Cython:“严重错误:numpy / arrayobject.h:没有此类文件或目录”

问题:Cython:“严重错误:numpy / arrayobject.h:没有此类文件或目录”

我试图加快答案在这里使用用Cython。我尝试编译代码(在完成此处cygwinccompiler.py介绍的hack 之后),但出现错误。谁能告诉我我的代码是否有问题,或者Cython有点神秘?fatal error: numpy/arrayobject.h: No such file or directory...compilation terminated

下面是我的代码。

import numpy as np
import scipy as sp
cimport numpy as np
cimport cython

cdef inline np.ndarray[np.int, ndim=1] fbincount(np.ndarray[np.int_t, ndim=1] x):
    cdef int m = np.amax(x)+1
    cdef int n = x.size
    cdef unsigned int i
    cdef np.ndarray[np.int_t, ndim=1] c = np.zeros(m, dtype=np.int)

    for i in xrange(n):
        c[<unsigned int>x[i]] += 1

    return c

cdef packed struct Point:
    np.float64_t f0, f1

@cython.boundscheck(False)
def sparsemaker(np.ndarray[np.float_t, ndim=2] X not None,
                np.ndarray[np.float_t, ndim=2] Y not None,
                np.ndarray[np.float_t, ndim=2] Z not None):

    cdef np.ndarray[np.float64_t, ndim=1] counts, factor
    cdef np.ndarray[np.int_t, ndim=1] row, col, repeats
    cdef np.ndarray[Point] indices

    cdef int x_, y_

    _, row = np.unique(X, return_inverse=True); x_ = _.size
    _, col = np.unique(Y, return_inverse=True); y_ = _.size
    indices = np.rec.fromarrays([row,col])
    _, repeats = np.unique(indices, return_inverse=True)
    counts = 1. / fbincount(repeats)
    Z.flat *= counts.take(repeats)

    return sp.sparse.csr_matrix((Z.flat,(row,col)), shape=(x_, y_)).toarray()

I’m trying to speed up the answer here using Cython. I try to compile the code (after doing the cygwinccompiler.py hack explained here), but get a fatal error: numpy/arrayobject.h: No such file or directory...compilation terminated error. Can anyone tell me if it’s a problem with my code, or some esoteric subtlety with Cython?

Below is my code.

import numpy as np
import scipy as sp
cimport numpy as np
cimport cython

cdef inline np.ndarray[np.int, ndim=1] fbincount(np.ndarray[np.int_t, ndim=1] x):
    cdef int m = np.amax(x)+1
    cdef int n = x.size
    cdef unsigned int i
    cdef np.ndarray[np.int_t, ndim=1] c = np.zeros(m, dtype=np.int)

    for i in xrange(n):
        c[<unsigned int>x[i]] += 1

    return c

cdef packed struct Point:
    np.float64_t f0, f1

@cython.boundscheck(False)
def sparsemaker(np.ndarray[np.float_t, ndim=2] X not None,
                np.ndarray[np.float_t, ndim=2] Y not None,
                np.ndarray[np.float_t, ndim=2] Z not None):

    cdef np.ndarray[np.float64_t, ndim=1] counts, factor
    cdef np.ndarray[np.int_t, ndim=1] row, col, repeats
    cdef np.ndarray[Point] indices

    cdef int x_, y_

    _, row = np.unique(X, return_inverse=True); x_ = _.size
    _, col = np.unique(Y, return_inverse=True); y_ = _.size
    indices = np.rec.fromarrays([row,col])
    _, repeats = np.unique(indices, return_inverse=True)
    counts = 1. / fbincount(repeats)
    Z.flat *= counts.take(repeats)

    return sp.sparse.csr_matrix((Z.flat,(row,col)), shape=(x_, y_)).toarray()

回答 0

在你里面setup.pyExtension应该有论据include_dirs=[numpy.get_include()]

另外,您np.import_array()的代码中缺少您。

示例setup.py:

from distutils.core import setup, Extension
from Cython.Build import cythonize
import numpy

setup(
    ext_modules=[
        Extension("my_module", ["my_module.c"],
                  include_dirs=[numpy.get_include()]),
    ],
)

# Or, if you use cythonize() to make the ext_modules list,
# include_dirs can be passed to setup()

setup(
    ext_modules=cythonize("my_module.pyx"),
    include_dirs=[numpy.get_include()]
)    

In your setup.py, the Extension should have the argument include_dirs=[numpy.get_include()].

Also, you are missing np.import_array() in your code.

Example setup.py:

from distutils.core import setup, Extension
from Cython.Build import cythonize
import numpy

setup(
    ext_modules=[
        Extension("my_module", ["my_module.c"],
                  include_dirs=[numpy.get_include()]),
    ],
)

# Or, if you use cythonize() to make the ext_modules list,
# include_dirs can be passed to setup()

setup(
    ext_modules=cythonize("my_module.pyx"),
    include_dirs=[numpy.get_include()]
)    

回答 1

对于像您这样的单文件项目,另一种选择是使用pyximportsetup.py如果使用IPython,则无需创建… …甚至无需打开命令行…都非常方便。您可以尝试在IPython或普通的Python脚本中运行以下命令:

import numpy
import pyximport
pyximport.install(setup_args={"script_args":["--compiler=mingw32"],
                              "include_dirs":numpy.get_include()},
                  reload_support=True)

import my_pyx_module

print my_pyx_module.some_function(...)
...

当然,您可能需要编辑编译器。这使得导入和重新加载对.pyx文件的作用与对文件的作用相同.py

资料来源:http : //wiki.cython.org/InstallingOnWindows

For a one-file project like yours, another alternative is to use pyximport. You don’t need to create a setup.py … you don’t need to even open a command line if you use IPython … it’s all very convenient. In your case, try running these commands in IPython or in a normal Python script:

import numpy
import pyximport
pyximport.install(setup_args={"script_args":["--compiler=mingw32"],
                              "include_dirs":numpy.get_include()},
                  reload_support=True)

import my_pyx_module

print my_pyx_module.some_function(...)
...

You may need to edit the compiler of course. This makes import and reload work the same for .pyx files as they work for .py files.

Source: http://wiki.cython.org/InstallingOnWindows


回答 2

该错误意味着在编译过程中找不到numpy头文件。

尝试这样做export CFLAGS=-I/usr/lib/python2.7/site-packages/numpy/core/include/,然后进行编译。这是几个不同软件包的问题。在ArchLinux中,存在针对同一问题的错误: https //bugs.archlinux.org/task/22326

The error means that a numpy header file isn’t being found during compilation.

Try doing export CFLAGS=-I/usr/lib/python2.7/site-packages/numpy/core/include/, and then compiling. This is a problem with a few different packages. There’s a bug filed in ArchLinux for the same issue: https://bugs.archlinux.org/task/22326


回答 3

简单的答案

一种更简单的方法是将路径添加到文件中distutils.cfg。默认情况下,它代表Windows 7的路径C:\Python27\Lib\distutils\。您只需声明以下内容即可解决:

[build_ext]
include_dirs= C:\Python27\Lib\site-packages\numpy\core\include

整个配置文件

为了给您一个示例,配置文件的外观,我的整个文件显示为:

[build]
compiler = mingw32

[build_ext]
include_dirs= C:\Python27\Lib\site-packages\numpy\core\include
compiler = mingw32

Simple answer

A way simpler way is to add the path to your file distutils.cfg. It’s path behalf of Windows 7 is by default C:\Python27\Lib\distutils\. You just assert the following contents and it should work out:

[build_ext]
include_dirs= C:\Python27\Lib\site-packages\numpy\core\include

Entire config file

To give you an example how the config file could look like, my entire file reads:

[build]
compiler = mingw32

[build_ext]
include_dirs= C:\Python27\Lib\site-packages\numpy\core\include
compiler = mingw32

回答 4

它应该能够在此处cythonize()提到的函数中执行此操作,但是由于存在已知问题,因此它不起作用

It should be able to do it within cythonize() function as mentioned here, but it doesn’t work beacuse there is a known issue


回答 5

如果您懒得编写设置文件并弄清楚包含目录的路径,请尝试cyper。它可以编译您的Cython代码并进行设置include_dirs自动为Numpy。

将您的代码加载到字符串中,然后简单地运行cymodule = cyper.inline(code_string),然后您的函数cymodule.sparsemaker即刻可用。像这样

code = open(your_pyx_file).read()
cymodule = cyper.inline(code)

cymodule.sparsemaker(...)
# do what you want with your function

您可以通过安装cyper pip install cyper

If you are too lazy to write setup files and figure out the path for include directories, try cyper. It can compile your Cython code and set include_dirs for Numpy automatically.

Load your code into a string, then simply run cymodule = cyper.inline(code_string), then your function is available as cymodule.sparsemaker instantaneously. Something like this

code = open(your_pyx_file).read()
cymodule = cyper.inline(code)

cymodule.sparsemaker(...)
# do what you want with your function

You can install cyper via pip install cyper.