在Cython中向/从函数传递输入/输出 [英] Passing Input/Output to/from functions in Cython

问题描述

我正在尝试在cython中编写一个函数，该函数应该从python接收一个list参数，方法是通过在C / C ++中生成它的2D数组，然后以2D列表的形式返回给python，从而以某种方式对其进行操作。我简化了代码，问了我的问题：

I am trying to write a function in cython which should receive a list argument from python manipulate it in some way by generating a 2D array of it in C/C++ and then return it to python as a 2D list. I simplified the code to ask my question:

我希望 c_Func 可以执行无需编译的过程错误。第二个函数是可调用函数，但显然不起作用。首先，我必须处理不能用 double * 替换列表的问题，其次是 py_Func 无法返回 double * 。那么我应该如何更改这两个呢？

I expect c_Func to do the procedure which I can compile it without error. The second function is the callable function but obviously it doesn't work. First I have to deal with the problem that a list cannot be replaced by a double* and second it the problem that py_Func can't return a double*. So how should I change these two?

cdef double** c_Func(int dim,double* init_val):
    cdef double** frozen_ans= <double**> malloc(dim*sizeof(double))
    frozen_ans[0]=init_val
    return frozen_ans
def py_Func(int dim, double* init_val):
    return c_Func(dim,init_val)

推荐答案

我假设您要操作来自C / C ++。

I assume that you want to manipulate the data from C/C++.

请勿使用malloc，因为稍后您将无法释放该指针，并且代码将泄漏内存。取而代之的是使用可以稍后由python处理的容器，例如numpy数组。

Do not use malloc, as you're not going to be able to free that pointer later, and your code will leak memory. Use instead a container that can be handled later by python, like a numpy array for example.

使用'handle'是指当numpy数组以

With 'handle' I mean the fact that when the numpy array ends up in the python garbage collector, python will deallocate that memory block for you.

扩展numpy选项，您可以创建一个连续的c样式numpy数组 arr ，使用其地址& arr [0] （如（不为空），然后将其作为python numpy.ndarray 对象返回。请参阅此，以方便numpy对象访问。这样做的优点是 arr 可以被c代码当作ac数组。

Expanding on the numpy option, you can create a contiguous, c-style numpy array arr from within cython, fill it/use it as a c array from pure c code using its address &arr[0] (as long as it's not empty), and then return it as a python numpy.ndarray object. See this on numpy objects convenient access. This has the strong advantage that arr and can be treated as a c array from c code.

您的cython函数，如果您不想返回一个numpy数组，则可以使用 arr.tolist（）方法，但这会产生开销，因为您创建新列表。

At the end of your cython function, if you don't want to return a numpy array, you can use arr.tolist() method, but this will incur in a overhead, because you are creating a new list.

关于输入部分，您说您的函数必须接受python列表。它可以是：

Regarding the input part, you say your function must accept a python list. It could either:

• 接受一个numpy数组，对其进行操作并返回它。


• 接受一个python列表 l ，将其转换为具有 np.ascontiguousarray（l）的numpy数组，对其进行处理并返回。在这种情况下，您会产生复制开销，但是您几乎无能为力。

• accept a numpy array, manipulate it and return it.
• accept a python list l, cast it to a numpy array with np.ascontiguousarray(l), manipulate it and return it. In this case you're incurring in a copy overhead, but there's little you can about it.

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