def checkbrainkexistence(server,token,bkhash) :
querystring = ''.join([server, "/object.xml?key=brainkhash&value=", bkhash])
documentlist = common.checkexistence(server,token,querystring)
if len(documentlist) == 0:
return None
else:
return documentlist[0]
def checkdicomexistence(server,token,uid):
querystring = ''.join([server, "/object.xml?key=series-instance-uid&value=", uid])
documentlist = common.checkexistence(server,token,querystring)
if len(documentlist) == 0:
return None
else:
return documentlist[0]
def find_parent_braink(server,token,lfm_hdr_path) :
parent_bk_files=['dipolesFileName1','dipolesFileName2','geometryFileName','normalsFileName','sensorsFileName']
parsed_lfmhdr=parselfmheader(lfm_hdr_path)
idsets=[]
for p in parent_bk_files :
bkhash=common.rawfilehash(parsed_lfmhdr[p])
# now search on these tags ... how to do it ?
# print bkhash
querystring = ''.join(
[server,
"/object.xml?key=artifacthash&value=",
bkhash])
idlist_curr=[common.get_id_from_parsed_xml(xml) for xml in
common.checkexistence(server, token, querystring) ]
idsets.append( frozenset(idlist_curr) )
# If I understand correctly, calling reduce with intersection
# function on list of sets computes intersection of all the sets
intersect_ids=reduce(frozenset.intersection,idsets)
if len(intersect_ids)==0 :
return None
if len(intersect_ids)>1 :
print 'Warning : multiple matching BrainK objects found : '
for id in intersect_ids :
print id
return list(intersect_ids)[0]
def checksubjectexistence(server, token, subject):
querystring = ''.join(
[server,
"/object.xml?key=name&value=",
subject.name])
subjectlist = common.checkexistence(server, token, querystring)
if len(subjectlist) == 0:
return None
else:
return subjectlist[0]
