Try this code. It fits y = mx + b to your (x,y) data. The arguments to linreg are linreg(int n, REAL x[], REAL y[], REAL* b, REAL* m, REAL* r) n = number of data points x,y = arrays of data *b = output intercept *m = output slope *r = output correlation coefficient … Read more
If I read the source code right (Numpy 1.8.2, Scipy 0.14.1 ), numpy.linalg.lstsq() uses the LAPACK routine xGELSD and scipy.linalg.lstsq() usesxGELSS. The LAPACK Manual Sec. 2.4 states The subroutine xGELSD is significantly faster than its older counterpart xGELSS, especially for large problems, but may require somewhat more workspace depending on the matrix dimensions. That means … Read more