Pfannkuchener
Member
Hi @rotobld
I currently solve 3bld with M2/OP with Buffers DF and RDF and want to swtich to 3-Style with buffers UB and URF.
For learning the 3-Style-Algs I am looking for a tool/timer, where I can specify a subset of algs I currently want to learn and have scrambles only for a certain subset of targets.
E.g. I want to practice all edge-algorithms, where one (/the first) target is UB. Afterwards I would maybe want to practice all edge-algorithms, where one (/the first) target is UR. Afterwards I want to pracitce all algorithms where one (/the first) target is UB or UR together. ...and so on.
In csTimer you can practice subsets (OLL / PLL / ...), but I haven't found something similar for the case I explained above.
Do you consider implementing something like that?
Or do you know a timer/tool, which can already do that?
I have several bluetooth-cubes, so I really look forward to use your TrainBLD in the future. I hope you can fix it soon, so I can try it out
I also want to say thank you, that you share the Code in github: Thank you! I will have a look into it when I have time.
I currently solve 3bld with M2/OP with Buffers DF and RDF and want to swtich to 3-Style with buffers UB and URF.
For learning the 3-Style-Algs I am looking for a tool/timer, where I can specify a subset of algs I currently want to learn and have scrambles only for a certain subset of targets.
E.g. I want to practice all edge-algorithms, where one (/the first) target is UB. Afterwards I would maybe want to practice all edge-algorithms, where one (/the first) target is UR. Afterwards I want to pracitce all algorithms where one (/the first) target is UB or UR together. ...and so on.
In csTimer you can practice subsets (OLL / PLL / ...), but I haven't found something similar for the case I explained above.
Do you consider implementing something like that?
Or do you know a timer/tool, which can already do that?
I have several bluetooth-cubes, so I really look forward to use your TrainBLD in the future. I hope you can fix it soon, so I can try it out
I also want to say thank you, that you share the Code in github: Thank you! I will have a look into it when I have time.