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#!/usr/bin/env python
# File created on 10 Mar 2011
from __future__ import division
__author__ = "Justin Kuczynski"
__copyright__ = "Copyright 2011, The QIIME project"
__credits__ = ["Justin Kuczynski"]
__license__ = "GPL"
__version__ = "1.4.0"
__maintainer__ = "Justin Kuczynski"
__email__ = "justinak@gmail.com"
__status__ = "Release"
from qiime.util import parse_command_line_parameters
from qiime.util import make_option
from qiime.parse import parse_mapping_file_to_dict, parse_distmat
import os
import sys
import numpy
from qiime.cluster_quality import clust_qual_ratio
script_info={}
script_info['brief_description']="""compute the quality of a cluster"""
script_info['script_description']="""The input is a distance matrix (i.e. resulting file from beta_diversity.py)."""
script_info['script_usage']=[]
script_info['script_usage'].append(("""cluster quality based on the treatment category:""","""to compute the quality of clusters, and print to stdout, use the following idiom:""","""cluster_quality.py -i unweighted_unifrac_distance_matrix.txt -m Fasting_Map.txt -c Treatment"""))
script_info['script_usage'].append(('','',''))
script_info['output_description']="""The output is either a single number (with -s), or a more detailed output of the similarity between and within clusters."""
script_info['required_options']=[
make_option('-i', '--input_path',
help='input distance matrix file'),\
make_option('-m', '--map',
help='mapping file'),
make_option('-c', '--category',
help='column of mapping file delimiting clusters'),
]
script_info['optional_options']=[
make_option('-o', '--output_path',default=None,
help='output path, prints to stdout if omitted'),
make_option('-s', '--short',action="store_true",
help='print only '+\
'the ratio of mean dissimilarities between/within clusters'+\
' instead of more detailed output'),
make_option('--metric', default='ratio',
help='choice of quality metric to apply. Currently only one option '+\
'exists, the ratio of mean(distances between samples from different '+\
'clusters) to mean(distances between samples from the same cluster) '+\
'Default: %default'),
]
script_info['version'] = __version__
def main():
option_parser, opts, args = parse_command_line_parameters(**script_info)
if opts.output_path != None:
outf = open(opts.output_path,'w')
else:
outf = sys.stdout
dists = parse_distmat(open(opts.input_path,'U'))
map_data = parse_mapping_file_to_dict(open(opts.map,'U'))
diff_dists, same_dists = clust_qual_ratio(dists, map_data, opts.category)
if opts.short:
print >> outf, numpy.mean(diff_dists)/numpy.mean(same_dists)
else:
print >> outf, "dissimilarity ratio between/within (large for clustered data):"
print >> outf, numpy.mean(diff_dists)/numpy.mean(same_dists)
print >> outf, "dissimilarities between clusters: mean, std, num:"
print >> outf, '\t'.join(map(str,[numpy.mean(diff_dists), numpy.std(diff_dists),
len(diff_dists)]))
print >> outf, "dissimilarities within clusters: mean, std, num:"
print >> outf, '\t'.join(map(str,[numpy.mean(same_dists), numpy.std(same_dists),
len(same_dists)]))
if __name__ == "__main__":
main()
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