/trunk/Python/lena_line.py
 
 
 

 
/trunk/Python/lena_line.py   r18
 
 

 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 

 

 
 
 
 
 
 
 
1
 
 
 
from sga import sgaGenotype
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
2
 
 
 
from PIL import Image, ImageDraw
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
3
 
 
 

 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
4
 
 
 
def ConvertToImage(gen,n):
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
5
 
 
 
	im = Image.new("L",(200,200),255)
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
6
 
 
 
	draw = ImageDraw.Draw(im)
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
7
 
 
 
	for gr in gen.Lgroups:
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
8
 
 
 
		draw.line([gr[0].Genes[n], \
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
9
 
 
 
		           gr[1].Genes[n], \
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
10
 
 
 
		           gr[0].Genes[n] + gr[2].Genes[n], \
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
11
 
 
 
		           gr[1].Genes[n] + gr[3].Genes[n]], fill = gr[4].Genes[n], width = gr[5].Genes[n] )
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
12
 
 
 
	return im
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
13
 
 
 

 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
14
 
 
 
def MeasureColorDifference(gen,n):
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
15
 
 
 
		global data
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
16
 
 
 
		dif = 0
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
17
 
 
 
		for co,cg in zip(data,list(ConvertToImage(gen,n).getdata())):
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
18
 
 
 
			dif+=abs(co-cg)
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
19
 
 
 
		return dif
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
20
 
 
 

 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
21
 
 
 
def BetterFoundNotify(gen, it):
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
22
 
 
 
	global cycles
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
23
 
 
 
	print "Iteration",it,"of",cycles,';','Fitness',gen.Fitness[2]
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
24
 
 
 
	ConvertToImage(gen,2).save('/tmp/0000'+str(it)+'.png')
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
25
 
 
 

 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
26
 
 
 
data = list(Image.open("LenaG.png").getdata()) # 200x200 pixels Lena image
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
27
 
 
 
cycles = 100000  # How much iterations do we try
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
28
 
 
 
dxy = 20
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
29
 
 
 

 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
30
 
 
 
gen = sgaGenotype([range(dxy,200-dxy),range(dxy,200-dxy) # line start x,y \
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
31
 
 
 
		,range(-dxy,dxy+1),range(-dxy,dxy+1) # line dx,dy \
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
32
 
 
 
		, [x for x in range(220) if x%5 == 0] # line grayscale color\
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
33
 
 
 
		, range(1,8) ] # line width in pixels\
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
34
 
 
 
		, 200 # Number of lines\
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
35
 
 
 
		, MeasureColorDifference # Fitness function, for determining picture quality\
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
36
 
 
 
		, BetterFoundNotify # Notify function, informs when better solution is found\
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
37
 
 
 
		, Minimize = True) # Do we need to minimize or maximize fitness function
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
38
 
 
 
gen.Evolve(cycles)
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
39
 
 
 
print "Done. Now you can go to drink coffee."