PDR/3.BackUp/PDR-Origin-Version/include/pdr_linearFit.h

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2022-09-15 16:35:25 +08:00
/******************** (C) COPYRIGHT 2020 VIVO************************************
* File Name : pdr_linearFit.h
* Department : Sensor Algorithm Team
* Current Version : V2.0(compare QCOM SAP 5.0)
* Author : yuanlin_rjyb@vivo.com & zhanli@vivo.com
* Date of Issued : 2020.7.4
* Comments : PDR <EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>غ<EFBFBD><EFBFBD><EFBFBD>֧<EFBFBD><EFBFBD>
********************************************************************************/
#ifdef __cplusplus
extern "C" {
#endif
#ifndef _PDR_LINEAR_FIT_H_
#define _PDR_LINEAR_FIT_H_
/**----------------------------------------------------------------------
* Function : pdr_linearLeastSquaresFitting
* Description : <EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>С<EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> Y = c0 + c1 x
Ŀ<EFBFBD><EFBFBD><EFBFBD>Ϊsum| nDataY - (a*nDataX+b)|^2<EFBFBD><EFBFBD>С
* Date : 2020/7/4 zhanli@vivo.com
*---------------------------------------------------------------------**/
int linearLeastSquaresFit(const double *nDataX, const double *nDataY,
const int nLength, double *a, double *b);
/**************************************************************************
* Description : <EFBFBD><EFBFBD>ά<EFBFBD><EFBFBD><EFBFBD><EFBFBD>ϵ<EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ϣ<EFBFBD>ax+by+c=0, Ŀ<EFBFBD><EFBFBD><EFBFBD>Ϊ<EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ֱ<EFBFBD>ߵľ<EFBFBD><EFBFBD><EFBFBD>
ƽ<EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>С
* Input : x<EFBFBD><EFBFBD> y<EFBFBD><EFBFBD><EFBFBD><EFBFBD>ά<EFBFBD><EFBFBD><EFBFBD><EFBFBD>X<EFBFBD><EFBFBD>Y
num, <EFBFBD><EFBFBD>ά<EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
* Output : para<EFBFBD><EFBFBD> <EFBFBD><EFBFBD><EFBFBD><EFBFBD>ֱ<EFBFBD>߲<EFBFBD><EFBFBD><EFBFBD>, para[0]:a, para[0]:b, para[0]:c
**************************************************************************/
int leastDistanceLinearFit(double x[], double y[], int num, double para[]);
/**----------------------------------------------------------------------
* Function : gsl_fit_linear
* Description : Fit the data (x_i, y_i) to the linear relationship
Y = c0 + c1 x
returning,
c0, c1 -- coefficients
cov00, cov01, cov11 -- variance-covariance matrix of
c0 and c1,
sumsq -- sum of squares of residuals
This fit can be used in the case where the errors for
the data are uknown, but assumed equal for all points.
The resulting variance-covariance matrix estimates the
error in the coefficientsfrom the observed variance of
the points around the best fit line.
* Date :
*---------------------------------------------------------------------**/
static int gslFitLinear(const double* x, const size_t xstride,
const double* y, const size_t ystride,
const size_t n,
double* c0, double* c1,
double* cov_00, double* cov_01, double* cov_11, double* sumsq);
#endif // !_LINEAR_FITTING_H_
#ifdef __cplusplus
}
#endif