speed improvements

[Co-eus]

at some point we should use the timeit function to track down the slow routines, and make them faster!

see for example here: https://scipy-cookbook.readthedocs.io/items/PerformancePython.html

[TillSchlemmermeier]

We should also look into pythons multiprocessing to use pipes to exchange data between applications (Main-Controller with GUI, Send-Module, Visualizer, Sound-To-Light...) to get rid of runtime dependencies. This might also speed up things in general.

[Co-eus]

For testing the generators and effects I will write a small testsuite, which will just call all the effects with different parameters and log their CPU time. Maybe we can identify the bottlenecks of the generators and effects this way

[Co-eus]

Output of the testscript:

---

Starting test run to study the performance

Time used by g_corner_grow per frame in milliseconds: 0.8263

Time used by g_growing_sphere per frame in milliseconds: 283.615

Time used by g_planes per frame in milliseconds: 0.7372

Time used by g_shooting_star per frame in milliseconds: 334.2029

Time used by g_corner per frame in milliseconds: 1.1129

Time used by g_orbiter per frame in milliseconds: 386.8811

Time used by g_randomlines per frame in milliseconds: 1.2152

Time used by g_snake per frame in milliseconds: 1.1734

Time used by g_cube per frame in milliseconds: 12.3328

Time used by g_planes_falling per frame in milliseconds: 8.1245

Time used by g_random per frame in milliseconds: 2.6302

Time used by g_sphere per frame in milliseconds: 215.9358

[Co-eus]

Okay, all the problems can be easily solved by shifting the 10x10x10 for-loops of the slow routines in a fortran routine, which easily can be import via f2py. I just checked for_g_sphere, this are the times I got:

---

Starting test run to study the performance

Time used by fortran_test_sphere per frame in milliseconds: 0.0096

Time used by g_sphere per frame in milliseconds: 1.1528

[Co-eus]

Some other ideas for speed improvements:

• fortran implementation of world2list or world2vox
• parallel computing of the three channels - e.g. with joblib or multiprocessing (https://stackoverflow.com/questions/7207309/python-how-can-i-run-python-functions-in-parallel)
• memoize or memory from joblib class to check whether a generator has to re-compute something completely (https://pythonhosted.org/joblib/memory.html)

[Co-eus]

Fortran implementation of world2vox is done, but untested yet!

-> works