[SciPy-user] optimize.leastsq()
Francesc Alted
falted at pytables.org
Thu Oct 21 13:20:50 CDT 2004
Hi,
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 [96]: x = arange(0,6e-2,6e-2/30)
In [97]: A,k,theta = 10, 1.0/3e-2, pi/6
In [98]: y_true = A*sin(2*pi*k*x+theta)
In [99]: y_meas = y_true + 2*randn(len(x))
In [100]: def residuals(p, y, x):
.....: A,k,theta = p
.....: err = y-A*sin(2*pi*k*x+theta)
.....: return err
.....:
In [101]: p0 = [8, 1/2.3e-2, pi/3]
In [107]: optimize.leastsq(residuals, p0, args=(y_meas, x))
Out[107]:
(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.
BTW, thanks for clearifying the question about derivative() parameters. It's
much more clear now.
--
Francesc Alted
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