自动比较两个系列-相异性检验

Here is a C implementation of an algorithm to compute the divergence of actual data from predicted data. The algorithm comes from a book entitled Practical BASIC Programs from Osborne/McGraw-Hill copyright 1980.

这是.h文件:

/*
 * divergence.h
 *
 *  Created on: Jan 13, 2011
 *      Author: Erik Oosterwal
 */

#ifndef DIVERGENCE_H_
#define DIVERGENCE_H_

typedef struct
{
    int DataSize;
    float TotalError;
    float AbsError;       //< Total Absolute Error
    float SqError;        //< Total Squared Error
    float MeanError;
    float MeanAbsError;
    float MeanSqError;
    float RMSError;     //< Root Mean Square Error
}DIVERGENCE_ERROR_TYPE;

void Divergence__Error(int size, float expected[], float actual[], DIVERGENCE_ERROR_TYPE *error);


// Prefer to use abs() from "stdlib.h"
#ifndef ABS
    #define ABS(x) ((x)>0) ? (x) : (0-(x))     //< Not safe!!! - Do not increment parameter inside ABS()!
#endif


#endif /* DIVERGENCE_H_ */

....c 文件:

/*
 * divergence.c
 *
 *  Created on: Jan 13, 2011
 *      Author: Erik Oosterwal
 */

#include "math.h"
#include "divergence.h"

/**
 *      @brief  Compute divergence from expected values.
 *
 *      @details    Compute the raw errors, absolute errors, root mean square errors,
 *                  etc. for a series of values.
 *
 *      @param  size - integer value defines the number of values to compare.
 */
void Divergence__Error(int size, float expected[], float actual[], DIVERGENCE_ERROR_TYPE *error)
{
    double total_err = 0.0;
    double abs_err = 0.0;
    double abs_sqr_err = 0.0;
    double temp = 0.0;
    int index = 0;

    for(index=0; index<size; index++)
    {
        temp = (double)(actual[index])-(double)(expected[index]);
        total_err+=temp;
        abs_err+=ABS(temp);
        abs_sqr_err+=pow(ABS(temp),2);
    }

    temp = (double)size;
    error->DataSize = (int)size;
    error->TotalError = (float)total_err;
    error->AbsError = (float)abs_err;
    error->SqError = (float)abs_sqr_err;
    error->MeanError = (float)(total_err/temp);
    error->MeanAbsError = (float)(abs_err/temp);
    error->MeanSqError = (float)(abs_sqr_err/temp);
    error->RMSError = (float)(sqrt(abs_sqr_err/temp));
}

...以及用于测试函数的示例 main():

/*
 * main.c
 *
 *  Created on: Jan 13, 2011
 *      Author: Erik Oosterwal
 */

#include <stdio.h>
#include "divergence.h"

float vote[]={40.3, 22.5, 16.3, 10.5, 7.2, 3.2};
float poll[]={42.7, 21.4, 18.2, 6.0, 7.4, 4.3};
float actual[] ={74, 70, 58, 60, 65, 73, 70};
float predict[]={49, 62, 75, 82, 37, 58, 92};

int main(int argc, char *argv[])
{
    DIVERGENCE_ERROR_TYPE stats;

    Divergence__Error(6, poll, vote, &stats);
    printf("%i
%f
%f
%f
%f
%f
%f
%f


",stats.DataSize,stats.TotalError,stats.AbsError,stats.SqError,stats.MeanError,stats.MeanAbsError,stats.MeanSqError,stats.RMSError);

    Divergence__Error(7, predict, actual, &stats);
    printf("%i
%f
%f
%f
%f
%f
%f
%f


",stats.DataSize,stats.TotalError,stats.AbsError,stats.SqError,stats.MeanError,stats.MeanAbsError,stats.MeanSqError,stats.RMSError);

    return(0);
}