blocks|key|454121|text|您可以使用链接加载器依赖工具来查看构建的C级挂钩组件，并查看它们是否对您选择的blas和lapack具有外部依赖关系。我现在不在linux机器附近，但在OS+X机器上，您可以在包含安装的site-packages目录中执行此操作：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|454122|$+otool+-L+numpy/core/_dotblas.so+
numpy/core/_dotblas.so:
++++/System/Library/Frameworks/Accelerate.framework/Versions/A/Accelerate+(compatibility+version+1.0.0,+current+version+4.0.0)
++++/usr/lib/libSystem.B.dylib+(compatibility+version+1.0.0,+current+version+125.2.0)
++++/System/Library/Frameworks/vecLib.framework/Versions/A/vecLib+(compatibility+version+1.0.0,+current+version+268.0.1)

$+otool+-L+scipy/linalg/flapack.so+
scipy/linalg/flapack.so+(architecture+i386):
++++/System/Library/Frameworks/Accelerate.framework/Versions/A/Accelerate+(compatibility+version+1.0.0,+current+version+4.0.0)
++++/usr/local/lib/libgcc_s.1.dylib+(compatibility+version+1.0.0,+current+version+1.0.0)
++++/usr/lib/libSystem.B.dylib+(compatibility+version+1.0.0,+current+version+111.1.4)
++++/System/Library/Frameworks/vecLib.framework/Versions/A/vecLib+(compatibility+version+1.0.0,+current+version+242.0.0)
scipy/linalg/flapack.so+(architecture+ppc):
++++/System/Library/Frameworks/Accelerate.framework/Versions/A/Accelerate+(compatibility+version+1.0.0,+current+version+4.0.0)
++++/usr/local/lib/libgcc_s.1.dylib+(compatibility+version+1.0.0,+current+version+1.0.0)
++++/usr/lib/libSystem.B.dylib+(compatibility+version+1.0.0,+current+version+111.1.4)

$+otool+-L+scipy/linalg/fblas.so+
scipy/linalg/fblas.so+(architecture+i386):
++++/System/Library/Frameworks/Accelerate.framework/Versions/A/Accelerate+(compatibility+version+1.0.0,+current+version+4.0.0)
++++/usr/local/lib/libgcc_s.1.dylib+(compatibility+version+1.0.0,+current+version+1.0.0)
++++/usr/lib/libSystem.B.dylib+(compatibility+version+1.0.0,+current+version+111.1.4)
++++/System/Library/Frameworks/vecLib.framework/Versions/A/vecLib+(compatibility+version+1.0.0,+current+version+242.0.0)
scipy/linalg/fblas.so+(architecture+ppc):
++++/System/Library/Frameworks/Accelerate.framework/Versions/A/Accelerate+(compatibility+version+1.0.0,+current+version+4.0.0)
++++/usr/local/lib/libgcc_s.1.dylib+(compatibility+version+1.0.0,+current+version+1.0.0)
++++/usr/lib/libSystem.B.dylib+(compatibility+version+1.0.0,+current+version+111.1.4)|code-block|syntax|javascript|454123|在gnu/Linux系统上用ldd代替otool，您应该会得到所需的答案。|offset|length|style|CODE|454124|entityMap^0|0|0|E|3|J|5|0^^$0|@$1|2|3|4|5|6|7|O|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|P|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|Q|8|@$I|R|J|S|K|L]|$I|T|J|U|K|L]]|9|@]|A|$]]|$1|M|3|-4|5|6|7|V|8|@]|9|@]|A|$]]]|N|$]]

You can use the link loader dependency tool to look at the C level hook components of your build and see whether they have external dependencies on your blas and lapack of choice. I am not near a linux box right now, but on an OS X machine you can do this inside the site-packages directory which holds the installations:

<pre><code>$ otool -L numpy/core/_dotblas.so 
numpy/core/_dotblas.so:
 /System/Library/Frameworks/Accelerate.framework/Versions/A/Accelerate (compatibility version 1.0.0, current version 4.0.0)
 /usr/lib/libSystem.B.dylib (compatibility version 1.0.0, current version 125.2.0)
 /System/Library/Frameworks/vecLib.framework/Versions/A/vecLib (compatibility version 1.0.0, current version 268.0.1)

$ otool -L scipy/linalg/flapack.so 
scipy/linalg/flapack.so (architecture i386):
 /System/Library/Frameworks/Accelerate.framework/Versions/A/Accelerate (compatibility version 1.0.0, current version 4.0.0)
 /usr/local/lib/libgcc_s.1.dylib (compatibility version 1.0.0, current version 1.0.0)
 /usr/lib/libSystem.B.dylib (compatibility version 1.0.0, current version 111.1.4)
 /System/Library/Frameworks/vecLib.framework/Versions/A/vecLib (compatibility version 1.0.0, current version 242.0.0)
scipy/linalg/flapack.so (architecture ppc):
 /System/Library/Frameworks/Accelerate.framework/Versions/A/Accelerate (compatibility version 1.0.0, current version 4.0.0)
 /usr/local/lib/libgcc_s.1.dylib (compatibility version 1.0.0, current version 1.0.0)
 /usr/lib/libSystem.B.dylib (compatibility version 1.0.0, current version 111.1.4)

$ otool -L scipy/linalg/fblas.so 
scipy/linalg/fblas.so (architecture i386):
 /System/Library/Frameworks/Accelerate.framework/Versions/A/Accelerate (compatibility version 1.0.0, current version 4.0.0)
 /usr/local/lib/libgcc_s.1.dylib (compatibility version 1.0.0, current version 1.0.0)
 /usr/lib/libSystem.B.dylib (compatibility version 1.0.0, current version 111.1.4)
 /System/Library/Frameworks/vecLib.framework/Versions/A/vecLib (compatibility version 1.0.0, current version 242.0.0)
scipy/linalg/fblas.so (architecture ppc):
 /System/Library/Frameworks/Accelerate.framework/Versions/A/Accelerate (compatibility version 1.0.0, current version 4.0.0)
 /usr/local/lib/libgcc_s.1.dylib (compatibility version 1.0.0, current version 1.0.0)
 /usr/lib/libSystem.B.dylib (compatibility version 1.0.0, current version 111.1.4)
</code></pre>

substitute <code>ldd</code> in place of <code>otool</code> on a gnu/Linux system and you should get the answers you need.

blocks|key|454175|text|您要搜索的内容是：system+info|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|454176|我用atlas编译了numpy/scipy，我可以用以下命令检查：|454177|import+numpy.distutils.system_info+as+sysinfo
sysinfo.get_info('atlas')|code-block|syntax|javascript|454178|有关更多命令，请查看文档。|454179|entityMap|0|LINK|mutability|MUTABLE|url|https://github.com/numpy/numpy/blob/master/numpy/distutils/system_info.py^0|9|B|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|U|8|@]|9|@$A|V|B|W|1|X]]|C|$]]|$1|D|3|E|5|6|7|Y|8|@]|9|@]|C|$]]|$1|F|3|G|5|H|7|Z|8|@]|9|@]|C|$I|J]]|$1|K|3|L|5|6|7|10|8|@]|9|@]|C|$]]|$1|M|3|-4|5|6|7|11|8|@]|9|@]|C|$]]]|N|$O|$5|P|Q|R|C|$S|T]]]]

What you are searching for is this:
<a href="https://github.com/numpy/numpy/blob/master/numpy/distutils/system_info.py" rel="noreferrer">system info</a>

I compiled numpy/scipy with atlas and i can check this with:

<pre><code>import numpy.distutils.system_info as sysinfo
sysinfo.get_info('atlas')
</code></pre>

Check the documentation for more commands.

blocks|key|454231|text|方法numpy.show_config()+(或numpy.__config__.show())输出在构建时收集的有关链接的信息。我的输出如下所示。我想这意味着我正在使用Mac+OS附带的BLAS/LAPACK。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|454232|>>>+import+numpy+as+np
>>>+np.show_config()

lapack_opt_info:
++++extra_link_args+=+['-Wl,-framework',+'-Wl,Accelerate']
++++extra_compile_args+=+['-msse3']
++++define_macros+=+[('NO_ATLAS_INFO',+3)]
blas_opt_info:
++++extra_link_args+=+['-Wl,-framework',+'-Wl,Accelerate']
++++extra_compile_args+=+['-msse3',+'-I/System/Library/Frameworks/vecLib.framework/Headers']
++++define_macros+=+[('NO_ATLAS_INFO',+3)]|code-block|syntax|javascript|454233|entityMap^0|2|J|O|N|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@$9|N|A|O|B|C]|$9|P|A|Q|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|R|8|@]|D|@]|E|$I|J]]|$1|K|3|-4|5|6|7|S|8|@]|D|@]|E|$]]]|L|$]]

The method <code>numpy.show_config()</code> (or <code>numpy.__config__.show()</code>) outputs information about linkage gathered at build time. My output looks like this. I think it means I am using the BLAS/LAPACK that ships with Mac OS. 

<pre><code>&gt;&gt;&gt; import numpy as np
&gt;&gt;&gt; np.show_config()

lapack_opt_info:
 extra_link_args = ['-Wl,-framework', '-Wl,Accelerate']
 extra_compile_args = ['-msse3']
 define_macros = [('NO_ATLAS_INFO', 3)]
blas_opt_info:
 extra_link_args = ['-Wl,-framework', '-Wl,Accelerate']
 extra_compile_args = ['-msse3', '-I/System/Library/Frameworks/vecLib.framework/Headers']
 define_macros = [('NO_ATLAS_INFO', 3)]
</code></pre>

blocks|key|454277|text|您可以使用show_config()显示BLAS、LAPACK、MKL链接|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|454278|import+numpy+as+np
np.show_config()|code-block|syntax|javascript|454279|对我来说，它给出了输出：|454280|mkl_info:
++++libraries+=+['mkl_rt',+'pthread']
++++library_dirs+=+['/my/environment/path/lib']
++++define_macros+=+[('SCIPY_MKL_H',+None),+('HAVE_CBLAS',+None)]
++++include_dirs+=+['/my/environment/path/include']
blas_mkl_info:
++++libraries+=+['mkl_rt',+'pthread']
++++library_dirs+=+['/my/environment/path/lib']
++++define_macros+=+[('SCIPY_MKL_H',+None),+('HAVE_CBLAS',+None)]
++++include_dirs+=+['/my/environment/path/include']
blas_opt_info:
++++libraries+=+['mkl_rt',+'pthread']
++++library_dirs+=+['/my/environment/path/lib']
++++define_macros+=+[('SCIPY_MKL_H',+None),+('HAVE_CBLAS',+None)]
++++include_dirs+=+['/my/environment/path/include']
lapack_mkl_info:
++++libraries+=+['mkl_rt',+'pthread']
++++library_dirs+=+['/my/environment/path/lib']
++++define_macros+=+[('SCIPY_MKL_H',+None),+('HAVE_CBLAS',+None)]
++++include_dirs+=+['/my/environment/path/include']
lapack_opt_info:
++++libraries+=+['mkl_rt',+'pthread']
++++library_dirs+=+['/my/environment/path/lib']
++++define_macros+=+[('SCIPY_MKL_H',+None),+('HAVE_CBLAS',+None)]
++++include_dirs+=+['/my/environment/path/include']|454281|entityMap^0|5|D|0|0|0|0^^$0|@$1|2|3|4|5|6|7|Q|8|@$9|R|A|S|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|T|8|@]|D|@]|E|$I|J]]|$1|K|3|L|5|6|7|U|8|@]|D|@]|E|$]]|$1|M|3|N|5|H|7|V|8|@]|D|@]|E|$I|J]]|$1|O|3|-4|5|6|7|W|8|@]|D|@]|E|$]]]|P|$]]

You can display BLAS, LAPACK, MKL linkage using <code>show_config()</code>:

<pre><code>import numpy as np
np.show_config()
</code></pre>

Which for me gives output: 

<pre><code>mkl_info:
 libraries = ['mkl_rt', 'pthread']
 library_dirs = ['/my/environment/path/lib']
 define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
 include_dirs = ['/my/environment/path/include']
blas_mkl_info:
 libraries = ['mkl_rt', 'pthread']
 library_dirs = ['/my/environment/path/lib']
 define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
 include_dirs = ['/my/environment/path/include']
blas_opt_info:
 libraries = ['mkl_rt', 'pthread']
 library_dirs = ['/my/environment/path/lib']
 define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
 include_dirs = ['/my/environment/path/include']
lapack_mkl_info:
 libraries = ['mkl_rt', 'pthread']
 library_dirs = ['/my/environment/path/lib']
 define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
 include_dirs = ['/my/environment/path/include']
lapack_opt_info:
 libraries = ['mkl_rt', 'pthread']
 library_dirs = ['/my/environment/path/lib']
 define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
 include_dirs = ['/my/environment/path/include']
</code></pre>

blocks|key|454323|text|如果你安装了anaconda导航器(在www.anaconda.com/anaconda/install/对于linux，Windows或macOS)+-+blas，scipy和numpy都会被安装，你可以通过点击导航器主页左侧的环境标签来查看它们(按照字母顺序查找每个目录)。安装完整的anaconda+(而不是miniconda或单独的包)将负责安装数据科学所需的许多基本包。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|454324|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|D|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|E|8|@]|9|@]|A|$]]]|C|$]]

If you installed anaconda-navigator (at www.anaconda.com/anaconda/install/ for linux, Windows or macOS) - blas, scipy and numpy will all be installed and you can see them by clicking environments tab on left side of navigator home page (look for each directory in alpha order). Installing full anaconda (as opposed to miniconda or individual packages) will take care of installing many of the essential packages needed for data science.

I am builing my numpy/scipy environment based on blas and lapack more or less based on <a href="http://www.tfinley.net/notes/blas-lapack/" rel="noreferrer">this</a> walk through. 

When I am done, how can I check, that my numpy/scipy functions really do use the previously built blas/lapack functionalities?

How to check BLAS/LAPACK linkage in NumPy and SciPy?

Windows

Linux

我正在基于blas和lapack构建我的numpy/scipy环境，或多或少基于遍历。完成后，如何检查我的numpy/scipy函数是否真的使用了之前构建的blas/lapack功能？

问如何在NumPy和SciPy中检查BLAS/LAPACK链接？
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