How to get Jacobian from returned least square () data?

Question

I often use scipy.optimize.leastsq() for my Ph.D. dissertation, but I have no idea how I can get the Jacobian score from the data returned by leastsq() . I need to know the Jacobian estimate that is used to minimize, to compare with the minimum approximation at the minimum.

Does anyone have a formula on how to get it?

It can be a little complicated when you check how, for example, the covariance matrix is ​​computed inside leastsq()

Answer 1

I think the answer is that no one was able to restore the Jacobian from optimize.leastsq.

last threat on this http://mail.scipy.org/pipermail/scipy-user/2011-August/030320.html

From some examples of the covariance matrix returned by the smallest number, I think that there are many cases where the accuracy with the default settings is not very high.

To check how good this is, you can compare the returned covariance matrix with the external product of your Jacobian.