Deterministic Release Automation Playbook
Release automation gets better the moment you stop asking AI to do the fuzzy part first.
Release automation gets better the moment you stop asking AI to do the fuzzy part first.
I finished my first external Pure Data object, a note determining object. This object takes in the number of Hz a note is measured to be and outputs what note it is (the low A on a piano being 1, going up to 88), determining how many cent off it is and how many Hz extra there is (i.e, 415Hz = A flat (tone 47), one cent (minus 0.174Hz) low. Fourth output is a text with the note name, in this case Ab. This object uses equal temperament and was just an excercise for me to see if it can be done.
Christian Mondrup has added an italian madrigal Tu che del mio dolore by Giovanni Battista Dalla Gostena (c.1558-1593) for 5 recorders to the recorder archive. Keep up the good work, Christian!
I decided I prefer writing normal logic in a language I'm used to, so I went looking for a Python-external for Pure Data. And sure enough, I found [Thomas Grill][1]'s [py/pyext][2] (built upon flext, a C layer for Python externals). I didn't figure out how to install the binaries (didn't take the time to experiment) so I just compiled them up. Works great. ![]()
Thought you'd might want to see just how simple it is: my pyext example for Pure Data. I'm planning to make an object that takes in a floating point number of frequency height and determines what note it is and the amount of error according to different scale temperaments, i.e. Valotti, Werkmeister 3, Kirnberger, Meantone and Equal tempering.
I'd really like to get to know blogs that focus on Pure Data and/or Max/MSP and use it for development and performances. Leave a comment with your blog URL
I think it's about time I introduce my project:
Missing: 
A statue of Edvard Munch in a Our Saviour's Cementary in Oslo has been stolen of his grave only short time after Madonna and Scream were stolen (via VG and Aftenposten)