#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""A tool to calc inf_all, inf_stack, inf_WC, inf_nWC, SNS_WC, PPV_WC, SNS_nWC, PPV_nWC between two structures.
Mind, that ClaRNA is pretty slow, it takes even a few seconds to analyze a structure,
so for, say, 1000 models you need a few hours.
How to make it faster? First, you can use ``--number_of_threads`` to specify the number of cores used for multiprocessing.
Second, the procedure implemented in here is composed of two steps, first for each structure ClaRNA is used to generate an output with contacts, then these files are used for comparisons. So, if you want to re-run your analysis, you don't have to run re-run ClaRNA itself. Thus, be default ClaRNA is not executed if <model>.outCR is found next to the analyzed files. To change this behavior force (``--force``) rna_cal_inf.py to re-run ClaRNA.
ClaRNA_play required!
https://gitlab.genesilico.pl/RNA/ClaRNA_play (internal GS gitlab server). Contact <magnus@genesilico.pl>.
import progressbar (in version 2) is required! """
from __future__ import print_function
import progressbar
import argparse
import sys
import os
import subprocess
import re
import tempfile
import csv
import shutil
from multiprocessing import Pool, Lock, Value, Process
from rna_tools.tools.clarna_app import clarna_app
#from rna_tools.opt.BasicAssessMetrics.BasicAssessMetrics import InteractionNetworkFidelity
[docs]def get_parser():
parser = argparse.ArgumentParser()#usage="%prog [<options>] <pdb files (test_data/*)>")
parser.add_argument('-t',"--target_fn",
dest="target_fn",
default='',
help="pdb file")
parser.add_argument('-m',"--number_of_threads",
dest="nt",
default=3,
help="number of threads used for multiprocessing, if 1 then mp is not used \
(useful for debugging)!")
parser.add_argument('-s',"--ss",
dest="ss",
default='',
help="A:(([[))]]")
parser.add_argument('--stacking',
action="store_true",
help="take into account also stacking")
parser.add_argument('--debug',
action="store_true")
parser.add_argument('--method', default="clarna", help="you can use mcannotate or clarna")
parser.add_argument('-f',"--force",
dest="force",
action="store_true",
help="force to run ClaRNA even if <pdb>.outCR file is there")
parser.add_argument('-v',"--verbose",
dest="verbose",
action="store_true",
help="be verbose, tell me more what're doing")
parser.add_argument('-o',"--out_fn",
dest="out_fn",
default='inf.csv',
help="out csv file, be default `inf.csv`")
parser.add_argument('files', help="files, .e.g folder_with_pdbs/*pdbs", nargs='+')
return parser
# Prepare the lock and the counter for MP
from ctypes import c_int
lock = Lock()
counter = Value(c_int)
DEBUG = False
[docs]def do_job(i): # , method='clarna'):
"""Run ClaRNA & Compare, add 1 to the counter, write output
to csv file (keeping it locked)"""
#if method == 'clarna':
# run clarna & compare
i_cl_fn = clarna_app.clarna_run(i, args.force, args.stacking)
output = clarna_app.clarna_compare(target_cl_fn,i_cl_fn, DEBUG)
if args.verbose:
print(output)
## else:
## rmsd, DI_ALL, INF_ALL, INF_WC, INF_NWC,INF_STACK = InteractionNetworkFidelity(os.path.abspath(target_fn),
## '/tmp/empty-index',
## os.path.abspath(i),
## '/tmp/empty-index')
## if args.debug:
## print(rmsd)
# counter and bar
global counter
counter.value += 1
bar.update(counter.value)
# write csv
lock.acquire()
# take only filename of target
cells = output.split()
cells[0] = os.path.basename(cells[0])
csv_writer.writerow(cells)
csv_file.flush()
lock.release()
#main
if __name__ == '__main__':
parser = get_parser()
args = parser.parse_args()
if args.debug:
print(args)
if len(sys.argv) == 1:
print((parser.print_help()))
sys.exit(1)
input_files = args.files
target_fn = args.target_fn
ss = args.ss
if ss:
# generate target_fn
ss_txt = open(ss).read().split('\n')[2]
target_cl_fn = clarna_app.get_ClaRNA_output_from_dot_bracket(ss_txt, temp=False)
else:
target_cl_fn = clarna_app.clarna_run(target_fn, args.force)
# keep target save, don't overwrite it when force and
# target is in the folder that you are running ClaRNA on
# /tmp/tmp2nmeVB/1i6uD_M1.pdb.outCR
d = tempfile.mkdtemp()
tmp_target_cl_fn = d + os.sep + os.path.basename(target_cl_fn)
shutil.copyfile(target_cl_fn, tmp_target_cl_fn)
target_cl_fn = tmp_target_cl_fn
##
out_fn = args.out_fn
# Open output file
csv_file = open(out_fn, 'w')
csv_writer = csv.writer(csv_file, delimiter=',')
csv_writer.writerow('target,fn,inf_all,inf_stack,inf_WC,inf_nWC,sns_WC,ppv_WC,sns_nWC,ppv_nWC'.split(','))
csv_file.flush()
# Init bar and to the job
try:
bar = progressbar.ProgressBar(max_value=len(input_files))
bar.update(0)
except TypeError:
print('Please install progressbar2 (not progressbar), e.g. pip install progressbar2')
sys.exit(1)
# Main meat
number_processes = int(args.nt)
open('/tmp/empty-index', 'a').close() ## ugly hack
if number_processes > 1: # multi
p = Pool(number_processes)
p.map(do_job, input_files) # , args.method)
else: # single process
for c, i in enumerate(input_files):#, range(len(input_files))):
do_job(i, args.method)
print('csv was created! ', out_fn)