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assign_taxonomy_rdp.py
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assign_taxonomy_rdp.py
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#!/usr/bin/env python
from __future__ import division
from optparse import OptionParser
from os import popen, system, mkdir, makedirs
from os.path import split, splitext
from subprocess import check_call, CalledProcessError
from cogent.app.util import get_tmp_filename
from qiime.parallel.util import split_fasta, get_random_job_prefix, write_jobs_file,\
submit_jobs, compute_seqs_per_file, build_filepaths_from_filepaths,\
get_poller_command, get_rename_command, write_filepaths_to_file,\
write_merge_map_file_assign_taxonomy
from qiime.util import qiime_config
__author__ = "Greg Caporaso"
__copyright__ = "Copyright 2010, The QIIME Project"
__credits__ = ["Greg Caporaso"]
__license__ = "GPL"
__version__ = "0.9"
__maintainer__ = "Greg Caporaso"
__email__ = "gregcaporaso@gmail.com"
__status__ = "Pre-release"
def get_commands(python_exe_fp,assign_taxonomy_fp,confidence,fasta_fps,\
rdp_jar_fp,output_dir,working_dir,command_prefix=None,command_suffix=None):
"""Generate RDP classifier commands which should be submitted to cluster
"""
# Create basenames for each of the output files. These will be filled
# in to create the full list of files created by all of the runs.
out_filenames = [job_prefix + '.%d_tax_assignments.log',
job_prefix + '.%d_tax_assignments.txt']
command_prefix = command_prefix or\
'/bin/bash; export RDP_JAR_PATH=%s; ' % rdp_jar_fp
command_suffix = command_suffix or\
'; exit'
commands = []
result_filepaths = []
for i,fasta_fp in enumerate(fasta_fps):
# Each run ends with moving the output file from the tmp dir to
# the output_dir. Build the command to perform the move here.
rename_command, current_result_filepaths = get_rename_command(\
[fn % i for fn in out_filenames],working_dir,output_dir)
result_filepaths += current_result_filepaths
command = '%s %s %s -c %1.2f -m rdp -o %s -i %s %s %s' %\
(command_prefix,\
python_exe_fp,\
assign_taxonomy_fp,\
confidence,
working_dir,
fasta_fp,
rename_command,
command_suffix)
commands.append(command)
return commands, result_filepaths
usage_str = """usage: %prog [options] {-i INPUT_FP -o OUTPUT_DIR}
[] indicates optional input (order unimportant)
{} indicates required input (order unimportant)
Example usage:
Split the input file (-i) into five jobs (-O), start them,
and write the results (-o) to /home/caporaso/out:
assign_taxonomy_rdp.py -O 5 -i /home/caporaso/10_seq.fasta -o /home/caporaso/out
"""
def parse_command_line_parameters():
""" Parses command line arguments """
usage = usage_str
version = 'Version: %prog 0.1'
parser = OptionParser(usage=usage, version=version)
# define relevant align_seqs.py parameters
parser.add_option('-i','--input_fasta_fp',action='store',\
type='string',help='full path to '+\
'input_fasta_fp [REQUIRED]')
# Update when retraining is ready
# parser.add_option('-t','--id_to_taxonomy_fp',action='store',\
# type='string',help='full path to id_to_taxonomy mapping '+\
# 'file [default: None; REQUIRED with -r to retrain]')
#
# parser.add_option('-r','--reference_seqs_fp',action='store',\
# type='string',help='full path to reference sequence filepath '+\
# '[default: None; REQUIRED with -t to retrain]')
parser.add_option('-o','--output_dir',action='store',\
type='string',help='path to store output files '+\
'[REQUIRED]')
parser.add_option('-r','--rdp_classifier_fp',action='store',\
type='string',help='full path to rdp classifier jar file '+\
'[default: %default]',\
default=qiime_config['rdp_classifier_fp'])
parser.add_option('-c','--confidence',action='store',\
type='float',help='Minimum confidence to'+\
' record an assignment [default: %default]',default=0.80)
# Define parallel-script-specific parameters
parser.add_option('-N','--assign_taxonomy_fp',action='store',\
type='string',help='full path to '+\
'qiime/assign_taxonomy.py [default: %default]',\
default=qiime_config['assign_taxonomy_fp'])
parser.add_option('-O','--jobs_to_start',action='store',type='int',\
help='Number of jobs to start [default: %default]',default=24)
parser.add_option('-P','--poller_fp',action='store',\
type='string',help='full path to '+\
'qiime/parallel/poller.py [default: %default]',\
default=qiime_config['poller_fp'])
parser.add_option('-R','--retain_temp_files',action='store_true',\
help='retain temporary files after runs complete '+\
'(useful for debugging) [default: %default]',\
default=False)
parser.add_option('-S','--suppress_submit_jobs',action='store_true',\
help='Only split input and write commands file - don\'t submit '+\
'jobs [default: %default]',default=False)
parser.add_option('-T','--poll_directly',action='store_true',\
help='Poll directly for job completion rather than running '+\
'poller as a separate job. If -T is specified this script will '+\
'not return until all jobs have completed. [default: %default]',\
default=False)
parser.add_option('-U','--cluster_jobs_fp',action='store',\
type='string',help='path to cluster_jobs.py script ' +\
' [default: %default]',\
default=qiime_config['cluster_jobs_fp'])
parser.add_option('-W','--suppress_polling',action='store_true',
help='suppress polling of jobs and merging of results '+\
'upon completion [default: %default]',\
default=False)
parser.add_option('-X','--job_prefix',action='store',\
type='string',help='job prefix '+\
'[default: RDP_ + 5 random chars]')
parser.add_option('-Y','--python_exe_fp',action='store',\
type='string',help='full path to python '+\
'executable [default: %default]',\
default=qiime_config['python_exe_fp'])
parser.add_option('-Z','--seconds_to_sleep',type='int',\
help='Number of seconds to sleep between checks for run '+\
' completion when polling runs [default: %default]',default=60)
opts,args = parser.parse_args()
required_options = ['input_fasta_fp','output_dir']
for option in required_options:
if eval('opts.%s' % option) == None:
parser.error('Required option --%s omitted.' % option)
# Update when retraining is ready
# if (opts.id_to_taxonomy_fp or opts.reference_seqs_fp) and not
# (opts.id_to_taxonomy_fp and opts.reference_seqs_fp):
# parser.error('-t and -r must be provided together or not at all.')
return opts,args
if __name__ == "__main__":
opts,args = parse_command_line_parameters()
# create local copies of command-line options
python_exe_fp = opts.python_exe_fp
assign_taxonomy_fp = opts.assign_taxonomy_fp
confidence = opts.confidence
rdp_classifier_fp = opts.rdp_classifier_fp
cluster_jobs_fp = opts.cluster_jobs_fp
input_fasta_fp = opts.input_fasta_fp
jobs_to_start = opts.jobs_to_start
output_dir = opts.output_dir
poller_fp = opts.poller_fp
retain_temp_files = opts.retain_temp_files
suppress_polling = opts.suppress_polling
seconds_to_sleep = opts.seconds_to_sleep
poll_directly = opts.poll_directly
try:
makedirs(output_dir)
except OSError:
# output dir already exists
pass
created_temp_paths = []
# split the input filepath into directory and filename, base filename and
# extension
input_dir, input_fasta_fn = split(input_fasta_fp)
input_file_basename, input_fasta_ext = splitext(input_fasta_fn)
# set the job_prefix either based on what the user passed in,
# or a random string beginning with RDP
job_prefix = opts.job_prefix or get_random_job_prefix('RDP')
# A temporary output directory is created in output_dir named
# job_prefix. Output files are then moved from the temporary
# directory to the output directory when they are complete, allowing
# a poller to detect when runs complete by the presence of their
# output files.
working_dir = '%s/%s' % (output_dir,job_prefix)
try:
mkdir(working_dir)
created_temp_paths.append(working_dir)
except OSError:
# working dir already exists
pass
# compute the number of sequences that should be included in
# each file after splitting the input fasta file
num_seqs_per_file = compute_seqs_per_file(input_fasta_fp,jobs_to_start)
# split the fasta files and get the list of resulting files
tmp_fasta_fps =\
split_fasta(open(input_fasta_fp),num_seqs_per_file,job_prefix,output_dir)
created_temp_paths += tmp_fasta_fps
# build the filepath for the 'jobs script'
jobs_fp = '%s/%sjobs.txt' % (output_dir, job_prefix)
created_temp_paths.append(jobs_fp)
# generate the list of commands to be pushed out to nodes
commands, job_result_filepaths = \
get_commands(python_exe_fp,assign_taxonomy_fp,confidence,tmp_fasta_fps,\
rdp_classifier_fp,output_dir,working_dir)
created_temp_paths += job_result_filepaths
# Set up poller apparatus if the user does not suppress polling
if not suppress_polling:
# Write the list of files which must exist for the jobs to be
# considered complete
expected_files_filepath = '%s/expected_out_files.txt' % working_dir
write_filepaths_to_file(job_result_filepaths,expected_files_filepath)
created_temp_paths.append(expected_files_filepath)
# Write the mapping file which described how the output files from
# each job should be merged into the final output files
merge_map_filepath = '%s/merge_map.txt' % working_dir
write_merge_map_file_assign_taxonomy(job_result_filepaths,output_dir,\
merge_map_filepath,input_file_basename)
created_temp_paths.append(merge_map_filepath)
# Create the filepath listing the temporary files to be deleted,
# but don't write it yet
deletion_list_filepath = '%s/deletion_list.txt' % working_dir
created_temp_paths.append(deletion_list_filepath)
# Generate the command to run the poller, and the list of temp files
# created by the poller
if not poll_directly:
poller_command, poller_result_filepaths =\
get_poller_command(python_exe_fp,poller_fp,expected_files_filepath,\
merge_map_filepath,deletion_list_filepath,\
seconds_to_sleep=seconds_to_sleep)
created_temp_paths += poller_result_filepaths
# append the poller command to the list of job commands
commands.append(poller_command)
else:
poller_command, poller_result_filepaths =\
get_poller_command(python_exe_fp,poller_fp,\
expected_files_filepath,merge_map_filepath,\
deletion_list_filepath,seconds_to_sleep=seconds_to_sleep,\
command_prefix='',command_suffix='')
created_temp_paths += poller_result_filepaths
if not retain_temp_files:
# If the user wants temp files deleted, now write the list of
# temp files to be deleted
write_filepaths_to_file(created_temp_paths,deletion_list_filepath)
else:
# Otherwise just write an empty file
write_filepaths_to_file([],deletion_list_filepath)
# write the commands to the 'jobs files'
write_jobs_file(commands,job_prefix=job_prefix,jobs_fp=jobs_fp)
# submit the jobs file using cluster_jobs, if not suppressed by the
# user
if not opts.suppress_submit_jobs:
submit_jobs(cluster_jobs_fp,jobs_fp,job_prefix)
if poll_directly:
try:
check_call(poller_command.split())
except CalledProcessError, e:
print '**Error occuring when calling the poller directly. '+\
'Jobs may have been submitted, but are not being polled.'
print str(e)
exit(-1)