Empower data points

Hi ,

Can you display raw data (acquired) points in a chromatogram  ?

I can only tabulate points across peak or 'enable tick marks' (not entirely sure what this is for) but not show data points on baseline plot


Answers

  • I'm not aware of a way to turn off the "connect-the-dots" aspect, but if you zoom in, you should be able to see the individual data points connected by straight lines.  If you use the "enable tick marks", it should further highlight the individual data points.  So if your peak is at 10 minutes of a 20 minute run, set the start/end around your peak, and set the seconds value at your data rate (convert pts/sec to seconds per pt so 2 pts/sec is 0.5 sec in the setting) to highlight each datapoint.
  • thanks

    Currently most our LC's are default with 'Peak width : >0.1min (2 s resp time (5Hz)), though I am struggling to see how 'enable tick marks' shows these individual points and corresponds to points across peak (assuming increments in this case 0.20 seconds?)

  • You can always export the raw data and drop it into Excel if the run time and sampling rate are not too high... I used to do this to check on gradient linearity and dwell volumes.
  • not entirely sure why or how you would want to drop data into excel for assessing datapoints for integration
  • There is no option for displaying acquired data points in Empower. Export the chromatogram to Excel and the data points are now visible and countable. For theoretical data points, right click the chromatogram plot properties. In here set the number of ticks. The number of ticks per retention time can be calculated via the data rate of acquisition. 
  • Ok ,, not what I expected

    Would be nice to actually see where data points are collected for peak integration by Apex track, especially low level response and for sensitivity  

    Only option as attached (if 0.2 increments correct using UV setting?)

    this gives theoretical data points ?

  • What do you mean by the points collected for peak integration?  How the algorithm sees the data points to perform the determination?

    Assuming you align the peak start/end settings properly in the view and use the correct increments for your data rate (so a 0.2 sec setting would be for a 5 pt/sec data rate), those vertical hashmarks are your actual data points that are used.  The algorithm would be calculating the slope between each of those to determine if it is a peak and where the beginning/end of the peak are based on your integration settings.
  • See attached

    Top right example displaying sample points (auto I believe) on another CDS and identifying small peak (algorithm as described in previous post)

    I'm not fully understanding where vertical hashmarks are and use of increments

    You can set this between 0.00 - 39354 ?

  • Ah...I think I even see them in your example...they will be perfectly inbetween the numbers as the numbers are just counting the segments created in the view.

    First, you probably need to tweak your "seconds" value.  A setting of 10 seconds would mean your IM's sampling rate (in order to match the actual datapoints) would have to be 0.1 pts/sec...which is clearly not the case based on that baseline.  So what is your actual sampling rate?  I've attached an example from an analysis.

    Then, to help visualize if you need it, you can zoom in a bit more.  You can also change the color and thickness of the hashmarks if you need to...under the plot properties' Colors tab...Tick Marks/Fractions.  Note that it seems as if you need to go really big (I had to go at least to a thickness of 20+ to get much of a visual change).  Maybe set them to something like red to contrast the black of the baseline to help see them?
  • Further to discussion I believe there is no option for displaying data points of a chromatogram. The above examples show theoretical data points then the number of ticks per retention time can be calculated (by data rate) . By exporting to Excel the data points can be visible (though never attempted this, or indeed want to ) 
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