def closest_pairs(spots_r, spots_c):
"""Calculate the closest neighbours of given reference spots.
Parameters
----------
spots_r, spots_c : coordinate lists
The coordinates (lists of 3-tuples of floats) of objects.
Returns
-------
edm : euclidean distance matrix
pairs : list((int, int))
The list of pairs of closest neighbours (index numbers).
"""
pairs = []
edm = dist_matrix(np.vstack([spots_r, spots_c]))
# create a mask to ignore the reference spots
ref_mask = [1] * len(spots_r) + [0] * len(spots_c)
for refid in range(len(spots_r)):
# the result of find_neighbor() must be adjusted by the length of the
# spots_r list to retrieve the index number for the spots_c list:
nearest = find_neighbor(refid, edm, ref_mask) - len(spots_r)
pair = (refid, nearest)
print_summary(edm, spots_c, spots_r, pair)
pairs.append(pair)
return (edm, pairs)
#!/usr/bin/python
'''Test script for the "volpy" module.'''
from volpy import dist_matrix
from numpy import loadtxt, array_str, set_printoptions
basedir = 'TESTDATA/filaments/'
infile = basedir + 'testdata-filaments.csv'
outfile = basedir + 'result_volpy_fil_detailed.txt'
data = loadtxt(open(infile, 'r'), delimiter=',')
dist_mat = dist_matrix(data)
set_printoptions(threshold=999999)
outstr = array_str(dist_mat, max_line_width=999999)
output = open(outfile, 'w')
output.write(outstr)
print 'Parsed %i points from "%s"' % \
(len(data), infile)
print('Written distance matrix to "%s"' % outfile)
