def output_oneline(ip, startDate, startTime, endDate, endTime, requestedNum,
outputFile):
inactDue = time_diff(startDate, startTime, endDate, endTime)
oneline = ip + "," + startDate + " " + startTime + "," + endDate + " " + endTime + "," + str(
inactDue + 1) + "," + str(requestedNum) + "\n"
f = open(outputFile, "a")
# print ("write to file: "+oneline)
# print (outputFile)
# print(os.path.abspath(outputFile))
f.write(oneline)
ARR_VS_DEP = {}
ARR_VS_ARR = {}
#Make windows for departing train
for train in DEPARTING:
if not str(DEP_DICT[train]) == 'nan':
DEP_VS_DEP[train] = []
DEP_VS_ARR[train] = []
#Match with departing trains
for candidate in DEPARTING:
if not str(DEP_DICT[candidate]) == 'nan':
#skip comparisons with train
if candidate == train:
pass
elif abs(time_diff(DEP_DICT[train],
DEP_DICT[candidate])) < WINDOWSIZE/2.:
DEP_VS_DEP[train].append(candidate)
#Match with arriving trains
for candidate in ARRIVING:
if not str(ARR_DICT[candidate]) == 'nan':
#skip comparisons with train
if candidate == train:
pass
elif abs(time_diff(DEP_DICT[train],
ARR_DICT[candidate])) < WINDOWSIZE/2.:
DEP_VS_ARR[train].append(candidate)
#Write spreadsheets
WRITER = csv.writer(open('DATA_OSLOS/DEP_VS_DEP.csv', 'w'), delimiter=',')
WRITER.writerow(['Subject', 'Possible delayers ->'])
def test(self):
"""
Test function time_diff()
"""
self.assertEqual(time_diff('14.12.2014 09.57.00',
'14.12.2014 09.56.51'), 9)
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import csv
from time_diff import time_diff
# Writing data to CSV file
df = pd.read_csv('/Volumes/Samir\'s Files/DATA/mimic/ADMISSIONS.csv.gz')
df['TARGET'] = 0
data = df[['HADM_ID', 'SUBJECT_ID', 'ADMITTIME', 'DEATHTIME', 'TARGET']]
data = data.replace(np.nan, 'nan', regex=True)
col = data.columns.values.tolist()
data = np.array(data)
for i in range(len(data)):
if data[i][3] != 'nan':
if time_diff(data[i][3], data[i][2]) <= 168:
data[i][4] = 1
with open('test.csv', 'w') as csv_file:
csvwriter = csv.writer(csv_file, delimiter='\t')
csvwriter.writerow(col)
for row in range(len(data)):
csvwriter.writerow(data[row])
for oneRecord in f:
recordList = oneRecord.split(",")
ip = recordList[index_ip]
date = recordList[index_date]
time = recordList[index_time]
cik = recordList[index_cik]
accession = recordList[index_accession]
extention = recordList[index_extention]
# check if the active users passed the inactive period
tempUserOrder = deepcopy(activeUserOrder)
for user in activeUserOrder:
curLastDate = activeUserSet[user].lastDate
curLastTime = activeUserSet[user].lastTime
inactDue = time_diff(curLastDate, curLastTime, date, time)
if inactDue > inactPeriod:
output_oneline(user, activeUserSet[user].startDate,
activeUserSet[user].startTime,
activeUserSet[user].lastDate,
activeUserSet[user].lastTime,
activeUserSet[user].requestedNum, outputFile)
del (activeUserSet[user])
tempUserOrder.remove(user)
activeUserOrder = deepcopy(tempUserOrder)
# check if IP address existing
if ip in activeUserSet:
# Update the last request date, update the requested document number by checking the CAE
activeUserSet[ip].lastDate = date
activeUserSet[ip].lastTime = time
import numpy as np
import csv
from time_diff import time_diff
filename = 'all.csv'
new_filename = 'newfile.csv'
admittime = 2
deathtime = 3
target = 4
# FILE TO FIX
all_scores = pd.read_csv(filename, delimiter='\t')
col = all_scores.columns.values.tolist()
all_scores = np.array(all_scores)
corrected = 0
for i in range(len(all_scores)):
adtime = all_scores[i][admittime]
if all_scores[i][target] == 1:
if time_diff(all_scores[i][admittime], all_scores[i][deathtime]) > 7:
all_scores[i][target] = 0
corrected += 1
print(corrected)
with open(new_filename, 'w') as csv_file:
csvwriter = csv.writer(csv_file, delimiter='\t')
csvwriter.writerow(col)
for row in range(len(all_scores)):
csvwriter.writerow(all_scores[row])
