tobytes, copy, searchsorted, view,
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* flatten, ravel, squeeze#
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* flatten, ravel, squeeze, bit_count#
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*/
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static PyObject *
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gentype_@name@(PyObject *self, PyObject *args, PyObject *kwds)
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{"sum",
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(PyCFunction)gentype_sum,
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METH_VARARGS | METH_KEYWORDS, NULL},
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{"bit_count",
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(PyCFunction)gentype_bit_count,
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METH_VARARGS | METH_KEYWORDS, NULL},
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{"cumsum",
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(PyCFunction)gentype_cumsum,
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METH_VARARGS | METH_KEYWORDS, NULL},

‎numpy/core/src/npymath/npy_math_internal.h.src

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/**end repeat1**/
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/**end repeat**/
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#define __popcnt32 __popcnt
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/**begin repeat
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*

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