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doc/manual/faq: more minor details

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Sebastien Bourdeauducq 2015-03-25 16:37:17 +01:00
parent bd2f6ea9f9
commit 2d1bbdf22a
1 changed files with 11 additions and 12 deletions
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doc/manual/faq.rst
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@ -4,7 +4,7 @@ FAQ
How do I ...
============
override the `sysclk` frequency of just one dds?
override the `sysclk` frequency of just one DDS?
------------------------------------------------
Override the parameter using an argument in the DDB.
@ -18,15 +18,14 @@ Names need to be unique.
enforce functional dependencies between parameters?
---------------------------------------------------
If you want to override a parameter `b` in the PDB to be `b = 2*a`,
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.
get rid of `DBKeys`?
--------------------
get rid of ``DBKeys``?
----------------------
`DBKeys` enforces valid parameter/argument names, references
keys in PDB and hints at metadata on how values can be retrieved.
``DBKeys`` references keys in PDB, DDB and RDB.
write a generator feeding a kernel feeding an analyze function?
---------------------------------------------------------------
@ -49,8 +48,8 @@ write a generator feeding a kernel feeding an analyze function?
def do(self, i):
return i
create and use variable lengths arrays?
------------------------------------------------
create and use variable lengths arrays in kernels?
--------------------------------------------------
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.
@ -58,15 +57,15 @@ function call, push them upstream and retry until the gate time closes.
execute multiple slow controller RPCs in parallel without losing time?
----------------------------------------------------------------------
Use `threading.Thread`: portable, fast, simple for one-shot calls.
Use ``threading.Thread``: portable, fast, simple for one-shot calls.
write part of my experiment as a coroutine/asyncio task/generator?
------------------------------------------------------------------
You can not change the API that your experiment exposes: `__init__()`,
`build()`, `run()` and `analyze()` need to be regular functions, not
You can not change the API that your experiment exposes: ``__init__()``,
``build()``, ``run()`` and ``analyze()`` need to be regular functions, not
generators or asyncio coroutines. That would make reusing your own code in
sub-experiments difficult and fragile. You can however always use the
scheduler API to achieve the same (`scheduler.yield(duration=0)`)
scheduler API to achieve the same (``scheduler.yield(duration=0)``)
or wrap your own generators/coroutines/tasks in regular functions that
you then expose as part of the API.