LRP (ish)

There is something fishy with a chart in the right part close to the end. If you look at above CunobelinDC score distribution you would see that there is no corresponding red points for stronger opponents, while blue and grean are there. This is quite common theme for other bots as well.

Also have a look at this EvBot score distribution you would see the problem with normalizing, i.e. about 1/4 of the space in the right part of the chart has no points. Which is non optimal use of the chart space.

Is it still showing the problem? I don't see anything wrong right now. I had some issues with (I suspect) bad bytecode and versioning, but that should be fixed now.

As for the EvBot chart, that is because in meleerumble nobody gets higher than ~75%, so the top 25% is empty. Although I guess I could normalise to the top score, I'd rather have the charts consistent as better bots are released.

Aha, I see now why melee charts were somewhat off.

But I insist that I do not see red points for X>95% for CunobelinDC. Look at 5 the rightmost green points, I cannot locate red (APS) or blue for the same X values. It might be aliasing problem or may be points are just on top of each other.

I've changed it so they all use APS on the X axis, so it should be clearer now.

I like new charts better and they are easier to understand. Thanks.

They are some white space on left and right, but I think it is ok since presentation is clearer now.

There is amasing correlation between APS and Survival in roborumble scores :)

Would it be a good idea, to make survival difference green on bot comparison charts? This way color scheme matches the main chart.

Done.

Wow. I did not expect such quick fix. Thanks Skilgannon.

Now I would like to complain about this green color :) I personally think it is not very contrast on a white background.

I like our red and blue, but I think it would be better to replace currently light colored green with either much darker green or better yet something else, for example black.

I only speak for my own eyes, but I think our potentially color blinded participants will appreciate it as well.

Wow, sorry I missed these. The reason I use this green is because I just do a simple RGB 3-layer image, and set the different pixels manually. I would have to do a much more complex transform to get better colours. If you want to investigate my uber-messy code and provide a patch feel free =)

Hi Skilgannon,

I am not a plotting wizard but I plot enough in my life to make a fullish attempt to improve it a bit.

Though, it looks like the colors were chosen for the speed and not beauty, and it might be hard to have still fast yet beautiful output.

But I'll try to help. How can I look at the code?

Check here =)

Here is the suggested patch. Note that image array now created in uint8 RGB space, since resulting png image is in RGB space as well. As result it removes unnecessary image manipulation, after the array is prepared.

Beware, I was not able to fully test it since I am missing database and google modules. But it should work fine.

Note that colorAPSvsKNPBI is not used in this script but probably needed for another python script responsible for a given bot stats.

--- BotCompare.py	2014-09-15 15:40:19.000000000 -0400
+++ BotCompare.new.py	2014-11-26 22:28:50.000000000 -0500
@@ -266,28 +266,34 @@
                 
                 out.append("</td><td rowspan=\"7\">")
                 enemyScores = pickle.loads(zlib.decompress(rumble.ParticipantsScores))
+                # RGB color model
+                # Default colors
+                # colorSurvival = (0,255,0)
+                # colorAPS = (255,0,0)
+                # colorAPSvsKNPBI = (0,0,255)
+                # Colors suggested at 
+                # http://ksrowell.com/blog-visualizing-data/2012/02/02/optimal-colors-for-graphs/
+                colorSurvival = (62,150,81)
+                colorAPS = (204,37,41)
+                colorAPSvsKNPBI = (57,106,177)
                 size = 169
-                a = numpy.empty((size+1,size+1,4), dtype=numpy.float32)
+                a = numpy.empty((size+1,size+1,3), dtype=numpy.uint8)
                 a[...,(0,1,2)]=255
                 for cp in commonList:
                     eScore = enemyScores.get(cp.Name,None)
                     if eScore:
-                        a[max(0,min(size,size-int(round((cp.A_APS - cp.B_APS + 50)*0.01*size)))),
-                          int(round(eScore.APS*0.01*size)),(0)]=0
+                        x = int(round(eScore.APS*0.01*size))
+                        y = max(0,min(size,size-int(round((cp.A_APS - cp.B_APS + 50)*0.01*size))))
+                        a[x,y,(0,1,2)] = colorAPS
                         
-                        a[max(0,min(size,size-int(round((cp.A_Survival - cp.B_Survival + 50)*0.01*size)))),
-                          int(round(eScore.APS*0.01*size)),(1)]=0
+                        y = [max(0,min(size,size-int(round((cp.A_Survival - cp.B_Survival + 50)*0.01*size))))
+                        a[x,y,(0,1,2)] = colorSurvival
 #                        if eScore.ANPP > 0 and b.NPP >= 0:
  #                           a[size-int(round(b.NPP*0.01*size)),int(round(eScore.ANPP*0.01*size)),(0,1)]=0
                 
-                b = Image.fromarray(a.astype("uint8"), "CMYK")
-                c = cStringIO.StringIO()
-                b = b.convert("RGB")
-                a = numpy.array(b)
-                a[(a == (0,0,0)).all(axis=2)] = (255,255,255)
                 a[size - int(round(.5*size)),...] = 127
-                a
-                b = Image.fromarray(a,"RGB")
+                b = Image.fromarray(a.astype("uint8"),"RGB")
+                c = cStringIO.StringIO()
                 b.save(c,format="png")
                 d = c.getvalue()
                 c.close()

I'm very busy at the moment, but I'll take a look at this on the weekend.

No problem. I also made a pull request at the bitbucket to simplify import. This request is completely analogous to the presented here patch.

I've integrated your changes, with a few modifications of my own (just implementation details - averaging colours for multi-hit pixels). I also added it to the BotDetails page.

Skilgannon,

Thanks for taking the patch into the account.

It looks like you do some sort weighting for colors based on counts. But I am afraid my changes to the RGB color model are not very suitable for this task. Since the resulting color is hard to predict and decipher back to APS and Survival.

I would suggest a few things to avoid this:

• (easiest) let single count take it all, chose either APS or Survival
• (better in my opinion) make separate APS and Survival maps. The comparison table underneath is quite wide, we can easily fit 2 maps above. How to handle 3 maps in the bot details page is unclear for me.
• (alternatively) enlarge X-size of the map and use point size as count indicator

I would suggest to increase size of the map and points in any case. The current 169x169 image is painfully small on modern displays. May be we should convert to the vector SVG format supported by modern browsers?

Sorry to be such a pain. But I have one more thought. May be APS as X axis is not such a good choice. Since in meleerumble there is white spaces on left and right. No bots have APS above 70% and below 10%.

Would it be better to use rating? Or may be ANPP? Those take full scale.

I use APS because it is stable and always available. ANPP is sometimes not available (just after stabilising, before batches have run). I could use rating, but that I feel is too closely fit to which other bots are in the rumble at the time of viewing, and I would prefer the image to be more stable for long-term comparison.