/dports/astro/py-astropy/astropy-5.0/astropy/timeseries/tests/ |
H A D | test_downsample.py | 14 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))
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/dports/astro/py-astropy/astropy-5.0/astropy/timeseries/ |
H A D | downsample.py | 16 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)
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/dports/astro/py-astropy/astropy-5.0/astropy/table/ |
H A D | groups.py | 246 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)
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/dports/math/py-pandas/pandas-1.2.5/pandas/_libs/ |
H A D | ops_dispatch.pyx | 64 method : {'reduce', 'accumulate', 'reduceat', 'outer', 'at', '__call__'}
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/dports/math/py-numpy/numpy-1.20.3/doc/source/release/ |
H A D | 1.7.2-notes.rst | 34 * gh-2892: Regression in ufunc.reduceat with zero-sized index array
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H A D | 1.13.0-notes.rst | 555 ``reduceat`` methods. This is mostly for compatibility with ``__array_ufunc``;
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/dports/astro/py-astropy/astropy-5.0/astropy/units/tests/ |
H A D | test_quantity_ufuncs.py | 1140 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)
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/dports/devel/py-numba/numba-0.51.2/docs/source/reference/ |
H A D | jit-compilation.rst | 472 .. 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…
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/dports/math/py-numpy/numpy-1.20.3/numpy/core/tests/ |
H A D | test_mem_overlap.py | 707 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)
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H A D | test_umath.py | 2408 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 …]
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H A D | test_ufunc.py | 215 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)
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/dports/math/py-numpy/numpy-1.20.3/doc/neps/ |
H A D | nep-0008-groupby_additions.rst | 49 to use version of reduceat, while the reduceby method is intended to
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H A D | nep-0013-ufunc-overrides.rst | 159 methods: ``"reduce"``, ``"accumulate"``, ``"reduceat"``, ``"outer"``, 171 argument (even for the ``reduce``, ``accumulate``, and ``reduceat`` methods
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/dports/science/py-scikit-learn/scikit-learn-1.0.2/sklearn/utils/ |
H A D | sparsefuncs.py | 421 value = ufunc.reduceat(X.data, X.indptr[major_index])
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/dports/math/py-numpy/numpy-1.20.3/doc/source/reference/ |
H A D | internals.code-explanations.rst | 482 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
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H A D | arrays.classes.rst | 63 (one of ``"__call__"``, ``"reduce"``, ``"reduceat"``,
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H A D | ufuncs.rst | 548 ufunc.reduceat
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/dports/science/py-scipy/scipy-1.7.1/scipy/sparse/ |
H A D | coo.py | 551 data = np.add.reduceat(data, unique_inds, dtype=self.dtype)
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H A D | compressed.py | 635 value = ufunc.reduceat(data,
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/dports/astro/py-astropy/astropy-5.0/docs/table/ |
H A D | operations.rst | 335 If the specified function has a :meth:`numpy.ufunc.reduceat` method, this will 341 :meth:`numpy.ufunc.reduceat` include: 378 their respective ``reduceat`` methods.
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/dports/math/py-pandas/pandas-1.2.5/pandas/core/groupby/ |
H A D | generic.py | 650 out = np.add.reduceat(inc, idx).astype("int64", copy=False) 732 rep = partial(np.repeat, repeats=np.add.reduceat(inc, idx))
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/dports/science/py-OpenMC/openmc-0.12.2/openmc/mgxs/ |
H A D | mgxs.py | 1350 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,
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/dports/science/openmc/openmc-0.12.2/openmc/mgxs/ |
H A D | mgxs.py | 1350 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,
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/dports/math/py-numpy/numpy-1.20.3/doc/source/user/ |
H A D | basics.subclassing.rst | 441 ``"reduceat"``, ``"outer"``, or ``"at"``.
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/dports/devel/pycharm-pro/pycharm-2020.2.3/plugins/python/helpers/python-skeletons/numpy/core/ |
H A D | __init__.py | 3988 …def reduceat(self, a, indices, axis=0, dtype=None, out=None): # real signature unknown; restored … member in ufunc
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