Shamus Cunningham

This is a solution for a question that came in the support channel that I though would be of general interest. The question was how to designate a fixed training range for a signal and then calculate upper and lower limits of the signal using the 3rd and 97th percentile and apply those limits to the entire history of the signal This requires a two step process. The first is to create scalar signals for the upper and lower limits. Next we use those upper and lower limits to clean the signal using the remove() formula Step 1) Calculating the Scalar values for the 97th and 3rd Percentiles In the example below the training range start and end dates are hard coded into the formulas for simplicity $trainingRangeStart = '2022-10-01T00:00:00Z' $trainingRangeEnd = '2022-10-31T00:00:00Z' $trainingCondition = condition(capsule($trainingRangeStart,$trainingRangeEnd)) $calcPercentile = $signal.aggregate(percentile(97), $trainingCondition, startKey()) $calcPercentile.toScalars(capsule($trainingRangeStart,$trainingRangeEnd)).average() Similar formula for the lower limit $trainingRangeStart = '2022-10-01T00:00:00Z' $trainingRangeEnd = '2022-10-31T00:00:00Z' $trainingCondition = condition(capsule($trainingRangeStart,$trainingRangeEnd)) $calcPercentile = $signal.aggregate(percentile(3), $trainingCondition, startKey()) $calcPercentile.toScalars(capsule($trainingRangeStart,$trainingRangeEnd)).average() Step 2) Clean the signal using the new scalar values for upper and lower limits $signal .remove(isGreaterThan($upper)) .remove(islessthan($lower))

A newer and simpler method for this using the Table view and conditions is linked below

Here is an example of how to convert a String signal into a table where each row contains information on the start / end time and total duration of each time the string signal changed values Step 1: Convert your string signal into a condition inside of Formula $signal.tocondition() -> This formula creates a new capsule every time that the string signal changes value regardless of how many sample points have the same string value. Step 2: Create a table view of the condition. Select the "Tables and Charts" view and the "Condition" mode Step 3: Add Capsule properties as values to the table. To add the "Value" property which is the value from the string signal type in "Value" into the Capsule property statistics table. You can also select the duration here Final Product

This seems like a use case that would greatly benefit from being able to share screens and view the raw signals. Could you please schedule a time at office hours for one of our Analytics Engineers to work through this scenario with you https://outlook.office365.com/owa/calendar/SeeqOfficeHours@seeq.com/bookings/

The following is a mini-guide on best practices for setting up a scheduled refresh of an oData in PowerBI Step 1: Configure your exports using the "Auto-Update" option. This is an important step and makes sure that whenever the powerbi service requests data from Seeq that the data range window updates to "now" https://support.seeq.com/space/KB/112868662/OData+Export#Configuring-the-OData-Export Step 2: Create an access key and authenticate with the access key in powerbi to begin building your dashboards. https://support.seeq.com/space/KB/740721558 Step 3: Publish to your PowerBI workspace of choice Step 4: In your PowerBI workspace open up the settings for your dataset Step 5: For each export included in your dataset click the edit credentials link and then enter your access key information from Step 2. Click Sign In to verify the information Step 6: Configure your Scheduled Refresh cadence and click Apply

The first response with the hard coded dates will give you the answer you are looking for as long as you do anticipate adding new capsules to the "Data Valid" condition in the future. The part of the formula that limits the scope of the search is the $signal.within($ValidData) section. This means that only data that falls within capsules part of the ValidData condition AND within the capsule("2020-01-01T00:00:00Z","2022-07-28T00:00:00Z") date range

It is possible to create a moving window for the SearchArea --- please read below $SearchArea = capsule("2020-01-01T00:00:00Z",now()) However there could be some performance impacts if there are a lot of downstream calculations dependent on this value. Since this value would need to be continuously evaluated Seeq will not be able to cache the result and so this number as well as any calculations which are dependent on it will show up as dotted lines indicating that the results are subject to change. If this is just for a visualization or the number of datapoints is not that large it may not be a problem, however if you are seeing performance issues consider moving the SearchArea back to a fixed range

I think what you are going for will look like the formula below Where $SearchArea is the total range where any of your valid data capsule could fall (you can be very conservative with these dates). This formula will work if you have multiple valid data range capsules as long as they all fall within the $SearchArea $SearchArea = capsule("2020-01-01T00:00:00Z","2022-07-28T00:00:00Z") $Signal.within($ValidData).maxValue($SearchArea).toSignal()

Ray, There are probably two ways to approach this and I would try each out and see what works best to capture what you are looking for Method 1 Use derivative to find instantaneous rate of change. Then search for period when that instantaneous value is high for an extended period of time. Step 1 Create derivative signal - you may also want to optionally apply some simple signal smoothing to your raw signal to accommodate for any spikes in the data. In the example below I am using 2 min smoothing and the AgileFilter function but this should be tuned to your data. You could also add the abs() function to the end of this formula if you are interested in any types of rate of change events not just positive increases. $TankLevel.agilefilter(2min).derivative('h') Step 2 Use value search to find period when derivative is above your target value of 4 for a specified period of time (30 minutes in the demo below) Method 2 Directly calculate the rate of change over an hour at a specified sampling rate. The formula below calculated the delta between the signal at a point in time and in 1 hour. The second line periods() function sets up the sampling interval where this will be evaluated every 10 minutes. The startkey() parameter places the value for the difference between value at the start of the 1 hours period. This could be adjusted to the endkey() or middlekey() depending on your needs. Finally, the toStep() function makes this a step interpolated signal but you could remove this line if you would like a lineally interpolated value. For this example the step interpolation helps tell the story of the delta evaluation at distinct moments in time. Finding period of high rate of change would be the same as the ValueSearch step above in method 1 $TankLevel.aggregate(delta(), periods(1hour,10min), startKey()) .toStep()

Quick Guide to adding a table of current signal values to an Organizer Topic Create the Table in Workbench Add signals of interest to the display and then switch to Tables & Charts mode Add a new Column with Last Value (Optional) Remove Average column rename Last column to "Current Value" Add Table to Organizer and setup date range Insert table into your document either by pasting in the url of the workbench or navigating to the document Create Date range and update schedule and attach it to the table. The Range for the data can be anything from 1 day to 1 hour depending on how frequently your signals are sampled. You want to make sure to set a duration that will always include at least one data point. Set Update rate for the document in this example 1 hour updates are shown but you can change the update frequency if a more live view is desired

Brett, There is not currently a direct equivalent function that would allow you to move a capsule using a variable amount. However, below is a formula that does the same thing in a couple of steps. It comes with a couple of caveats however If you have capsule properties on the first calculation they will not be transferred over to the delayed signal This formula will delay the start and end of the capsule the same amount as defined by the value of your delay signal at the capsule start. You could probably extend this to do more complex transformations if needed $step1 = $condition.aggregate(totalDuration("min"), $condition, startKey(), 0s) $step2 = $step1.move($timeShiftSignal,2h) $step2.toCapsules($sample -> capsule($sample.key(),$sample.key()+$sample.value()),30d) Let me know if this helps get you on the right track. Also I am curious to understand more about your use case so that we can help improve the built-in functions in the future. Shamus

Eric, There is not currently a way to add stats to the capsule panel. What kind of statistics are you interested in adding?

The Scorecard tool does not have all of the timezone options in it and instead uses the default server time. The easy work around is to create a monthly condition using the Periodic Condition Tool with our desired timezone and then switch your Scorecard to a "Condition" type using that new monthly condition.

I am sure that there are probably a few ways to do this but here is a solution I came up with $conditionToSamples = $condition.aggregate(count(),$condition,durationkey()) $countingRange = condition(capsule('2020-01-01T00:00Z', '2023-01-01T00:00Z')) $countSignal = $ConditionToSamples.runningsum($countingRange) $condition.setProperty('Capsule Count',$countSignal,average()) Step by Step Outline $conditiontoSamples - Take your input condition and turn it into a signal with a value of 1 whenever the condition exists $countingRange - the range we are going to count these capsules over. In this example beginning of 2020 to beginning of 2023 $countSignal - Create a signal that counts up those values for each condition starting at the start date Set the value of the $countSignal as a property on your original condition

Today in Office Hours I ran into an interesting problem when using the removeoutliers() function on a signal that also had gaps in the data. If you use the function directly on a signal of this type it will not detect the outlier point as you might expect. However there is a quick work around that I will detail below. The signal looks like the one above where the outlier was right after a data gap. In order to work around this problem we chained together a couple of functions in formula. $gaps = $signal.isValid() $signal.validValues().removeOutliers().within($gaps) Step 1 - create a condition $gaps that captures only the periods of time that contained valid data in the original signal Step 2 - use the validValue() function to ignore the gaps in the original signal, next run the removeoutliers() function finally add back in the gaps by using the within function

There is not a mechanism to move the graphics directly to PowerBI but you can move the data that developed the graphs using the oData export https://support.seeq.com/space/KB/112868662/OData Export#Example-Importing-to-Microsoft-Power-BI-(Authenticate-Using-Seeq-Username-and-Password) This will require building the graphics again inside of PowerBI and I would recommend using the Signal export on a fixed grid in order to get datapoints that are at the exact same timestamp which will make life in PowerBI much easier Shamus

As an Admin you can view additional user information not available through the Administration panel through Seeq Data Lab. The attached script will give you a dataframe containing the last login date for any given user. View All User Data (2).ipynb

I know that this is an old post but I wanted to give an update. Unfortunately there is not currently a way to pass user credentials or delete worksheets/workbooks using the URL builder functionality.

There is an easy way to filter a condition to only keep capsules that are either longer or shorter than a specified duration. In formula just use one of the following function $myCondition.removelongerthan(5h) or $myCondition.removeshorterthan(5h)

Kenny, There is not currently a way to delete oData exports for non-admins. However, the exports do not put any load on the Seeq system unless they are being used by an external system (PowerBI, Tableau, etc) To answer your second question we are creating a new export url endpoint every time someone runs the tool in workbench. These oData feeds are in active development and we have plans for making the creation and maintenance of them easier in upcoming releases.

I wanted to put together a quick guide on how to clear the cache for a particular signals inside of Seeq Workbench. Come common reasons for wanting to clear the cache on a signal Data source caching is turned on and you have changed a calculation in your source database You have added prior history to a tag and filled in a gap Steps to Clear the cache Open Item Properties Open Advanced Settings Click "Clear Cached Values"

In R52+ we have replaced the concept of document owner with folders for each individual users. There are two slightly different methods for changing ownership depending on if the document orignates from a User's folder or the Corporate Drive If you want to change the owner of a document that has not been published to the corporate drive you need to move that document from the existing user's folder to your target new users. The gif below gives a quick overview of the process. If the document is in the Corporate Drive admins can edit the document and directly transfer ownership to another user. The document owner for Topics is important as the document owner will act as the user permissions to render all of the charts and graphics. The document owner thus must have access to all the datasources in a topic in order for it to render properly.

We have had a couple of users ask for a method to create a table of timestamps and values for each of the samples in a signal. Below is a quick method to create such a table using the new features available in versions R53+ This method in general makes the most sense for finding the timestamps of discrete points but could be used for signal Step 1: Create a condition with a capsule for every sample point $signal.toCapsules() Step 2: Move to the table view and select the "Condition" option The general settings you are going to want to pick are Condition mode Headers = Start Time Columns Capsule Property = Value Final Product:

There is a quick little trick to do this by combining two formulas together $signal.tocondition().tosignal() What this formula does is create a condition .tocondition() where each capsule starts when the value in your ID signal changes (eliminating duplicate values) and then transforms those capsules back into a signal using .tosignal() Let me know if this example helps solve your question

Currently there is not a way inside of Seeq formula to access a signal or condition's metadata for use in a formula. This comes up when users would like to do things like plot a special property that has been added to a signal from an external system such as OSIsoft Pi AF. There is a simple way to add these properties as scalars inside of Seeq DataLab however using the example notebook below. The key pieces are to make sure to include the all_properties=True flag in the spy.search() command and then to define your new signal names in your metadata dataframe Push Signal Metadata as Scalars.ipynb