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OpenOpt FAQ
- How to turn text output (all those "starting solver ...", "time elapsed ...", etc) off?
- Use iprint = 0 (final output only) or iprint < 0 (btw it's mentioned in NLP docstring). In future warnings are intended to be shown if iprint >= -1. However, some solvers like ALGENCAN have their own text output system, that's hard to suppress, it requires using different approach like, for example, the one.
- How to handle maximization problems?
- Use p.goal = 'max' or 'maximum'. However, this is valid only for some problem types (NLP, NSP, some other).
- Does this have any parallel computation code?
- NLP solver IPOPT uses MUMPS that can be turned (during installation) to use several CPU
- GLP solver pswarm can handle several CPU (via MPI) but I'm not sure it's relevant to his Python API
- There are some efforts of parallel numpy, such as this one or commercial StarP.
- MATLAB OpenOpt (that is no longer supported) can calculate 1st derivative df numerically via parallel cycle by parfor. However, it can benefit for costly funcs only. I intended to implement something like that in Python, but I don't know which library is better, and those that I had seen have (as for me) inconvenient syntax & complicated documentation. If someone is familiar with a Python library for parallel calculation, he could easily use it to calculate df, dc, dh numerically: (func(x+dx[i])-func(x)/dx). Parallel computation is intended to be provided in future.
- (to be continued)
