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PandA dataset naming #330
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Decision is:
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@callumforrester has my favourite suggestion so far:
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As part of this issue, I'm going to move save and load to the ophyd level. It doesn't really make sense to me that they're currently plan stubs - they currently assume I think |
The current save/load functions don't need any protocols, they just walk the device and set signals. It's only when we need some intelligence in a device (i.e. it knows the special way to save/load itself) that we need a protocol. Is there a use case for that here? |
Hmmm true. I supposes I could do |
Please keep these as plan stubs, we considered new protocols, but we decided to add as few new protocols as possible. Either saving or loading will require application specific logic which is better placed in a plan |
I'll be moving the current plan stubs from core |
Yesterday @coretl and I agreed that the dataset names should be set through the IOC. This turns this into three Issues...
Then down the line we can...
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@callumforrester Instead of searching through device children for things ending in ophyd-async/src/ophyd_async/panda/writers/_hdf_writer.py Lines 38 to 54 in 0b05b9c
we can just look for devices with a
Additionally, putting to this will give it a different scientific name in the file output |
@evalott100 so to clarify: There will be a new PV |
Yep, once using PandABlocks/PandABlocks-client#91 and PandABlocks/PandABlocks-ioc#118 |
Based on discussion with @abbiemery @evalott100 and @coretl, we are going to slightly change the plan and push more logic down to the IOC. The previous plan has ophyd-async putting dataset names to the panda and then reconstructing a data structure for So the new plan:
Most of the complex logic now goes in the IOC, it needs to produce the
In this case, The table also has to be kept up-to-date live, i.e. if a new value is put to a |
I suggest we use numpy datatypes, so
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At the moment the PandA HDF writer will always write datasets like "INENC1.VAL.Mean", "COUNTER1.OUT.Diff". These are exposed in the descriptor as "panda1-inenc-1-val-Mean" and "panda1-counter-1-out-Diff". These don't make any scientific sense, so we should allow scientific names to be given to the datasets and set the ophyd name accordingly.
The options:
HDFPanda(prefix, dp, dataset_names = {"inenc-1-val": "sample-x", "counter-1-out": "izero"})
panda1.set_datsets({panda1.inenc[1].val: "sample-x"})
in the planThe text was updated successfully, but these errors were encountered: