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FAQ
###
How do I ...
============
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override the `sysclk` frequency of just one dds?
------------------------------------------------
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Override the parameter using an argument in the DDB.
organize parameters in folders?
-------------------------------
Use gui auto-completion and filtering.
Names need to be unique.
enforce functional dependencies between parameters?
---------------------------------------------------
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If you want to override a parameter `b` in the PDB to be `b = 2*a`,
use wrapper experiments, overriding parameters by passing them to the
experiment's constructor.
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get rid of `DBKeys`?
--------------------
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`DBKeys` enforces valid parameter/argument names, references
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keys in PDB and hints at metadata on how values can be retrieved.
write a generator feeding a kernel feeding an analyze function?
---------------------------------------------------------------
Like this::
def run(self):
self.parse(self.pipe(iter(range(10))))
def pipe(self, gen):
for i in gen:
r = self.do(i)
yield r
def parse(self, gen):
for i in gen:
pass
@kernel
def do(self, i):
return i
create and use variable lengths arrays?
------------------------------------------------
Don't. Preallocate everything. Or chunk it and e.g. read 100 events per
function call, push them upstream and retry until the gate time closes.
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execute multiple slow controller RPCs in parallel without losing time?
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Use `threading.Thread`: portable, fast, simple for one-shot calls.
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write part of my experiment as a coroutine/asyncio task/generator?
------------------------------------------------------------------
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You can not change the API that your experiment exposes: `__init__()`,
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`build()`, `run()` and `analyze()` need to be regular functions, not
generators or asyncio coroutines. That would make reusing your own code in
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sub-experiments difficult and fragile. You can however always use the
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scheduler API to achieve the same (`scheduler.yield(duration=0)`)
or wrap your own generators/coroutines/tasks in regular functions that
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you then expose as part of the API.