Thinking of starting a Tutorial Development topic unpicking the properties of this versatile pipe.
It would be really useful to have a wider range of use examples beyond my own
(I’ve probably used less than half the possible What|Into options).
Examples with patches/screenshots (inc any mappings) added below most appreciated.
Thanks in advance…
I have one that implements a delay pipe for MIDI transport messages. The current delay pipe only supports notes. I’m using the transform pipe after the delay pipe to work around that.
useful to have some Transforms to ‘Transport’ messages
nicely documented, thx!
Some useful uses for Transform is for creating triggerable actions, like I’ve seen one MIDI keyboard lacking proper Transport controls (start, stop, continue), so it’s possible to workaround that by making some pads produce these messages.
Another interesting use would be to use Transform together with Sync Delay, so Transform converts some trigger message into Start, sends it to Sync Delay pipe to produce or drop Clock to nudge the pattern forward or backward. Similar technique can be used to manually trigger Arp steps, or even mess around with synced pipes like LFO or Delay, but not sure how useful that is in practice. 
Indeed. I’ll make a mention of that (with a user example if anyone posts one 
)
Transform together with Sync Delay, so Transform converts some trigger message into Start, sends it to Sync Delay pipe to produce or drop Clock
@szszoke would that work your dg/dt patch ?
Similar technique can be used to manually trigger Arp steps, or even mess around with synced pipes like LFO or Delay
Anyone got an example of either of these?
I’d like to see a Sync Delay Primer as a separate primer!
Here:
I made a patch that transforms note numbers into velocity values for MPC-style 16 Levels functionality. Is that the kind of thing you mean?
Yes, post it up please, Danny:
As Transform is such a versatile pipe, I think it would be useful to have a Deep Dive ( maybe borrow the Minibrute “CookBook” language?) which would show eachother in-context transformations that we might not think of by ourselves.