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firefly_fcm.py
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import sys
import copy
import math
import numpy as np
from PIL import Image
from collections import namedtuple
from operator import attrgetter
import random
import matplotlib.pyplot as plt
firefly = namedtuple("firefly", "error intensity")
def ffa(numfireflies):
numclusters=int(input("Enter no. of clusters: "))
maxepochs=50
ming=0.0
maxg=255
b0=0.0
g=1.0
a=0.2
displayinterval=maxepochs/10
besterror=sys.maxsize
swarm=[]
gs=np.empty((0))
for i in range(numfireflies):
tmp = np.empty((0))
for j in range(numclusters):
g=(maxg-ming)*random.uniform(0,1)+ming
tmp=np.append(tmp,g)
swarm.append(firefly(0.0,0.0))
if i==0:
gs=tmp
else:
gs=np.vstack([gs,tmp])
err=ffa_clustering(gs,numclusters,numfireflies)
print(gs)
print(err)
for i in range(numfireflies):
swarm[i]=swarm[i]._replace(error=err[i])
swarm[i]=swarm[i]._replace(intensity=1/(swarm[i].error+1))
if swarm[i].error<besterror:
besterror=swarm[i].error
bestposition=np.copy(gs[i])
epoch=0
while epoch<maxepochs:
if epoch%displayinterval==0 and epoch<maxepochs:
print("epoch = ",epoch," error = ",besterror)
key1 = 0
key2 = 0
key3 = 0
for i in range(1, numfireflies):
key1 = swarm[i].error
key2 = swarm[i].intensity
key3 = np.copy(gs[i])
j = i - 1
while j >= 0 and swarm[j].error > key1:
swarm[j + 1] = swarm[j + 1]._replace(error=swarm[j].error)
swarm[j + 1] = swarm[j + 1]._replace(intensity=swarm[j].intensity)
gs[j + 1][:] = gs[j][:]
j = j - 1
swarm[j + 1] = swarm[j + 1]._replace(error=key1)
swarm[j + 1] = swarm[j + 1]._replace(intensity=key2)
gs[j + 1][:] = key3[:]
for i in range(numfireflies):
for j in range(1,numclusters):
key1=gs[i][j]
k=j-1
while k>=0 and gs[i][k]>key1:
gs[i][k+1]=gs[i][k]
k=k-1
gs[i][k+1]=key1
print(gs)
if swarm[0].error<besterror:
besterror=swarm[0].error
bestposition=gs[0]
for i in range(numfireflies):
key1 = swarm[i].error
key2 = swarm[i].intensity
key3 = np.copy(gs[i])
if i==0:
for k in range(numclusters):
gs[i][k]=gs[i][k]+random.uniform(0,1)
else:
#r=np.sqrt(((gs[i]-gs[j])**2))
#beta=b0*math.exp(-g*np.sum(r)*np.sum(r))
beta=0.01
gs[i]=gs[i]+beta*(gs[0]-gs[i])
gs[i]=gs[i]+a*(random.uniform(0,1)-0.5)
for k in range(numclusters):
if gs[i][k]<ming or gs[i][k]>maxg:
gs[i][k]=(maxg-ming)*random.uniform(0,1)+ming
err = ffa_clustering(gs,numclusters,numfireflies)
swarm[i] = swarm[i]._replace(error=err[i])
swarm[i] = swarm[i]._replace(intensity=1 / (swarm[i].error + 1))
if key1<swarm[i].error:
swarm[i] = swarm[i]._replace(error=key1)
swarm[i] = swarm[i]._replace(intensity=key2)
gs[i][:] = key3[:]
for i in range(numfireflies):
print(swarm[i].error)
epoch=epoch+1
print(epoch)
key1 = 0
key2 = 0
key3 = 0
for i in range(1, numfireflies):
key1 = swarm[i].error
key2 = swarm[i].intensity
key3 = gs[i]
j = i - 1
while j >= 0 and swarm[j].error > key1:
swarm[j + 1] = swarm[j + 1]._replace(error=swarm[j].error)
swarm[j + 1] = swarm[j + 1]._replace(intensity=swarm[j].intensity)
gs[j + 1] = gs[j]
j = j - 1
swarm[j + 1] = swarm[j + 1]._replace(error=key1)
swarm[j + 1] = swarm[j + 1]._replace(intensity=key2)
gs[j + 1] = key3
for i in range(numfireflies):
for j in range(1,numclusters):
key1 = gs[i][j]
k = j - 1
while k >= 0 and gs[i][k] > key1:
gs[i][k + 1] = gs[i][k]
k = k - 1
gs[i][k + 1] = key1
print(gs)
if swarm[0].error < besterror:
besterror = swarm[0].error
bestposition = gs[0]
clustering(bestposition,numclusters)
return
def clustering(centroids,num_centroids):
num_data=height*width
cond=0
e=0.01
loop=0
m=2
while cond==0:
loop=loop+1
v = np.zeros(num_centroids)
tmp=np.zeros((num_centroids,num_data))
for i in range(num_centroids):
distki = abs(pixels - centroids[i])
for j in range(num_centroids):
distkj = abs(pixels - centroids[j])
tmp[i]=tmp[i]+((distki/distkj)**(2/(m-1)))
tmp[i]=1/tmp[i]
for i in range(num_centroids):
num=np.sum((tmp[i]**m)*pixels)
den=np.sum(tmp[i]**m)
v[i]=num/den
if np.average(abs(centroids-v))<e or loop==150:
print("Final centroids are : ",v)
cond=cond+1
else:
print(v)
centroids=np.copy(v)
db(v, num_centroids)
d(v, num_centroids)
print(loop)
draw_img(v, num_centroids)
return
def db(centroids,num_centroids):
num_data = height * width
m=2
max_c=np.zeros(num_centroids)
tmp = np.zeros((num_centroids,num_data))
for i in range(num_centroids):
distki = abs(pixels - centroids[i])
for j in range(num_centroids):
distkj = abs(pixels - centroids[j])
tmp[i] = tmp[i] + ((distki / distkj) ** (2 / (m - 1)))
tmp[i] = 1 / tmp[i]
for i in range(num_centroids):
for j in range(num_centroids):
if i!=j:
dist=abs(centroids[i]-centroids[j])
i_spr = np.sum((tmp[i]**m)*((pixels-centroids[i])**2))/np.sum(tmp[i]**m)
j_spr = np.sum((tmp[j]**m)*((pixels-centroids[j])**2))/np.sum(tmp[j]**m)
final=(i_spr+j_spr)/dist
if final>max_c[i]:
max_c[i]=final
db_val=np.sum(max_c)/num_centroids
print("DB index value is : ",db_val)
return
def d(centroids,num_centroids):
num_data=height*width
m=2
final=0
tmp = np.zeros((num_centroids, num_data))
for i in range(num_centroids):
distki = abs(pixels - centroids[i])
for j in range(num_centroids):
distkj = abs(pixels - centroids[j])
tmp[i] = tmp[i] + ((distki / distkj) ** (2 / (m - 1)))
tmp[i] = 1 / tmp[i]
for i in range(num_centroids):
i_spr = np.sum((tmp[i] ** m) * ((pixels - centroids[i]) ** 2)) / np.sum(tmp[i] ** m)
if i_spr>final:
final=i_spr
i_spr=final
d_val=sys.maxsize
for i in range(num_centroids):
for j in range(num_centroids):
if i!=j:
dist=abs(centroids[i]-centroids[j])
final=dist/i_spr
if final<d_val:
d_val=final
print("Dunn index value is : ",d_val)
return
def draw_img(centroids,num_centroids):
num_data = height * width
m = 2
tmp = np.zeros((num_centroids, num_data))
for i in range(num_centroids):
distki = abs(pixels - centroids[i])
for j in range(num_centroids):
distkj = abs(pixels - centroids[j])
tmp[i] = tmp[i] + ((distki / distkj) ** (2 / (m - 1)))
tmp[i] = 1 / tmp[i]
img=np.zeros((num_centroids,height,width))
for k in range(num_centroids):
z=0
for i in range(height):
for j in range(width):
img[k][i][j]=tmp[k][z]
z=z+1
fig = plt.figure()
for i in range(num_centroids):
ax = fig.add_subplot(2,2,i+1)
ax.imshow(img[i])
plt.show()
return
def ffa_clustering(centroids,numclusters,num_fireflies):
num_data=height*width
m=2
mem=np.zeros((num_fireflies,numclusters,num_data))
for i in range(num_fireflies):
tmp1=np.zeros(num_data)
for k in range(numclusters):
distki=abs(pixels-centroids[i][k])
tmp2=np.zeros(num_data)
for j in range(numclusters):
distkj=abs(pixels-centroids[i][j])
tmp2=tmp2+((distki/distkj)**(2/(m-1)))
tmp2=1/tmp2
if k==0:
tmp1=tmp2
else:
tmp1=np.vstack([tmp1,tmp2])
mem[i]=tmp1
err=[]
for i in range(num_fireflies):
add=0
for j in range(numclusters):
dist=(pixels-centroids[i][j])**2
tmp=(mem[i][j]**m)*dist
add=add+np.sum(tmp)
err.append(add)
return err
im=Image.open("C:/Users/User/Desktop/brain.tif")
pixels = list(im.getdata())
width,height=im.size
#for i in range(len(pixels)):
# pixels[i]=int(round(sum(pixels[i]) / float(len(pixels[i]))))
pixels=np.array(pixels)
ffa(15)