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Data processing inside a plan, involving externally-stored data (e.g. images)
from ophyd.sim import img as detector
from bluesky.plan_stubs import open_run, stage, unstage, close_run, trigger_and_read, subscribe, unsubscribe
from bluesky_live.bluesky_run import BlueskyRun, DocumentCache
def plan():
Take 10 shots with a detector and do some data processing on the result.
Key points
* This detector writes data in external files (temporary files in this
case). The complexity comes from getting that data out so we can process
* The processing here is happening "in band", within the loop of the plan
logic and in a blocking fashion. For expensive data processing this
should be moved into a separate process to avoid slowing down the data
acquisition process and blocking its ability to (for example) monitor for
Ctrl+C or other interruptions. But of course that adds yet more
complexity, so this is suitable for light processing.
# We'll collect documents from the run in here. This is a callable that
# accepts (name, doc) pairs, so we can just subscribe it.
dc = DocumentCache()
token = yield from subscribe("all", dc)
yield from stage(detector)
md = {} # Put some metadata about plan parameters, intent, etc. in here.
yield from open_run(md=md)
# The BlueskyRun object provide an interfact to the documents that works
# exactly like what you get back from databroker.v2, as in
# run = catalog[-1]
# but unlike databroker the documents are in memory (in DocumentCache) not
# coming from a database.
run = BlueskyRun(dc)
for i in range(10):
yield from trigger_and_read([detector])
data =["img"]
last_image = data[-1] # most recent image
# Do some computation...
print("Total intensity", last_image.sum())
yield from close_run()
yield from unsubscribe(token)
yield from unstage(detector)
if __name__ == "__main__":
from bluesky import RunEngine
RE = RunEngine()
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