Teddy

Pat, The only workaround I can think of is to return them with the output item. Here is a link to a post that returns the properties as part of condition. A similar thing could be done for a one time prediction by constructing a string scalar as the output and using it to build the model. Then you would only need to refer to the string scaler to get all your properties. Hope this helps. Also I will check if there are any feature requests for this and add you to them. Teddy

A connection to Bentley Nevada has been discussed in the past, but to my knowledge there are no production systems running with a connection to Bentley Nevada. It usually comes down to what type of data you are looking to pull from Bentley Nevada and does it make sense to use that data in your Seeq analysis. If you are interested in a Bentley Nevada connection, I would recommend contacting Seeq support or your point of contact to discuss in more detail. Regards, Teddy

In version R60 and up Seeq supports native notifications for SaaS customers. Below is a link to the detailed documentation. https://support.seeq.com/space/KB/2594111502/Notifications+on+Conditions

In version R60 and up Seeq supports native notifications for SaaS customers. Below is a link to the detailed documentation. https://support.seeq.com/space/KB/2594111502/Notifications+on+Conditions

I think this is what you're looking for or at least something very similar. The following formula will find the max value of a signal during each capsule in the condition and then keep the capsules whose Max values fall within the range of 48 and 54. $condition.setProperty('max of signal', $signal, maxValue()) .keep('max of signal', isbetween(48,54)) Regards, Teddy

MArgarida, If I understand your question correctly it sounds like you are trying to create a metric/scorecard metric with formula. Seeq doesn’t support the creation of metrics with formula. If this is what you are trying to do, I don’t think it will be possible. I would suggest opening a feature request and detailing what you are trying to do. If you are trying to do something else, can you provide a little bit more information on what your goal is. Link to support portal to submit feature request. You can send the feature request to the Analytics Help section. https://seeq.atlassian.net/servicedesk/customer/portal/3 Regards, Teddy

Ivan, If you would like to resample, I would recommend doing it in a standalone formula prior to the regression formula. The reason for this is that only formula outputs are cached. The intermediates are not cached, so it would not reduce the number of samples that the formula needs to look at since it is doing the resampling in the same formula. Resampling in the same formula would reduce the samples in the fitting but typically it is better to reduce samples pulled. Resampling the predictor variables would have some benefit. Seeq will apply the prediction output to every sample so it would reduce the number of total samples that the output will be applied to. I would also recommend, only using the necessary order of predictors. Since you are writing it as a formula you can select which variables you need to have higher orders and which ones can be linear. Regards, Teddy

Ivan, As you indicated the main concern is the fitting/refitting of the model. Depending on the scale I imagine this would take quite a bit of time. Any change to the inputs would force a refit. Also, if the inputs aren’t completely certain within the training window the model will look for new data and try a refit while the model is open. There are other events that could force a refit, like manual cache clearing, but that would be so infrequent I wouldn’t worry. Regards, Teddy

FYI: I think English(Australia) will give you the 12 hour format so you may need to use the United Kingdom one.

Kate, The date format is controlled by your web browser. In order to change it you will need to go to your browser’s settings and change it to a location that uses the format you desire. In google chrome this is the language setting. Another browser might be different. Screenshot of the Chrome Language Settings: Screenshot of the Seeq result: I hope this helps. Regards, Teddy

Maren, I recommend trying to avoid setting the problem up in a way that it depends on an initial value if you can. Initial values lead to excessive calculations because it will need to calculate from the initial value to your current window. If finding the instantaneous residence time and averaging that over an hour is an option, it would be much more performant even when including mass weighted averaging. If you still want to go down the initial value route you will want to look at the reduce() function in formula. Regards, Teddy

Can you explain in more detail how you are calculating residence time? It sounds like you are doing something more complicated than Volume/Flow.

Ayub, It looks like dash or jupyter-dash is creating/hosting a web server to view the data from. It will be difficult to implement this on a Datalab server because of all the network and containerization complexities you would need to navigate. As long as you have a Datalab license you can authenticate and use spy (Seeq Python) from any IDE. Since the spy library can be imported into any IDE, I suggest running this locally or creating a server to host it so others can access your work. Regards, Teddy

I ran some tests on R54 and everything worked as expected. I suggest opening a support ticket here (https://seeq.atlassian.net/servicedesk/customer/portal/3) so someone can take a closer look at what is going on. I would attach a link to this post in the ticket.

Are you creating new signals during your updating? If you are creating new signals you will need to create a new export from the export tab. I tested formula changes on an OData connection to excel and it worked fine for me. I don’t have a Power BI license to test with. What version are you on? I can run a test on the same version to check. Teddy