myprojects-hg-reborn

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#! /usr/bin/env python

import scipy as s
import numpy as n
import pylab as p
#from rpy import r
import distance_calc as d_calc
import igraph as ig


density=0.01
threshold=1.06

box_size=(5000./density)**(1./3.)  #here the box size does not depend 


filename="../read_pos_338"

test=n.loadtxt(filename)

x_pos=test[:,0]
y_pos=test[:,1]
z_pos=test[:,2]


dist_mat=d_calc.distance_calc(x_pos,y_pos,z_pos, box_size)

print "dist_mat is, ", dist_mat

n.savetxt("distance_matrix.dat", dist_mat)


# cluster_obj=ig.Graph.Adjacency((dist_mat <= threshold).tolist(),\
# 					       ig.ADJ_UNDIRECTED)

# cluster_obj.simplify()
# clustering=cluster_obj.clusters()

# print "the number of clusters is, ", len(clustering)

# print "cluster size distribution is, ", clustering.sizes()

print "So far so good"