def backUp(inputDirs, backUpTo, DataBaseAddress, spreadsheet):
subjectClassList = []
for newDirectory in inputDirs:
subjClass = subj.subject(newDirectory, backUpTo)
checkFileNumbers(subjClass)
subjectClassList.append(subjClass)
executeCopy(subjClass)
subjDf = saveLog(subjClass)
dbDf = processDB(DataBaseAddress)
newDf = pd.concat([dbDf, subjDf]).reset_index()
newDf = newDf[[
u'koreanName', u'subjectName', u'subjectInitial', u'group', u'sex',
u'age', u'DOB', u'scanDate', u'timeline', u'studyname',
u'patientNumber', u'T1', u'T2', u'REST_LR', u'REST_LR_SBRef',
u'REST_BLIP_LR', u'REST_BLIP_RL', u'DTI_LR_1000', u'DTI_LR_2000',
u'DTI_LR_3000', u'DTI_BLIP_LR', u'DTI_BLIP_RL', u'dx',
u'folderName', u'backUpBy', u'note'
]]
#please confirm here
newDf['koreanName'] = newDf['koreanName'].str.decode('utf-8')
newDf['note'] = newDf['note'].str.decode('utf-8')
newDf.to_excel(DataBaseAddress, 'Sheet1')
# os.chmod(DataBaseAddress, 0o2770)
updateSpreadSheet.main(False, DataBaseAddress, spreadsheet) #False
print('Completed\n')
def main(entity, entity_code):
if entity == 'chapters':
return chapter(entity_code)
if entity == 'units':
return unit(entity_code)
if entity == 'concepts':
return concept(entity_code)
if entity == 'subjects':
return subject(entity_code)
def backUp(inputDirs, backUpTo,
DataBaseAddress, spreadsheet):
subjectClassList = []
for newDirectory in inputDirs:
subjClass = subj.subject(newDirectory, backUpTo)
checkFileNumbers(subj.correct_modality_re_dict, subjClass)
subjectClassList.append(subjClass)
executeCopy(subjClass)
subjDf = saveLog(subjClass)
print(subjDf)
dbDf = processDB(DataBaseAddress)
newDf = pd.concat([dbDf, subjDf]).reset_index()
# ordering
newDf = newDf[[ u'koreanName',
u'subjectName',
u'subjectInitial',
u'group',
u'sex',
u'age',
u'DOB',
u'scanDate',
u'timeline',
u'studyname',
u'patientNumber'] + \
[subj.correct_modality_re_dict] + \
[u'dx',
u'folderName',
u'backUpBy',
u'note']]
#please confirm here
newDf['koreanName'] = newDf['koreanName'].str.decode('utf-8')
newDf['note'] = newDf['note'].str.decode('utf-8')
newDf.to_excel(DataBaseAddress, 'Sheet1', encode='utf-8')
# os.chmod(DataBaseAddress, 0o2770)
updateSpreadSheet.main(False, DataBaseAddress, spreadsheet)#False
print('Completed\n')
def create_and_save_subjects():
##### initialize subjects from score.csv #####
scores_df = pd.read_csv('../data/scores.csv')
condition_df = scores_df[23:]
mean_days = condition_df['days'].mean()
print(mean_days)
# replace nan & empty str with -1
scores_df = scores_df.replace(np.nan, -1)
scores_df = scores_df.replace(' ', -1)
print(sum(scores_df['days']))
# check there is no nan
assert scores_df.isnull().sum().sum() == 0
subjects = [
subject(row.number, row.days, row.gender, row.age, row.afftype,
row.melanch, row.inpatient, row.edu, row.marriage, row.work,
row.madrs1, row.madrs2) for row in scores_df.itertuples()
]
#for s in subjects:
#print(s)
# add motor data
for s in subjects:
file = '../data/' + s.label + '/' + s.number + '.csv'
s.add_motor_data(file)
### correct & verify number of days in subject.days, values from scores.csv are incorrect ###
# number of groups
for s in subjects:
num_of_group = len(s.motor_data_days)
num_of_distinct_days = len(set(s.motor_data_df['date']))
assert num_of_group == num_of_distinct_days
s.days = num_of_distinct_days
### end of correction & verification ###
# save subjects to file
save_object(subjects, '../data/subject.pkl')
return
def backUp(inputDirs, backUpFrom, USBlogFile, backUpTo, DataBaseAddress, spreadsheet, freesurferOn, motionOn, copyExecuteOn, nasBackupOn):
# External HDD log
if USBlogFile:
logFileInUSB = USBlogFile
elif inputDirs:
logFileInUSB = os.path.join(os.getcwd(),"log.xlsx")
else:
logFileInUSB = os.path.join(backUpFrom,"log.xlsx")
logDf = copiedDirectoryCheck(backUpFrom,logFileInUSB)
newDirectoryList,logDf = newDirectoryGrep(inputDirs, backUpFrom,logDf)
logDf.to_excel(logFileInUSB,'Sheet1')
if newDirectoryList==[]:
sys.exit('Everything have been backed up !')
subjectClassList = []
for newDirectory in newDirectoryList:
subjClass = subj.subject(newDirectory, backUpTo)
checkFileNumbers(subjClass)
subjectClassList.append(subjClass)
if copyExecuteOn:
executeCopy(subjClass)
subjDf = saveLog(subjClass)
dbDf = processDB(DataBaseAddress)
newDf = pd.concat([dbDf, subjDf]).reset_index()
newDf = newDf[[ u'koreanName', u'subjectName', u'subjectInitial',
u'group', u'sex', u'age',
u'DOB', u'scanDate', u'timeline',
u'studyname', u'patientNumber', u'T1Number',
u'DTINumber', u'DKINumber', u'RESTNumber',
u'REST2Number', u'folderName', u'backUpBy',
u'note']]
newDf['koreanName'] = newDf['koreanName'].str.decode('utf-8')
newDf['note'] = newDf['note'].str.decode('utf-8')
newDf.to_excel(DataBaseAddress, 'Sheet1')
#os.chmod(DataBaseAddress, 0o2770)
updateSpreadSheet.main(False, DataBaseAddress, spreadsheet)
if motionOn:
print 'Now, running motion_extraction'
for subjectClass in subjectClassList:
motion_extraction.main(subjectClass.targetDir, True, True, False)
if nasBackupOn:
server = '147.47.228.192'
for subjectClass in subjectClassList:
copiedDir=os.path.dirname(subjectClass.targetDir)
server_connect(server, copiedDir)
if freesurferOn:
for subjectClass in subjectClassList:
freesurfer.main(subjectClass.targetDir,
os.path.join(subjectClass.targetDir, 'FREESURFER'))
freesurfer_summary.main(copiedDir, None, "ctx_lh_G_cuneus", True, True, True, True)
print 'Completed\n'
def backUp(inputDirs, backUpFrom, USBlogFile, backUpTo,
DataBaseAddress, spreadsheet,
freesurfer, motion, copyExecute, nasBackup):
# External HDD log
if USBlogFile:
logFileInUSB = USBlogFile
elif inputDirs:
logFileInUSB = os.path.join(os.getcwd(),"log.xlsx")
else:
logFileInUSB = os.path.join(backUpFrom,"log.xlsx")
logDf = copiedDirectoryCheck(backUpFrom, logFileInUSB)
newDirectoryList,logDf = newDirectoryGrep(inputDirs, backUpFrom, logDf)
logDf.to_excel(logFileInUSB,'Sheet1')
if newDirectoryList == []:
sys.exit('Everything have been backed up !')
subjectClassList = []
for newDirectory in newDirectoryList:
subjClass = subj.subject(newDirectory, backUpTo)
checkFileNumbers(subjClass)
subjectClassList.append(subjClass)
if copyExecute:
executeCopy(subjClass)
subjDf = saveLog(subjClass)
dbDf = processDB(DataBaseAddress)
newDf = pd.concat([dbDf, subjDf]).reset_index()
newDf = newDf[[ u'koreanName', u'subjectName', u'subjectInitial',
u'group', u'sex', u'age',
u'DOB', u'scanDate', u'timeline',
u'studyname', u'patientNumber', u'T1Number',
u'DTINumber', u'DKINumber', u'RESTNumber',
u'REST2Number', u'folderName', u'backUpBy',
u'note']]
newDf['koreanName'] = newDf['koreanName'].str.decode('utf-8')
newDf['note'] = newDf['note'].str.decode('utf-8')
newDf.to_excel(DataBaseAddress, 'Sheet1')
# os.chmod(DataBaseAddress, 0o2770)
updateSpreadSheet.main(False, DataBaseAddress, spreadsheet)#False
if motion:
print 'Now, running motion_extraction'
for subjectClass in subjectClassList:
motionExtraction.main(subjectClass.targetDir, True, True, False)
bien.dtiFit(os.path.join(subjectClass.targetDir,'DTI'))
if nasBackup:
server = '147.47.228.192'
for subjectClass in subjectClassList:
copiedDir = os.path.dirname(subjectClass.targetDir)
server_connect(server, copiedDir)
if freesurfer:
for subjectClass in subjectClassList:
easyFreesurfer.main(subjectClass.targetDir,
os.path.join(subjectClass.targetDir,'FREESURFER'))
freesurfer_Summary.main(copiedDir, None, #bienseo: only use freesurfer.
"ctx_lh_G_cuneus", True, True, True, True)
print 'Completed\n'
import textwrap
import pickle
import backUp
import pandas as pd
import motion_extraction
import freesurfer
import freesurfer_summary
import subject as subj
if os.path.isfile('subjectPickle'):
with open('subjectPickle', 'r') as f:
subjClass = pickle.load(f)
else:
with open('subjectPickle', 'w') as f:
subjClass = subj.subject('/Users/kangik/KIM_SE_UK_46676612', '/Volumes/promise/nas_BackUp/CCNC_MRI_3T/')
pickle.dump(subjClass, f)
#execute copy test
try:
backUp.executeCopy(subjClass)
except:
pass
print subjClass.folderName
subjDf = backUp.saveLog(subjClass)
print subjDf
DataBaseAddress = 'database.xls'
dbDf = backUp.processDB(DataBaseAddress)
newDf = pd.concat([dbDf, subjDf])
p2=[]
p3=[]
p4=[]
p5=[]
count_comma = 0
cc=0
trigger=int
for item in res1:
if item == ',':
count_comma = res1.count(item)
print('整句中有 %d 个逗号' %(count_comma))
if count_comma == 0:
subject(res)
object(res)
object_by_tree(t)
attrib(res)
advclause(res)
predicat(res)
special(res)
nonFinite(res)
compara(res)
for j in range(0,len(t)):
for k in t[j].treepositions()[1:]:
if type(t[j]) == nltk.tree.Tree and t[j].label() == 'VP':
if t[j,0,0] in ['am','is','are']:
print('主系表结构','一般现在时','系动词为: %s'%(t[j,0,0]))
def getSubjectbyID(self, sid):
return subject.subject(sid, self)
def crawl_subject(self): import subject subj = subject.subject(self.target_ita_url) self.subject_dict = subj.publish_subject_dict()
import argparse
import textwrap
import pickle
import backUp
import pandas as pd
import motion_extraction
import freesurfer
import freesurfer_summary
import subject as subj
if os.path.isfile('subjectPickle'):
with open('subjectPickle', 'r') as f:
subjClass = pickle.load(f)
else:
with open('subjectPickle', 'w') as f:
subjClass = subj.subject('/Users/kangik/KIM_SE_UK_46676612',
'/Volumes/promise/nas_BackUp/CCNC_MRI_3T/')
pickle.dump(subjClass, f)
#execute copy test
try:
backUp.executeCopy(subjClass)
except:
pass
print subjClass.folderName
subjDf = backUp.saveLog(subjClass)
print subjDf
DataBaseAddress = 'database.xls'
dbDf = backUp.processDB(DataBaseAddress)
newDf = pd.concat([dbDf, subjDf])
#print newDf
import login
import subject
import download
import requests
import zippy
import os
if __name__ == '__main__':
userid = input("id : ")
userpw = input("pw : ")
req = requests.Session()
dirname = os.getcwd() + "/" + str(userid)
req, result = login.login(req, str(userid), str(userpw))
if not os.path.isdir(dirname):
os.mkdir(dirname)
if (result):
print("login success")
sub_name, sub_num = subject.subject(req)
for i in range(len(sub_name) - 1):
download.download(req, dirname, sub_num[i], sub_name[i])
zippy.makezip(userid, userid)
else:
print("login failed")
