On 10/12/06, Greg Willden <[EMAIL PROTECTED]> wrote:
The polyfit function looks seriously busted. If I do the fits by hand I get the same results using the (not so hot) MPL version or lstsq. I don't know what the problem is. The docstring is also incorrect for the method. Hmmm...
Chuck
On 10/12/06, Charles R Harris <[EMAIL PROTECTED] > wrote:I'm guessing that the rcond number in the lstsq version (default 1e-10) is the difference. Generally the lstsq version should work better than the MPL version because at*a is not as well conditioned and vandermonde matrices are notoriously ill conditioned anyway for higher degree fits. It would help if you attached the data files in ascii form unless they happen to contain thousands of data items. Just the x will suffice, zip it up if you have to.
Here are the files.
Since the two algorithms behave differently and each has it place then can both be included in numpy?
i.e. numpy.polyfit(x,y,N, mode='alg1')
numpy.polyfit (x,y,N, mode='alg2')
replacing alg1 and alg2 with meaningful names.
The polyfit function looks seriously busted. If I do the fits by hand I get the same results using the (not so hot) MPL version or lstsq. I don't know what the problem is. The docstring is also incorrect for the method. Hmmm...
Chuck
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