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  • slevang · 1 ✖

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  • Handle scipy fitting errors in `xarray.curve_fit` · 1 ✖

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  • CONTRIBUTOR 1
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1057116313 https://github.com/pydata/xarray/issues/6317#issuecomment-1057116313 https://api.github.com/repos/pydata/xarray/issues/6317 IC_kwDOAMm_X84_AlCZ slevang 39069044 2022-03-02T16:24:37Z 2022-03-02T16:24:37Z CONTRIBUTOR

These errors can often be eliminated by passing appropriate initial guesses for each parameter through the p0 argument (which it looks like you're already doing), and/or by passing additional kwargs through to scipy.optimize.leastsq(), like ftol and maxfev which set the fit tolerance and max number of iterations.

Even so, there will be cases where some of your data just doesn't fit the desired function and you want to move on and return a result anyway. Your proposal seems fine as long as errors are raised by default and the documentation adequately describes the behavior when set to True.

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  Handle scipy fitting errors in `xarray.curve_fit` 1157140667

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