Commit 74dafdd6 authored by Hua-Ting Yao's avatar Hua-Ting Yao
Browse files

Update jar3d.py

parent 67c03c69
......@@ -5,6 +5,7 @@ import statistics
import sys
import ast
from Bio import SeqIO
import json
#mod_seqs,full_seqs,indexes = pickle.load(open("../models/RECOMB_sequences.pickle","rb"))
tr = {"A":0,"C":1,"G":2,"U":3}
......@@ -30,13 +31,14 @@ def gen_seq(weights,size):
def direct_score(modules,file,dataset="RECOMB",is_list=False,retrain=False,THRESHOLD=3.5,pretrained=False):
mod_data=json.load(open("../models/"+dataset+".json"))
if pretrained:
BNs = pickle.load(open("../models/" + dataset + "_models.pickle", "rb"))
else:
BNs = {}
for module in modules:
BN = makeBN.call_makeBN(module, dataset,"NONE",False,"", retrain=retrain)
#BN = makeBN.call_makeBN(module, dataset,"NONE",False,"", retrain=retrain)
BN = makeBN.call_makeBN(module, dataset,mod_data[str(module)],False,"", retrain=retrain)
BNs[module] = BN
print("TRAINED BAYES NETS",BNs)
if is_list:
......@@ -90,4 +92,4 @@ if __name__ == "__main__":
a = direct_score(mod,file,dataset,pretrained=True)
else:
a = direct_score(mod,file,dataset,pretrained=False)
print(a[1])
\ No newline at end of file
print(a[1])
......@@ -409,6 +409,31 @@ def call_makeBN(mod, dataset, module_data, Lambda=1, Theta=1,retrain=False):
'''
# Temporary placeholder function for CV for building a Bayesian Network
def make_BN(module, dataset, graphs, motif_sequences, Lambda=0.35, Theta=1):
# Test sequences should be tuple of seq and positions, seems like it is outdated/not used
test_seqs = []
# Build the BN with the motif sequences
g = graphs[module][0]
aln = {}
for n in sorted(list(g.nodes())):
aln[n] = n
alignment = get_alignment(g, aln, motif_sequences)
motif = make_graph_from_carnaval(g, alignment)
pwm = BN_builder.build_pwm(sorted(list(motif.nodes())), alignment)
BN = BN_builder.build_BN(motif, pwm, alignment)
# PDBs array is also empty, outdated?
BN.from_alignment_dataset(dataset, module, [g], alignment, test_seqs, [], Lambda, Theta)
return BN
if __name__ == "__main__":
......
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