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BA8C.py
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BA8C.py
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#!/usr/bin/env python
# Copyright (C) 2017 Greenweaves Software Pty Ltd
# This is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This software is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License
# along with GNU Emacs. If not, see <http://www.gnu.org/licenses/>
def trivial_centres(k,m,data):
return [data[i] for i in range(k)]
def distance(p1,p2,m):
return sum((p1[i]-p2[i])**2 for i in range (m))
def kmeans(k,m,data,centres=trivial_centres):
centroids=centres(k,m,data)
step_size=float("inf")
while step_size>0:
new_centroids=step(k,m,data,centroids)
step_size=sum([distance(new_centroids[i],centroids[i],m) for i in range(k)] )
centroids=new_centroids[:]
return centroids
def step(k,m,data,centres):
def nearest(p):
index=-1
best=float('inf')
for i in range(k):
d1=distance(p,centres[i],m)
if d1<best:
index=i
best=d1
return index
def centroid(i,indices):
#print ('centroid', i, indices)
count=0
point=[0 for j in range(m)]
for j in range(len(data)):
if indices[j]==i:
count+=1
for l in range(m):
point[l]+=data[j][l]
return [p/max(count,1) for p in point]
indices = [nearest(p) for p in data]
return [centroid(i,indices) for i in range(k)]
if __name__=='__main__':
m = -1
k = -1
points=[]
with open (r'C:\Users\Weka\Downloads\rosalind_ba8c.txt') as f:
#with open('BA8C.txt') as f:
for line in f:
if k==-1:
values=line.strip().split()
k=int(values[0])
m=int(values[1])
else:
points.append([float(v) for v in line.strip().split()])
for pt in kmeans(k,m,points):
print (' '.join('{0:.3f}'.format(p) for p in pt))