All internal and public errors have been revised (GPT 5.6 Sol) to return
more detail without horrendously long error classes, this has reduced
the number of error types but each now carries a reason and a code for
differentiation if needed
PlaybackEngine has been implemented and is functional, core mode changes
what signal descriptors are returned to avoid duplicates, the playback
engine currently discards the derived signals that would be recorded in
the DLPak and derived signals are reprocessed live
Future will require the behavior listed above to be selectable so one of
two options are possible:
A - Derived signals are reprocessed live by the relevant derive units
(current behavior
B - Derived signals are played back directly from the PlaybackEngine,
this requires turning off the routing to the live derive units to avoid
duplicate values
This will also require the option to perform offline processing with
derive units to be able to create derived signals after the fact, this
will likely incur a new 'offline' mode in the core to gate things
correctly, this will likely be useful for heavier processing that cannot
be done live, filters that require a lookahead, or more precise derived
signals using interpolated signals for higher acurracy which also brings
the ability to offline process on a fixed timebase instead of following
either input signal to the derived signal
Derive units are now available in the core and has their relevant input
values routed and outputs are looped back into the core router
Fixed the dlpak manifest which had no signal descriptors
SignalDescriptor now have a new origin field to distinguish "source"
from "derived" signals, this is ahead of the internal loopback system
for data processing, all external conectors must use source, derived is
targeted only for internal use
The connector registry has been adapted to now have a unique internal
loopback, this does not have an associated endpoint so it is stored
apart and all relevant functions have been updated to include it for
proper handling of signals by DLPak etc
Implemented DLPak design with zip storage, DLPak consists of two files,
a manifest.json which provides details on the signals, time of recording
and currently blank comment field and data.csv which stores all the
signals as csv with the nanosecond timestamp and indexed against the
signal id
ValueBuffer is now the default buffer object for storing data for
recording and processing purposes, a simple recording implementation has
been done, core.py example starts recording as soon as the core has
started then on exit it saves the output as a csv file through the
ValueBuffer export_csv method
h3cx