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 X-axis timescale behavior change

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KevinAndrewLipscomb Posted - 19 Dec 2017 : 15:10:14
I think my question belongs in QCChart2D land even though I'm noticing an issue as I use SPCTimeVariableControlChart objects.

It looks like there's been a behavior change between v1.7 and v3.0 of QCSPCChaertNet, and I'm trying to get back to the v1.7 behavior. Specifically, when I plot a single metric tied to the first day of each month, I was seeing the following timescale marks on the X-axis under v1.7:

(tick) (tick) 2016 (tick) (tick) ... (tick) 2017 (tick) (tick) ...

But using v3.0, the marks I get show up as:

2015 (tick) D (tick) F M A M J J A S O N D (tick) F M A M ...

With v1.7, a full-height vertical index line appeared above the year numbers only. With v3.0, these lines appear above the year number, every tick, and every month initial.

The v1.7 behavior is a lot less cluttered and is what I'd like to get back to. How should I go about doing that?
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quinncurtis Posted - 19 Dec 2017 : 16:10:07
Sorry, but the new QCSPCChart revision has drastically changed the tick mark labeling and positioning for the time axis - which now uses an EventAxis, not a TimeAxis. Because users hated the fact that in the earlier versions (up to Revision 2.3) the time axis did not actually label the time stamp of the sample interval, and rather just labeled the linear time values which were unrelated to the sample interval. The end result was that we always pushed users into using the Batch SPC charts, where the tick mark was always placed on a sample interval, evenly spaced on the axis, no matter the time stamp. Because of this, our large OEM customers always used the Batch SPC charts in all cases. You seem to be one of the few who wanted it the old way, which of course is to be expected. But there is no going back to old linear time axis, it is gone from the software. We will look into a way to remove the month letters from the tick marks (all sample intervals are major tick marks), which may be all that you need. But if you use the zooming feature they may come back, because that is all handled using our auto-scaling routines, which will revert back to the default scaling when the range of the time axis is changed.

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