[Numpy-discussion] ScientificPython with numarray support
John Hunter
jdhunter at ace.bsd.uchicago.edu
Fri Jan 14 16:21:22 CST 2005
>>>>> "Sebastian" == Sebastian Haase <haase at msg.ucsf.edu> writes:
Sebastian> The LeastSquare-fit is exactly what I'm interested in,
Sebastian> since I couldn't find something similar anywhere else
Sebastian> (like: It's not in SciPy, right?)
from scipy import exp, arange, zeros, Float, ones, transpose
from RandomArray import normal
from scipy.optimize import leastsq
parsTrue = 2.0, -.76, 0.1
distance = arange(0, 4, 0.001)
def func(pars):
a, alpha, k = pars
return a*exp(alpha*distance) + k
def errfunc(pars):
return data - func(pars) #return the error
# some pseudo data; add some noise
data = func(parsTrue) + normal(0.0, 0.1, distance.shape)
guess = 1.0, -.4, 0.0 # the intial guess of the params
best, info, ier, mesg = leastsq(errfunc, guess, full_output=1)
print 'true', parsTrue
print 'best', best
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