Thu Jun 27 08:35:27 CDT 2013
I'm pretty baffled by these questions. optimize.leastsq() does not
take a covariance matrix as input, but can give one as output. It
can take functions used to compute the Jacobian... Perhaps that would
accomplish what you're trying to do?
optimize.curve_fit() is a wrapper around leastsq() for the common case
of "fitting data" in which one has a set of observations at a set of
sampled "data points", and a set of variables used in a model for the
data. Like leastsq(), it returns the covariance. If curve_fit()
does what you need but seems sup-optimal, than leastsq() is probably
what you want to use.
Hope that helps, but maybe I'm not understanding what you're trying to do.
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