使用cython_gsl进行集成（加上将numpy.array寻址到cython）

我想提高代码的速度，所以我将我的原始Python代码转移到Cython。代码的瓶颈是我对

scipy.integral.quad

所做的集成部分，这是一组

numpy.array

和

sum

在2D数组的每一行上进行的串联。所以我试图重新编写我在Cython中使用的类

我的课程如下：

import numpy as np
import cosmology
from cython_gsl cimport *

ctypedef double * double_ptr
ctypedef void * void_ptr


cdef class Cosmology(object):
    cdef double omega_c
    def __init__(self, double omega_m=0.3, double omega_lam=0.7):
        # no quintessence, no radiation in this universe!
        self.omega_m = omega_m
        self.omega_lam = omega_lam
        self.omega_c = (1. - omega_m - omega_lam)

    cdef double a(self, double z):
        return 1./(1+z)

    cdef double E(self, double a):
        return (self.omega_m*a**(-3) + self.omega_c*a**(-2) + self.omega_lam)**0.5

    cdef double __angKernel(self, double x, void * params) nogil:
        cdef double alpha, f
        alpha = (<double_ptr> params)[0]
        f=self.E(alpha*x**-1)**-1
        return f

    cdef double Da(self, int size, double *z, double z_ref=0):
        cdef gsl_integration_workspace *w
        cdef double result, error, expected, alpha
        w = gsl_integration_workspace_alloc (1000)
        cdef gsl_function F
        if size>1:
           da = np.zeros(size)
           for i in range(size):
               da[i] = self.Da(1, &z[i], z_ref)
           return da
        else:
           if z[0] < 0:
                    raise ValueError("Redshift z must not be negative")
           if z[0] < z_ref:
                    raise ValueError("Redshift z must not be smaller than the reference redshift")

           expected = -4.0
           alpha = 1

           F.function = &self.__angKernel
           F.params = &alpha

           gsl_integration_qags (&F, z_ref+1, z[0]+1, 0, 1e-7, 1000, w, &result, &error)
           d=result
           rk = (abs(self.omega_c))**0.5
           if (rk*d > 0.01):
              if self.omega_c > 0:
                 d = sinh(rk*d)/rk
              if self.omega_c < 0:
                 d = sin(rk*d)/rk
           return d/(1+z[0])


cdef class halo_positions(object):
    cdef double *x 
    cdef double *y 
    def __init__(self, double[:] positions):
        self.x = &positions[0]
        self.y = &positions[1]

我不知道应该如何定义函数F来避免这个问题

---

秒：在

类halo_位置

中，我想更改它，以获得一个2xN维数组，并将其划分为两个1xN维数组，并将其分配给

x

和

y

< P>似乎类似于C++中的问题（我不在Python中编码，但问题似乎是相同的）。无法将成员函数转换为全局函数。请记住，gsl_函数是以下c_结构

struct gsl_function_struct 
{
   double (* function) (double x, void * params);
   void * params;
};

typedef struct gsl_function_struct gsl_function ;

您可以看到gsl.function是一个指向全局函数的指针（成员函数有一个额外的参数来保存指针“this”）

cython_gsl的github具有在全局函数上进行集成的功能

from cython_gsl cimport *

ctypedef double * double_ptr
ctypedef void * void_ptr

cdef double normal(double x, void * params) nogil:
  cdef double mu = (<double_ptr> params)[0]
  cdef double sigma = (<double_ptr> params)[1]

  return gsl_ran_gaussian_pdf(x - mu, sigma)

def cdf_numerical(double x, double mu, double sigma):
  cdef double alpha, result, error, expected
  cdef gsl_integration_workspace * W
  W = gsl_integration_workspace_alloc(1000)
  cdef gsl_function F
  cdef double params[1]
  cdef size_t neval

  params[0] = mu
  params[1] = sigma

  F.function = &normal
  F.params = params

  gsl_integration_qag(&F, -10, x, 1e-2, 1e-2, 1000, GSL_INTEG_GAUSS15, W, &result, &error)
  gsl_integration_workspace_free(W)

  return result

来自cython\u gsl cimport的

*
ctypedef double*double\u ptr
ctypedef void*void\u ptr
cdef双标准（双x，无效*参数）编号：
cdef双mu=（参数）[0]
cdef双西格玛=（参数）[1]
返回gsl\u ran\u gaussian\u pdf（x-mu，sigma）
def cdf_数值（双x、双mu、双西格玛）：
cdef双阿尔法，结果，错误，应为
cdef gsl_集成_工作区*W
W=gsl\u集成\u工作空间\u分配（1000）
cdef gsl_函数F
cdef双参数[1]
cdef大小
参数[0]=mu
参数[1]=西格玛
函数=&normal
F.params=params
gsl_积分_qag（&F，-10，x，1e-2，1e-2，1000，gsl_积分_高斯15，W，和结果，和错误）
gsl_集成_工作空间_自由（W）
返回结果

解决这个问题的一种方法是创建一个全局函数来包装成员函数。在这种情况下，需要在void参数中发送类指针

from cython_gsl cimport *

ctypedef double * double_ptr
ctypedef void * void_ptr

cdef double normal(double x, void * params) nogil:
  cdef double mu = (<double_ptr> params)[0]
  cdef double sigma = (<double_ptr> params)[1]

  return gsl_ran_gaussian_pdf(x - mu, sigma)

def cdf_numerical(double x, double mu, double sigma):
  cdef double alpha, result, error, expected
  cdef gsl_integration_workspace * W
  W = gsl_integration_workspace_alloc(1000)
  cdef gsl_function F
  cdef double params[1]
  cdef size_t neval

  params[0] = mu
  params[1] = sigma

  F.function = &normal
  F.params = params

  gsl_integration_qag(&F, -10, x, 1e-2, 1e-2, 1000, GSL_INTEG_GAUSS15, W, &result, &error)
  gsl_integration_workspace_free(W)

  return result