Each outlet is a separate device in both Kasa and Sense-land. My only advice is that there isn’t that great an ROI to to replace an outlet strip connected to an HS110 with an HS300 if you have mostly networking stuff on the strip. All the networking equipment (router/switch/access point/base station/bridges) have very flat power utilization. Better to treat them all as one “virtual device”.
My only comment is that I would put the less variable ones on the bottom, e.g. always on. And then the most variable ones on top. That way the plot would be easier to read, now it seems that the red is very variable, but it is pretty constant really.
So you (or Sense) could compute the Std Dev of all the points in time for each of them, and calculate the relative std dev (Std Dev / Mean) and stack them with the lowest RSD at the bottom and then by increasing RSD. Except always on probably should always be at the very bottom.
(Not asking what you do this with your plot, though I’d surely be curious to see it if you did …
The script I posted, runs in the R language and environment, all free and downloadable. It takes in one or more Sense yearly downloads with 1 hour resolution. R is an open-source statistical language that is taught in virtually all non-comp-sci focused data science courses today.
R is something new to me and I’m just getting started trying to learn a little. Where I have my phone all the time and not a computer, I got the app from the Apple store.
Not sure exactly what I’ll be able to do from the phone just yet but the highlight of the description was the ability to learn from the app.
Looks like the App is a fairly full-featured version of R with all the requisite packages. But man, trying to code via a tiny touch screen or view graphical output is going to be challenging. Still useful for learning.
Python (another scripting language) has a similar iPhone app. @kevin1 is correct that programming on a touch screen is difficult/tedious, but if I had a script already made, running it in the app was pretty straight forward. @samwooly1 keep us updated if you get it set up and working in this app… I may try it out if you have some success.
Quickly tried to port my script to iPhone/iPad R Compiler app. The first issue that I bumped up against is that file IO is very different in iOS-land (suspect the same for Android). That means that some of the nice R packages that make it much easier to parse and input .CSV files don’t really work. There also seem to be a capacity limitation of 128kB when I try to bring files in via other routes. Will invest a little more time playing around.
I don’t use R but I have used similar programs (Igor in particular) extensively, and I teach an introductory class about programming every year to our graduate students (who mostly have never programmed). In my experience trying to learn such a system on a phone is not a viable option. I think those phone apps are for experts that already know R very well and want to be able to process some data while away from their computers. But for learning from scratch, I VERY strongly encourage you to try to learn in a computer. It is hard enough already
Finally got the code to run on my iPad with the R Compiler App. But it took a lot of changes.
Due to the 128K input file limit, I had to move to a daily rather than hourly download from Sense, plus I had to seriously reduce the file size even for Jan-April by removing 70% of my devices (only kept the top 12 or so)
Had to give up on reading the data file in directly and do as the coder of this app recommends - read the data file into the In (stdin), then read.csv (in the code) from “stdin”. Typical R offers much more graceful access to data.
And forget about debugging on the iPhone/iPad - one error and the compiler craps out giving a cryptic message, with no indication of which line of code caused it.
The combination of code and datafile below should work on iPad/iPhone if you can get everything into the right place on your device.
@RyanAtSense I’ve seen requests for this feature in a number of posts, but, it most clearly described here. This is an incredibly valuable visualization for tracking down energy use. I am a green building consultant, and, versions of this graph are the baseline tools we use to explain loads to clients and target energy conservation measures. It is especially useful for behavioral ECMs. The bubbles are cute, though, I’m afraid, not actually all that useful. It seems to me this is a tiny bit of coding that would have a large impact on the user experience.
I really want this too. I would love to be able to use this to help identify some appliances, and to see what’s actually happening in the moment. On the web interface this is possible to do without too much effort and I use the web interface a lot more than the mobile interface.
Is anyone at Sense actually looking at this feature?