def mp_helper_special_mode(one_fragment,
fragment_file_chunks,
options,
chunk_size=100):
iteration_depth = options.iteration_depth
repeats = options.repeats
results = list()
# one_fragment in a list of one fragment
fragments = one_fragment
def mp_callback(res):
r, f = res
if r:
results.append(r)
if f:
fragments.append(f)
for repeat_number in range(repeats):
logging.info(
'%s run. You can change the repeat count with --repeats.' %
(repeat_number + 1))
for counter, fragment_file_two in enumerate(fragment_file_chunks):
combined_fragments = tempfile.NamedTemporaryFile(
dir=temp_dir, prefix='tmp_fragments_', delete=False)
unique_files(fragments, combined_fragments, '1')
#logging.debug('fragments (%s)' % ( open(combined_fragments.name).read().strip() ))
if counter > 0:
clean(fragments)
fragments = [combined_fragments.name]
#logging.debug('Linecount: %s (%s) - loop-counter (%s)' % ( CountLines( combined_fragments.name ), combined_fragments.name, counter))
splitted_files = split_smi_library(combined_fragments.name,
chunk_size)
logging.debug(
'Fragments to process: %s (%s); Files to process: %s (%s)' %
(CountLines(combined_fragments.name), combined_fragments.name,
len(splitted_files), counter))
pool = multiprocessing.Pool(options.processors)
for fragment_file in splitted_files:
pool.apply_async(mp_helper,
args=(fragment_file, fragment_file_two,
iteration_depth),
callback=mp_callback)
pool.close()
pool.join()
clean(splitted_files)
if results:
combined_results = tempfile.NamedTemporaryFile(dir=temp_dir,
prefix='tmp_results_',
delete=False)
unique_files(results, combined_results, '2')
clean(results)
return combined_results.name
else:
return False
def run(compound_path, procs, schema, conn_string, filetype):
clean_up_files = False
if os.path.isdir(compound_path):
paths = []
for root, dirs, files in os.walk(compound_path):
for compound_file in files:
path = os.path.join(root, compound_file)
paths.append((path, schema, conn_string, filetype))
paths.sort()
else:
if filetype in ["smi", "inchi"]:
clean_up_files = True
compound_count = cheminfolib.CountLines(compound_path)
sys.stdout.write(
"Splitting inputfile (%s) with %s molecules in files with %s molecules.\n"
% (compound_path, compound_count, int(compound_count / procs)))
paths = cheminfolib.split_smi_library(compound_path,
structures_in_one_file=int(
compound_count / procs))
paths = [(path, schema, conn_string, filetype) for path in paths]
if filetype == "sdf":
paths = [compound_path]
pool = Pool(processes=procs)
sys.stdout.write("Process initialized with %s processes.\n" % procs)
result = pool.map_async(start_parser, paths)
result.get()
if clean_up_files:
for path in paths:
os.remove(path[0])
def run(compound_path, procs, schema, conn_string, filetype):
clean_up_files = False
if os.path.isdir( compound_path ):
paths = []
for root, dirs, files in os.walk(compund_path):
for filename in files:
path = os.path.join( root, compound_file )
paths.append( (path, schema, conn_string, filetype) )
paths.sort()
else:
if filetype in ['smi', 'inchi']:
clean_up_files = True
compound_count = cheminfolib.CountLines( compound_path )
sys.stdout.write('Splitting inputfile (%s) with %s molecules in files with %s molecules.\n' % (compound_path, compound_count, int(compound_count / procs)))
paths = cheminfolib.split_smi_library( compound_path, structures_in_one_file = int(compound_count / procs) )
paths = [(path, schema, conn_string, filetype) for path in paths]
if filetype == 'sdf':
paths = [compound_path]
pool = Pool(processes = procs)
sys.stdout.write('Process initialized with %s processes.\n' % procs)
result = pool.map_async(start_parser, paths)
result.get()
if clean_up_files:
for path in paths:
os.remove( path[0] )
def mp_helper_special_mode(one_fragment, fragment_file_chunks, options, chunk_size = 100):
iteration_depth = options.iteration_depth
repeats = options.repeats
results = list()
# one_fragment in a list of one fragment
fragments = one_fragment
def mp_callback(res):
r, f = res
if r:
results.append(r)
if f:
fragments.append(f)
for repeat_number in range(repeats):
logging.info('%s run. You can change the repeat count with --repeats.' % ( repeat_number + 1 ) )
for counter, fragment_file_two in enumerate( fragment_file_chunks ):
combined_fragments = tempfile.NamedTemporaryFile(dir=temp_dir, prefix='tmp_fragments_', delete=False)
unique_files( fragments, combined_fragments, '1' )
#logging.debug('fragments (%s)' % ( open(combined_fragments.name).read().strip() ))
if counter > 0:
clean( fragments )
fragments = [combined_fragments.name]
#logging.debug('Linecount: %s (%s) - loop-counter (%s)' % ( CountLines( combined_fragments.name ), combined_fragments.name, counter))
splitted_files = split_smi_library( combined_fragments.name, chunk_size )
logging.debug('Fragments to process: %s (%s); Files to process: %s (%s)' % ( CountLines(combined_fragments.name), combined_fragments.name, len(splitted_files), counter) )
pool = multiprocessing.Pool( options.processors )
for fragment_file in splitted_files:
pool.apply_async(mp_helper, args=(fragment_file, fragment_file_two, iteration_depth), callback=mp_callback)
pool.close()
pool.join()
clean( splitted_files )
if results:
combined_results = tempfile.NamedTemporaryFile(dir=temp_dir, prefix='tmp_results_', delete=False)
unique_files( results, combined_results, '2' )
clean( results )
return combined_results.name
else:
return False
log_level = logging.INFO
logging.basicConfig(level=log_level)
test(options)
temp_dir = tempfile.mkdtemp(dir=options.tempdir)
unique_compounds = set()
multiple_merge_compounds = set()
trash_list = list()
result_files = list()
unique_input, unique_input_non_fragments = filter_input_files(
options.input_path)
# adding the non-fragments to the results
# result_files.append( unique_input_non_fragments.name )
splitted_files = split_smi_library(unique_input.name, 1)
trash_list.extend(splitted_files)
# If we have two input files, merge one against the other
if options.second_input:
logging.info("Merging file %s against file %s." %
(options.input_path, options.second_input))
unique_input2, unique_input_non_fragments2 = filter_input_files(
options.second_input)
# adding the non-fragments to the results
# result_files.append( unique_input_non_fragments2.name )
splitted_files2 = split_smi_library(unique_input2.name, 1)
trash_list.extend(splitted_files2)
for counter, fragment_file_one in enumerate(splitted_files):
logging.basicConfig(level=log_level)
test(options)
temp_dir = tempfile.mkdtemp(dir=options.tempdir)
unique_compounds = set()
multiple_merge_compounds = set()
trash_list = list()
result_files = list()
unique_input, unique_input_non_fragments = filter_input_files( options.input_path )
# adding the non-fragments to the results
# result_files.append( unique_input_non_fragments.name )
splitted_files = split_smi_library( unique_input.name, 1 )
trash_list.extend( splitted_files )
# If we have two input files, merge one against the other
if options.second_input:
logging.info('Merging file %s against file %s.' % (options.input_path, options.second_input ))
unique_input2, unique_input_non_fragments2 = filter_input_files( options.second_input )
# adding the non-fragments to the results
# result_files.append( unique_input_non_fragments2.name )
splitted_files2 = split_smi_library( unique_input2.name, 1 )
trash_list.extend( splitted_files2 )
for counter, fragment_file_one in enumerate( splitted_files ):