I have been having trouble the past few days getting this post past the site's spam filters. So I am going to break it up into pieces in an attempt to figure out what it is that the site thinks is spam.
I recently posted about a tool I wish I had that you could play the audio of a song into, and it would come back with suggestions about which Performances and Arpeggios to use. As a result of that post, I found out about a feature of Yamaha arranger keyboards called Music Finder.
Music Finder is a searchable database of songs that can tell you which PSR/Tyros Style is the best fit for playing that song. Database files are available as a free download at PSRTutorial.com.
Music Finder database files can be downloaded in a form (tab-delimited text) that is very easy to read into a Python program. It occurred to me that I could make a program functionally equivalent to Music Finder, except that it would recommend Montage/MODX Performances instead of PSR/Tyros Styles. All I would need to do this was a Music Finder database, and information that showed for each PSR/Tyros Style, the most similar Montage/MODX Performance.
The Python software doesn't do anything useful at the moment because I do not have the similarity information about which Montage/MODX Performance is closest to each PSR/Tyros Style. I wrote the software in the hope that by posting it I would motivate/inspire/encourage someone at Yamaha (or anyone else) to provide the necessary information.
If you want to run it to see what it does, you will first need to install a Python 3.x interpreter, which you can get from Python.org. Pick the latest release version.
Then you can run it from the command line like this:
[code type=markup]python mmf.py[/code]
Run like this, it will print out instructions for how to use it.
I'm really hoping that Yamaha (or someone else) will provide the information I need to make this software useful to Montage/MODX users, I think it would be very beneficial.
This is free, open-source software, written for the benefit of Montage/MODX users.
(The zip file is actually a compressed Visual Studio 2017 Python project. If you're a software developer, that would be a good way to look at the code.)
Here's the zip file. I currently don't have the real version of the similarity information, so I created a dummy version: it's a tab-delimited file named similar.txt.
Apparently the spam problem was somehow due to all of the pieces being combined in one post. The site accepted it once I broke it up into pieces. Weird.