在运行t检验时，Python运行时错误

Python Runtime Error on running T-Test

本文关键字：Python 运行时错误 检验 运行      更新时间：2023-10-16

我正在调用一个python函数，以从我的C 代码中计算" t检验"。函数调用如下：

#include <iostream>
#include "Python.h"
#include "/usr/local/lib/python2.7/site-packages/numpy/core/include/numpy/arrayobject.h"
#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION
int main(int argc, char** argv)
{
    Py_Initialize();
    PyRun_SimpleString("import sys");
    PyRun_SimpleString("sys.path.append("PATH_TO_MOD")");
    PyObject *pName = PyString_FromString("tmpPyth");
    PyObject *pModule = PyImport_Import(pName);

    double arr[] ={9.74219, 10.2226, 8.7469, 8.69791, 9.96442, 9.96472, 9.37913, 9.75004};
    double arr1[] ={9.74219, 10.2226, 8.7469, 8.69791, 9.96442, 9.96472, 9.37913, 9.75004};
    PyObject *lst = PyList_New(8);
    PyObject *lst1 = PyList_New(8);
    // if (!lst)
    //     return NULL;
    for (int i = 0; i < 8; i++) {
        PyObject *num = PyFloat_FromDouble(arr[i]);
        PyObject *num1 = PyFloat_FromDouble(arr1[i]);
        PyList_SET_ITEM(lst, i, num);
        PyList_SET_ITEM(lst1, i, num1);
    }
    PyObject *pArgs = PyTuple_New(2);
    PyTuple_SetItem(pArgs, 0, lst);
    PyTuple_SetItem(pArgs, 1, lst1);
    if (pModule != NULL) {
        PyObject *pFunc = PyObject_GetAttrString(pModule, "blah");
        if(pFunc != NULL){
            PyObject_CallObject(pFunc, pArgs);
        }
    }
    else
        std::cout << "Module path provided may be wrong. Module not found.nn";
    return 0;
}

和我的Python模块定义如下：

import numpy
import scipy
import matplotlib
from scipy import stats
def blah(baseline, follow_up):
    paired_sample  = stats.ttest_rel(baseline , follow_up )
    print "The t-statistic is %.3f and the p-value is %.3f." % paired_sample

现在，当我尝试运行此操作时，我会得到以下运行时例外：

/usr/local/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/stats/stats.py:3458: RuntimeWarning: invalid value encountered in divide
  t = np.divide(dm, denom)

但是，如果我明确定义列表并尝试执行" t检验"功能，则运行良好。运行函数定义如下：

import numpy
import scipy
import matplotlib
from scipy import stats
    def blah():
        baseline = [9.74219, 10.2226, 8.7469, 8.69791, 9.96442, 9.96472, 9.37913, 9.75004]
        follow_up = [9.94227,9.46763,8.53081,9.43679,9.97695,10.4285,10.159,8.86134]
        paired_sample  = stats.ttest_rel(baseline , follow_up )
        print "The t-statistic is %.3f and the p-value is %.3f." % paired_sample

我假设我在定义传递给Python脚本的列表时犯了一些错误，但无法弄清楚什么。任何帮助将不胜感激。

arr1在您的C 代码中与arr相同，因此除以零。由于您的Python代码中的baseline和follow_up不同，因此您不会遇到错误。

对于较大的数组，您不想通过python列表将它们包装，而是直接将阵列发送到Python。我已经修改了您上面的代码以执行此操作：

-- pyfromc.cc --
#include <iostream>
#include <Python.h>
int main(int argc, char** argv)
{
    Py_Initialize();
    PyRun_SimpleString("import sys; sys.path.append('.')");
    // PyRun_SimpleString("print '\n'.join(sys.path)");
    PyObject *pName = PyString_FromString("ttest");
    PyObject *pModule = PyImport_Import(pName);
    double arr[] ={9.74219, 10.2226, 8.7469, 8.69791, 9.96442, 9.96472, 9.37913, 9.75004};
    double arr1[] ={9.94227,9.46763,8.53081,9.43679,9.97695,10.4285,10.159,8.86134};
    PyObject *pArgs = PyTuple_New(3);
    PyTuple_SetItem(pArgs, 0, PyLong_FromLong(8));
    PyTuple_SetItem(pArgs, 1, PyLong_FromVoidPtr(arr));
    PyTuple_SetItem(pArgs, 2, PyLong_FromVoidPtr(arr1));
    if (pModule != NULL) {
        PyObject *pFunc = PyObject_GetAttrString(pModule, "blahptr");
        if(pFunc != NULL){
            PyObject_CallObject(pFunc, pArgs);
        }
    }
    else
        std::cout << "Module path provided may be wrong. Module not found.nn";
    return 0;
}

和python侧：

-- ttest.py --
from ctypes import POINTER, c_double, cast
c_double_p = POINTER(c_double)
import numpy as np
from scipy import stats
def blahptr(n, baseline_ptr, follow_up_ptr):
    baseline = np.ctypeslib.as_array(cast(baseline_ptr, c_double_p), shape=(n,))
    follow_up = np.ctypeslib.as_array(cast(follow_up_ptr, c_double_p), shape=(n,))
    return blah(baseline, follow_up)
def blah(baseline, follow_up):
    paired_sample  = stats.ttest_rel(baseline , follow_up )
    print "The t-statistic is %.3f and the p-value is %.3f." % paired_sample
    return paired_sample

为了在Mac OS X上编译并运行代码，我使用以下内容：

$ PYENV=/path/to/python/env
$ c++ pyfromc.cc -I$PYENV/include/python2.7 -L$PYENV/lib -lpython2.7    
$ PYTHONHOME=$PYENV DYLD_LIBRARY_PATH=$PYENV/lib ./a.out 
The t-statistic is -0.187 and the p-value is 0.857.

通过将环境变量设置在与可执行文件相同的行上，BASH解释器仅在命令的持续时间内将它们设置为其他命令。

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