/usr/share/pyshared/mpi_kmeans.py is in python-mpikmeans 1.5-1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 | #!/usr/bin/python
# Wrapper for the MPI-Kmeans library by Peter Gehler
from ctypes import c_int, c_double, c_uint
from numpy.ctypeslib import ndpointer
import numpy as N
from numpy import empty,array,reshape,arange
def kmeans(X, nclst, maxiter=0, numruns=1):
"""Wrapper for Peter Gehlers accelerated MPI-Kmeans routine."""
mpikmeanslib = N.ctypeslib.load_library("libmpikmeans.so", ".")
mpikmeanslib.kmeans.restype = c_double
mpikmeanslib.kmeans.argtypes = [ndpointer(dtype=c_double, ndim=1, flags='C_CONTIGUOUS'), \
ndpointer(dtype=c_double, ndim=1, flags='C_CONTIGUOUS'), \
ndpointer(dtype=c_uint, ndim=1, flags='C_CONTIGUOUS'), \
c_uint, c_uint, c_uint, c_uint, c_uint ]
npts,dim = X.shape
assignments=empty( (npts), c_uint )
bestSSE=N.Inf
bestassignments=empty( (npts), c_uint)
Xvec = array( reshape( X, (-1,) ), c_double )
permutation = N.random.permutation( range(npts) ) # randomize order of points
CX = array(X[permutation[:nclst],:], c_double).flatten()
SSE = mpikmeanslib.kmeans( CX, Xvec, assignments, dim, npts, min(nclst, npts), maxiter, numruns)
return reshape(CX, (nclst,dim)), SSE, (assignments+1)
if __name__ == "__main__":
from numpy import array
from numpy.random import rand
X = array( rand(12), c_double )
X.shape = (4,3)
clst,dist,labels = kmeans(X, 2)
print "cluster centers=\n",clst
print "dist=",dist
print "cluster labels",labels
|