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remove_naps_hub_No_IT_sec.py
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remove_naps_hub_No_IT_sec.py
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import argparse
import os.path
import csv
import ipdb
# the "nap" needs to be greater than or equal to this time in order to be filtered out
NAP_TIME_MIN = '600'
INDEX_PARTICIPANT_ID = 22
INDEX_AGE = 1
INDEX_DURATION = 4 #was a time
INDEX_MEANINGFUL = 9 #was a time
INDEX_DISTANT = 11 #was a time
INDEX_TV = 12 #was a time
INDEX_NOISE = 14 #was a time
INDEX_SILENCE = 15 #was a time
INDEX_AWC_ACTUAL = 5
INDEX_CTC_ACTUAL = 6
INDEX_CVC_ACTUAL = 7
def open_source_file(parser, arg):
if not os.path.exists(arg):
parser.error("The file %s does not exist" % arg)
else:
return open(arg, 'r')
def open_dest_file(parser, arg):
if os.path.exists(arg):
parser.error("The file %s exists already" % arg)
else:
return open(arg, 'w', newline='\r\n')
def write_stats(raw_stats, filtered_stats, stat_file, filtered_line_count):
if (stat_file is not None) and (len(raw_stats) != 0):
stat_file.write(','.join(raw_stats) + '\r\n')
stat_file.write(','.join(filtered_stats) + '\r\n')
print('Processed visit: PARTICIPANT_ID=' + raw_stats[INDEX_PARTICIPANT_ID] + ', AGE=' + raw_stats[INDEX_AGE])
print('Filtered out ' + str(filtered_line_count) + ' lines')
# AWC is 0, CVC is 0, CTC is 0, AND at least 3 of the 5 min are either noise or silence
def line_passes_filter(parsed_list):
noise_or_silence = add_numbers(parsed_list[INDEX_NOISE], parsed_list[INDEX_SILENCE])
return (int(parsed_list[INDEX_AWC_ACTUAL]) != 0) or (int(parsed_list[INDEX_CTC_ACTUAL]) != 0) or (int(parsed_list[INDEX_CVC_ACTUAL]) > 10) or (int(noise_or_silence) < 180)
def add_numbers(number1, number2):
#ipdb.set_trace()
return str(int(number1) + int(number2))
def is_time_gte(time1, time2):
if int(time1 > time2):
return True
if int(time1) < int(time2):
return False
return True
def add_to_stats(parsed_list, stats):
stats[INDEX_DURATION] = add_numbers(stats[INDEX_DURATION], parsed_list[INDEX_DURATION])
stats[INDEX_MEANINGFUL] = add_numbers(stats[INDEX_MEANINGFUL], parsed_list[INDEX_MEANINGFUL])
stats[INDEX_DISTANT] = add_numbers(stats[INDEX_DISTANT], parsed_list[INDEX_DISTANT])
stats[INDEX_TV] = add_numbers(stats[INDEX_TV], parsed_list[INDEX_TV])
stats[INDEX_NOISE] = add_numbers(stats[INDEX_NOISE], parsed_list[INDEX_NOISE])
stats[INDEX_SILENCE] = add_numbers(stats[INDEX_SILENCE], parsed_list[INDEX_SILENCE])
stats[INDEX_AWC_ACTUAL] = add_numbers(stats[INDEX_AWC_ACTUAL], parsed_list[INDEX_AWC_ACTUAL])
stats[INDEX_CTC_ACTUAL] = add_numbers(stats[INDEX_CTC_ACTUAL], parsed_list[INDEX_CTC_ACTUAL])
stats[INDEX_CVC_ACTUAL] = add_numbers(stats[INDEX_CVC_ACTUAL], parsed_list[INDEX_CVC_ACTUAL])
# python cli arguments
parser = argparse.ArgumentParser(description='Remove nap rows from LENA data file.')
parser.add_argument("-s", dest="source_file", required=True,
help="source file", metavar="FILE",
type=lambda x: open_source_file(parser, x))
parser.add_argument("-d", dest="dest_file", required=True,
help="destination file", metavar="FILE",
type=lambda x: open_dest_file(parser, x))
parser.add_argument("-t", dest="stat_file", required=True,
help="stats file", metavar="FILE",
type=lambda x: open_dest_file(parser, x))
args = parser.parse_args()
# write out header
header = next(args.source_file)
args.dest_file.write(header)
args.stat_file.write(header)
# loop through source file
raw_stats = []
filtered_stats = []
visit_count = 0
filtered_line_count = 0
parsed_list = []
nap_raw_lines = []
nap_parsed_lists = []
print('Processing visits...')
for raw_line in args.source_file:
if len(raw_line.strip()) == 0:
continue
parsed_line = csv.reader([raw_line], delimiter=',', quotechar='"')
parsed_list = next(parsed_line)
line_passed = line_passes_filter(parsed_list)
# this line is for a different visit from the previous
is_new_visit = len(raw_stats) == 0 or (raw_stats[INDEX_PARTICIPANT_ID] != parsed_list[INDEX_PARTICIPANT_ID]) or (raw_stats[INDEX_AGE] != parsed_list[INDEX_AGE])
if is_new_visit:
# handle accumulated nap lines
nap_length_accum = '0'
for nap_parsed_list in nap_parsed_lists:
nap_length_accum = add_numbers(nap_length_accum, nap_parsed_list[INDEX_DURATION])
if is_time_gte(nap_length_accum, NAP_TIME_MIN):
filtered_line_count += len(nap_parsed_lists)
else:
for nap_parsed_list in nap_parsed_lists:
add_to_stats(nap_parsed_list, filtered_stats)
for nap_raw_line in nap_raw_lines:
args.dest_file.write(nap_raw_line)
nap_parsed_lists = []
nap_raw_lines = []
# write out stats for the previous visit
write_stats(raw_stats, filtered_stats, args.stat_file, filtered_line_count)
visit_count += 1
# start fresh with the new visit
raw_stats = parsed_list.copy()
filtered_stats = parsed_list.copy()
filtered_line_count = 0
if not line_passed:
nap_parsed_lists.append(parsed_list.copy())
nap_raw_lines.append(raw_line)
filtered_stats[INDEX_DURATION] = '0'
filtered_stats[INDEX_MEANINGFUL] = '0'
filtered_stats[INDEX_DISTANT] = '0'
filtered_stats[INDEX_TV] = '0'
filtered_stats[INDEX_NOISE] = '0'
filtered_stats[INDEX_SILENCE] = '0'
filtered_stats[INDEX_AWC_ACTUAL] = '0'
filtered_stats[INDEX_CTC_ACTUAL] = '0'
filtered_stats[INDEX_CVC_ACTUAL] = '0'
else:
args.dest_file.write(raw_line)
# this line is for the same visit as the previous
else:
add_to_stats(parsed_list, raw_stats)
if line_passed:
# handle accumulated nap lines
nap_length_accum = '0'
for nap_parsed_list in nap_parsed_lists:
nap_length_accum = add_numbers(nap_length_accum, nap_parsed_list[INDEX_DURATION])
if is_time_gte(nap_length_accum, NAP_TIME_MIN):
filtered_line_count += len(nap_parsed_lists)
else:
for nap_parsed_list in nap_parsed_lists:
add_to_stats(nap_parsed_list, filtered_stats)
for nap_raw_line in nap_raw_lines:
args.dest_file.write(nap_raw_line)
nap_parsed_lists = []
nap_raw_lines = []
add_to_stats(parsed_list, filtered_stats)
args.dest_file.write(raw_line)
else:
nap_parsed_lists.append(parsed_list.copy())
nap_raw_lines.append(raw_line)
# process final visit
write_stats(raw_stats, filtered_stats, args.stat_file, filtered_line_count)
print('Processed ' + str(visit_count) + ' visits')