#include "Calculation.hpp"



Calculation::Calculation()
{
}

Calculation::~Calculation()
{
}



/************************************************************************/
/* 一维数据的复数快速傅里叶变换                                             */
/************************************************************************/
void Calculation::FFT(int n, fftw_complex* in, fftw_complex* out)
{
	if (in == NULL || out == NULL) return;
	fftw_plan p;
	p = fftw_plan_dft_1d(n, in, out, FFTW_FORWARD, FFTW_ESTIMATE);
	fftw_execute(p);
	fftw_destroy_plan(p);
	fftw_cleanup();
}

/************************************************************************/
/* 一维数据的实数快速傅里叶变换                                             */
/************************************************************************/
void Calculation::FFT_R(int n, std::vector<float> & vecData, fftw_complex* out)
{
    double in[n];
	for (int i = 0; i < n; i++) {
		in[i] = vecData[i];
	}

	for (int i = 0; i < n; i++)
	{
		out[i][0] = (double)vecData[i];
		out[i][1] = 0;
	}
	//create a DFT plan and execute it
	fftw_plan plan = fftw_plan_dft_r2c_1d(n, in, out, FFTW_ESTIMATE);
	fftw_execute(plan);
	//destroy the plan to prevent a memory leak
	fftw_destroy_plan(plan);
	fftw_cleanup();
}

/************************************************************************/
/* 一维数据的快速傅里叶逆变换                                          */
/************************************************************************/
void Calculation::iFFT(int n, fftw_complex* in, fftw_complex* out)
{
	if (in == NULL || out == NULL) return;
	fftw_plan p;
	p = fftw_plan_dft_1d(n, in, out, FFTW_BACKWARD, FFTW_ESTIMATE);
	fftw_execute(p);
	fftw_destroy_plan(p);
	fftw_cleanup();
}

//************************************
// Method:    caculateAmp_Pha
// FullName:  Calculation::caculateAmp_Pha
// Access:    public static 
// Returns:   void
// Qualifier:
// Parameter: int n
// Parameter: fftw_complex * in
// Parameter: int frequency
// Parameter: double & amplitude
// Parameter: double & phase
// 函数功能是计算特定频率的幅值和相位，原来的讨论中是传入一个特定的频率，然后在给定的频率左右范围内找幅值和相位
// 目前的函数实现是计算FFT变换后特定点的幅值和相位
// 然后还有一个地方需要修改，即给定频率和FFT变换结果序列
//************************************
void Calculation::caculateAmp_Pha(int n, fftw_complex* in, int frequency, double &amplitude, double &phase)
{
	int  index = frequency;
	amplitude = 2 * sqrt((in[index][0] / n) * (in[index][0] / n) + (in[index][1] / n) * (in[index][1] / n));
	phase = 180 * atan(in[index][1] / in[index][0]) / M_PI;
}


float Calculation::max(std::vector<float> & vecData)
{
	std::vector<float>::iterator it;
	it = std::max_element(vecData.begin(), vecData.end());
	if (it != vecData.end()) {
		return *it;
	}
    return 0;
}

float Calculation::min(std::vector<float> & vecData)
{
	std::vector<float>::iterator it;
	it = std::min_element(vecData.begin(), vecData.end());
	if (it != vecData.end()) {
		return *it;
	}
    return 0;
}


void Calculation::absVec(std::vector<float> & vecAbsData, std::vector<float> & vecData)
{
	for (int i = 0; i < vecData.size(); i++) {
        vecAbsData.push_back(fabs(vecData[i]));
	}
	return;
}


float Calculation::mean(std::vector<float> & vecData)
{
	double meanTemp = 0;
	for (int i = 0; i < vecData.size(); i++) {
        meanTemp = meanTemp += vecData[i];
	}
    return meanTemp / vecData.size();
}


void Calculation::drop_mean(std::vector<float> & vecDropMeanData, std::vector<float> & vecData)
{
	float fMean = mean(vecData);
	for (int i = 0; i < vecData.size(); i++) {
        vecDropMeanData.push_back(vecData[i] - fMean);
	}
    return;
}

float Calculation::srm(std::vector<float> & vecData)
{
	double dSrmTemp = 0;
	for (int i = 0; i < vecData.size(); i++){
        dSrmTemp = dSrmTemp + sqrt(vecData[i]);
	}
	dSrmTemp = dSrmTemp / vecData.size();
	return dSrmTemp * dSrmTemp;
}


float Calculation::rms(std::vector<float> & vecData)
{
	double rmsTemp = 0;
	for (int i = 0; i < vecData.size(); i++) {
        rmsTemp = rmsTemp += (vecData[i] * vecData[i]);
	}
	rmsTemp = rmsTemp / vecData.size();
	return sqrt(rmsTemp);
}


float Calculation::variance(std::vector<float> & vecDropMeanData)
{
	double varianceTemp = 0;
	for (int i = 0; i < vecDropMeanData.size(); i++) {
        varianceTemp = varianceTemp += (vecDropMeanData[i] * vecDropMeanData[i]);
	}
	return varianceTemp/vecDropMeanData.size();
}


float Calculation::skew_state(std::vector<float> & vecDropMeanData, float fVariance)
{
	double tempSkew = 0;
	for (int i = 0; i < vecDropMeanData.size(); i++) {
		tempSkew = tempSkew + pow(vecDropMeanData[i], 3);
	}
	tempSkew = tempSkew / vecDropMeanData.size();
	tempSkew = tempSkew / pow(fVariance, 1.5);
	return tempSkew;
}


float Calculation::kurtosis(std::vector<float> & vecDropMeanData, float fVariance)
{
	double tempkurtosis = 0;
	for (int i = 0; i < vecDropMeanData.size(); i++) {
		tempkurtosis = tempkurtosis + pow(vecDropMeanData[i], 4);
	}
	tempkurtosis = tempkurtosis / vecDropMeanData.size();
	tempkurtosis = tempkurtosis / pow(fVariance, 2);
	return tempkurtosis;
}

void Calculation::hilbert(std::vector<float> & vecData, std::vector<float> & vecHilbertData, int N)
{

    double in[N];
	for (int i = 0; i < N; i++) {
		in[i] = vecData[i];
	}
	fftw_complex *out;
	out  = (fftw_complex *)fftw_malloc(sizeof(fftw_complex) * N);

	for (int i = 0; i < N; ++i)
	{
		out[i][0] = (double)vecData[i];
		out[i][1] = 0;
	}
	//create a DFT plan and execute it
	fftw_plan plan = fftw_plan_dft_r2c_1d(N, in, out, FFTW_ESTIMATE);
	fftw_execute(plan);
	//destroy the plan to prevent a memory leak
	fftw_destroy_plan(plan);
	int hN = N >> 1;			// half of the length (N /2)
	int numRem = hN;		// the number of remaining elements
	// multiply the appropriate values by 2
	// (those that should be multiplied by 1 are left intact because they wouldn't change)
	for (int i = 1; i < hN; ++i) // 1,2,...,N/2 - 1 的项乘以2
	{
		out[i][0] *= 2;
		out[i][1] *= 2;
	}
	// if the length is even, the number of remaining elements decreases by 1
	if (N % 2 == 0)
		numRem--;
	// if it's odd and greater than 1, the middle value must be multiplied by 2
	else if (N > 1)  // 奇数非空
	{
		out[hN][0] *= 2; 
		out[hN][1] *= 2;
	}
	// set the remaining values to 0
	// (multiplying by 0 gives 0, so we don't care about the multiplicands)
	memset(&out[hN + 1][0], 0, numRem * sizeof(fftw_complex));
	// create an IDFT plan and execute it
	plan = fftw_plan_dft_1d(N, out, out, FFTW_BACKWARD, FFTW_ESTIMATE); 
	fftw_execute(plan);
	// do some cleaning
	fftw_destroy_plan(plan); 
	fftw_cleanup();
	// scale the IDFT output 
	for (int i = 0; i < N; ++i)
	{
		out[i][0] /= N;
		out[i][1] /= N;
	}

    for( int n=0; n<N; n++ )//输出
    {
      //  xr[n]=cos(n*pi/6);//原始信号
      //  y_r[n] = s_i[n];
        complex complex_after;
		complex_after.real = out[n][1];
		complex_after.imag = out[n][0];
        float amp = sqrt(complex_after.real * complex_after.real +complex_after.imag * complex_after.imag);
		vecHilbertData.push_back(amp);
      //  printf("%d    %f\n",n,vecHilbertData[n]);
    }			 	
}


void Calculation::fftShift(fftw_complex* in, int l)
{
	double temp;
	double temp2;

	for (int j = 0;j<l/2;j++) {
		temp = in[j+l/2][0];
		temp2 = in[j+l/2][1];
		in[j+l/2][0] = in[j][0];
		in[j+l/2][1] = in[j][1];
		in[j][0] = temp;
		in[j][1] = temp2;
	}
}

void Calculation::FFTSpec(std::vector<float> & vecData, std::vector<float> & vecFFTSpecData)
{
    fftw_complex *inFFt, *outFFt;
    inFFt  = (fftw_complex *)fftw_malloc(sizeof(fftw_complex) * vecData.size());
    outFFt = (fftw_complex *)fftw_malloc(sizeof(fftw_complex) * vecData.size());
	printf("1---------------------------------------------->%d\n",vecData.size());
	
    for (int j = 0; j < vecData.size(); j++) {
        inFFt[j][0] = (double)vecData[j];
        inFFt[j][1] = 0;
    }
    FFT(vecData.size(),inFFt, outFFt);
    for(int j = 0; j < vecData.size()/2; j++) {
        vecFFTSpecData.push_back(sqrt(outFFt[j][0]*outFFt[j][0] + outFFt[j][1]*outFFt[j][1])*2/vecData.size());
    }

}

void Calculation::envSpec(std::vector<float> & vecData, std::vector<float> & vecEnvSpecData)
{
    std::vector<float> vecDropMeanData;
    drop_mean(vecDropMeanData, vecData);

    std::vector<float> vecHilbertData;
    hilbert(vecDropMeanData, vecHilbertData, vecDropMeanData.size());

    fftw_complex *inHilFFt, *outHilFFt;
    inHilFFt  = (fftw_complex *)fftw_malloc(sizeof(fftw_complex) * vecHilbertData.size());
    outHilFFt = (fftw_complex *)fftw_malloc(sizeof(fftw_complex) * vecHilbertData.size());

    for (int j = 0; j < vecHilbertData.size(); j++) {
        inHilFFt[j][0] = (double)vecHilbertData[j];
        inHilFFt[j][1] = 0;
    }

    FFT(vecHilbertData.size(), inHilFFt, outHilFFt);
    fftShift(outHilFFt,  vecHilbertData.size());

    vecEnvSpecData.push_back(0);
    for (int i = vecHilbertData.size() / 2 + 1; i < vecHilbertData.size(); i++) {
        float ftemp = 2 * sqrt(outHilFFt[i][0] * outHilFFt[i][0] + outHilFFt[i][1] * outHilFFt[i][1]) / vecHilbertData.size();
        vecEnvSpecData.push_back(ftemp);
    }
}