def ReadFiles(options):
# set variables
ensemble_paths = options.ensemble_paths
# read ensembles into ensemble lookup {'Ensemble_N' : [query_name_list]}
ensemble_lookup = {}
for ensemble_path in ensemble_paths:
try:
ensemble_file = open(ensemble_path, 'r')
except IOError:
print("\nUnable to open ensemble_list: {l}\n".format(
l=ensemble_path))
return 1
ensemble_queries = [
query.strip() for query in ensemble_file.read().split(',')
]
ensemble_file.close()
if len(ensemble_queries) == 0 or '' in ensemble_queries:
print("\n{l} is empty\n".format(l=ensemble_path))
return 1
key = os.path.basename(ensemble_path)
ensemble_lookup[key] = ensemble_queries
# Run consistency checks on the input csv
uniq = []
for ensemble in ensemble_lookup.keys():
for unique_query in [
query for query in ensemble_lookup[ensemble]
if query not in uniq
]:
uniq.append(unique_query)
# read input csv
inputpath = os.path.abspath(options.inputpath)
print('')
print(" Reading input file ...")
print('')
molecules = csv_interface.read_csv(inputpath, options, uniq)
if not molecules:
print("\n '%s' was unable to be parsed\n")
sys.exit(1)
return molecules, ensemble_lookup
def run(itf):
"""
Run optimize functions.
"""
if not itf:
return 1
# access user input
options = SplitInput(itf)
# read input
inputpath = os.path.abspath(options.inputpath)
print(" Reading input file ...")
molecules = csv_interface.read_csv(inputpath, options)
if not molecules:
print("\n '{flag}' was unable to be parsed\n".format(
flag=os.path.basename(options.inputpath)))
sys.exit(1)
# determine the sort order & ensemble_size
#sort_order = classification.get_sort_order(molecules)
sort_order = 'asc'
ensemble_size = options.ensemble_size
# loop over all ensembles
# temp 2/3/15 append to auc_list ef_list & write it out for later histogram construction
auc_list = []
ef_list = []
for size in [x + 1 for x in range(ensemble_size)]:
auc, ef = optimizor(molecules, sort_order, size, options)
auc_list += auc
ef_list += ef
# temp 2/9/15 write auc_list & ef_list out to files for subsequent post-processing
f = open('auc_histogram.csv', 'w')
for value in auc_list:
f.write('%f\n' % value)
#f.write('%f, %s\n' % (value[0], value[1]))
f.close()
f = open('ef_histogram.csv', 'w')
for value in ef_list:
f.write('%f\n' % value)
f.close()
def run(itf):
"""
Run optimize functions.
"""
if not itf:
return 1
# access user input
options = SplitInput(itf)
# read input
inputpath = os.path.abspath(options.inputpath)
print(" Reading input file ...")
molecules = csv_interface.read_csv(inputpath, options)
if not molecules:
print("\n '{flag}' was unable to be parsed\n".format(flag=os.path.basename(options.inputpath)))
sys.exit(1)
# determine the sort order & ensemble_size
#sort_order = classification.get_sort_order(molecules)
sort_order = 'asc'
ensemble_size = options.ensemble_size
# loop over all ensembles
# temp 2/3/15 append to auc_list ef_list & write it out for later histogram construction
auc_list = []
ef_list = []
for size in [x + 1 for x in range(ensemble_size)]:
auc, ef = optimizor(molecules, sort_order, size, options)
auc_list += auc
ef_list += ef
# temp 2/9/15 write auc_list & ef_list out to files for subsequent post-processing
f = open('auc_histogram.csv', 'w')
for value in auc_list:
f.write('%f\n' % value)
#f.write('%f, %s\n' % (value[0], value[1]))
f.close()
f = open('ef_histogram.csv', 'w')
for value in ef_list:
f.write('%f\n' % value)
f.close()
def run(itf):
"""
run approximate functions
:param itf:
:return:
"""
if not itf:
return 1
# access user input
options = SplitInput(itf)
# read input
print(" Reading input file ...")
molecules = csv_interface.read_csv(os.path.abspath(options.inputpath), options)
if not molecules:
print("\n '{f} was unable to be parsed\n".format(f=os.path.basename(options.inputpath)))
sys.exit(1)
approximator(molecules, options)
def ReadFiles(options):
# set variables
ensemble_paths = options.ensemble_paths
# read ensembles into ensemble lookup {'Ensemble_N' : [query_name_list]}
ensemble_lookup = {}
for ensemble_path in ensemble_paths:
try:
ensemble_file = open(ensemble_path, 'r')
except IOError:
print("\nUnable to open ensemble_list: {l}\n".format(l=ensemble_path))
return 1
ensemble_queries = [query.strip() for query in ensemble_file.read().split(',')]
ensemble_file.close()
if len(ensemble_queries) == 0 or '' in ensemble_queries:
print("\n{l} is empty\n".format(l=ensemble_path))
return 1
key = os.path.basename(ensemble_path)
ensemble_lookup[key] = ensemble_queries
# Run consistency checks on the input csv
uniq = []
for ensemble in ensemble_lookup.keys():
for unique_query in [query for query in ensemble_lookup[ensemble] if query not in uniq]:
uniq.append(unique_query)
# read input csv
inputpath = os.path.abspath(options.inputpath)
print('')
print(" Reading input file ...")
print('')
molecules = csv_interface.read_csv(inputpath, options, uniq)
if not molecules:
print("\n '%s' was unable to be parsed\n")
sys.exit(1)
return molecules, ensemble_lookup
