https://github.com/libmir/mir-optim

This work has been sponsored by Symmetry Investments and Kaleidic Associates.

http://symmetryinvestments.com
https://github.com/kaleidicassociates

On Monday, 9 July 2018 at 13:54:17 UTC, 9il wrote:
> https://github.com/libmir/mir-optim
>
> This work has been sponsored by Symmetry Investments and Kaleidic Associates.
>
> http://symmetryinvestments.com
> https://github.com/kaleidicassociates

It looks like the docs are not correctly handling the parameters you have in the struct.

https://mir-optim.dpldocs.info/mir.least_squares.LeastSquaresLM.html

On Monday, 9 July 2018 at 13:54:17 UTC, 9il wrote:
> https://github.com/libmir/mir-optim
>
> This work has been sponsored by Symmetry Investments and Kaleidic Associates.
>
> http://symmetryinvestments.com
> https://github.com/kaleidicassociates

great! do you have any plans of algorithms to be supported?

On Monday, 9 July 2018 at 21:52:22 UTC, Shigeki Karita wrote:
> On Monday, 9 July 2018 at 13:54:17 UTC, 9il wrote:
>> https://github.com/libmir/mir-optim
>>
>> This work has been sponsored by Symmetry Investments and Kaleidic Associates.
>>
>> http://symmetryinvestments.com
>> https://github.com/kaleidicassociates
>
> great! do you have any plans of algorithms to be supported?

The algorigbms from https://github.com/JuliaNLSolvers are good candidates. No plans to implement them for now, but PRs are wellcome.

On Tuesday, 10 July 2018 at 02:10:56 UTC, 9il wrote:
>
> The algorigbms from https://github.com/JuliaNLSolvers are good candidates. No plans to implement them for now, but PRs are wellcome.

Dlangscience has headers for the nlopt and glpk C libraries that I've used in the past. ipopt is another one that I've used, but I don't think there's a D interface. IMHO, you'd need a good reason to implement all of the functionality of a non-linear optimizer on your own. Simple linear and quadratic programming are probably a useful start, but beyond that the ability to interface with C/Fortran libraries goes a long way.

On Tuesday, 10 July 2018 at 02:10:56 UTC, 9il wrote:
>
> The algorigbms from https://github.com/JuliaNLSolvers are good candidates. No plans to implement them for now, but PRs are wellcome.

Another type of functionality that would be useful:
https://www.mathworks.com/help/matlab/ref/fzero.html

This can be done with a non-linear least squares, but I don't think that's the most efficient method.

On Friday, 13 July 2018 at 16:20:30 UTC, jmh530 wrote:
> On Tuesday, 10 July 2018 at 02:10:56 UTC, 9il wrote:
>>
>> The algorigbms from https://github.com/JuliaNLSolvers are good candidates. No plans to implement them for now, but PRs are wellcome.
>
> Another type of functionality that would be useful:
> https://www.mathworks.com/help/matlab/ref/fzero.html
>
> This can be done with a non-linear least squares, but I don't think that's the most efficient method.

D's findRoot probably is the world's most efficient and robust implementation. For single initial point fzero we can be implemented as IEEE set binary search of second initial point x1 such that sign(f(x0)) != sign(f(x1)) plus D's findRoot.