Python Scipy minimize(method=’Nelder-Mead’) equivalent in LabView

[gawex]

Hello,

I need to rewrite an optimization algorithm from Python to LabView.

It uses the minimize(method=’Nelder-Mead’) method from Scipy package.
https://docs.scipy.org/doc/scipy/reference/optimize.minimize-neldermead.html#optimize-minimize-nelde...

I found that LabView has a similar VI - Downhill Simplex VI.
https://www.ni.com/docs/en-US/bundle/labview-api-ref/page/vi-lib/gmath/numericaloptimization/downhil...

I put the same start array to both codes but from the first iteration I am starting to receive different results.

Does anybody know if there is a 1to1 relation between those 2 functions? Need to add that I retrieved completely different results once the optimization was done and not only a difference at lower digits of precision than I expected.

Thank you for your help.

[santo_13]

You can check the VI's help to determine the algorithm used and see if there is a difference.

Do take into account the difference in data types between programming languages as the rounding method and errors will differ.