Re: [Matplotlib-users] Eye patterns (Heat plot?)

On 1/23/2012 1:55 PM, Russ Dill wrote:
> On Mon, Jan 23, 2012 at 11:17 AM, Stan West<sta...@nr...>  wrote:
>>> From: Russ Dill [mailto:rus...@gm...]
>>> Sent: Saturday, January 21, 2012 16:31
>>>
>>> I'm using matplotlib from pylab to generate eye patterns for signal
>>> simulations.
>> ...
>>
>>> Is there any way within matplotlib to do that right now?
>> One way combines Numpy's histogram2d and matplotlib's imshow, as in the
>> example in the histogram2d docs [1].  The example's x array should become all
>> of the time samples in your traces, strung together in one dimension; the y
>> array, the corresponding voltage samples.
>>
> I'll try it out and see what I get, but I don't think it will work so
> well. The problem is that while the data is made up of x/y samples, it
> actually represents a line. The samples should be evenly distributed
> not along the x or y axis, but along the length of the line. I feel
> like I'll need a line drawing algorithm.
>
> (For example, if samples are evenly distributed along the x axis, a 89
> degree line is highly under-represented, but a 1 degree line is highly
> over-represented. The number of samples should be sqrt(dx^2 + dy^2),
> but with evenly spaced x samples, its just dx.

I don't know of a way to directly produce the LeCroy heatmap in Python, 
so here's my idea for a hack:
*Each sample point you have from the trace represents a point in XY 
coordinates.
*Similarly, the plot area is filled with regularly spaced XY coordinates.
*Every trace sample will fall within a square bounding box with four points.
*Each plot area point gets a membership value, based on distance between 
centers of the sample point and the plot area point.
*To construct the heat diagram, sum the membership values of all sample 
points for all traces.
*Display it with a contour plot, but without the isovalue lines.

-Ethan