将C结构数组转换为numpy数组 [英] Casting an array of C structs to a numpy array

问题描述

我从共享库中调用的函数返回的结构类似于以下信息:

A function I'm calling from a shared library returns a structure called info similar to this:

typedef struct cmplx {
  double real;
  double imag;
} cmplx;

typedef struct info{
  char *name;
  int arr_len;
  double *real_data
  cmplx *cmplx_data;
} info;

结构的一个字段是双精度数组，另一个字段是复数数组.如何将复数数组转换为numpy数组?对于双打，我有以下内容:

One of the fields of the structure is an array of doubles while the other is an array of complex numbers. How do I convert the array of complex numbers to a numpy array? For doubles I have the following:

from ctypes import *
import numpy as np

class cmplx(Structure):
    _fields_ = [("real", c_double),
                ("imag", c_double)]


class info(Structure):
    _fields_ = [("name", c_char_p),
                ("arr_len", c_int),
                ("real_data", POINTER(c_double)),
                ("cmplx_data", POINTER(cmplx))]

c_func.restype = info
ret_val = c_func()
data = np.ctypeslib.as_array(ret_val.contents.real_data, shape=(info.contents.arr_len,))

是否存在一个用于数字复数的小数线?我可以使用循环来做到这一点.

Is there a numpy one liner for complex numbers? I can do this using loops.

推荐答案

将字段定义为double并使用numpy创建复杂的视图:

Define your field as double and make a complex view with numpy:

class info(Structure):
    _fields_ = [("name", c_char_p),
                ("arr_len", c_int),
                ("real_data", POINTER(c_double)),
                ("cmplx_data", POINTER(c_double))]

c_func.restype = info
ret_val = c_func()
data = np.ctypeslib.as_array(ret_val.contents.real_data, shape=(info.contents.arr_len,))
complex_data = np.ctypeslib.as_array(ret_val.contents.cmplx_data, shape=(info.contents.arr_len,2)).view('complex128')

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