Datasets:
vinsblack
/
The_Stack_Processed-v2

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import pytest\n\nimport numpy as np\nfrom numpy import histogram, histogram_bin_edges, histogramdd\nfrom numpy.testing import (\n assert_,\n assert_allclose,\n assert_almost_equal,\n assert_array_almost_equal,\n assert_array_equal,\n assert_array_max_ulp,\n assert_equal,\n assert_raises,\n as...
.venv\Lib\site-packages\numpy\lib\tests\test_histograms.py
test_histograms.py
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import pytest\n\nimport numpy as np\nfrom numpy.lib._index_tricks_impl import (\n c_,\n diag_indices,\n diag_indices_from,\n fill_diagonal,\n index_exp,\n ix_,\n mgrid,\n ndenumerate,\n ndindex,\n ogrid,\n r_,\n s_,\n)\nfrom numpy.testing import (\n assert_,\n assert_almost_equ...
.venv\Lib\site-packages\numpy\lib\tests\test_index_tricks.py
test_index_tricks.py
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"""\nTests specific to `np.loadtxt` added during the move of loadtxt to be backed\nby C code.\nThese tests complement those found in `test_io.py`.\n"""\n\nimport os\nimport sys\nfrom io import StringIO\nfrom tempfile import NamedTemporaryFile, mkstemp\n\nimport pytest\n\nimport numpy as np\nfrom numpy.ma.testutils impo...
.venv\Lib\site-packages\numpy\lib\tests\test_loadtxt.py
test_loadtxt.py
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import numbers\nimport operator\n\nimport numpy as np\nfrom numpy.testing import assert_, assert_equal, assert_raises\n\n# NOTE: This class should be kept as an exact copy of the example from the\n# docstring for NDArrayOperatorsMixin.\n\nclass ArrayLike(np.lib.mixins.NDArrayOperatorsMixin):\n def __init__(self, val...
.venv\Lib\site-packages\numpy\lib\tests\test_mixins.py
test_mixins.py
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import inspect\nimport warnings\nfrom functools import partial\n\nimport pytest\n\nimport numpy as np\nfrom numpy._core.numeric import normalize_axis_tuple\nfrom numpy.exceptions import AxisError, ComplexWarning\nfrom numpy.lib._nanfunctions_impl import _nan_mask, _replace_nan\nfrom numpy.testing import (\n assert_,...
.venv\Lib\site-packages\numpy\lib\tests\test_nanfunctions.py
test_nanfunctions.py
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from itertools import chain\n\nimport pytest\n\nimport numpy as np\nfrom numpy.testing import assert_array_equal, assert_equal, assert_raises\n\n\ndef test_packbits():\n # Copied from the docstring.\n a = [[[1, 0, 1], [0, 1, 0]],\n [[1, 1, 0], [0, 0, 1]]]\n for dt in '?bBhHiIlLqQ':\n arr = np.ar...
.venv\Lib\site-packages\numpy\lib\tests\test_packbits.py
test_packbits.py
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import pytest\n\nimport numpy as np\nimport numpy.polynomial.polynomial as poly\nfrom numpy.testing import (\n assert_,\n assert_allclose,\n assert_almost_equal,\n assert_array_almost_equal,\n assert_array_equal,\n assert_equal,\n assert_raises,\n)\n\n# `poly1d` has some support for `np.bool` and `...
.venv\Lib\site-packages\numpy\lib\tests\test_polynomial.py
test_polynomial.py
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\nimport numpy as np\nimport numpy.ma as ma\nfrom numpy.lib.recfunctions import (\n append_fields,\n apply_along_fields,\n assign_fields_by_name,\n drop_fields,\n find_duplicates,\n get_fieldstructure,\n join_by,\n merge_arrays,\n recursive_fill_fields,\n rename_fields,\n repack_fields,...
.venv\Lib\site-packages\numpy\lib\tests\test_recfunctions.py
test_recfunctions.py
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import os\n\nimport numpy as np\nfrom numpy.testing import (\n _assert_valid_refcount,\n assert_,\n assert_array_almost_equal,\n assert_array_equal,\n assert_equal,\n assert_raises,\n)\n\n\nclass TestRegression:\n def test_poly1d(self):\n # Ticket #28\n assert_equal(np.poly1d([1]) - n...
.venv\Lib\site-packages\numpy\lib\tests\test_regression.py
test_regression.py
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import functools\nimport sys\n\nimport pytest\n\nimport numpy as np\nfrom numpy import (\n apply_along_axis,\n apply_over_axes,\n array_split,\n column_stack,\n dsplit,\n dstack,\n expand_dims,\n hsplit,\n kron,\n put_along_axis,\n split,\n take_along_axis,\n tile,\n vsplit,\n)...
.venv\Lib\site-packages\numpy\lib\tests\test_shape_base.py
test_shape_base.py
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import pytest\n\nimport numpy as np\nfrom numpy._core._rational_tests import rational\nfrom numpy.lib._stride_tricks_impl import (\n _broadcast_shape,\n as_strided,\n broadcast_arrays,\n broadcast_shapes,\n broadcast_to,\n sliding_window_view,\n)\nfrom numpy.testing import (\n assert_,\n assert_...
.venv\Lib\site-packages\numpy\lib\tests\test_stride_tricks.py
test_stride_tricks.py
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"""Test functions for matrix module\n\n"""\nimport pytest\n\nimport numpy as np\nfrom numpy import (\n add,\n arange,\n array,\n diag,\n eye,\n fliplr,\n flipud,\n histogram2d,\n mask_indices,\n ones,\n tri,\n tril_indices,\n tril_indices_from,\n triu_indices,\n triu_indices...
.venv\Lib\site-packages\numpy\lib\tests\test_twodim_base.py
test_twodim_base.py
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import numpy as np\nfrom numpy import (\n common_type,\n iscomplex,\n iscomplexobj,\n isneginf,\n isposinf,\n isreal,\n isrealobj,\n mintypecode,\n nan_to_num,\n real_if_close,\n)\nfrom numpy.testing import assert_, assert_array_equal, assert_equal\n\n\ndef assert_all(x):\n assert_(np.a...
.venv\Lib\site-packages\numpy\lib\tests\test_type_check.py
test_type_check.py
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import numpy as np\nfrom numpy import fix, isneginf, isposinf\nfrom numpy.testing import assert_, assert_array_equal, assert_equal, assert_raises\n\n\nclass TestUfunclike:\n\n def test_isposinf(self):\n a = np.array([np.inf, -np.inf, np.nan, 0.0, 3.0, -3.0])\n out = np.zeros(a.shape, bool)\n tgt...
.venv\Lib\site-packages\numpy\lib\tests\test_ufunclike.py
test_ufunclike.py
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from io import StringIO\n\nimport pytest\n\nimport numpy as np\nimport numpy.lib._utils_impl as _utils_impl\nfrom numpy.testing import assert_raises_regex\n\n\ndef test_assert_raises_regex_context_manager():\n with assert_raises_regex(ValueError, 'no deprecation warning'):\n raise ValueError('no deprecation w...
.venv\Lib\site-packages\numpy\lib\tests\test_utils.py
test_utils.py
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import os\nimport urllib.request as urllib_request\nfrom shutil import rmtree\nfrom tempfile import NamedTemporaryFile, mkdtemp, mkstemp\nfrom urllib.error import URLError\nfrom urllib.parse import urlparse\n\nimport pytest\n\nimport numpy.lib._datasource as datasource\nfrom numpy.testing import assert_, assert_equal, ...
.venv\Lib\site-packages\numpy\lib\tests\test__datasource.py
test__datasource.py
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import time\nfrom datetime import date\n\nimport numpy as np\nfrom numpy.lib._iotools import (\n LineSplitter,\n NameValidator,\n StringConverter,\n easy_dtype,\n flatten_dtype,\n has_nested_fields,\n)\nfrom numpy.testing import (\n assert_,\n assert_allclose,\n assert_equal,\n assert_rais...
.venv\Lib\site-packages\numpy\lib\tests\test__iotools.py
test__iotools.py
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"""Tests for the NumpyVersion class.\n\n"""\nfrom numpy.lib import NumpyVersion\nfrom numpy.testing import assert_, assert_raises\n\n\ndef test_main_versions():\n assert_(NumpyVersion('1.8.0') == '1.8.0')\n for ver in ['1.9.0', '2.0.0', '1.8.1', '10.0.1']:\n assert_(NumpyVersion('1.8.0') < ver)\n\n for ...
.venv\Lib\site-packages\numpy\lib\tests\test__version.py
test__version.py
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!<arch>\n/ -1 0 186 `\n
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from typing import Final, TypedDict, type_check_only\n\nimport numpy as np\nfrom numpy._typing import NDArray\n\nfrom ._linalg import fortran_int\n\n###\n\n@type_check_only\nclass _GELSD(TypedDict):\n m: int\n n: int\n nrhs: int\n lda: int\n ldb: int\n rank: int\n lwork: int\n info: int\n\n@type...
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def __getattr__(attr_name):\n import warnings\n\n from numpy.linalg import _linalg\n ret = getattr(_linalg, attr_name, None)\n if ret is None:\n raise AttributeError(\n f"module 'numpy.linalg.linalg' has no attribute {attr_name}")\n warnings.warn(\n "The numpy.linalg.linalg has b...
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from ._linalg import (\n LinAlgError,\n cholesky,\n cond,\n cross,\n det,\n diagonal,\n eig,\n eigh,\n eigvals,\n eigvalsh,\n inv,\n lstsq,\n matmul,\n matrix_norm,\n matrix_power,\n matrix_rank,\n matrix_transpose,\n multi_dot,\n norm,\n outer,\n pinv,\n ...
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from collections.abc import Iterable\nfrom typing import (\n Any,\n NamedTuple,\n Never,\n SupportsIndex,\n SupportsInt,\n TypeAlias,\n TypeVar,\n overload,\n)\nfrom typing import Literal as L\n\nimport numpy as np\nfrom numpy import (\n complex128,\n complexfloating,\n float64,\n # ...
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from typing import Final\nfrom typing import Literal as L\n\nimport numpy as np\nfrom numpy._typing._ufunc import _GUFunc_Nin2_Nout1\n\n__version__: Final[str] = ...\n_ilp64: Final[bool] = ...\n\n###\n# 1 -> 1\n\n# (m,m) -> ()\ndet: Final[np.ufunc] = ...\n# (m,m) -> (m)\ncholesky_lo: Final[np.ufunc] = ...\ncholesky_up:...
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"""\n``numpy.linalg``\n================\n\nThe NumPy linear algebra functions rely on BLAS and LAPACK to provide efficient\nlow level implementations of standard linear algebra algorithms. Those\nlibraries may be provided by NumPy itself using C versions of a subset of their\nreference implementations but, when possibl...
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from . import _linalg as _linalg\nfrom . import _umath_linalg as _umath_linalg\nfrom . import linalg as linalg\nfrom ._linalg import (\n cholesky,\n cond,\n cross,\n det,\n diagonal,\n eig,\n eigh,\n eigvals,\n eigvalsh,\n inv,\n lstsq,\n matmul,\n matrix_norm,\n matrix_power,\...
.venv\Lib\site-packages\numpy\linalg\__init__.pyi
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2025-04-17T22:15:24.030635
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"""Test deprecation and future warnings.\n\n"""\nimport numpy as np\nfrom numpy.testing import assert_warns\n\n\ndef test_qr_mode_full_future_warning():\n """Check mode='full' FutureWarning.\n\n In numpy 1.8 the mode options 'full' and 'economic' in linalg.qr were\n deprecated. The release date will probably b...
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""" Test functions for linalg module\n\n"""\nimport itertools\nimport os\nimport subprocess\nimport sys\nimport textwrap\nimport threading\nimport traceback\n\nimport pytest\n\nimport numpy as np\nfrom numpy import (\n array,\n asarray,\n atleast_2d,\n cdouble,\n csingle,\n dot,\n double,\n iden...
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""" Test functions for linalg module\n"""\n\nimport pytest\n\nimport numpy as np\nfrom numpy import arange, array, dot, float64, linalg, transpose\nfrom numpy.testing import (\n assert_,\n assert_array_almost_equal,\n assert_array_equal,\n assert_array_less,\n assert_equal,\n assert_raises,\n)\n\n\ncl...
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\n\n
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.. -*- rest -*-\n\n==================================================\nAPI changes in the new masked array implementation\n==================================================\n\nMasked arrays are subclasses of ndarray\n---------------------------------------\n\nContrary to the original implementation, masked arrays are ...
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