Rupesh Parbhoo

In order to compare the actual value of the signal before and after some event, you must first identify the event. Method 1: Running Delta. Note: an approach using the running delta function can be preferred to the derivative function (Method 2) when step changes are present as the derivative is infinite during these steps. Using the derivative function works best if the signal is first cleansed/filtered and the interpolation method changed to linear. Use Seeq Formula to create a new signal that is the running delta of the original signal. Use the syntax: $OrigianlSignal.runningdelta() Use the “Search Documentation” bar on the right side of the Formula window to learn more about the running delta function and syntax Once the new running delta signal has been created, do a value search on when it exceeds some threshold to identify the time periods over which you would like to know the start and end values. Note: if the step changes are occurring in both the increasing and decreasing directions, you can still identify all events by using Seeq Formula to take the absolute value of your running delta function ($runningDeltaSignal.abs()) and applying the value search tool to the absolute value signal. The time periods identified using value search can be further manipulated to yield exactly the time periods that you are interested in using Seeq formula and the grow(), shrink(), and/or move() functions. Once the events during which the step change occurs have been identified, you can calculate statistics on them using the Signal from Condition tool. The inputs to the tool will be your original signal and the new condition that you’ve created to identify the events. A few statistics that you may be interested in: Delta: the end value minus the start value of the signal. This would give you the value drop (or gain) during one of these events. Value at start: this will grab the value of the original signal at the start of the event Value at end: this will grab the value of the original signal at the end of the event Method 2: Derivative. Best approach for most rate of change problems, excluding step changes. Use Low Pass Filter tool or Seeq Formula agileFilter() function to cleanse the original signal to remove typical noise from signal. Use Seeq Formula to create a new signal that is the derivative of the cleansed signal. Use the syntax: $CleansedSignal.derivative() Use the “Search Documentation” bar on the right side of the Formula window to learn more about the derivative() function and syntax Once the new derivative signal has been created, do a value search on when it exceeds some threshold to identify the time periods over which you would like to know the start and end values. Note: if the value changes are occurring in both the increasing and decreasing directions, you can still identify all events by using Seeq Formula to take the absolute value of your derivative function ($derivativeSignal.abs()) and applying the value search tool to the absolute value signal. The time periods identified using value search can be further manipulated to yield exactly the time periods that you are interested in using Seeq formula and the grow(), shrink(), and/or move() functions. Once the events during which the value change occurs have been identified, you can calculate statistics on them using the Signal from Condition tool. The inputs to the tool will be your original signal and the new condition that you’ve created to identify the events. A few statistics that you may be interested in: Delta: the end value minus the start value of the signal. This would give you the value drop (or gain) during one of these events. Value at start: this will grab the value of the original signal at the start of the event Value at end: this will grab the value of the original signal at the end of the event

Hello Baishun, You are correct. When using the Histogram Tool with the aggregation type "time," the timezone of UTC is used. One way to ensure the aggregation time fits your time zone is to create a new condition with your appropriate time zone from Tools > Identify > Periodic Condition. Using this new condition, change the aggregation type in your histogram to Condition (instead of time). Let me know if this works for you. Best Regards, Rupesh

Thanks Tyler, Can you check one more thing. I think you mentioned it above, that the time range for the organizer topic and workbench are different. I am assuming you will see that phantom capsule when you update your current workbench to near now (currently its at the end of March). The way to get rid of this uncertain condition is you can take your current condition ($condition) and apply the inside(past()) function to it. This should remove that last uncertain capsule. $condition.inside(past())

Hi Tyler, I needed some clarification on your request. If the capsule is in progress, do you prefer that it doesn't show up at all or that it shows up as a normal capsule. The issue you are dealing with is called uncertainty. Uncertain data can’t be cached, so these regions of uncertainty require the computation to be repeated, showing that open bar. There are various causes of uncertainty in a condition or signal. Are you able to share the formula for the blowdown event condition?

Hello Bao, When upgrading to r60+ you will need to use spy.upgrade() instead of the pip install seeq commands. Please let me know if this works for you. spy.upgrade() Regards, Rupesh