---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
Cell In[5], line 5
3 import numpy as np
4 import matplotlib.pyplot as plt
----> 5 from scipy.spatial.distance import cdist
6 print(f"numpy: {np.__version__}, matplotlib: {plt.matplotlib.__version__}")
7 except ImportError as e:
File D:\miniconda\lib\site-packages\scipy\spatial\__init__.py:110
1 """
2 =============================================================
3 Spatial algorithms and data structures (:mod:`scipy.spatial`)
(...)
107 QhullError
108 """ # noqa: E501
--> 110 from ._kdtree import *
111 from ._ckdtree import * # type: ignore[import-not-found]
112 from ._qhull import *
File D:\miniconda\lib\site-packages\scipy\spatial\_kdtree.py:4
1 # Copyright Anne M. Archibald 2008
2 # Released under the scipy license
3 import numpy as np
----> 4 from ._ckdtree import cKDTree, cKDTreeNode # type: ignore[import-not-found]
6 __all__ = ['minkowski_distance_p', 'minkowski_distance',
7 'distance_matrix',
8 'Rectangle', 'KDTree']
11 def minkowski_distance_p(x, y, p=2):
File _ckdtree.pyx:11, in init scipy.spatial._ckdtree()
File D:\miniconda\lib\site-packages\scipy\sparse\__init__.py:300
294 # Original code by Travis Oliphant.
295 # Modified and extended by Ed Schofield, Robert Cimrman,
296 # Nathan Bell, and Jake Vanderplas.
298 import warnings as _warnings
--> 300 from ._base import *
301 from ._csr import *
302 from ._csc import *
File D:\miniconda\lib\site-packages\scipy\sparse\_base.py:5
1 """Base class for sparse matrices"""
3 import numpy as np
----> 5 from ._sputils import (asmatrix, check_reshape_kwargs, check_shape,
6 get_sum_dtype, isdense, isscalarlike,
7 matrix, validateaxis, getdtype)
9 from ._matrix import spmatrix
11 __all__ = ['isspmatrix', 'issparse', 'sparray',
12 'SparseWarning', 'SparseEfficiencyWarning']
File D:\miniconda\lib\site-packages\scipy\sparse\_sputils.py:10
8 from math import prod
9 import scipy.sparse as sp
---> 10 from scipy._lib._util import np_long, np_ulong
13 __all__ = ['upcast', 'getdtype', 'getdata', 'isscalarlike', 'isintlike',
14 'isshape', 'issequence', 'isdense', 'ismatrix', 'get_sum_dtype',
15 'broadcast_shapes']
17 supported_dtypes = [np.bool_, np.byte, np.ubyte, np.short, np.ushort, np.intc,
18 np.uintc, np_long, np_ulong, np.longlong, np.ulonglong,
19 np.float32, np.float64, np.longdouble,
20 np.complex64, np.complex128, np.clongdouble]
File D:\miniconda\lib\site-packages\scipy\_lib\_util.py:13
10 from typing import TypeAlias, TypeVar
12 import numpy as np
---> 13 from scipy._lib._array_api import array_namespace, is_numpy, xp_size
14 from scipy._lib._docscrape import FunctionDoc, Parameter
17 AxisError: type[Exception]
File D:\miniconda\lib\site-packages\scipy\_lib\_array_api.py:18
15 import numpy.typing as npt
17 from scipy._lib import array_api_compat
---> 18 from scipy._lib.array_api_compat import (
19 is_array_api_obj,
20 size as xp_size,
21 numpy as np_compat,
22 device as xp_device,
23 is_numpy_namespace as is_numpy,
24 is_cupy_namespace as is_cupy,
25 is_torch_namespace as is_torch,
26 is_jax_namespace as is_jax,
27 is_array_api_strict_namespace as is_array_api_strict
28 )
30 __all__ = [
31 '_asarray', 'array_namespace', 'assert_almost_equal', 'assert_array_almost_equal',
32 'get_xp_devices',
(...)
38 'xp_take_along_axis', 'xp_unsupported_param_msg', 'xp_vector_norm',
39 ]
42 # To enable array API and strict array-like input validation
File D:\miniconda\lib\site-packages\scipy\_lib\array_api_compat\numpy\__init__.py:1
----> 1 from numpy import * # noqa: F403
3 # from numpy import * doesn't overwrite these builtin names
4 from numpy import abs, max, min, round # noqa: F401
File D:\miniconda\lib\site-packages\numpy\testing\__init__.py:11
8 from unittest import TestCase
10 from . import _private
---> 11 from ._private.utils import *
12 from ._private.utils import (_assert_valid_refcount, _gen_alignment_data)
13 from ._private import extbuild
File D:\miniconda\lib\site-packages\numpy\testing\_private\utils.py:469
465 pprint.pprint(desired, msg)
466 raise AssertionError(msg.getvalue())
--> 469 @np._no_nep50_warning()
470 def assert_almost_equal(actual, desired, decimal=7, err_msg='', verbose=True):
471 """
472 Raises an AssertionError if two items are not equal up to desired
473 precision.
(...)
537
538 """
539 __tracebackhide__ = True # Hide traceback for py.test
File D:\miniconda\lib\site-packages\numpy\__init__.py:414, in __getattr__(attr)
410 raise AttributeError(__former_attrs__[attr], name=None)
412 if attr in __expired_attributes__:
413 raise AttributeError(
--> 414 f"`np.{attr}` was removed in the NumPy 2.0 release. "
415 f"{__expired_attributes__[attr]}",
416 name=None
417 )
419 if attr == "chararray":
420 warnings.warn(
421 "`np.chararray` is deprecated and will be removed from "
422 "the main namespace in the future. Use an array with a string "
423 "or bytes dtype instead.", DeprecationWarning, stacklevel=2)
AttributeError: module 'numpy' has no attribute '_no_nep50_warning'
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这篇文章深入解析了NumPy库中的testing.assert_equal函数，介绍了如何在Python科学计算中进行精确的数据比较，适合对数值计算和测试感兴趣的开发者阅读。
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