资源简介
附带安装指导,。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。
代码片段和文件信息
#!/usr/bin/env python
“““NumPy: array processing for numbers strings records and objects.
NumPy is a general-purpose array-processing package designed to
efficiently manipulate large multi-dimensional arrays of arbitrary
records without sacrificing too much speed for small multi-dimensional
arrays. NumPy is built on the Numeric code base and adds features
introduced by numarray as well as an extended C-API and the ability to
create arrays of arbitrary type which also makes NumPy suitable for
interfacing with general-purpose data-base applications.
There are also basic facilities for discrete fourier transform
basic linear algebra and random number generation.
“““
from __future__ import division print_function
DOCLINES = (__doc__ or ‘‘).split(“\n“)
import os
import sys
import subprocess
import textwrap
if sys.version_info[:2] < (2 6) or (3 0) <= sys.version_info[0:2] < (3 2):
raise RuntimeError(“Python version 2.6 2.7 or >= 3.2 required.“)
if sys.version_info[0] >= 3:
import builtins
else:
import __builtin__ as builtins
CLASSIFIERS = “““\
Development Status :: 5 - Production/Stable
Intended Audience :: Science/Research
Intended Audience :: Developers
License :: OSI Approved
Programming Language :: C
Programming Language :: Python
Programming Language :: Python :: 2
Programming Language :: Python :: 2.6
Programming Language :: Python :: 2.7
Programming Language :: Python :: 3
Programming Language :: Python :: 3.2
Programming Language :: Python :: 3.3
Programming Language :: Python :: 3.4
Programming Language :: Python :: 3.5
Programming Language :: Python :: Implementation :: CPython
Topic :: Software Development
Topic :: Scientific/Engineering
Operating System :: Microsoft :: Windows
Operating System :: POSIX
Operating System :: Unix
Operating System :: MacOS
“““
MAJOR = 1
MINOR = 11
MICRO = 2
ISRELEASED = True
VERSION = ‘%d.%d.%d‘ % (MAJOR MINOR MICRO)
# Return the git revision as a string
def git_version():
def _minimal_ext_cmd(cmd):
# construct minimal environment
env = {}
for k in [‘SYSTEMROOT‘ ‘PATH‘]:
v = os.environ.get(k)
if v is not None:
env[k] = v
# LANGUAGE is used on win32
env[‘LANGUAGE‘] = ‘C‘
env[‘LANG‘] = ‘C‘
env[‘LC_ALL‘] = ‘C‘
out = subprocess.Popen(cmd stdout = subprocess.PIPE env=env).communicate()[0]
return out
try:
out = _minimal_ext_cmd([‘git‘ ‘rev-parse‘ ‘HEAD‘])
GIT_REVISION = out.strip().decode(‘ascii‘)
except OSError:
GIT_REVISION = “Unknown“
return GIT_REVISION
# BEFORE importing setuptools remove MANIFEST. Otherwise it may not be
# properly updated when the contents of directories change (true for distutils
# not sure about setuptools).
if os.path.exists(‘MANIFEST‘):
os.remove(‘MANIFEST‘)
# This is a bit hackish: we are setting a global variable so that the
属性 大小 日期 时间 名称
----------- --------- ---------- ----- ----
文件 3251 2016-07-09 22:12 numpy-1.11.2\THANKS.txt
文件 14151 2016-10-03 17:51 numpy-1.11.2\setup.py
文件 5270 2016-10-03 17:42 numpy-1.11.2\INSTALL.rst.txt
文件 2060 2016-10-03 18:00 numpy-1.11.2\PKG-INFO
文件 7879 2016-10-03 17:42 numpy-1.11.2\site.cfg.example
文件 1252 2016-09-26 13:56 numpy-1.11.2\MANIFEST.in
文件 1543 2016-09-26 13:56 numpy-1.11.2\LICENSE.txt
文件 4926 2016-09-26 13:56 numpy-1.11.2\tools\swig\README
文件 3293 2016-09-26 13:56 numpy-1.11.2\tools\swig\pyfragments.swg
文件 808 2016-09-26 13:56 numpy-1.11.2\tools\swig\Makefile
文件 108672 2016-10-03 17:42 numpy-1.11.2\tools\swig\numpy.i
文件 889 2016-09-26 13:56 numpy-1.11.2\tools\swig\test\Array1.h
文件 15018 2016-09-26 13:56 numpy-1.11.2\tools\swig\test\testVector.py
文件 1420 2016-09-26 13:56 numpy-1.11.2\tools\swig\test\Vector.i
文件 1274 2016-09-26 13:56 numpy-1.11.2\tools\swig\test\Flat.cxx
文件 2309 2016-09-26 13:56 numpy-1.11.2\tools\swig\test\Array1.cxx
文件 905 2016-09-26 13:56 numpy-1.11.2\tools\swig\test\Fortran.i
文件 734 2016-09-26 13:56 numpy-1.11.2\tools\swig\test\Fortran.h
文件 1004 2016-09-26 13:56 numpy-1.11.2\tools\swig\test\ArrayZ.h
文件 2141 2016-09-26 13:56 numpy-1.11.2\tools\swig\test\setup.py
文件 16492 2016-09-26 13:56 numpy-1.11.2\tools\swig\test\testSuperTensor.py
文件 870 2016-09-26 13:56 numpy-1.11.2\tools\swig\test\Fortran.cxx
文件 1548 2016-09-26 13:56 numpy-1.11.2\tools\swig\test\Tensor.i
文件 1697 2016-09-26 13:56 numpy-1.11.2\tools\swig\test\SuperTensor.i
文件 14309 2016-09-26 13:56 numpy-1.11.2\tools\swig\test\testMatrix.py
文件 2579 2016-09-26 13:56 numpy-1.11.2\tools\swig\test\Farray.cxx
文件 1039 2016-09-26 13:56 numpy-1.11.2\tools\swig\test\Array2.h
文件 2210 2016-09-26 13:56 numpy-1.11.2\tools\swig\test\Matrix.h
文件 1402 2016-09-26 13:56 numpy-1.11.2\tools\swig\test\Matrix.i
文件 2303 2016-09-26 13:56 numpy-1.11.2\tools\swig\test\Vector.h
文件 16445 2016-09-26 13:56 numpy-1.11.2\tools\swig\test\testTensor.py
............此处省略1172个文件信息
- 上一篇:unity 液体动画特效(包含血液,雨,水流等)
- 下一篇:scrapy
相关资源
- NumPy Essentials epub
- Matplotlib中文手册.pdf
- numpy-1.12.1-cp35-none-win_amd64 whl zip包
- numpy-1.15.0-cp37-none-win32
- 《SciPy and NumPy》中文精要版
- 2018电影票房分析numpypandasmatplotlib
- 2019年华中杯B题数学建模数据处理
- Numpy 中文手册学习文档
- numpy-1.11.2-cp27-none-win32.whl
- NumPy中文文档97306
- SciPy and NumPy.pdf
- Pandas官方文档CHM格式
- numpy-1.18.3+mkl-cp38-cp38-win_amd64.whl
- numpy-1.16.2+mkl-cp37-cp37m-win_amd64.whl
- numpy-1.8.0-win64-py2.7
- numpy-1.17.2-cp37-cp37m-win_amd64.whl
- 免积分 numpy-1.11.3+mkl-cp27-cp27m-win_amd6
- TensorFlow、Keras、numpy安装库及安装方法
- numpy-1.16.5+mkl-cp37-cp37m-win_amd64.whl
- numpy-1.16.2-cp37-cp37m-win_amd64.whl
- numpy-1.13.3+mkl-cp27-cp27m-win_amd64.whl.zip
- numpy-1.14.5-cp36-cp36m-manylinux1_x86_64.whl
- scipy-0.19.1-cp27-cp27m-win32.whl(免积分)
- numpy-1.19.1+mkl-cp38-cp38-win_amd64.whl
- numpy-1.19.2+mkl-cp39-cp39-win_amd64.whl
- numpy-1.13.3+mkl-cp36-cp36m-win_amd64
- numpy-1.13.1+mkl-cp36-cp36m-win_amd64.whl
- numpy-1.16.5+mkl-cp36-cp36m-win_amd64.whl
- numpy-1.16.4+mkl-cp35-cp35m-win_amd64.whl
- KNN实现代码+数据可视化+决策边界
评论
共有 条评论