Python 将Anaconda MKL连接到C++/赛顿计划

我试图编译一个Cython程序，但是我在尝试链接LAPACK和BLAS时出错（它找不到库）。我有Anaconda Accelerate，它会自动将MKL链接到NumPy，所以我尝试复制NumPy的链接

>>> import numpy as np
>>> np.show_config()
mkl_info:
    include_dirs = ['/home/ubuntu/miniconda3/envs/LDFMap/include']
    define_macros = [('SCIPY_MKL_H', None)]
    libraries = ['mkl_intel_lp64', 'mkl_intel_thread', 'mkl_core', 'iomp5', 'pthread']
    library_dirs = ['/home/ubuntu/miniconda3/envs/LDFMap/lib']
blas_mkl_info:
    include_dirs = ['/home/ubuntu/miniconda3/envs/LDFMap/include']
    define_macros = [('SCIPY_MKL_H', None)]
    libraries = ['mkl_intel_lp64', 'mkl_intel_thread', 'mkl_core', 'iomp5', 'pthread']
    library_dirs = ['/home/ubuntu/miniconda3/envs/LDFMap/lib']
lapack_mkl_info:
    include_dirs = ['/home/ubuntu/miniconda3/envs/LDFMap/include']
    define_macros = [('SCIPY_MKL_H', None)]
    libraries = ['mkl_lapack95_lp64', 'mkl_intel_lp64', 'mkl_intel_thread', 'mkl_core', 'iomp5', 'pthread']
    library_dirs = ['/home/ubuntu/miniconda3/envs/LDFMap/lib']
blas_opt_info:
    include_dirs = ['/home/ubuntu/miniconda3/envs/LDFMap/include']
    define_macros = [('SCIPY_MKL_H', None)]
    libraries = ['mkl_intel_lp64', 'mkl_intel_thread', 'mkl_core', 'iomp5', 'pthread']
    library_dirs = ['/home/ubuntu/miniconda3/envs/LDFMap/lib']
openblas_lapack_info:
  NOT AVAILABLE
lapack_opt_info:
    include_dirs = ['/home/ubuntu/miniconda3/envs/LDFMap/include']
    define_macros = [('SCIPY_MKL_H', None)]
    libraries = ['mkl_lapack95_lp64', 'mkl_intel_lp64', 'mkl_intel_thread', 'mkl_core', 'iomp5', 'pthread']
    library_dirs = ['/home/ubuntu/miniconda3/envs/LDFMap/lib']

这是我的

setup.py

文件

from distutils.core import setup
from distutils.extension import Extension
from Cython.Distutils import build_ext
from Cython.Build import cythonize
import numpy as np
import os

setup(
    author = "Rohan Pandit",
    url='https://www.github.com/rohanp/LDFMap',
    ext_modules = cythonize([Extension("LDFMap",
                            sources = ["LDFMap.pyx"],
                            include_dirs = [np.get_include(), "/home/ubuntu/LDFMap/src/include", "/home/ubuntu/miniconda3/envs/LDFMap/include"],
                            language="c++",
                            libraries = ['mkl_lapack95_lp64', 'mkl_intel_lp64', 'mkl_intel_thread', 'mkl_core', 'iomp5', 'pthread'],
                            library_dirs = ["/home/ubuntu/LDFMap/src/include", '/home/ubuntu/miniconda3/envs/LDFMap/lib'],
                            extra_compile_args = ["-I /home/ubuntu/LDFMap/src/include", "-I /usr/local/include"],
                                        )])

        )

下面是我的错误消息： （为了可读性，我添加了换行符）

---

我不明白的是，如果此链接适用于NumPy，为什么它不适用于我的程序？

明确指定用于安装的包含路径和BLAS/LAPACK库将导致一个非常依赖平台且难以维护的模块

---

相反，您应该做的是使用scipy获取指向所需LAPACK函数的指针，如本文所述（请特别参阅第一个链接中的）。这样，如果Scipy安装了MKL，您的Cython程序也会自动使用MKL BLAS／LAPACK。

我从SyPy.LalAlq.Cython LaCack-C导入DGESVD 尝试了<代码>，（DGESVD是我使用的C++头文件所需要的），但我仍然有一个错误：<代码>符号未找到：（我试过…

cimport-dgesvd-as(u-dgesvd)

和…

cimport-dgesvd-as-dgesvd(u)

）@rohanp只适用于

=scipy-0.16

，对于早期版本的scipy，您需要执行整个

f2py_指针（scipy.linalg.blas.dgemm.\u cpointer）

等操作（例如对于dgemm）正如我在C++中所解释的那样，错误是在编译时，而不是在运行时发生的。这可能与我在使用C++代码>使用代码> CDEF ExtReNe>代码>的外部C++函数中调用DGESVD有关吗？你知道如何在AcANDA中用C++代码链接MKL库吗？

g++ -pthread -shared -L/home/ubuntu/miniconda3/envs/LDFMap/lib -Wl,  
-rpath=/home/ubuntu/miniconda3/envs/LDFMap/lib,--no-as-needed 
build/temp.linux-x86_64-3.4/LDFMap.o -L/home/ubuntu/LDFMap/src/include
-L/home/ubuntu/miniconda3/envs/LDFMap/lib -
L/home/ubuntu/miniconda3/envs/LDFMap/lib -lmkl_lapack95_lp64 - 
lmkl_intel_lp64 -lmkl_intel_thread -lmkl_core -liomp5 -lpthread - 
lpython3.4m -o /home/ubuntu/LDFMap/src/LDFMap.cpython-34m.so 

/usr/bin/ld: cannot find -lmkl_lapack95_lp64