oliphant at ee.byu.edu
Thu Oct 21 14:01:37 CDT 2004
Francesc Alted wrote:
>Sorry for the bunch of questions, but I'm preparing some 'hands-on' on
>scipy, and I'm excercising many parts of it.
>I've tried to follow the Travis' tutorial for finding the best fit of a
>series of data, but my results are different from those stated there:
>In : x = arange(0,6e-2,6e-2/30)
>In : A,k,theta = 10, 1.0/3e-2, pi/6
>In : y_true = A*sin(2*pi*k*x+theta)
>In : y_meas = y_true + 2*randn(len(x))
>In : def residuals(p, y, x):
> .....: A,k,theta = p
> .....: err = y-A*sin(2*pi*k*x+theta)
> .....: return err
>In : p0 = [8, 1/2.3e-2, pi/3]
>In : optimize.leastsq(residuals, p0, args=(y_meas, x))
>(array([ -2.17634575, 57.4116454 , -3.03266312]),
> 'Both actual and predicted relative reductions in the sum of squares\n are at most 0.000000')
>this results are quite different from the 'true' values:
>[ 10. 33.3333 0.5236]
>Do you have any idea about this error? I suppose that the message should
>indicate it, but I can't understand it. I'm using scipy 0.3.2 on Linux.
Can you look at the output of peval(x,p) and compare it to y_true?
I just re-ran this experiment and get
array([-10.053690336957587, 33.659758123232756, 3.591816659730455)])
which seems right (except for the fact that some of the phase has been
used to give -10 instead of 10).
More information about the SciPy-user