예제 #1
0
// Return the value for vector c which best fits the linear model y = Xc.
// X is a matrix given by its row vectors: each row corresponds to a y value;
// columns within the row correspond to coefficients for parameters in c.
func Linear(y vec.Vector, X []vec.Vector) vec.Vector {
	n := C.size_t(len(y))    // number of observations
	p := C.size_t(len(X[0])) // number of parameters
	c, gslY := C.gsl_vector_alloc(p), C.gsl_vector_alloc(n)
	cov, gslX := C.gsl_matrix_alloc(p, p), C.gsl_matrix_alloc(n, p)
	vecToGSL(y, gslY)
	matrixToGSL(X, gslX)
	chisq := C.double(0)
	work := C.gsl_multifit_linear_alloc(n, p)
	C.gsl_multifit_linear(gslX, gslY, c, cov, &chisq, work)
	C.gsl_multifit_linear_free(work)
	result := vecFromGSL(c)
	C.gsl_matrix_free(gslX)
	C.gsl_matrix_free(cov)
	C.gsl_vector_free(gslY)
	C.gsl_vector_free(c)
	return result
}
예제 #2
0
// Return an ordered slice of the eigenvalues of sym, and a slice of the
// eigenvectors in the same order.
func (sym *SymmetricMatrix) Eigensystem() ([]float64, [][]float64) {
	originalSize := sym.length
	reduced, convert := sym.RemoveEmptyRows()
	size := C.size_t(reduced.length)
	eigenvalues := C.gsl_vector_alloc(size)
	eigenvectors := C.gsl_matrix_alloc(size, size)
	matrix := reduced.toMatrix()
	work := C.gsl_eigen_symmv_alloc(size)
	err := C.gsl_eigen_symmv(matrix, eigenvalues, eigenvectors, work)
	if err != 0 {
		// handle it
	}
	goEigenvalues := vectorToSlice(eigenvalues)
	goEigenvectors := matrixColumnsToSlices(eigenvectors)
	C.gsl_vector_free(eigenvalues)
	C.gsl_matrix_free(eigenvectors)
	C.gsl_matrix_free(matrix)
	C.gsl_eigen_symmv_free(work)
	retEigenvectors := InsertEmptyRows(goEigenvectors, convert, originalSize)
	return goEigenvalues, retEigenvectors
}