the buildsystem will now pick up and link
all test cases according to the layer, e.g.
backend tests will automatically be linked
against the backend + library solely.
tests used to be defined ad hoc and test definitions
are scattered confusingly over various directories.
Now built some simple rules into the buildsystem
to allow organising the tests into layers and
linking them accordingly.
Note: this switches to building shared objects
for the test classes too, which effectively speeds up
both re-building and re-running of test cases
while refactoring, I thought it might be a good idea
only to use Query objects. But in this special case,
most often you'd just want to pass in a simple query
with a literal query string. So this convenience shortcut
indeed makes sense.
This template was a leftover from the early days
of Lumiera development and doesn't provide any
substantial value as an abstraction.
For the more intricate cases, we're using the
lib::MultiFact template, which allows to install
several "fabrication" functions at runtime
the solution is to introduce a superinterface
and let Dispatcher augment that with the specific parts.
This way, the Job planning only has to rely on the
rather generic stuff (TimeAnchor, FrameCoord)
NOTE: this commit makes the whole JobPlanning machinery
compilable for the first time!
brainstorming how to implement the job planning stage
the idea is to built on top of the IterExplorer,
but have the "stack" of re-evaluation integrated
into a custom type, which exploits the static
node network structure to avoid heap allocations
solution idea: again use a builder function?
this enables expansion of a (functional) data structure
until exhaustion -- which is what we need to
build job functors by traversing and expanding
an arbitrarily nested job definition structure
the intention is to use this to simplify
generating render jobs based on the elaborated
dependency network of the render nodes. The key
challenge is to overcome the necessity to
store partially done evaluations as
continuation
the tricky part seems to be how to combine the
source iterators into a new monad instance, while
keeping this "Combinator" Strategy configurable
...just passes the compiler, while still lacking
even the generic implementation of joining
together the source iterators
The idea is to avoid building a data structure
for intermediary results, while still being able
to process a variably sized and arbitrary shaped
set of source data
implemented as extension to the linear combinations.
I decided to use the same "always floor" rule
as employed for time quantisation. Moreover,
we don't support floating point, only rationals
