[SciPy-user] scipy.optimize.leastsq failure
fdu.x...@gmail.com
I get an ier flag of 2 when running the following code:
----------------------------------------------------------
from scipy.optimize import leastsq
from numpy import array
x = array([1.2, 3.4, 5.6, 7.8])
y = (x-1.234)**2+3.456
def obj_f(pp, xx, yy):
return pp[0] * (xx-pp[1])**2 + pp[2] - yy
b = leastsq(obj_f, (1., 1., 2.), args=(x,y), full_output=2)
print b
print obj_f(b[0], x, y)
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The output is:
----------------------------------------------------------
(array([ 1. , 1.234, 3.456]), array([[ 0.01067209, 0.03485503, 0.04927042],
[ 0.03485503, 0.12416711, 0.22839652],
[ 0.04927042, 0.22839652, 0.91824454]]), {'qtf': array([
-5.72325346e-10, -3.96833152e-10, -2.98440470e-11]), 'nfev': 13, 'fjac':
array([[-47.37134237, 0.09903785, 0.40239425, 0.9100936 ],
[ 15.89408601, 3.85306656, 0.61349297, -0.32983294],
[ -1.41155008, -0.95837977, 1.04356817, 0.82836952]]), 'fvec':
array([ -8.88178420e-16, 0.00000000e+00, 0.00000000e+00,
-7.10542736e-15]), 'ipvt': array([1, 2, 3])}, 'The relative error
between two consecutive iterates is at most 0.000000', 2)
[ -8.88178420e-16 0.00000000e+00 0.00000000e+00 -7.10542736e-15]
----------------------------------------------------------
Tt seems that the result is rather accurate, but while I get an ier flag of 2?
I don't quite understand the error message.
Regards,
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Steve Schmerler
leastq() uses the underlying Fortran routines from MINPACK: LMDIF if you don't
provide a Jacobain (Dfun=None) or LMDER otherwise. The message tells you that
the routine met one of it's convergence criteria. See the source of leastsq()
in optimize/minpack.py and the docstrings of the Fortran routines ('info' flag):
http://www.netlib.org/minpack/lmdif.f
http://www.netlib.org/minpack/lmder.f
--
cheers,
steve
I love deadlines. I like the whooshing sound they make as they fly by. --
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