• 9il (5/5) Jul 09 2018 https://github.com/libmir/mir-optim
• jmh530 (4/9) Jul 09 2018 It looks like the docs are not correctly handling the parameters
• Shigeki Karita (2/7) Jul 09 2018 great! do you have any plans of algorithms to be supported?
• 9il (4/13) Jul 09 2018 The algorigbms from https://github.com/JuliaNLSolvers are good
• jmh530 (8/11) Jul 10 2018 Dlangscience has headers for the nlopt and glpk C libraries that
• jmh530 (5/8) Jul 13 2018 Another type of functionality that would be useful:
• 9il (5/14) Jul 14 2018 D's findRoot probably is the world's most efficient and robust

9il <ilyayaroshenko gmail.com> writes:

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

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

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

jmh530 <john.michael.hall gmail.com> writes:

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

Shigeki Karita <shigekikarita gmail.com> writes:

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?

9il <ilyayaroshenko gmail.com> writes:

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.

jmh530 <john.michael.hall gmail.com> writes:

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.

jmh530 <john.michael.hall gmail.com> writes:

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.

9il <ilyayaroshenko gmail.com> writes:

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.