if (libFBCAGen.compareFPs(fpCur.fP,fpNew.fP) == 1): #If similar, add to the list
temp.append(fpNew)
ignoreList.append(idx2) #In the future, ignore the similar one
temp.append(fpCur) #Add this one too
ignoreList.append(idx) #ignore this one in the future
behaviours.append(temp) #Add this behaviour class to the behaviours list
print(f"Sorted FPs for ({n},{m})") #Makes it easier on the eyes
morphRecord=open(f"{quantifer}","w") # Records the behaviours in a file
morphRecord.write(f"All behaviours in morph of sMs{sMs[n]}sMs{sMs[m]} \n")
morphRecord.write(f"Behaviours go from black -> red -> orange -> yellow -> white \n")
for behaviour in behaviours:
morphRecord.write(f"Iso-behavioural grain similar to sM with lambda = {behaviour[0].lambd} \n")
for behaviour in behaviours:
if (libFBCAGen.useImages == 1):
myEyes=str(round(behaviour[0].lambd,5))
libFBCAGen.genIm(behaviour[0].fPrint,libFBCAGen.numOfGens,d,f"{quantifer} {myEyes}")
print(f"Generating Image for ({n},{m})")
#Probably should comment this below
imageColourStep=(255*3)/(len(behaviours))
im= Image.new('RGB', ((morphRes+1),imageHeight), 1)
for idx,behaviour in enumerate(behaviours):
colourVal=int(idx*imageColourStep)
if (colourVal-255<0):
r = colourVal
g=0
b=0
else:
r=255
colourVal-=255
if (colourVal-255<0):
g = colourVal
float(protoScoreMatrix[5][0:(len(protoScoreMatrix[5]) -
1)]))
scoreMatrix.append(
float(protoScoreMatrix[6][0:(len(protoScoreMatrix[6]) -
1)]))
scoreMatrix.append(
float(protoScoreMatrix[7][0:(len(protoScoreMatrix[7]) -
2)]))
#Ex: ['12.592848008753737', '-12.192848008754211', '-7.0071519912456495', '6.6071519912461225']
#Generate the FBCA
CAMap = []
CAMap = libFBCAGen.copyOver(CAMapInit)
gif = []
for n in range(numOfGens):
if (useImages == 1):
gif.append(
libFBCAGen.genIm(CAMap, n, d,
behaviourNum[1][:-1]))
CAMap = libFBCAGen.updateMap(CAMap, scoreMatrix)
if (useImages == 1):
gif.append(
libFBCAGen.genIm(CAMap, n, d, behaviourNum[1][:-1]))
print("Finished " + str(behaviourNum[1][:-1]))
if (useImages == 1):
gif[0].save(d + str(behaviourNum[1][:-1]) + '.gif',
save_all=True,
append_images=gif[1:],
optimize=False,
duration=100,
loop=0)
print("Finished " + str(fileName))
import FBCAConsts import libFBCAGen exFBCA = FBCAConsts.Fbca() exFBCA.levelMap = libFBCAGen.initCA(exFBCA) libFBCAGen.genIm(exFBCA, quantifer="/genIm")
import FBCAConsts
import libFBCAGen
exFBCA = FBCAConsts.Fbca()
exFBCA.scoreMatrix = [0,0.5,0.2,0.6]
exFBCA.levelMap = libFBCAGen.initCA(exFBCA)
totalNumOfGens = 5
for n in range(totalNumOfGens):
libFBCAGen.genIm(exFBCA,gen = n, quantifer = "/updateMap")
exFBCA.levelMap = libFBCAGen.updateMap(exFBCA)