def retrieveDocs(pmid):
docs = [] #list of strings
#connect to db for citing id's
db_pmcids = db_citation_pmc_ids(pmid)
for pmcid in db_pmcids:
annotated = pmcidAnnotated(pmcid)
if annotated == 'yes':
pass
if annotated == 'no':
pass
if annotated == 'empty':
prefix = pmcid[0:3]
suffix = pmcid[3:6]
folder = '/home/hclent/data/pmcids/' + str(prefix) + '/' + str(
suffix) #look in folder that matches pmcid
filename = str(folder + '/' + str(pmcid)) + '.txt'
docdict = {"pmcid": pmcid, "filepath": filename}
docs.append(docdict)
logging.debug('retrieved list of documents to processes')
return docs
def retrieveDocs(pmid, conn):
docs = [] #list of strings
#connect to db for citing id's
db_pmcids = db_citation_pmc_ids(pmid, conn)
for pmcid in db_pmcids:
annotated = pmcidAnnotated(pmcid, conn)
if annotated == 'yes':
pass
if annotated == 'no':
pass
if annotated == 'empty':
prefix = pmcid[0:3]
suffix = pmcid[3:6]
#~path/123/456/12345678.txt
folder = str(prefix)+'/'+str(suffix)+'/'+str(pmcid)+'.txt' #
filename = os.path.join((app.config['PATH_TO_CACHE']), folder)
docdict = {"pmcid": pmcid, "filepath": filename}
docs.append(docdict)
logging.debug('retrieved list of documents to processes')
return docs
def retrieveBioDocs(pmid):
#print("retrieving biodocs")
biodocs = [] #list of strings
db_pmcids = db_citation_pmc_ids(pmid)
for pmcid in db_pmcids:
annotated = pmcidAnnotated(pmcid)
if annotated == 'no':
pass
if annotated == 'empty':
pass
if annotated == 'yes':
prefix = pmcid[0:3]
suffix = pmcid[3:6]
folder = '/home/hclent/data/pmcids/' + str(prefix) + '/' + str(
suffix) # look in folder that matches pmcid
filename = str(folder + '/' + str(pmcid)) + '.json'
biodict = {"pmcid": pmcid, "jsonpath": filename}
biodocs.append(biodict)
logging.debug('retrieved list of Bio documents to work with')
return biodocs
def retrieveBioDocs(pmid, conn):
#print("retrieving biodocs")
biodocs = [] #list of strings
db_pmcids = db_citation_pmc_ids(pmid, conn)
for pmcid in db_pmcids:
annotated = pmcidAnnotated(pmcid, conn)
if annotated == 'no':
pass
if annotated == 'empty':
pass
if annotated == 'yes':
prefix = pmcid[0:3]
suffix = pmcid[3:6]
folder = str(prefix) + '/' + str(suffix) + '/' + str(pmcid) + '.json' #
filename = os.path.join((app.config['PATH_TO_CACHE']), folder)
biodict = {"pmcid": pmcid, "jsonpath": filename}
biodocs.append(biodict)
logging.debug('retrieved list of Bio documents to work with')
return biodocs
def make_venn(pmid_list, conn):
i = 0
i_count = []
all_pmcids = [] #[pmc1, pmc2, ... pmc-n]
pmc_id_list = [] #list of lists [[pmid_ids paper1], [pmid_ids paper2]]
citationsDict = defaultdict(list)
possible_vals = []
venn_data = []
for pmid in pmid_list:
#add pmc_ids to master list for making citationsDict
pmc_ids = db_citation_pmc_ids(pmid, conn)
pmc_id_list.append(pmc_ids)
for id in pmc_ids:
all_pmcids.append(id)
#do first entries for venn
x = [int(i)]
pmid_label = 'PMID:'+str(pmid)+' ('+str(len(pmc_ids))+')'
pmid_Dict = {'sets': x, 'label': pmid_label, 'size': (len(pmc_ids))}
venn_data.append(pmid_Dict)
i_count.append(str(i))
i+=1
#if there is more than one pmid,
if (len(pmid_list)) > 1:
#make dictionary of {citating: ['papers', 'that', 'are', 'cited'] }
for citation in all_pmcids:
j = 0
papers = []
for pmclist in pmc_id_list:
if citation in pmclist:
#print(str(citation) + " is in P"+str(j))
if j not in papers:
papers.append(j)
j +=1
#print(papers)
citationsDict[citation] = papers
### enumerate all possible dictionary values ####
s = ''
combos = s.join(i_count) #format combos for 'combinations' method
#print(combos)
for n in range(2, len(pmid_list)+1):
compare_all = (combinations(combos, int(n)))
for c in compare_all:
option_list = [] #dict keys are in list format [1, 2]
for number in c:
option_list.append(int(number))
possible_vals.append(option_list)
#if there were multiple pmids, must look at overlap
if citationsDict:
for p_vals in possible_vals:
#print(p_vals)
sum = 0
for key, value in citationsDict.items():
if value == p_vals:
#print(str(key)+' has '+str(value)+' == '+str(p_vals))
sum += 1
#print(sum)
if sum > 0:
count_label = str(sum)
overlap_Dict = {'sets': p_vals, 'label': count_label, 'size': sum }
venn_data.append(overlap_Dict)
#if there was only 1 input pmid, no other work needed
if not citationsDict:
#print("there's no citationDict")
pass
return venn_data