scaler Value Removal

[Jitesh Vachheta]

Hi All,

I've got few Scaler values in my data-set (E.g High,On,OFF) , I have convert all of them into Capsule by toCapsule() Function.

Now wanted to remove only those capsules which are having "OFF" Status.

Regards,

Jitesh Vachheta

Edited July 8, 2019 by Jitesh Vachheta
For Missing Tag

[Thorsten Vogt]

Hi Jitesh,

you can achieve this by filtering the values with the filter() function:

$stage.toCapsules().filter($x -> $x.getProperty("Value") != "OFF")

You should think of using toCondition() instead of using toCapsules(), as toCapsules() generates a capsule for each interval between recorded points even if the value stays the same. You can see this in the Capsules window of your screenshot. By using toCondition() you will get only one capsule per change of value:

$stage.toCondition()

If you want to filter the results of toCondition() you have to specify a maximum duration for the capsules before using filter():

$stage.toCondition().setMaximumDuration(1wk).filter($x -> $x.getProperty("Value") != "OFF")

Regards,

Thorsten

 

 

[Danilo]

Hello Jitesh, 

Another option to filter the OFF condition would be to create a Value Search for when your compressor is OFF, then create a composite condition between the OFF condition and the Compressor Stages Conditions to only output when your compressor is on Stage 1, 2 or in Transition (You can achieve that by using the outside logic). 

 

Use this new condition as the input into your histogram. 

 

 

Finally, I agree with @Thorsten Vogt suggestion to use tocondition() instead tocapsules(). 

Hope this helps.

Danilo

 

 

[Allison Buenemann]

Another possible method is to first cleanse the compressor stage signal to remove values equal to 'OFF' and then apply the toCondition() function. This can be done in one step using formula: 

$CompressorStage.remove(isEqualTo('OFF')).toCondition()

 

[Ben Johnson]

The subtlety in the last option of filtering by sample values rather than capsule properties is that the maximum interpolation of the signal may span over the removed samples, resulting in extra time for the adjacent states.