It's really common in analytics for an algorithm to do windowing. For example, for our audio processing, we typically take a window of 25ms for analysis and then step through the audio 10ms at a time. The result is that the analytics run on overlapping windows of the input data.
Currently, this sort of windowing is directly in the analytics routines (e.g. feature computation), but I could see it being a really useful general tool. Does such a thing already exist in mpf or gstreamer?
If not, my thought for creating one is to store an internal buffer (initially empty) in a mpf_window component. As data is read in, the input buffer is appended to the internal buffer. When there's at least a window's worth of data in the internal buffer, you write out the data and make the internal buffer shorter by the amount you wrote. Does this sound right?
Adam

use queue2/navseek?
I don't know of an existing single component that does this, but the pipeline does support the idea of 'seek by amount of time' events and there is a 'queue2' element that holds a defined block of time, so maybe there's a way to arrange something with a queue2 (or several of them) and an element that just generates seek events (maybe you write an element/component that injects left/right arrow events and you just use navseek to make those into pipeline seek events?)
If you elect to write a full-on windowing component, I'd suggest you consider a data structure to support a multitap buffer (I've needed that in previous endeavors). That is, one list of data objects On, On+1, On+2, ... , Om and the ability to get output streams on slices of that list as the data shifts through - like a T with with outputs on list-locations instead of on the single data element in the current "tee" ... it would be a 'sometimes' pad I could ask for by indicating the delay as a parameter in the mimetype, in either time-delay or in samples-delay. With a multitap-delay, you could also easily run the overlapping analysis parts in parallel.
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