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Status Completed
Categories Symbols
Created by Guest
Created on Aug 18, 2022

Trend: Scatter plot - Switch off connecting lines

In trends give the user the option of disabling the connecting lines so that markers representing only the archived or calculated values are shown as a scatter plot.
  • ADMIN RESPONSE
    Aug 18, 2022
    In PI Vision 2020, new trend symbol enhancements were introduced including the ability to disable connecting lines and only show data markers. For additional information on PI Vision 2020, please see the release announcement here: https://customers.osisoft.com/s/knowledgearticle?knowledgeArticleUrl=000031641
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  • Guest
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    Aug 18, 2022
    add ability to plot only points
  • Guest
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    Aug 18, 2022
    When you want to have a look at a longer timespan with lots of data, it might get difficult to visualize the detail of the values of each individual point since the lines that connect each point are hirering the individual points. By using small points (size could be configurable) you can see the cloud of points and therefore visualy understand where the values are positioned on your trend. Thickness of the line between points, when used, could also be configurable. See an example: When you want to have a look at a longer timespan with lots of data, it might get difficult to visualize the detail of the values of each individual point since the lines that connect each point are hirering the individual points. By using small points (size could be configurable) you can see the cloud of points and therefore visualy understand where the values are positioned on your trend. Thickness of the line between points, when used, could also be configurable. See an example: When you want to have a look at a longer timespan with lots of data, it might get difficult to visualize the detail of the values of each individual point since the lines that connect each point are hirering the individual points. By using small points (size could be configurable) you can see the cloud of points and therefore visualy understand where the values are positioned on your trend. Thickness of the line between points, when used, could also be configurable. See an example: When you want to have a look at a longer timespan with lots of data, it might get difficult to visualize the detail of the values of each individual point since the lines that connect each point are hirering the individual points. By using small points (size could be configurable) you can see the cloud of points and therefore visualy understand where the values are positioned on your trend. Thickness of the line between points, when used, could also be configurable. See an example attached. Thanks in advance for supporting our idea.
  • Guest
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    Aug 18, 2022
    We would like to have option to have Dots instead of line for charts like in process book. When you are comparing lab data it is better all our users are requesting dots for labs. Example in attachment
  • Kenneth Barber
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    Aug 18, 2022
    Related: https://feedback.osisoft.com/forums/555148-pi-server/suggestions/40829293-be-able-to-turn-off-interpolation-for-a-pi-point https://feedback.osisoft.com/forums/555148-pi-server/suggestions/40829017-have-an-option-to-use-step-interpolation-to-the-pr
  • Kenneth Barber
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    Aug 18, 2022
    Currently, trends will always interpolate between stored events to produce as much of a continuous line as possible. However, it can be useful to see only the stored events. This can help users identify gaps in data or over-collection of data. Seeing individual events is also useful in cases where the stored events represent real-life events (e.g. the rejection of a defective product) or manually logged values. Please add an option to plot only stored events on a trend. The same graph should be produced regardless of the value of the PI Point's Step attribute. Each event should be represented by a line stemming from the time axis, similar to Fourier transform graphs, to make events easier to find and the time gap between events easier to judge compared to having only a dot for each event.