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/dports/astro/py-astropy/astropy-5.0/astropy/timeseries/tests/
H A Dtest_downsample.py14 from astropy.timeseries.downsample import aggregate_downsample, reduceat
23 add_output = np.add.reduceat(np.arange(8),[0, 4, 1, 5, 2, 6, 3, 7])
25 sum_output = reduceat(np.arange(8), [0, 4, 1, 5, 2, 6, 3, 7], np.sum)
28 mean_output = reduceat(np.arange(8), np.arange(8)[::2], np.mean)
30 nanmean_output = reduceat(np.arange(8), [0, 4, 1, 5, 2, 6, 3, 7], np.mean)
32 assert_equal(reduceat(np.arange(8), np.arange(8)[::2], np.mean),
33 reduceat(np.arange(8), np.arange(8)[::2], np.nanmean))
/dports/astro/py-astropy/astropy-5.0/astropy/timeseries/
H A Ddownsample.py16 def reduceat(array, indices, function): function
22 return np.array(function.reduceat(array, indices))
199 data[unique_indices] = u.Quantity(reduceat(values.value, groups, aggregate_func),
204 data[unique_indices] = reduceat(values, groups, aggregate_func)
/dports/astro/py-astropy/astropy-5.0/astropy/table/
H A Dgroups.py246 reduceat = hasattr(func, 'reduceat')
250 if not masked and (reduceat or sum_case or mean_case):
252 vals = np.add.reduceat(par_col, i0s) / np.diff(self.indices)
256 vals = func.reduceat(par_col, i0s)
/dports/math/py-pandas/pandas-1.2.5/pandas/_libs/
H A Dops_dispatch.pyx64 method : {'reduce', 'accumulate', 'reduceat', 'outer', 'at', '__call__'}
/dports/math/py-numpy/numpy-1.20.3/doc/source/release/
H A D1.7.2-notes.rst34 * gh-2892: Regression in ufunc.reduceat with zero-sized index array
H A D1.13.0-notes.rst555 ``reduceat`` methods. This is mostly for compatibility with ``__array_ufunc``;
/dports/astro/py-astropy/astropy-5.0/astropy/units/tests/
H A Dtest_quantity_ufuncs.py1140 np.sin.reduceat(s, i)
1156 s_add_reduceat = np.add.reduceat(s, i)
1157 check_add_reduceat = np.add.reduceat(check, i)
1170 np.greater.reduceat(s, i)
1180 np.multiply.reduceat(s, i)
1193 s_multiply_reduceat = np.multiply.reduceat(s, i)
1194 check_multiply_reduceat = np.multiply.reduceat(check, i)
/dports/devel/py-numba/numba-0.51.2/docs/source/reference/
H A Djit-compilation.rst472 .. method:: reduceat(A, indices, *, axis, dtype, out)
475 axis. See `ufunc.reduceat`_.
510 .. _`ufunc.reduceat`: http://docs.scipy.org/doc/numpy/reference/generated/numpy.ufunc.reduceat.html…
/dports/math/py-numpy/numpy-1.20.3/numpy/core/tests/
H A Dtest_mem_overlap.py707 return np.add.reduceat(a, idx, out=out, axis=axis)
714 c1 = ufunc.reduceat(a.copy(), ind.copy(), out=out.copy())
715 c2 = ufunc.reduceat(a, ind, out=out)
H A Dtest_umath.py2408 res = np.multiply.reduceat(a, [4, 2], 'axis0', 'dtype0', 'out0')
2429 res = np.multiply.reduceat(a, [4, 2], 0, None, None)
2433 res = np.multiply.reduceat(a, [4, 2], None, None, out=(None,))
2761 check = np.add.reduceat(d, indices, axis=1)
2762 c = np.add.reduceat(a, indices, axis=1)
2766 c = np.add.reduceat(a, indices, 1, None, b)
3358 h1 = np.add.reduceat(a['value'], indx)
3364 h1 = np.add.reduceat(a['value'], indx)
3372 result = np.add.reduceat(x, indices)
3377 result = np.add.reduceat(x, [], axis=0)
[all …]
H A Dtest_ufunc.py215 assert_array_equal(np.add.reduceat(x, idx)[::2], [1, 3, 5, 7])
1224 np.add.reduceat(arr, np.arange(4), out=arr)
1225 np.add.reduceat(arr, np.arange(4), out=arr)
1233 np.add.reduceat(arr, np.arange(4), out=arr, axis=-1)
1234 np.add.reduceat(arr, np.arange(4), out=arr, axis=-1)
/dports/math/py-numpy/numpy-1.20.3/doc/neps/
H A Dnep-0008-groupby_additions.rst49 to use version of reduceat, while the reduceby method is intended to
H A Dnep-0013-ufunc-overrides.rst159 methods: ``"reduce"``, ``"accumulate"``, ``"reduceat"``, ``"outer"``,
171 argument (even for the ``reduce``, ``accumulate``, and ``reduceat`` methods
/dports/science/py-scikit-learn/scikit-learn-1.0.2/sklearn/utils/
H A Dsparsefuncs.py421 value = ufunc.reduceat(X.data, X.indptr[major_index])
/dports/math/py-numpy/numpy-1.20.3/doc/source/reference/
H A Dinternals.code-explanations.rst482 reduceat. Each of these methods requires a setup command followed by a
510 accumulate, or reduceat. If an output array is already provided, then
590 triple: ufunc; methods; reduceat
593 The reduceat function is a generalization of both the reduce and
H A Darrays.classes.rst63 (one of ``"__call__"``, ``"reduce"``, ``"reduceat"``,
H A Dufuncs.rst548 ufunc.reduceat
/dports/science/py-scipy/scipy-1.7.1/scipy/sparse/
H A Dcoo.py551 data = np.add.reduceat(data, unique_inds, dtype=self.dtype)
H A Dcompressed.py635 value = ufunc.reduceat(data,
/dports/astro/py-astropy/astropy-5.0/docs/table/
H A Doperations.rst335 If the specified function has a :meth:`numpy.ufunc.reduceat` method, this will
341 :meth:`numpy.ufunc.reduceat` include:
378 their respective ``reduceat`` methods.
/dports/math/py-pandas/pandas-1.2.5/pandas/core/groupby/
H A Dgeneric.py650 out = np.add.reduceat(inc, idx).astype("int64", copy=False)
732 rep = partial(np.repeat, repeats=np.add.reduceat(inc, idx))
/dports/science/py-OpenMC/openmc-0.12.2/openmc/mgxs/
H A Dmgxs.py1350 mean = np.add.reduceat(mean, energy_indices, axis=i)
1351 std_dev = np.add.reduceat(std_dev**2, energy_indices,
3258 mean = np.add.reduceat(mean, energy_indices, axis=i)
3259 std_dev = np.add.reduceat(std_dev**2, energy_indices,
/dports/science/openmc/openmc-0.12.2/openmc/mgxs/
H A Dmgxs.py1350 mean = np.add.reduceat(mean, energy_indices, axis=i)
1351 std_dev = np.add.reduceat(std_dev**2, energy_indices,
3258 mean = np.add.reduceat(mean, energy_indices, axis=i)
3259 std_dev = np.add.reduceat(std_dev**2, energy_indices,
/dports/math/py-numpy/numpy-1.20.3/doc/source/user/
H A Dbasics.subclassing.rst441 ``"reduceat"``, ``"outer"``, or ``"at"``.
/dports/devel/pycharm-pro/pycharm-2020.2.3/plugins/python/helpers/python-skeletons/numpy/core/
H A D__init__.py3988 …def reduceat(self, a, indices, axis=0, dtype=None, out=None): # real signature unknown; restored … member in ufunc

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