def __init__(self , modelname=None ,para={}):
     self.predict_result = {}
     para = para or {}
     #start to compute model  results
     d = Dragon(smiles_str=para["smilestring"], molfile=para["filename"])
     d.mol2drs()
     self.predict_result["invalidnums"] = d.invalidnums
     modelname = modelname or []
     for name in modelname:
         self.models_computation(name, para ,d)
     print self.predict_result 
Beispiel #2
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 def logKOA(self,para):
     '''
     logKOA model computation
     '''
     self.predict_result = {}
     if not para['smilestring']:
         self.predict_result['warning'] = 'Cannot find your input smile numbers'
         print self.predict_result
         sys.exit()
     d = Dragon(para["smilestring"])
     d.mol2drs()
     abstract_value = d.abstractparameter(["X1sol", "Mor13v", "HATS5v", "RDF035m","Mor15u" ,"RDF090m", "H-050", "nRCOOR", "R5v", "T(O..Cl)", "RCI","nRCOOR"])
     for smilenum in abstract_value.keys():
         self.predict_result[smilenum] = 0.509 + 0.986*float(abstract_value[smilenum]['X1sol'])-1.018*float(abstract_value[smilenum]['Mor13v'])+1.384*float(abstract_value[smilenum]['H-050'])-1.528*float(abstract_value[smilenum]['R5v'])-0.015*float(abstract_value[smilenum]['T(O..Cl)'])+0.043*float(abstract_value[smilenum]['HATS5v'])-0.026*float(abstract_value[smilenum]['RDF035m'])-0.197*float(abstract_value[smilenum]['RCI'])-0.130*float(abstract_value[smilenum]['nRCOOR'])-0.077*float(abstract_value[smilenum]['Mor15u'])-0.077*float(abstract_value[smilenum]['RDF090m'])
     self.predict_result["invalidnums"] = d.invalidnums
     print self.predict_result
Beispiel #3
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#! /usr/bin/env python
#coding=utf-8
from controllers.Dragon import Dragon

d = Dragon("Clc2cccc3Oc1ccccc1Oc23,cc")
d.mol2drs()
print d.abstractparameter(["X1sol", "Mor13v", "HATS5v", "RDF035m","Mor15u" ,"RDF090m", "H-050", "nRCOOR", "R5v", "T(O..Cl)", "RCI","nRCOOR"])