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#!/usr/bin/env python
# File created on 14 Jul 2012
from __future__ import division
__author__ = "Greg Caporaso"
__copyright__ = "Copyright 2011, The QIIME project"
__credits__ = ["Greg Caporaso"]
__license__ = "GPL"
__version__ = "1.8.0"
__maintainer__ = "Greg Caporaso"
__email__ = "gregcaporaso@gmail.com"
from qiime.util import (parse_command_line_parameters, make_option)
from os.path import split, splitext, join
from qiime.util import get_tmp_filename, get_options_lookup
from qiime.parallel.multiple_rarefactions import ParallelMultipleRarefactions
options_lookup = get_options_lookup()
script_info={}
script_info['brief_description']="""Parallel multiple file rarefaction"""
script_info['script_description']="""This script performs like the multiple_rarefactions.py script, but is intended to make use of multicore/multiprocessor environments to perform analyses in parallel."""
script_info['script_usage']=[]
script_info['script_usage'].append(("""OTU tables of different depths""","""Build rarefied otu tables containing 10 (-m) to 140 (-x) sequences in steps of 10 (-s) with 2 (-n) repetions per number of sequences, from otu_table.biom (-i). Write the output files to the rarefied_otu_tables directory (-o, will be created if it doesn't exist). The name of the output files will be of the form rarefaction_<num_seqs>_<reptition_number>.biom. ALWAYS SPECIFY ABSOLUTE FILE PATHS (absolute path represented here as $PWD, but will generally look something like /home/ubuntu/my_analysis/).""","""%prog -o $PWD/rarefied_otu_tables/ -m 10 -x 140 -s 10 -n 2 -i $PWD/otu_table.biom"""))
script_info['script_usage'].append(("""OTU tables of the same depth""","""Build 8 rarefied otu tables each containing exactly 100 sequences per sample (even depth rarefaction). ALWAYS SPECIFY ABSOLUTE FILE PATHS (absolute path represented here as $PWD, but will generally look something like /home/ubuntu/my_analysis/).""","""%prog -o $PWD/even_otu_tables/ -m 100 -x 100 -n 8 -i $PWD/otu_table.biom"""))
script_info['output_description']="""The result of parallel_multiple_rarefactions.py consists of a number of files, which depend on the minimum/maximum number of sequences per samples, steps and iterations. The files have the same otu table format as the input otu_table.biom, and are named in the following way: rarefaction_100_0.txt, where "100" corresponds to the sequences per sample and "0" for the iteration."""
script_info['required_options'] = [\
make_option('-i', '--input_path',type='existing_filepath',
help='input filepath, (the otu table) [REQUIRED]'),\
make_option('-o', '--output_path',type='new_dirpath',
help="write output rarefied otu tables here makes dir if it doesn't exist [REQUIRED]"),\
make_option('-m', '--min', type=int,help='min seqs/sample [REQUIRED]'),\
make_option('-x', '--max', type=int,\
help='max seqs/sample (inclusive) [REQUIRED]'),\
]
script_info['optional_options'] = [
make_option('-n', '--num-reps', dest='num_reps', default=10, type=int,
help='num iterations at each seqs/sample level [default: %default]'),
make_option('--suppress_lineages_included', default=False, action="store_true",
help='Exclude taxonomic (lineage) information for each OTU.'),
make_option('-s', '--step', type=int, default=1,
help='levels: min, min+step... for level <= max [default: %default]'),
make_option('--subsample_multinomial',default=False,action='store_true',
help='subsample using subsampling with replacement [default: %default]'),
options_lookup['retain_temp_files'],
options_lookup['suppress_submit_jobs'],
options_lookup['poll_directly'],
options_lookup['cluster_jobs_fp'],
options_lookup['suppress_polling'],
options_lookup['job_prefix'],
options_lookup['seconds_to_sleep'],
options_lookup['jobs_to_start']
]
script_info['version'] = __version__
def main():
option_parser, opts, args = parse_command_line_parameters(**script_info)
# create dict of command-line options
params = eval(str(opts))
if not opts.step > 0:
option_parser.error(("Error: step size must be greater than 0.\n"
"If min = max, just leave step size at 1."))
parallel_runner = ParallelMultipleRarefactions(
cluster_jobs_fp=opts.cluster_jobs_fp,
jobs_to_start=opts.jobs_to_start,
retain_temp_files=opts.retain_temp_files,
suppress_polling=opts.suppress_polling,
seconds_to_sleep=opts.seconds_to_sleep)
parallel_runner(opts.input_path,
opts.output_path,
params,
job_prefix=opts.job_prefix,
poll_directly=opts.poll_directly,
suppress_submit_jobs=False)
if __name__ == "__main__":
main()
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