[SciPy-User] scipy.optimize leastsq with numpy longdouble?
Wed Nov 17 11:25:32 CST 2010
What do you mean where is the data coming from? It's from an experiment..
function I'm fitting is:
maxwell_boltzmann = lambda v,x: v*(x-C0)**(-4)*np.exp(-(L/v)**2*(x-C0)**(-2)) + v
and the data is in an array of longdoubles.
Does that answer your question?
On Nov 17, 2010, at 12:20 PM, Charles R Harris wrote:
> On Wed, Nov 17, 2010 at 10:13 AM, Joan Smith <firstname.lastname@example.org> wrote:
> I'm fitting a maxwell-botlzmann distribution, using SciPy leastsq. Because of the data I'm fitting, I need high precision (on both the high and low ends), so I'm using numpy.longdouble for my types. Is there a way to use this type with leastsq? As it stands, I'm getting this error:
> v = leastsq(self.chi_squared, self.v_0, args=self.args, full_output=1)
> File "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/scipy/optimize/minpack.py", line 281, in leastsq
> maxfev, epsfcn, factor, diag)
> TypeError: array cannot be safely cast to required type
> I've been using leastsq for a while, and haven't seen this error before, so I suspect it has to do with using an unusual type.
> Yep. But where is your data coming from? And how are you trying to do the fit? I suspect that a change of method it the proper way to go here. Josef may have something in the stats model package.
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