Jump to content
  • To Search the Seeq Knowledgebase:

    button_seeq-knowledgebase.png.ec0acc75c6f5b14c9e2e09a6e4fc8d12.png.4643472239090d47c54cbcd358bd485f.png

Search the Community

Showing results for tags 'scorecard'.



More search options

  • Search By Tags

    Type tags separated by commas.
  • Search By Author

Content Type


Forums

  • Community Technical Forums
    • General Seeq Discussions
    • Seeq Admin Forum
    • Training Resources
    • Product Suggestions
    • Seeq Data Lab
  • Community News
    • Seeq Blog Posts
    • News Articles
    • Press Releases
    • Upcoming Events

Categories

  • Seeq FAQs
  • Online Manual
    • General Information

Find results in...

Find results that contain...


Date Created

  • Start

    End


Last Updated

  • Start

    End


Filter by number of...

Joined

  • Start

    End


Group


About Me


Company


Title


Level of Seeq User

Found 15 results

  1. Sometimes it is desired to have custom units of measure display in Seeq Scorecards. This could be used when the signal or condition has no units or when you want to add a custom display or a unit that might not be a recognized Seeq unit. You can use Seeq's Number Format customization in the item properties panel to add custom text units to your scorecard. Here are some examples showing different ways to add text display units. The key here is including the text in quotation marks. More information on how to customize these number displays, including the syntax for adding custom text, can be found by clicking the "?" icon next to "Number Format".
  2. As covered in Push Scorecard from Seeq Data Lab, it is possible to push a scorecard from Seeq Data Lab into Seeq Workbench Analysis. In this post, we'll cover how we can format the display of a worksheet in Scorecard view. The scorecards can be pre-made in Workbench or have been previously pushed from Seeq Data Lab. Please refer to R21 Scorecard Metric for more information about how to modify scorecard display format in Workbench. To format the display of a worksheet, we will first need to access the worksheet to be changed. In these examples, we'll assume that we're modifying an existing worksheet. Similar logic can be applied to new worksheets being created. Step 1: Pull in the worksheet First, using the spy.search and spy.pull commands we can pull information about the workbook of interest. We can then navigate through the workbook in Python to access the contents of the worksheet. # The output of this command is a list of pulled workbooks that match the criteria passed into the search command pulled_workbooks = spy.workbooks.pull(spy.workbooks.search({"Workbook Type":"Analysis", "Name": "Example Analysis"})) # You can then access the worksheet looking to be changed using the command below. A variation to access the worksheet by its location rather than its name is listed beneath scorecard_worksheet = pulled_workbooks[0].worksheet("Scorecard Worksheet") # scorecard_interested =pulled_workbooks[0].worksheets[1] Step 2: Modifying the Scorecard View We can then modify the format of the display using the code below. # This line is only needed if the worksheet is not in Scorecard view scorecard_worksheet.view = "Scorecard" # The lines below change the format to only show the Start time in an "l" format, which is m/d/yyyy scorecard_worksheet.scorecard_date_display = "Start" scorecard_worksheet.scorecard_date_format = "l" For additional options for formatting, please take a look at the code below @property def scorecard_date_display(self): """ Get/Set the date display for scorecards Parameters ---------- str or None The dates that should be displayed for scorecards. Valid values are: =============== ================================ Date Display Result =============== ================================ None No date display 'Start' Start of the time period only 'End' End of the time period only 'Start And End' Start and end of the time period =============== ================================ Returns ------- str or None The scorecard date display """ return self._get_scorecard_date_display() @property def scorecard_date_format(self): """ Get/Set the format for scorecard date displays Parameters ---------- str The string defining the date format. Formats are parsed using momentjs. The full documentation for the momentjs date parsing can be found at https://momentjs.com/docs/#/displaying/ Examples -------- "d/m/yyy" omitting leading zeros (eg, 4/27/2020): l "Mmm dd, yyyy, H:MM AM/PM" (eg, Apr 27, 2020 5:00 PM) : lll "H:MM AM/PM" (eg, "5:00 PM"): LT Returns ------- str The formatting string """ return self._get_scorecard_date_format() Step 3: Push the workbook back to Workbench Pushing the workbook back into Workbench will cause the existing workbook to update to match the formatting we specified in Seeq Data Lab. # Push the workbook back into Workbench spy.workbooks.push(workbooks= pulled_workbooks)
  3. Hey there, My question splits into two parts: Firstly, I want to create a condition based on multiple criteria: if signal A equal to 3, B equal to 4, C is greater than 5 than condition is valid. I know i could create 3 individual capsule and overlap them. Is there a simple way to use formula to do so? Secondly, in my analysis i have 10 signals and associated conditions(alert), then I want to know in the past 7 days how many alert in total(repeated instance or capsule doesnt count) ? and How long is the total alert time? Thank you
  4. Background: One of the quirks of raw, ungridded time series data is that sampling frequencies may vary. Sometimes the sample frequency is different for two signals that you are comparing, and sometimes the sample frequency is different for a single signal at different points in time due to a process data historian's compression configuration. How you handle this variability in sampling rate can have a significant impact on calculations of summary statistics. Various approaches to calculating summary statistics and their implications: In this example we have four signals with different amounts of samples in the display range (as highlighted by the "count" statistic in the details pane. Our goal is to calculate a single "average" value for all of the signals during this window. Notice the different outcome values from each different approach. Method 1: One option that we have for getting a single "average" statistic is to take the average value of each of the 4 signals over the time window, then take the average of that. This method weights each of the signals evenly in the calculation of the final average value, since the final average value is equal to (0.25)*avg1 + (0.25)*avg2 + (0.25)*avg3 + (0.25)*avg4 Method 2: A second option is to first create a continuous average signal, then aggregate that over the display window to calculate an average. The average can be calculated using formula and the average function with the syntax shown below. Note that the sample count on the output signal has a significantly larger number of samples than any of the original signals. This is because the average function calculates a sample any time any of the input signals has a sample. For the signals that do not have a sample at a particular key, the linearly interpolated value of the signal is used in the average calculation. Then a scorecard aggregation of the average of the continuous average signal can be calculated in the Scorecard Metric tool to get the result below. Method 3: A third option is to take the average of all the data points in the display window, independent of which signal they belong to. This approach involves first combining all of the samples from the 4 signals into a single signal, then taking the average of that value over the display window. The sample count of the combined signal will be equal to the sum of the sample counts of all other signals, as demonstrated below. In this approach, the resultant signal also has a sample any time any of the other signals contain a sample. Note that if signals have the same frequency, a tiny delay can be applied to the 2nd through the nth signal (1 ns to n-1 ns) to ensure all samples are kept. A scorecard metric of the average of the combined signal can then be calculated. The overall average value returned using this method is much higher than the two previous methods due to the relatively higher amounts of samples in signals 3 & 4, which have generally have higher values than signals 1 & 2. Method 4: A non-time-weighted average (similar to method 3) can also be calculated using the following formula: average($signal1.toDiscrete(),$signal2.toDiscrete(),$signal3.toDiscrete(),$signal4.toDiscrete()) Once again the final signal contains a number of samples equal to the sum of all of the sample counts of the input signals. In conclusion.. Which method of averaging is best for your use case? The answer is probably "it depends" on the use case you are analyzing. Some examples of when different methods may be applied: An average over a specific time range - Method 1 An instantaneous average at a point in time - Method 2 An average of signals where each sample represents a unique event or independent measurement (e.g. lab or quality data) - Method 4 Regardless of your specific use case, having an understanding of how your data frequency, your historian's compression settings and your analytical approach can impact your results is an important starting point in any analysis!
  5. Question: I have a scorecard metric displaying the maximum value of a signal during a given capsule. I have the Scorecard coloring red if the value is >2%. Is there any way to display a scorecard with just color coded cells containing no values? What I am seeing now: What I would like to create: Solution: In general, the approach to creating a blank scorecard with color thresholds is to create a string signal comprised of varying amounts of spaces for each threshold/band. Then you can apply that number of spaces as a color threshold in the Scorecard metric tool. 1) Create your "empty" string signal in Formula. In the example below, we have a baseline signal that is a completely empty string and we are splicing in a string containing two spaces any time the value of the original signal is greater than 2%. You can see that the empty string signal has what looks like a constant value each time the original signal is > 2%, but when you hover the cursor over the signal you see that it is actually blank. 2) Use Formula to create a scalar threshold value to select as your threshold in Scorecard. Note, in versions R22.0.47 and greater, string values are accepted as thresholds in the scorecard metric tool, so this step can be skipped. 3) Calculate your scorecard metric. For versions before R22.0.47, the tool input for the thresholds will look like this: For versions R22.0.47 and newer, you can use: 4) The final scorecard (validated against the original one containing values):
  6. It is often useful to create a scorecard metric that displays a signal name for use in Organzier Topics. This is relatively simple using Formula and the toSignal() function. This Formula creates a string signal that has a value of "Signal Name" for all of time. After I have my string signal, I can use a simple scorecard metric with no statistics to create a scorecard that just displays the value of this string. I have changed the header to only display the end time. Now, I can use this scorecard in an auto-updating Organizer Topic that will always show "Signal Name". This functionality is very useful if you want to create a string signal that has more than one value. For example, say that I have three signals. I want to create a scorecard metric that tells me which of these three signals is the largest at any point in time. I will start by creating conditions for when each signal is larger than the other two. First, I use Deviation Search to find when Signal 1 > Signal 2 and for when Signal 1 > Signal 3. Then I use Composite Condition (logic: intersection), to find when Signal 1 is max. I repeat this process for Signal 2 - Deviation Search to find Signal 2 > Signal 1 and Signal 2 > Signal 3 + composite condition. Finally, I use Formula to find when Signal 3 is max by using union() and inverse() to find when Signal 1 or 2 are not max : $1max.union($2max).inverse(). Now I have 3 conditions which should cover the whole time series, which are true when each Signal is the maximum of the 3 at any point! I'm now ready to create the string signal. Just like I did for a single string, I will essentially be creating new signals with toString(), but this time, I will use splice() to splice in the different strings ("1 is max", "2 is max", or "3 is max") when each condition is present. This works because my "X is max" conditions will never overlap. The result is a string signal that equals whatever signal is the maximum at every point in time! Finally, I'll use Simple Scorecard again to create a metric that displays this Max Signal for use in Organizer Topics.
  7. FAQ: I have various conditions that I've created and I am trying to capture the minimum value of a signal during 1 condition and the maximum value of the same signal during another condition. I want these values displayed in a scorecard where the headers are the exact time stamps when the max or min value occurred. Solution: Let's take an example where we have two conditions for when a signal is increasing in value and when a signal is decreasing in value. We want to know the max ROC during the time periods when the signal is increasing, the min ROC when the signal is decreasing and I want them all summarized in a single scorecard metric for "max ROC". 1) Begin with the signals of interest in the display pane and conditions of interest identified. In this case we have a temperature signal, its derivative, and two conditions for when the temperature signal is increasing or decreasing in value. 2) We can use Signal from Condition to calculate the maximum ROC during each increasing time period. Make sure to specify that the time stamp of the statistic be placed at the point of max value. This will be important for displaying an accurate time header in our scorecard. 3) Use Signal from Condition again to calculate the min ROC during the decreasing time periods. This time place the time stamp of the statistic at the point of min value. 4) Use the CombineWith function in Formula to create a new signal combined of the min and max ROC value signals. 5) Use Formula to create a new condition comprised of tiny capsules for each data point in your combined min and max condition. This is done by doing a value search for when the combined ROC signal has valid data. You will notice that these capsules are so short in length that they do not render in the display pane, but you can see their start and end times, as well as the value of the combined signal during each event in the capsules pane. 6) Now switch to Scorecard view and pull the value of the combined min/max ROC signal into a condition based scorecard during the condition for when that signal has valid data. There is no need to calculate a statistic, as there is only one sample during each of these capsules. Adjust the date headers in the scorecard to display only the start or end time (as they are the same).
  8. Hi Seeq, I am trying to create a single scorecard in R21 with multiple metrics calculated over the last 7, 14, and 365 days, but I can't figure out how to do this. Could you please provide some guidance?
  9. Question: I have a condition with multiple properties that I have displayed in the capsules pane. Is there a way to get the data from the capsules pane into a Seeq Organizer Topic? Solution: Create a new string signal for each property that you are interested in displaying in your Organizer Topic, then create a scorecard that displays those values in a table that can be added to Organizer Topic. 1. Use Formula to create a new string signal with a value equal to the capsule data for a certain property. The formula syntax to do this is: $YourCondition.removeLongerThan(1d).transformToSamples($cap -> Sample($cap.getStart(),$cap.getProperty('Product')), 2d).toStep() 2. Duplicate step 1 for each of the other capsule properties that you are interested in. The best way to do this is by using the duplicate button found in the item properties for your new string signal. This will automatically open a new formula window with the same formula from the string signal that you created in step 1. All you need to do in the new formula window is change the name and change the property that you want to create a new signal from. 3. Repeat step 2 for each capsule property that you would like to be able to display in your organizer topic. 4. Now you can create a scorecard that displays the value of each string signal over each capsule. Switch to Scorecard View using the green drop down at the top of the Display Pane. 5. Click “Add a Metric” from the center of the display pane and populate the Scorecard Metric Tool input with your string signal, your condition with the properties, and the statistic Value at End (note Value at Start will also work since this is a string tag and the value is constant across each capsule). You’ll then see a single row in your scorecard like below. You can change the format that the column headers are displayed from the headers dropdown in the top of the display. Here I have selected to display only the start time as the header and selected the first pre-defined date format. 6. Follow the same calculation duplication method described in step 2 to create a new metric for each capsule property you want to display in your organizer topic. Make sure to change the Scorecard metric name and item to measure (input signal) each time. 7. Now add your score card to an Organizer Topic and configure custom date ranges as desired.
  10. Sometimes it is helpful to show the date range of the Seeq content used in an Organizer Topic that is shown in the topic itself. One way to do this and reduce manual updates to the topic is to leverage a scorecard to achieve an auto-updating date range. The the below steps detail how to create a date range scorecard metric: 1) Create a string signal with descriptive text using formula. The string will be displayed in the scorecard. "Current Date Range".toSignal() 2) Create a simple scorecard metric that measures the string signal created in step 1. The result is a scorecard metric showing the date range in the header and the descriptive text in the cell. 3) Remove the column with the scorecard metric name by selecting the green "x" at the top of the metric. 4) Insert the scorecard into the Organizer Topic and apply the desired date range. The scorecard will reflect the date range configured and applied from the Topic.
  11. Dear All, I would like to know how to set scorecard metrics for same time in all rows , Picture attached for reference. Regards,
  12. Beginning in the R21 release of Seeq, administrators can modify scorecard threshold colors, names, and levels (priorities) using the Seeq API Reference. The screenshot below shows an example of the parameters that can be customized: Please contact Seeq support for further details if you are interested in doing this.
  13. In reporting, users may be interested in creating a Scorecard that contains certain metric results over a variety of time periods, such as "April 2019", "Quarter 1", and "Year to Date", etc. This can be accomplished using the following steps: 1. Use Formula to create a condition that contains a capsule for each time period that you are interested in. Note that I assigned a property to each capsule; this text will be used as the column header in the scorecard: 2. Create a Condition based scorecard and add a metric for each item you are looking to calculate: 3. Finally, use the capsule property as the column headers:
  14. I have a condition with several capsules of various lengths; how do I determine the time period or length of each capsule? For example, my first capsule is 24 hours long, and then the next capsule is only about 3 hours. I'm looking for a way where I can get this information for all of my capsules.
  15. Hi, In Seeq R21. I am not able to see Scorecard color options. I hope I am not missing something here. Please let me know if there is easy way to work around this problem.
×
×
  • Create New...