/* ValueAt wraps gsl_fit_linear_est from gsl_fit.h.
* A LinearFit can be interrogated for the value of a result at a particular
* point x. All of the parameters mentioned below are taken from the
* LinearFit.
* From the GSL manual:
* This function uses the best-fit linear regression coefficients Y0, Slope
* and their covariance Cov00, Cov01, Cov11 to compute the fitted function
* y and its standard deviation y_err for the model
* Y = Y0 + Slope* X at the point x.
*/
func (f *LinearFit) ValueAt(x float64) (y, y_err float64, e error) {
er := C.gsl_fit_linear_est((C.double)(x),
(C.double)(f.Y0),
(C.double)(f.Slope),
(C.double)(f.Cov00),
(C.double)(f.Cov01),
(C.double)(f.Cov11),
(*C.double)(&y),
(*C.double)(&y_err))
if er != (C.int)(0) {
e = gsl.NewGSLError((int)(er))
}
return
}
func LinearEst(x float64, c0 float64, c1 float64, cov00 float64, cov01 float64, cov11 float64) (int32, float64, float64) {
var _outptr_6 C.double
var _outptr_7 C.double
_result := int32(C.gsl_fit_linear_est(C.double(x), C.double(c0), C.double(c1), C.double(cov00), C.double(cov01), C.double(cov11), &_outptr_6, &_outptr_7))
return _result, *(*float64)(unsafe.Pointer(&_outptr_6)), *(*float64)(unsafe.Pointer(&_outptr_7))
}