Bug 87149

Summary:	Data mode does not work well for equations or curves with widely spaced x values
Product:	[Applications] kst	Reporter:	Rick Chern <rchern>
Component:	general	Assignee:	kst
Status:	RESOLVED FIXED
Severity:	normal
Priority:	NOR
Version First Reported In:	1.x
Target Milestone:	---
Platform:	Compiled Sources
OS:	Linux
Latest Commit:		Version Fixed/Implemented In:
Sentry Crash Report:

Description Rick Chern 2004-08-13 20:22:11 UTC

Version:           0.99-devel (using KDE KDE 3.2.1)
Installed from:    Compiled From Sources
Compiler:          gcc (GCC) 3.3.2 20031022  
OS:                Linux

The red dot jumps around strangely when in data mode and over an equation with widely spaced x values

How to reproduce 
- start kst
- create a vector
- create a new equation, and for x axis generate 100 samples from 0 to 10.  Plot the equation
- enter data mode
- move cursor over the equation.  
Note that the red dot keeps on jumping to the top left corner of the plot.

Expected behaviour:
Red dot more closely follows the equation.

Comment 1 Rick Chern 2004-08-13 20:23:14 UTC

Actually, not top left, but the first point on the equation.

Comment 2 Andrew Walker 2004-08-14 00:03:28 UTC

I have a fix for this but will check it in later, when all the 0.99 stuff is done.

Comment 3 Netterfield 2004-08-14 02:29:29 UTC

I think this is pretty important.  It wrecks data mode w/ equations.  How 
invasive is the fix?  

On August 13, 2004 06:03 pm, Andrew Walker wrote:
> ------- You are receiving this mail because: -------
> You are the assignee for the bug, or are watching the assignee.
>
> http://bugs.kde.org/show_bug.cgi?id=87149
>
>
>
>
> ------- Additional Comments From arwalker sumusltd com  2004-08-14 00:03
> ------- I have a fix for this but will check it in later, when all the 0.99
> stuff is done. _______________________________________________
> Kst mailing list
> Kst@kde.org
> https://mail.kde.org/mailman/listinfo/kst

Comment 4 Andrew Walker 2004-08-16 17:42:07 UTC

Fix problem with highlighting nearest data point. This algorithm was working (barely) for increasing x values, but would typically fail to find the nearest point when the x values were not increasing.