

I have a range of values (voltage) over time (thousands of minutes, one value per minute). I am trying to chart these. Determining the length of my Y axis is quite a problem for me. If I take a minimum and maximum, and use that as the axis height, one or two zero values result in all the others being scrunched up at the top of the chart. If I remove zeroes, it looks much better, and for a chart, they aren't very important, I'll give all real values in a tabular report.
What I would like to do is determine the average height of the band of data points, sort of the space between the moving average of the low points and that of the heigh points. I figure to do that, I would need a median series, so I could determine a smoothed series of points above and below median, and make my Y axis 's' higher and 's' lower than those.
How do people normally do this?






Yeah, a but much for a simple charting app. Why a low pass, by the way?






I would post a question in the Algorithms forum here on CodeProject.
« I had therefore to remove knowledge, in order to make room for belief » Immanuel Kant





Can you exclude the zeroes as 'outofstatistic' or are they just 'the interesting pieces of data in the data set'?
THESE PEOPLE REALLY BOTHER ME!! How can they know what you should do without knowing what you want done?!?!
 C++ FQA Lite





It gets quite sweet when I exclude the zeroes. The chart then spreads across the Y axis nicely.





I see. But what is the physical reason of such zeroes (e.g. spurious measure values, ...) ?
THESE PEOPLE REALLY BOTHER ME!! How can they know what you should do without knowing what you want done?!?!
 C++ FQA Lite





Maybe that, maybe power outages. We get zero volts in the house quite frequently.






Looks like that project has been abandoned for some time.
The difficult we do right away...
...the impossible takes slightly longer.






Doesn't look like it does WPF though. OxyPlot also provides source, and operates on most .NET platforms.





what are you using to do the charting..?





OxyPlot. It's really quite good looking at their examples,but documentation is dismal.





Neat. took a look, but did see any way to implement the low pass filter idea....you could implement outside the livrary by averaging the previous 10 readings (110) or whatever value you like....the greater, the smoother values to average, then 211 etc.
I had a several day temperature test that had the occasional dropout/communication error that resulted in a similar waveform, everything scrunched at the top and spikes to 0. In that volume of air, there is no way it could spike like that, so it was a realistic solution....if your voltages are similar it might be a solution...or it could mask a real problem.....
Ken





Use either a Venn diagram, a pie chart, or a swimlanes chart, because those three are, without a doubt, the most incredibly useful and versatile charts that have ever been invented and will ever be invented.
I wanna be a eunuchs developer! Pass me a bread knife!





What you might want to do is outlyer detection, and just encode those results with some kind of symbol on the chart like a red line or something like that. Or, as others have said, just drop them and leave them as gaps.
Also, you can compute the median and standard deviation for your series, and then just plot everything within a few standard deviations of the median, which should be pretty close to the same thing.





How do I calculate the median. That would be a straight line  I want a 'median' between lows and highs that moves up and down with the lows and highs. I suppose I could do it point for point and calculate a median curve.





Ok, that gets into how you display the data. For a single static graph, I'd do it for the entire graph. That would give the bounds for the entire image.
If I was calculating a rolling average, I'd plot that as a curve overlay on top of the existing data. Check out various stock charts for that kind of visualization.
To calculate a rolling average, you just assign a window to each point, for example the last 30 data points and calculate the statistics on that window. The trick is really to use a window that makes sense for the underlying data.





By a window, you mean calculate the average low for 30 points, the same for high, and the mean of those is one point in your running central mean curve?





Also, if the y scale varies across the width of the graph according to the data, that is going to be very difficult to interpret, as you will be "straightening" out the data and none of the variation will be absolute.
Sometimes it's just easier to us a log scale for wildly varying data.





It's not at all widely varying. It's mains voltage over the day, and most samples vary by7 a few volts on 240V. It's juts a very few funny points that I think I will just ignore. You can't really depend ona graph as an accurate source of data, and I have a report of all the exact values.





Personally I would start in Excel  just to be able to play easily with various stats functions and see the result easily.
To determine your Y bounds:
Since we are looking at mains voltage, the maximum is of interest, so your Y max should be based on the maximum of your data.
Take the average M.
Calculate the standard deviation s.
In Excel take M  Ns for the lower bound  play with N to find a reasonable value. I suspect that 3 will probably work.
Now extract all those points below the lower bound and put them aside for later.
Now take the minimum of the remaining points round it to the nearest 5, 10 etc. based on the final range that you use.
Round the maximum in the same way.
(Note: depending on the measuring equipment you might get spurious high values too, you can do the same with the maximum bound if you want, but might need a different value for N)
This should give you the plot that you want.
Now, those pesky low values....
These should figure as points along the bottom of the graph, downward pointing arrows would be nice, since we need to be scientifically correct and show that the data has been "massaged".
Set their value to Ymin plus 7% of the Y range for example.
Hope this helps





Since the zero readings are anomalies, then I would exclude them from the chart data (thereby cleaning up the chart display), and keep a separate record of the zero readings viewable in a table with time of reading.
That way you get a clean chart & a separate table of anomalous values if you need to look at them. Or you could chart the zero readings in another way  number of zero readings per hour against time perhaps?




