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authorhakangunturkun2020-04-14 15:28:48 -0500
committerhakangunturkun2020-04-14 15:28:48 -0500
commitd6ce31ebbffe337ea8495cc01ff2021652080c90 (patch)
treef98c5e19b5caac0b4dc3a9b85b34a78001363138
parentdae63118271428a08efc402cb57ffc95c5f0a856 (diff)
downloadgenecup-d6ce31ebbffe337ea8495cc01ff2021652080c90.tar.gz
change in numbering of sentence list
-rwxr-xr-xserver.py9
1 files changed, 5 insertions, 4 deletions
diff --git a/server.py b/server.py
index fd1285b..0466607 100755
--- a/server.py
+++ b/server.py
@@ -616,7 +616,7 @@ def sentences():
out_pos = ""
out_neg = ""
num_abstract = 0
- stress_cellular = "<br><br><br>"+"<b>Sentence(s) describing celluar stress (classified using a deep learning model):</b><hr>"
+ stress_cellular = "<br><br><br>"+"</ol><b>Sentence(s) describing celluar stress (classified using a deep learning model):</b><hr><ol>"
stress_systemic = "<b>Sentence(s) describing systemic stress (classified using a deep learning model):</b><hr>"
with open(tf_name, "r") as df:
all_sents=df.read()
@@ -629,12 +629,13 @@ def sentences():
if(pmid+cat0 not in pmid_list):
pmid_list.append(pmid+cat0)
if(cat0=='stress'):
- out_pred = "<li> "+ text + " <a href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=" + pmid +"\" target=_new>PMID:"+pmid+"<br></a>"
out4 = predict_sent(text)
if(out4 == 'pos'):
- out_pos += out_pred
+ out_pred_pos = "<li> "+ text + " <a href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=" + pmid +"\" target=_new>PMID:"+pmid+"<br></a>"
+ out_pos += out_pred_pos
else:
- out_neg += out_pred
+ out_pred_neg = "<li>"+ text + " <a href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=" + pmid +"\" target=_new>PMID:"+pmid+"<br></a>"
+ out_neg += out_pred_neg
out1="<h3>"+gene0 + " and " + cat0 + "</h3>\n"
if len(pmid_list)>1:
out2 = str(num_abstract) + ' sentences in ' + str(len(pmid_list)) + ' studies' + "<br><br>"