Experimental Physics and
Industrial Control System

Mark Rivers <[email protected]> · Tue, 12 Mar 2013 17:41:19 +0000

Folks,

quadEM R4-0 is now available.  

This is from the release notes:

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Major update of the module. The device-dependent classes (AHxxx, APS_EM) have not changed significantly. However the base quadEM class has been rewritten. In R3-x the quadEM base class worked as follows: 

  - The ai records for the 11 parameters (Current[1-3],Sum[12,34,1234],Diff[12,34], and Position[12,34]) were computed using the asynInt32Average device support. 

  - This meant that there were 11 callbacks each time a new value came from the electrometer, or more than 70,000 callbacks per second under some circumstances. This was a significant CPU load. 

  - This approach produced average values, but it did not produce other useful statistics like the standard deviation, histogram of values, etc. 

  - There was no good way to stream all of the readings to a disk file for an arbitrarily long time. The TimeSeries support was limited to a fixed time length, limited by available memory. 

R4-0 addresses these problems as follows: 
  - The quadEM base class is now derived from the asynNDArray class in areaDetector, rather than directly from asynPortDriver. 

  - The data from the device-dependent drivers are now first placed into a ring buffer whose size is defined in the constructor. 

  - There is a new PV called AveragingTime that determines the time period over which to average the readings. The AveragingTime divided by the SampleTime determines the number of samples to average, NumAverage_RBV. When this number of samples have been accumulated in the ring buffer a separate thread copies them to a set of NDArrays and calls any registered plugins. 

  - There is a separate NDPluginStats plugin loaded for each of the 11 data values. This plugin receives an array of dimensions [NumAverage_RBV]. This plugin computes not only the mean (as in the previous version), but also the standard deviation, histogram of values, etc. 

  - One of the NDArrays contains all of the data values, and has dimensions [11,NumAverage_RBV]. This array can be passed to any of the file writing plugins, which can thus stream all of the data to disk for arbitrarily long time periods. 

  - An NDStdArrays plugin is also loaded. This can be used to pass all of the data [11,NumAverage_RBV] or any of the individual data arrays to any channel access client. 

  - This new approach provides much more information and flexibility. But it also significantly reduces the number of callbacks. For example if the averaging time is 1 second the number of callbacks is reduced from thousands per second to 12 per second, because the data are being passed in arrays. 

  - The computationally intensive work of calculating the statistics is now being done in plugins, so can be done in different threads, each potentially running in a separate core on modern CPUs. 
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The home page is here:
http://cars9.uchicago.edu/software/epics/quadEM.html

The documentation is here:
http://cars9.uchicago.edu/software/epics/quadEMDoc.html

The release notes are here:
http://cars9.uchicago.edu/software/epics/quadEMReleaseNotes.html

Let me know of any problems or suggestions.

Mark

Experimental Physics and Industrial Control System

Experimental Physics and
Industrial Control System