I'm a little bit stuck with NumPy here, and neither the docs nor trial&error seems to lead me anywhere: I've got a set of data points (x/y-coordinates) and want to fit a straight line through them, using LMSE linear regression. Simple enough. I thought instead of looking up the formulas I'd just see if there isn't a NumPy function that does exactly this. What I found was "linear_least_squares", but I can't figure out what kind of parameters it expects: I tried passing it my array of X-coordinates and the array of Y-coordinates, but it complains that the first parameter should be two-dimensional. But well, my data is 1d. I guess I could pack the X/Y coordinates into one 2d-array, but then, what do I do with the second parameter?
Mor generally: Is there any kind of documentation that tells me what the functions in NumPy do, and what parameters they expect, how to call them, etc. All I found was: "This function returns the least-squares solution of an overdetermined system of linear equations. An optional third argument indicates the cutoff for the range of singular values (defaults to 10-10). There are four return values: the least-squares solution itself, the sum of the squared residuals (i.e. the quantity minimized by the solution), the rank of the matrix a, and the singular values of a in descending order." It doesn't even mention what the parameters "a" and "b" are for... -- http://mail.python.org/mailman/listinfo/python-list
