Documented new Time Series records, removed references to MCA module
git-svn-id: https://subversion.xor.aps.anl.gov/synApps/areaDetector/trunk@14477 dc6c5ff5-0b8b-c028-a01f-ffb33f00fc8b
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rivers
@@ -10,7 +10,7 @@
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<h1>
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areaDetector Plugin NDPluginStats</h1>
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<h2>
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August 9, 2011</h2>
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February 12, 2012</h2>
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<h2>
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Mark Rivers</h2>
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<h2>
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@@ -48,6 +48,11 @@
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be perfomed on arrays of any dimension. Calculations 2 and 3 are restricted to 2-D
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arrays.
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</p>
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<p>
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Time-series arrays of the basic statistics, centroid and sigma statistics can also
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be collected. This is very useful for on-the-fly data acquisition, where the NDStats
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plugin computes the net or total counts in the detector or an ROI. It can also be
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used to quickly plot a time-history of beam position or width, etc.</p>
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<p>
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NDPluginStats inherits from NDPluginDriver. The <a href="areaDetectorDoxygenHTML/class_n_d_plugin_stats.html">
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NDPluginStats class documentation</a> describes this class in detail.
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@@ -64,7 +69,8 @@
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<tbody>
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<tr>
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<td align="center" colspan="7,">
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<b>Parameter Definitions in NDPluginStats.h and EPICS Record Definitions in NDStats.template</b></td>
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<b>Parameter Definitions in NDPluginStats.h and EPICS Record Definitions in NDStats.template</b>
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</td>
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</tr>
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<tr>
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<th>
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@@ -217,8 +223,7 @@
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is ≤ 0 then no background is computed. The net counts is available as an ai record.
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The net counts is also available as epicsInt32 values in an mca record via callbacks
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to the drvFastSweep driver. The mca record is very useful for on-the-fly data acquisition
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of the net counts in the detector or in an ROI.
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</td>
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of the net counts in the detector or in an ROI. </td>
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<td>
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NET</td>
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<td>
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@@ -381,6 +386,162 @@
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<td>
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ai</td>
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</tr>
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<tr>
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<td align="center" colspan="7,">
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<b>Time-Series data</b></td>
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</tr>
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<tr>
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<td>
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NDPluginStats<br />
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TSControl</td>
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<td>
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asynInt32</td>
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<td>
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r/w</td>
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<td>
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Controls time-series data collection. The enum choices are:
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<ul>
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<li>Erase/Start: Clears all time-series arrays, sets TS_CURRENT_POINT=0, and starts
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time-series data collection.</li>
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<li>Start: Starts time-series data collection without clearing arrays or modifying
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TS_CURRENT_POINT. Used to restart collection after a Stop operation.</li>
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<li>Stop: Stops times-series data collection. Performs callbacks on all time-series
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waveform records.</li>
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<li>
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Read: Performs callbacks on all time-series waveform records, updating the values.
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</ul>
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</td>
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<td>
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TS_CONTROL</td>
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<td>
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$(P)$(R)TSControl</td>
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<td>
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mbbo</td>
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</tr>
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<tr>
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<td>
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N.A.</td>
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<td>
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N.A.</td>
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<td>
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r/w</td>
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<td>
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Sends the "Read" command to the TSControl record above. This record can be periodically
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processed to update the time-series waveform records. It is scan disabled if TSAcquiring=Done,
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so that updates are only performed when time-series acquisition is in progress.
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</td>
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<td>
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N.A.</td>
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<td>
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$(P)$(R)TSRead</td>
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<td>
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longout</td>
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</tr>
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<tr>
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<td>
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NDPluginStats<br />
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TSNumPoints</td>
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<td>
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asynInt32</td>
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<td>
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r/w</td>
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<td>
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Controls the number of time-series points to collect. There is no maximum value,
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the time-series arrays in the plugin are freed and reallocated each time this value
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is changed. However, the size of the waveform records is fixed when the IOC is started,
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so NELM in those records must be large enough for the largest time-series needed.
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</td>
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<td>
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TS_NUM_POINTS</td>
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<td>
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$(P)$(R)TSNumPoints</td>
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<td>
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longout</td>
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</tr>
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<tr>
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<td>
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NDPluginStats<br />
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TSCurrentPoint</td>
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<td>
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asynInt32</td>
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<td>
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r/o</td>
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<td>
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The current time-series point. If TSCurrentPoint reaches TSNumPoints then time-series
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acquisition is automatically stopped, and callbacks are done on all time-series
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waveform records, updating the values. This means that even if TSRead has SCAN=Passive
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that the waveform records will update when time-series acquisition is complete.
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</td>
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<td>
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TS_CURRENT_POINT</td>
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<td>
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$(P)$(R)TSCurrentPoint</td>
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<td>
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longin</td>
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</tr>
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<tr>
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<td>
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NDPluginStats<br />
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TSAcquiring</td>
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<td>
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asynInt32</td>
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<td>
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r/o</td>
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<td>
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Indicates status of time-series data acquisition. Values are 0=Done and 1=Acquiring.
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</td>
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<td>
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TS_ACQUIRING</td>
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<td>
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$(P)$(R)TSAcquiring</td>
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<td>
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bi</td>
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</tr>
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<tr>
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<td>
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NDPluginStats<br />
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TSXXX</td>
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<td>
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asynFloat64Array</td>
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<td>
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r/o</td>
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<td>
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The time series data arrays. XXX is one of the following, corresponding to each
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of the basic statistics and centroid and sigma statistics described above:
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<ul>
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<li>MinValue</li>
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<li>MaxValue</li>
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<li>MeanValue</li>
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<li>Sigma</li>
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<li>Total</li>
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<li>Net</li>
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<li>CentroidX</li>
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<li>CentroidY</li>
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<li>SigmaX</li>
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<li>SigmaY</li>
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<li>SigmaXY</li>
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</ul>
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</td>
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<td>
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<ul>
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<li>TS_MIN_VALUE</li>
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<li>TS_MAX_VALUE</li>
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<li>TS_MEAN_VALUE</li>
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<li>TS_SIGMA_VALUE</li>
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<li>TS_TOTAL</li>
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<li>TS_NET</li>
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<li>TS_CENTROIDX_VALUE</li>
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<li>TS_CENTROIDY_VALUE</li>
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<li>TS_SIGMAX_VALUE</li>
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<li>TS_SIGMAY_VALUE</li>
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<li>TS_SIGMAXY_VALUE</li>
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</ul>
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</td>
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<td>
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$(P)$(R)TSXXX</td>
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<td>
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waveform</td>
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</tr>
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<tr>
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<td align="center" colspan="7,">
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<b>X and Y Profiles</b></td>
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@@ -807,24 +968,22 @@
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<img alt="NDStats5.png" src="NDStats5.png" />
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</div>
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<p>
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The following MEDM screen shows the MCA record containing the total counts from
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the Stats1 plugin. This is the total counts as a function of time, and is very useful
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for on-the-fly data acquisition, where the NDStats plugin computes the net or total
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counts in the detector or an ROI.
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The following MEDM screen shows the the total counts from the Stats5 plugin. This
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is the total counts as a function of time.
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</p>
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<div style="text-align: center">
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<h3>
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mca.adl</h3>
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<img alt="NDStatsTotalArray.png" src="NDStatsTotalArray.png" />
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NDTimeSeries.adl</h3>
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<img alt="NDTimeSeriesTotal.png" src="NDTimeSeriesTotal.png" />
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</div>
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<p>
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The following MEDM screen shows the MCA record containing the net counts from the
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Stats1 plugin.
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The following MEDM screen shows the Y centroid as a function of time from the Stats5
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plugin.
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</p>
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<div style="text-align: center">
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<h3>
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mca.adl</h3>
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<img alt="NDStatsNetArray.png" src="NDStatsNetArray.png" />
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NDTimeSeries.adl</h3>
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<img alt="NDTimeSeriesCentroidY.png" src="NDTimeSeriesCentroidY.png" />
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</div>
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</body>
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</html>
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